Search results for: sparse dictionary learning
Commenced in January 2007
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Edition: International
Paper Count: 6995

Search results for: sparse dictionary learning

65 Analysis of the Interest of High School Students in Tirana for Physical Activity, Sports and Foreign Languages

Authors: Zylfi Shehu, Shpetim Madani, Bashkim Delia

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Context: The study focuses on the interest and engagement of high school students in Tirana, Albania, in physical activity, sports, and foreign languages. It acknowledges the numerous physiological benefits of physical activity, such as cardiovascular health and improved mood. It also recognizes the importance of physical activity in childhood and adolescence for proper skeletal development and long-term health. Research Aim: The main purpose of the study is to investigate and analyze the preferences and interests of male and female high school students in Tirana regarding their functional development, physical activity, sports participation, and choice of foreign languages. The aim is to provide insights for the students and teachers to guide future objectives and improve the quality of physical education. Methodology: The study employed a survey-based approach, targeting both male and female students in public high schools in Tirana. A total of 410 students aged 15 to 19 years old, participated in the study. The data collected from the survey were processed using Excel and presented through tables and graphs. Findings: The results revealed that team sports were more favored by the students, with football being the preferred choice among males, while basketball and volleyball were more popular among females. Additionally, English was found to be the most preferred foreign language, selected by a higher percentage of females (38.57%) compared to males (16.90%). German followed as the second preferred language. Theoretical Importance: This study contributes to the understanding of students' interests in physical activity, sports, and foreign languages in Tirana's high schools. The findings highlight the need to focus on specific sports and languages to cater to students' preferences and guide future educational objectives. It also emphasizes the importance of physical education in promoting students' overall well-being and highlights potential areas for policy and program improvement. Data Collection and Analysis Procedures: The study collected data through surveys administered to high school students in Tirana. The survey responses were processed and analyzed using Excel, and the findings were presented through tables and graphs. The data analysis allowed for the identification of preferences and trends among male and female students, providing valuable insights for future decision-making. Question Addressed: The study aimed to address the question of high school students' interest in physical activity, sports, and foreign languages. It sought to understand the preferences and choices made by students in Tirana and investigate factors such as gender, family income, and accessibility to extracurricular sports activities. Conclusion: The study revealed that high school students in Tirana show a preference for team sports, with football being the most favored among males and basketball and volleyball among females. English was found to be the most preferred foreign language. The findings provide important insights for educators and policymakers to enhance physical education programs and consider students' preferences and interests to foster a more effective learning environment. The study also emphasizes the importance of physical activity and sports in promoting students' physical and mental well-being.

Keywords: female, male, foreign languages, sports, physical education, high school students

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64 The Beauty of Islamic Etiquette: How an Elegant Muslim Woman Represents Her Culture in a Multicultural Society

Authors: Julia A. Ermakova

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As a member of a multicultural society, it is imperative that individuals demonstrate the highest level of decorum in order to exemplify the beauty of their culture. Adab, the practice of praiseworthy words and deeds, as well as possessing good manners and pursuing that which is considered good, is a fundamental concept that guards against all types of mistakes. In Islam, etiquette for every situation in life is taught, and it constitutes the way of life for a Muslim. In light of this, the personality of an elegant Muslim woman can be described as one who embodies the following qualities: Firstly, cultural speech and erudition are essential components. Improving one's intellect, learning new things, reading diverse literature, expanding one's vocabulary, working on articulation, and avoiding obscene speech and verbosity are crucial. Additionally, listening more than speaking and being willing to discuss one's culture when asked are commendable qualities. Conversely, it is important to avoid discussing foolish matters with foolish people and to be able to respond appropriately and change the subject if someone attempts to hurt or manipulate. Secondly, the style of speech is also of paramount importance. It is recommended to speak in a measured tone with a quiet voice and deep breathing. Avoiding rushing and shortness of breath is also recommended. Thirdly, awareness of how to greet others is essential. Combining Shariah and small talk etiquette, such as making a gesture of respect by putting one's hand to the chest and smiling slightly when a man offers a handshake, is recommended. Understanding the rules of small talk, taboo topics, and self-presentation is also important. Fourthly, knowing how to give and receive compliments without devaluing them is imperative. Knowledge of the rules of good manners and etiquette, both secular and Shariah, is also essential. Fifthly, avoiding arguments and responding elegantly to rudeness and tactlessness is a sign of an elegant Muslim woman. Treating everyone with respect and avoiding prejudices, taboo topics, inappropriate questions, and bad habits are all aspects of politeness. Sixthly, a neat appearance appropriate to Shariah and the local community, as well as a well-put-together outfit with a touch of elegance and style, are crucial. Posture, graceful movement, and a pleasant gaze are also important. Finally, good spirits and inner calm are key to projecting a harmonious image, which encourages people to listen attentively. Giving thanks to Allah in every situation in life is the key to maintaining good spirits. In conclusion, an elegant Muslim woman in a multicultural society is characterized by her high moral qualities and adherence to Islamic etiquette. These qualities, such as cultural speech and erudition, style of speech, awareness of how to greet, knowledge of good manners and etiquette, avoiding arguments, politeness, a neat appearance, and good spirits, all contribute to projecting an image of elegance and respectability. By exemplifying these qualities, Muslim women can serve as positive ambassadors for their culture and religion in diverse societies.

Keywords: adab, elegance, muslim woman, multicultural societies, good manners, etiquette

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63 A Vision-Based Early Warning System to Prevent Elephant-Train Collisions

Authors: Shanaka Gunasekara, Maleen Jayasuriya, Nalin Harischandra, Lilantha Samaranayake, Gamini Dissanayake

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One serious facet of the worsening Human-Elephant conflict (HEC) in nations such as Sri Lanka involves elephant-train collisions. Endangered Asian elephants are maimed or killed during such accidents, which also often result in orphaned or disabled elephants, contributing to the phenomenon of lone elephants. These lone elephants are found to be more likely to attack villages and showcase aggressive behaviour, which further exacerbates the overall HEC. Furthermore, Railway Services incur significant financial losses and disruptions to services annually due to such accidents. Most elephant-train collisions occur due to a lack of adequate reaction time. This is due to the significant stopping distance requirements of trains, as the full braking force needs to be avoided to minimise the risk of derailment. Thus, poor driver visibility at sharp turns, nighttime operation, and poor weather conditions are often contributing factors to this problem. Initial investigations also indicate that most collisions occur in localised “hotspots” where elephant pathways/corridors intersect with railway tracks that border grazing land and watering holes. Taking these factors into consideration, this work proposes the leveraging of recent developments in Convolutional Neural Network (CNN) technology to detect elephants using an RGB/infrared capable camera around known hotspots along the railway track. The CNN was trained using a curated dataset of elephants collected on field visits to elephant sanctuaries and wildlife parks in Sri Lanka. With this vision-based detection system at its core, a prototype unit of an early warning system was designed and tested. This weatherised and waterproofed unit consists of a Reolink security camera which provides a wide field of view and range, an Nvidia Jetson Xavier computing unit, a rechargeable battery, and a solar panel for self-sufficient functioning. The prototype unit was designed to be a low-cost, low-power and small footprint device that can be mounted on infrastructures such as poles or trees. If an elephant is detected, an early warning message is communicated to the train driver using the GSM network. A mobile app for this purpose was also designed to ensure that the warning is clearly communicated. A centralized control station manages and communicates all information through the train station network to ensure coordination among important stakeholders. Initial results indicate that detection accuracy is sufficient under varying lighting situations, provided comprehensive training datasets that represent a wide range of challenging conditions are available. The overall hardware prototype was shown to be robust and reliable. We envision a network of such units may help contribute to reducing the problem of elephant-train collisions and has the potential to act as an important surveillance mechanism in dealing with the broader issue of human-elephant conflicts.

Keywords: computer vision, deep learning, human-elephant conflict, wildlife early warning technology

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62 Academic Major, Gender, and Perceived Helpfulness Predict Help-Seeking Stigma

Authors: Tran Tran

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Mental health issues are prevalent among Vietnamese undergraduate students, and they are greatly exacerbated during the COVID-19 pandemic for this population. While there is empirical evidence supporting the effectiveness and efficiency of therapy on mental health issues among college students, the rates of Vietnamese college students seeking professional mental health services were alarmingly low. Multiple factors can prevent those in need from finding support. The Internalized Stigma Model posits that public stigma directly affects intentions to seek psychological help via self-stigma and attitudes toward seeking help. However, little research has focused on what factors can predict public stigma toward seeking professional psychological support, especially among this population. A potential predictor is academic majors since academic majors can influence undergraduate students' perceptions, attitudes, and intentions. A study suggested that students who have completed two or more psychology courses have a more positive attitude toward seeking care for mental health issues and reduced stigma, which might be attributed to increased mental health literacy. In addition, research has shown that women are more likely to utilize mental health services and have lower stigma than men. Finally, studies have also suggested that experience of mental health services can increase endorsement of perceived need and lower stigma. Thus, it is expected that perceived helpfulness from past service uses can reduce stigma. This study aims to address this gap in the literature and investigate which factors can predict public stigma, specifically academic major, gender, and perceived helpfulness, potentially suggesting an avenue of prevention and ultimately improving the well-being of Vietnamese college students. The sample includes 408 undergraduate students (Mage = 20.44; 80.88% female) Hanoi city, Vietnam. Participants completed a pen-and-paper questionnaire. Students completed the Stigma Scale for Receiving Psychological Help, which yielded a mean public stigma score. Participants also completed a measurement assessing their perceived helpfulness of their university’s counseling center, which included eight subscales: future self-development, learning issues, career counseling, medical and health issues, mental health issues, conflicts between teachers and students, conflicts between parents and students, and interpersonal relationships. Items were summed to create a composite perceived helpfulness score. Finally, participants provided demographic information. This included gender, which was dichotomized between female and other. Additionally, it included academic major, which was also similarly dichotomized between psychology and other (e.g., natural science, social science, and pedagogy & social work). Linear relationships between public stigma and gender, academic major, and perceived helpfulness were analyzed individually with a regression model. Findings suggested that academic major, gender, and perceived counseling center's helpfulness predicted stigma against seeking professional psychological help. Specifically, being a psychology major predicted lower levels of public stigma (β = -.25, p < .001). Additionally, gender female predicted lower levels of public stigma (β = -.11, p < .05). Lastly, higher levels of perceived helpfulness of the counseling center also predicted lower levels of public stigma (β = -.16, p < .01). The study’s results offer potential intervention avenues to help reduce stigma and increase well-being for Vietnamese college students.

Keywords: stigma, vietnamese college students, counseling services, help-seeking

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61 Automatic Content Curation of Visual Heritage

Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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60 OASIS: An Alternative Access to Potable Water, Renewable Energy and Organic Food

Authors: Julien G. Chenet, Mario A. Hernandez, U. Leonardo Rodriguez

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The tropical areas are places where there is scarcity of access to potable water and where renewable energies need further development. They also display high undernourishment levels, even though they are one of the resources-richest areas in the world. In these areas, it is common to count on great extension of soils, high solar radiation and raw water from rain, groundwater, surface water or even saltwater. Even though resources are available, access to them is limited, and the low-density habitat makes central solutions expensive and investments not worthy. In response to this lack of investment, rural inhabitants use fossil fuels and timber as an energy source and import agrochemical for soils fertilization, which increase GHG emissions. The OASIS project brings an answer to this situation. It supplies renewable energy, potable water and organic food. The first step is the determination of the needs of the communities in terms of energy, water quantity and quality, food requirements and soil characteristics. Second step is the determination of the available resources, such as solar energy, raw water and organic residues on site. The pilot OASIS project is located in the Vichada department, Colombia, and ensures the sustainable use of natural resources to meet the community needs. The department has roughly 70% of indigenous people. They live in a very scattered landscape, with no access to clean water and energy. They use polluted surface water for direct consumption and diesel for energy purposes. OASIS pilot will ensure basic needs for a 400-students education center. In this case, OASIS will provide 20 kW of solar energy potential and 40 liters per student per day. Water will be treated form groundwater, with two qualities. A conventional one with chlorine, and as the indigenous people are not used to chlorine for direct consumption, second train is with reverse osmosis to bring conservable safe water without taste. OASIS offers a solution to supply basic needs, shifting from fossil fuels, timber, to a no-GHG-emission solution. This solution is part of the mitigation strategy against Climate Change for the communities in low-density areas of the tropics. OASIS is a learning center to teach how to convert natural resources into utilizable ones. It is also a meeting point for the community with high pedagogic impact that promotes the efficient and sustainable use of resources. OASIS system is adaptable to any tropical area and competes technically and economically with any conventional solution, that needs transport of energy, treated water and food. It is a fully automatic, replicable and sustainable solution to sort out the issue of access to basic needs in rural areas. OASIS is also a solution to undernourishment, ensuring a responsible use of resources, to prevent long-term pollution of soils and groundwater. It promotes the closure of the nutrient cycle, and the optimal use of the land whilst ensuring food security in depressed low-density regions of the tropics. OASIS is under optimization to Vichada conditions, and will be available to any other tropical area in the following months.

Keywords: climate change adaptation and mitigation, rural development, sustainable access to clean and renewable resources, social inclusion

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59 A Randomised Simulation Study to Assess the Impact of a Focussed Crew Resource Management Course on UK Medical Students

Authors: S. MacDougall-Davis, S. Wysling, R. Willmore

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Background: The application of good non-technical skills, also known as crew resource management (CRM), is central to the delivery of safe, effective healthcare. The authors have been running remote trauma courses for over 10 years, primarily focussing on developing participants’ CRM in time-critical, high-stress clinical situations. The course has undergone an iterative process over the past 10 years. We employ a number of experiential learning techniques for improving CRM, including small group workshops, military command tasks, high fidelity simulations with reflective debriefs, and a ‘flipped classroom’, where participants are asked to create their own simulations and assess and debrief their colleagues’ CRM. We created a randomised simulation study to assess the impact of our course on UK medical students’ CRM, both at an individual and a teams level. Methods: Sixteen students took part. Four clinical scenarios were devised, designed to be of similar urgency and complexity. Professional moulage effects and experienced clinical actors were used to increase fidelity and to further simulate high-stress environments. Participants were block randomised into teams of 4; each team was randomly assigned to one pre-course simulation. They then underwent our 5 day remote trauma CRM course. Post-course, students were re-randomised into four new teams; each was randomly assigned to a post-course simulation. All simulations were videoed. The footage was reviewed by two independent CRM-trained assessors, who were blinded to the before/after the status of the simulations. Assessors used the internationally validated team emergency assessment measure (TEAM) to evaluate key areas of team performance, as well as a global outcome rating. Prior to the study, assessors had scored two unrelated scenarios using the same assessment tool, demonstrating 89% concordance. Participants also completed pre- and post-course questionnaires. Likert scales were used to rate individuals’ perceived NTS ability and their confidence to work in a team in time-critical, high-stress situations. Results: Following participation in the course, a significant improvement in CRM was observed in all areas of team performance. Furthermore, the global outcome rating for team performance was markedly improved (40-70%; mean 55%), thus demonstrating an impact at Level 4 of Kirkpatrick’s hierarchy. At an individual level, participants’ self-perceived CRM improved markedly after the course (35-70% absolute improvement; mean 55%), as did their confidence to work in a team in high-stress situations. Conclusion: Our study demonstrates that with a short, cost-effective course, using easily reproducible teaching sessions, it is possible to significantly improve participants’ CRM skills, both at an individual and, perhaps more importantly, at a teams level. The successful functioning of multi-disciplinary teams is vital in a healthcare setting, particularly in high-stress, time-critical situations. Good CRM is of paramount importance in these scenarios. The authors believe that these concepts should be introduced from the earliest stages of medical education, thus promoting a culture of effective CRM and embedding an early appreciation of the importance of these skills in enabling safe and effective healthcare.

Keywords: crew resource management, non-technical skills, training, simulation

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58 International Collaboration: Developing the Practice of Social Work Curriculum through Study Abroad and Participatory Research

Authors: Megan Lindsey

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Background: Globalization presents international social work with both opportunities and challenges. Thus, the design of this international experience aligns with the three charges of the Commission on Global Social Work Education. An international collaborative effort between an American and Scottish University Social Work Program was based on an established University agreement. The presentation provides an overview of an international study abroad among American and Scottish Social Work students. Further, presenters will discuss the opportunities of international collaboration and the challenges of the project. First, we will discuss the process of a successful international collaboration. This discussion will include the planning, collaboration, execution of the experience, along with its application to the international field of social work. Second, we will discuss the development and implementation of participatory action research in which the student engage to enhance their learning experience. A collaborative qualitative research project was undertaken with three goals. First, students gained experience in Scottish social services, including agency visits and presentations. Second, a collaboration between American and Scottish MSW Students allowed the exchange of ideas and knowledge about services and social work education. Third, students collaborated on a qualitative research method to reflect on their social work education and the formation of their professional identity. Methods/Methodology: American and Scottish students engaged in participatory action research by using Photovoice methods while studying together in Scotland. The collaboration between faculty researchers framed a series of research questions. Both universities obtained IRB approval and trained students in Photovoice methods. The student teams used the research question and Photovoice method to discover images that represented their professional identity formation. Two Photovoice goals grounded the study's research question. First, the methods enabled the individual students to record and reflect on their professional strengths and concerns. Second, student teams promoted critical dialogue and knowledge about personal and professional issues through large and small group discussions of photographs. Results: The international participatory approach generated the ability for students to contextualize their common social work education and practice experiences. Team discussions between representatives of each country resulted in understanding professional identity formation and the processes of social work education that contribute to that identity. Students presented the photograph narration of their knowledge and understanding of international social work education and practice. Researchers then collaborated on finding common themes. The results found commonalities in the quality and depth of social work education. The themes found differences regarding how professional identity is formed. Students found great differences between their and American accreditation and certification. Conclusions: Faculty researchers’ collaboration themes sought to categorize the students’ experiences of their professional identity. While the social work education systems are similar, there are vast differences. The Scottish themes noted structures within American social work not found in the United Kingdom. The American researchers noted that Scotland, as does the United Kingdom, relies on programs, agencies, and the individual social worker to provide structure to identity formation. Other themes will be presented.

Keywords: higher education curriculum, international collaboration, social sciences, action research

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57 Satellite Connectivity for Sustainable Mobility

Authors: Roberta Mugellesi Dow

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As the climate crisis becomes unignorable, it is imperative that new services are developed addressing not only the needs of customers but also taking into account its impact on the environment. The Telecommunication and Integrated Application (TIA) Directorate of ESA is supporting the green transition with particular attention to the sustainable mobility.“Accelerating the shift to sustainable and smart mobility” is at the core of the European Green Deal strategy, which seeks a 90% reduction in related emissions by 2050 . Transforming the way that people and goods move is essential to increasing mobility while decreasing environmental impact, and transport must be considered holistically to produce a shared vision of green intermodal mobility. The use of space technologies, integrated with terrestrial technologies, is an enabler of smarter traffic management and increased transport efficiency for automated and connected multimodal mobility. Satellite connectivity, including future 5G networks, and digital technologies such as Digital Twin, AI, Machine Learning, and cloud-based applications are key enablers of sustainable mobility.SatCom is essential to ensure that connectivity is ubiquitously available, even in remote and rural areas, or in case of a failure, by the convergence of terrestrial and SatCom connectivity networks, This is especially crucial when there are risks of network failures or cyber-attacks targeting terrestrial communication. SatCom ensures communication network robustness and resilience. The combination of terrestrial and satellite communication networks is making possible intelligent and ubiquitous V2X systems and PNT services with significantly enhanced reliability and security, hyper-fast wireless access, as well as much seamless communication coverage. SatNav is essential in providing accurate tracking and tracing capabilities for automated vehicles and in guiding them to target locations. SatNav can also enable location-based services like car sharing applications, parking assistance, and fare payment. In addition to GNSS receivers, wireless connections, radar, lidar, and other installed sensors can enable automated vehicles to monitor surroundings, to ‘talk to each other’ and with infrastructure in real-time, and to respond to changes instantaneously. SatEO can be used to provide the maps required by the traffic management, as well as evaluate the conditions on the ground, assess changes and provide key data for monitoring and forecasting air pollution and other important parameters. Earth Observation derived data are used to provide meteorological information such as wind speed and direction, humidity, and others that must be considered into models contributing to traffic management services. The paper will provide examples of services and applications that have been developed aiming to identify innovative solutions and new business models that are allowed by new digital technologies engaging space and non space ecosystem together to deliver value and providing innovative, greener solutions in the mobility sector. Examples include Connected Autonomous Vehicles, electric vehicles, green logistics, and others. For the technologies relevant are the hybrid satcom and 5G providing ubiquitous coverage, IoT integration with non space technologies, as well as navigation, PNT technology, and other space data.

Keywords: sustainability, connectivity, mobility, satellites

Procedia PDF Downloads 90
56 Teachers Engagement to Teaching: Exploring Australian Teachers’ Attribute Constructs of Resilience, Adaptability, Commitment, Self/Collective Efficacy Beliefs

Authors: Lynn Sheridan, Dennis Alonzo, Hoa Nguyen, Andy Gao, Tracy Durksen

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Disruptions to teaching (e.g., COVID-related) have increased work demands for teachers. There is an opportunity for research to explore evidence-informed steps to support teachers. Collective evidence informs data on teachers’ personal attributes (e.g., self-efficacy beliefs) in the workplace are seen to promote success in teaching and support teacher engagement. Teacher engagement plays a role in students’ learning and teachers’ effectiveness. Engaged teachers are better at overcoming work-related stress, burnout and are more likely to take on active roles. Teachers’ commitment is influenced by a host of personal (e.g., teacher well-being) and environmental factors (e.g., job stresses). The job demands-resources model provided a conceptual basis for examining how teachers’ well-being, and is influenced by job demands and job resources. Job demands potentially evoke strain and exceed the employee’s capability to adapt. Job resources entail what the job offers to individual teachers (e.g., organisational support), helping to reduce job demands. The application of the job demands-resources model involves gathering an evidence-base of and connection to personal attributes (job resources). The study explored the association between constructs (resilience, adaptability, commitment, self/collective efficacy) and a teacher’s engagement with the job. The paper sought to elaborate on the model and determine the associations between key constructs of well-being (resilience, adaptability), commitment, and motivation (self and collective-efficacy beliefs) to teachers’ engagement in teaching. Data collection involved online a multi-dimensional instrument using validated items distributed from 2020-2022. The instrument was designed to identify construct relationships. The participant number was 170. Data Analysis: The reliability coefficients, means, standard deviations, skewness, and kurtosis statistics for the six variables were completed. All scales have good reliability coefficients (.72-.96). A confirmatory factor analysis (CFA) and structural equation model (SEM) were performed to provide measurement support and to obtain latent correlations among factors. The final analysis was performed using structural equation modelling. Several fit indices were used to evaluate the model fit, including chi-square statistics and root mean square error of approximation. The CFA and SEM analysis was performed. The correlations of constructs indicated positive correlations exist, with the highest found between teacher engagement and resilience (r=.80) and the lowest between teacher adaptability and collective teacher efficacy (r=.22). Given the associations; we proceeded with CFA. The CFA yielded adequate fit: CFA fit: X (270, 1019) = 1836.79, p < .001, RMSEA = .04, and CFI = .94, TLI = .93 and SRMR = .04. All values were within the threshold values, indicating a good model fit. Results indicate that increasing teacher self-efficacy beliefs will increase a teacher’s level of engagement; that teacher ‘adaptability and resilience are positively associated with self-efficacy beliefs, as are collective teacher efficacy beliefs. Implications for school leaders and school systems: 1. investing in increasing teachers’ sense of efficacy beliefs to manage work demands; 2. leadership approaches can enhance teachers' adaptability and resilience; and 3. a culture of collective efficacy support. Preparing teachers for now and in the future offers an important reminder to policymakers and school leaders on the importance of supporting teachers’ personal attributes when faced with the challenging demands of the job.

Keywords: collective teacher efficacy, teacher self-efficacy, job demands, teacher engagement

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55 Librarian Liaisons: Facilitating Multi-Disciplinary Research for Academic Advancement

Authors: Tracey Woods

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In the ever-evolving landscape of academia, the traditional role of the librarian has undergone a remarkable transformation. Once considered as custodians of books and gatekeepers of information, librarians have the potential to take on the vital role of facilitators of cross and inter-disciplinary projects. This shift is driven by the growing recognition of the value of interdisciplinary collaboration in addressing complex research questions in pursuit of novel solutions to real-world problems. This paper shall explore the potential of the academic librarian’s role in facilitating innovative, multi-disciplinary projects, both recognising and validating the vital role that the librarian plays in a somewhat underplayed profession. Academic libraries support teaching, the strengthening of knowledge discourse, and, potentially, the development of innovative practices. As the role of the library gradually morphs from a quiet repository of books to a community-based information hub, a potential opportunity arises. The academic librarian’s role is to build knowledge across a wide span of topics, from the advancement of AI to subject-specific information, and, whilst librarians are generally not offered the research opportunities and funding that the traditional academic disciplines enjoy, they are often invited to help build research in support of the academic. This identifies that one of the primary skills of any 21st-century librarian must be the ability to collaborate and facilitate multi-disciplinary projects. In universities seeking to develop research diversity and academic performance, there is an increasing awareness of the need for collaboration between faculties to enable novel directions and advancements. This idea has been documented and discussed by several researchers; however, there is not a great deal of literature available from recent studies. Having a team based in the library that is adept at creating effective collaborative partnerships is valuable for any academic institution. This paper outlines the development of such a project, initiated within and around an identified library-specific need: the replication of fragile special collections for object-based learning. The research was developed as a multi-disciplinary project involving the faculties of engineering (digital twins lab), architecture, design, and education. Centred around methods for developing a fragile archive into a series of tactile objects furthers knowledge and understanding in both the role of the library as a facilitator of projects, chairing and supporting, alongside contributing to the research process and innovating ideas through the bank of knowledge found amongst the staff and their liaising capabilities. This paper shall present the method of project development from the initiation of ideas to the development of prototypes and dissemination of the objects to teaching departments for analysis. The exact replication of artefacts is also balanced with the adaptation and evolutionary speculations initiated by the design team when adapted as a teaching studio method. The dynamic response required from the library to generate and facilitate these multi-disciplinary projects highlights the information expertise and liaison skills that the librarian possesses. As academia embraces this evolution, the potential for groundbreaking discoveries and innovative solutions across disciplines becomes increasingly attainable.

Keywords: Liaison librarian, multi-disciplinary collaborations, library innovations, librarian stakeholders

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54 Theory of Planned Behavior Predicts Graduation Intentions of College and University Students with and without Learning Disabilities / Attention Deficit Hyperactivity Disorder in Canada and Israel

Authors: Catherine S. Fichten, Tali Heiman, Mary Jorgensen, Mai Nhu Nguyen, Rhonda Amsel, Dorit Olenik-Shemesh

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The study examined Canadian and Israeli students' perceptions related to their intention to graduate from their program of studies. Canada and Israel are dissimilar in many ways that affect education, including language and alphabet. In addition, the postsecondary education systems differ. For example, in some parts of Canada (e.g., in Quebec, Canada’s 2nd largest province), students matriculate after 11 years of high school; in Israel, this typically occurs after 12 years. In addition, Quebec students attend two compulsory years of junior college before enrolling in a three-year university Bachelor program; in Israel students enroll in a three-year Bachelor program directly after matriculation. In addition, Israeli students typically enroll in the army shortly after high school graduation; in Canada, this is not the case. What the two countries do have in common is concern about the success of postsecondary students with disabilities. The present study was based on Ajzen’s Theory of Planned Behavior (TPB); the model suggests that behavior is influenced by Intention to carry it out. This, in turn, is predicted by the following correlated variables: Perceived Behavioral Control (i.e., ease or difficulty enacting the behavior - in this case graduation), Subjective Norms (i.e., perceived social/peer pressure from individuals important in the student’s life), and Attitude (i.e., positive or negative evaluation of graduation). A questionnaire was developed to test the TPB in previous Canadian studies and administered to 845 Canadian college students (755 nondisabled, 90 with LD/ADHD) who had completed at least one semester of studies) and to 660 Israeli university students enrolled in a Bachelor’s program (537 nondisabled, 123 with LD/ADHD). Because Israeli students were older than Canadian students we covaried age in SPSS-based ANOVA comparisons and included it in regression equations. Because females typically have better academic outcomes than males, gender was included in all analyses. ANOVA results indicate only a significant gender effect for Intention to graduate, with females having higher scores. Four stepwise regressions were conducted, with Intention to graduate as the predicted variable, and Gender and the three TPB predictors as independent variables (separate analyses for Israeli and Canadian samples with and without LD/ADHD). Results show that for samples with LD/ADHD, although Gender and Age were not significant predictors, the TPB predictors were, with all three TPB predictors being significant for the Canadian sample (i.e., Perceived Behavioral Control, Subjective Norms, Attitude, R2=.595), and two of the three (i.e., Perceived Behavioral Control, Subjective Norms) for the Israeli sample (R2=.528). For nondisabled students, the results for both countries show that all three TPB predictors were significant along with Gender: R2=.443 for Canada and R2=.332 for Israel; age was not significant. Our findings show that despite vast differences between our Canadian and Israeli samples, Intention to graduate was related to the three TPB predictors. This suggests that our TPB measure is valid for diverse samples and countries that it can be used as a quick, inexpensive way to predict graduation rates, and that strengthening the three predictor variables may result in higher graduation rates.

Keywords: disability, higher education, students, theory of planned behavior

Procedia PDF Downloads 349
53 Predictive Analytics for Theory Building

Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

Procedia PDF Downloads 243
52 Sentinel-2 Based Burn Area Severity Assessment Tool in Google Earth Engine

Authors: D. Madhushanka, Y. Liu, H. C. Fernando

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Fires are one of the foremost factors of land surface disturbance in diverse ecosystems, causing soil erosion and land-cover changes and atmospheric effects affecting people's lives and properties. Generally, the severity of the fire is calculated as the Normalized Burn Ratio (NBR) index. This is performed manually by comparing two images obtained afterward. Then by using the bitemporal difference of the preprocessed satellite images, the dNBR is calculated. The burnt area is then classified as either unburnt (dNBR<0.1) or burnt (dNBR>= 0.1). Furthermore, Wildfire Severity Assessment (WSA) classifies burnt areas and unburnt areas using classification levels proposed by USGS and comprises seven classes. This procedure generates a burn severity report for the area chosen by the user manually. This study is carried out with the objective of producing an automated tool for the above-mentioned process, namely the World Wildfire Severity Assessment Tool (WWSAT). It is implemented in Google Earth Engine (GEE), which is a free cloud-computing platform for satellite data processing, with several data catalogs at different resolutions (notably Landsat, Sentinel-2, and MODIS) and planetary-scale analysis capabilities. Sentinel-2 MSI is chosen to obtain regular processes related to burnt area severity mapping using a medium spatial resolution sensor (15m). This tool uses machine learning classification techniques to identify burnt areas using NBR and to classify their severity over the user-selected extent and period automatically. Cloud coverage is one of the biggest concerns when fire severity mapping is performed. In WWSAT based on GEE, we present a fully automatic workflow to aggregate cloud-free Sentinel-2 images for both pre-fire and post-fire image compositing. The parallel processing capabilities and preloaded geospatial datasets of GEE facilitated the production of this tool. This tool consists of a Graphical User Interface (GUI) to make it user-friendly. The advantage of this tool is the ability to obtain burn area severity over a large extent and more extended temporal periods. Two case studies were carried out to demonstrate the performance of this tool. The Blue Mountain national park forest affected by the Australian fire season between 2019 and 2020 is used to describe the workflow of the WWSAT. This site detected more than 7809 km2, using Sentinel-2 data, giving an error below 6.5% when compared with the area detected on the field. Furthermore, 86.77% of the detected area was recognized as fully burnt out, of which high severity (17.29%), moderate-high severity (19.63%), moderate-low severity (22.35%), and low severity (27.51%). The Arapaho and Roosevelt National Forest Park, California, the USA, which is affected by the Cameron peak fire in 2020, is chosen for the second case study. It was found that around 983 km2 had burned out, of which high severity (2.73%), moderate-high severity (1.57%), moderate-low severity (1.18%), and low severity (5.45%). These spots also can be detected through the visual inspection made possible by cloud-free images generated by WWSAT. This tool is cost-effective in calculating the burnt area since satellite images are free and the cost of field surveys is avoided.

Keywords: burnt area, burnt severity, fires, google earth engine (GEE), sentinel-2

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51 Using Participatory Action Research with Episodic Volunteers: Learning from Urban Agriculture Initiatives

Authors: Rebecca Laycock

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Many Urban Agriculture (UA) initiatives, including community/allotment gardens, Community Supported Agriculture, and community/social farms, depend on volunteers. However, initiatives supported or run by volunteers are often faced with a high turnover of labour as a result of the involvement of episodic volunteers (a term describing ad hoc, one-time, and seasonal volunteers), leading to challenges with maintaining project continuity and retaining skills/knowledge within the initiative. This is a notable challenge given that food growing is a knowledge intensive activity where the fruits of labour appear months or sometimes years after investment. Participatory Action Research (PAR) is increasingly advocated for in the field of UA as a solution-oriented approach to research, providing concrete results in addition to advancing theory. PAR is a cyclical methodological approach involving researchers and stakeholders collaboratively 'identifying' and 'theorising' an issue, 'planning' an action to address said issue, 'taking action', and 'reflecting' on the process. Through iterative cycles and prolonged engagement, the theory is developed and actions become better tailored to the issue. The demand for PAR in UA research means that understanding how to use PAR with episodic volunteers is of critical importance. The aim of this paper is to explore (1) the challenges of doing PAR in UA initiatives with episodic volunteers, and (2) how PAR can be harnessed to advance sustainable development of UA through theoretically-informed action. A 2.5 year qualitative PAR study on three English case study student-led food growing initiatives took place between 2014 and 2016. University UA initiatives were chosen as exemplars because most of their volunteers were episodic. Data were collected through 13 interviews, 6 workshops, and a research diary. The results were thematically analysed through eclectic coding using Computer-Assisted Qualitative Data Analysis Software (NVivo). It was found that the challenges of doing PAR with transient participants were (1) a superficial understanding of issues by volunteers because of short term engagement, resulting in difficulties ‘identifying’/‘theorising’ issues to research; (2) difficulties implementing ‘actions’ given those involved in the ‘planning’ phase often left by the ‘action’ phase; (3) a lack of capacity of participants to engage in research given the ongoing challenge of maintaining participation; and (4) that the introduction of the researcher acted as an ‘intervention’. The involvement of a long-term stakeholder (the researcher) changed the group dynamics, prompted critical reflections that had not previously taken place, and improved continuity. This posed challenges for providing a genuine understanding the episodic volunteering PAR initiatives, and also challenged the notion of what constitutes an ‘intervention’ or ‘action’ in PAR. It is recommended that researchers working with episodic volunteers using PAR should (1) adopt a first-person approach by inquiring into the researcher’s own experience to enable depth in theoretical analysis to manage the potentially superficial understandings by short-term participants; and (2) establish safety mechanisms to address the potential for the research to impose artificial project continuity and knowledge retention that will end when the research does. Through these means, we can more effectively use PAR to conduct solution-oriented research about UA.

Keywords: community garden, continuity, first-person research, higher education, knowledge retention, project management, transience, university

Procedia PDF Downloads 221
50 On the Utility of Bidirectional Transformers in Gene Expression-Based Classification

Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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49 Development and Evaluation of a Cognitive Behavioural Therapy Based Smartphone App for Low Moods and Anxiety

Authors: David Bakker, Nikki Rickard

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Smartphone apps hold immense potential as mental health and wellbeing tools. Support can be made easily accessible and can be used in real-time while users are experiencing distress. Furthermore, data can be collected to enable machine learning and automated tailoring of support to users. While many apps have been developed for mental health purposes, few have adhered to evidence-based recommendations and even fewer have pursued experimental validation. This paper details the development and experimental evaluation of an app, MoodMission, that aims to provide support for low moods and anxiety, help prevent clinical depression and anxiety disorders, and serve as an adjunct to professional clinical supports. MoodMission was designed to deliver cognitive behavioural therapy for specifically reported problems in real-time, momentary interactions. Users report their low moods or anxious feelings to the app along with a subjective units of distress scale (SUDS) rating. MoodMission then provides a choice of 5-10 short, evidence-based mental health strategies called Missions. Users choose a Mission, complete it, and report their distress again. Automated tailoring, gamification, and in-built data collection for analysis of effectiveness was also included in the app’s design. The development process involved construction of an evidence-based behavioural plan, designing of the app, building and testing procedures, feedback-informed changes, and a public launch. A randomized controlled trial (RCT) was conducted comparing MoodMission to two other apps and a waitlist control condition. Participants completed measures of anxiety, depression, well-being, emotional self-awareness, coping self-efficacy and mental health literacy at the start of their app use and 30 days later. At the time of submission (November 2016) over 300 participants have participated in the RCT. Data analysis will begin in January 2017. At the time of this submission, MoodMission has over 4000 users. A repeated-measures ANOVA of 1390 completed Missions reveals that SUDS (0-10) ratings were significantly reduced between pre-Mission ratings (M=6.20, SD=2.39) and post-Mission ratings (M=4.93, SD=2.25), F(1,1389)=585.86, p < .001, np2=.30. This effect was consistent across both low moods and anxiety. Preliminary analyses of the data from the outcome measures surveys reveal improvements across mental health and wellbeing measures as a result of using the app over 30 days. This includes a significant increase in coping self-efficacy, F(1,22)=5.91, p=.024, np2=.21. Complete results from the RCT in which MoodMission was evaluated will be presented. Results will also be presented from the continuous outcome data being recorded by MoodMission. MoodMission was successfully developed and launched, and preliminary analysis suggest that it is an effective mental health and wellbeing tool. In addition to the clinical applications of MoodMission, the app holds promise as a research tool to conduct component analysis of psychological therapies and overcome restraints of laboratory based studies. The support provided by the app is discrete, tailored, evidence-based, and transcends barriers of stigma, geographic isolation, financial limitations, and low health literacy.

Keywords: anxiety, app, CBT, cognitive behavioural therapy, depression, eHealth, mission, mobile, mood, MoodMission

Procedia PDF Downloads 237
48 The Role of Community Activism in Promoting Social Justice around Housing Issues: A Case Study of the Western Cape

Authors: Mapule Maema

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The paper aims to highlight the role that community activism has played in promoting social justice around housing issues in the Western Cape. The Western Cape is one of the largest spatially segregated provinces in South Africa which continues to exhibit grave inequalities between cities, townships and farms. These inequalities cut across intersectional issues such as, race, class, gender, and politics. The main challenges facing marginalized communities in the Western Cape include access to housing, land and basic services. This is not peculiar to only the Western Cape, the entire country is facing similar challenges however the Western Cape is seen as a fasted urbanizing province in the country due to tourism. Various social movements have been formed across the country to counter these challenges, however, this paper focuses on the resilience communities have fostered despite the myriad housing and spatial crisis they are faced with. The paper focuses on the Legal Resource’s Centre’s clients from an informal settlement called Imizamo Yethu based in Hout Bay Valley area. The 18 hectare settlement houses approximately 33600 people. On the 21st July 2017, Hout Bay experienced violent protests following an eviction order passed by the City of Cape Town. The protest was characterized by tensions within the community regarding the super-blocking initiative which aims to establish roads in informal settlements to ensure basic services. Residents against the process argued that there were no proper consultations done to educate them on what this process entailed. Public participation is one of the objectives the municipalities aim to promote however it remains a great challenge. In order to highlight the experiences of the LRC clients in relation to what motivated their involvement in the movement, how it felt their participation, and aspirations, the paper will employ qualitative research methods. Qualitative research methods enable the researcher to get a deeper and nuanced understanding of the social world in the eyes of those who experienced it. It is a flexible methodology that enables one to also understand social processes and the significance they generate. Data will be collected through the use of the World Cafe as a focus group method. The World Café is a simple, effective and flexible format for hosting group dialogue. The steps taken when setting up a World Café includes the following: setting the context (why you are bringing people together and what you want to achieve), create hospitality space (make participants feel at home and free to discuss issues), explore questions that matter, connect diverse perspectives (the opportunity to actively contribute your thinking), listen together for patterns and insights, share collective discoveries and learnings. Secondary data will be used to augment the data collected. Stories of impact will be drawn from the exercises. This paper will contribute to the discourse of sustainable housing and urban development and the research outputs will be disseminated to the public for learning.

Keywords: community activism, influence, social justice, development

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47 Improved Anatomy Teaching by the 3D Slicer Platform

Authors: Ahmedou Moulaye Idriss, Yahya Tfeil

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Medical imaging technology has become an indispensable tool in many branches of the biomedical, health area, and research and is vitally important for the training of professionals in these fields. It is not only about the tools, technologies, and knowledge provided but also about the community that this training project proposes. In order to be able to raise the level of anatomy teaching in the medical school of Nouakchott in Mauritania, it is necessary and even urgent to facilitate access to modern technology for African countries. The role of technology as a key driver of justifiable development has long been recognized. Anatomy is an essential discipline for the training of medical students; it is a key element for the training of medical specialists. The quality and results of the work of a young surgeon depend on his better knowledge of anatomical structures. The teaching of anatomy is difficult as the discipline is being neglected by medical students in many academic institutions. However, anatomy remains a vital part of any medical education program. When anatomy is presented in various planes medical students approve of difficulties in understanding. They do not increase their ability to visualize and mentally manipulate 3D structures. They are sometimes not able to correctly identify neighbouring or associated structures. This is the case when they have to make the identification of structures related to the caudate lobe when the liver is moved to different positions. In recent decades, some modern educational tools using digital sources tend to replace old methods. One of the main reasons for this change is the lack of cadavers in laboratories with poorly qualified staff. The emergence of increasingly sophisticated mathematical models, image processing, and visualization tools in biomedical imaging research have enabled sophisticated three-dimensional (3D) representations of anatomical structures. In this paper, we report our current experience in the Faculty of Medicine in Nouakchott Mauritania. One of our main aims is to create a local learning community in the fields of anatomy. The main technological platform used in this project is called 3D Slicer. 3D Slicer platform is an open-source application available for free for viewing, analysis, and interaction with biomedical imaging data. Using the 3D Slicer platform, we created from real medical images anatomical atlases of parts of the human body, including head, thorax, abdomen, liver, and pelvis, upper and lower limbs. Data were collected from several local hospitals and also from the website. We used MRI and CT-Scan imaging data from children and adults. Many different anatomy atlases exist, both in print and digital forms. Anatomy Atlas displays three-dimensional anatomical models, image cross-sections of labelled structures and source radiological imaging, and a text-based hierarchy of structures. Open and free online anatomical atlases developed by our anatomy laboratory team will be available to our students. This will allow pedagogical autonomy and remedy the shortcomings by responding more fully to the objectives of sustainable local development of quality education and good health at the national level. To make this work a reality, our team produced several atlases available in our faculty in the form of research projects.

Keywords: anatomy, education, medical imaging, three dimensional

Procedia PDF Downloads 207
46 Competence of the Health Workers in Diagnosing and Managing Complicated Pregnancies: A Clinical Vignette Based Assessment in District and Sub-District Hospitals in Bangladesh

Authors: Abdullah Nurus Salam Khan, Farhana Karim, Mohiuddin Ahsanul Kabir Chowdhury, S. Masum Billah, Nabila Zaka, Alexander Manu, Shams El Arifeen

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Globally, pre-eclampsia (PE) and ante-partum haemorrhage (APH) are two major causes of maternal mortality. Prompt identification and management of these conditions depend on competency of the birth attendants. Since these conditions are infrequent to be observed, clinical vignette based assessment could identify the extent of health worker’s competence in managing emergency obstetric care (EmOC). During June-August 2016, competence of 39 medical officers (MO) and 95 nurses working in obstetric ward of 15 government health facilities (3 district hospital, 12 sub-district hospital) was measured using clinical vignettes on PE and APH. The vignettes resulted in three outcome measures: total vignette scores, scores for diagnosis component, and scores for management component. T-test was conducted to compare mean vignette scores and linear regression was conducted to measure the strength and association of vignette scores with different cadres of health workers, facility’s readiness for EmOC and average annual utilization of normal deliveries after adjusting for type of health facility, health workers’ work experience, training status on managing maternal complication. For each of the seven component of EmOC items (administration of injectable antibiotics, oxytocic and anticonvulsant; manual removal of retained placenta, retained products of conception; blood transfusion and caesarean delivery), if any was practised in the facility within last 6 months, a point was added and cumulative EmOC readiness score (range: 0-7) was generated for each facility. The yearly utilization of delivery cases were identified by taking the average of all normal deliveries conducted during three years (2013-2015) preceding the survey. About 31% of MO and all nurses were female. Mean ( ± sd) age of the nurses were higher than the MO (40.0 ± 6.9 vs. 32.2 ± 6.1 years) and also longer mean( ± sd) working experience (8.9 ± 7.9 vs. 1.9 ± 3.9 years). About 80% health workers received any training on managing maternal complication, however, only 7% received any refresher’s training within last 12 months. The overall vignette score was 8.8 (range: 0-19), which was significantly higher among MO than nurses (10.7 vs. 8.1, p < 0.001) and the score was not associated with health facility types, training status and years of experience of the providers. Vignette score for management component (range: 0-9) increased with higher annual average number of deliveries in their respective working facility (adjusted β-coefficient 0.16, CI 0.03-0.28, p=0.01) and increased with each unit increase in EmOC readiness score (adjusted β-coefficient 0.44, CI 0.04-0.8, p=0.03). The diagnosis component of vignette score was not associated with any of the factors except it was higher among the MO than the nurses (adjusted β-coefficient 1.2, CI 0.13-2.18, p=0.03). Lack of competence in diagnosing and managing obstetric complication by the nurses than the MO is of concern especially when majority of normal deliveries are conducted by the nurses. Better EmOC preparedness of the facility and higher utilization of normal deliveries resulted in higher vignette score for the management component; implying the impact of experiential learning through higher case management. Focus should be given on improving the facility readiness for EmOC and providing the health workers periodic refresher’s training to make them more competent in managing obstetric cases.

Keywords: Bangladesh, emergency obstetric care, clinical vignette, competence of health workers

Procedia PDF Downloads 161
45 Top-Down, Middle-Out, Bottom-Up: A Design Approach to Transforming Prison

Authors: Roland F. Karthaus, Rachel S. O'Brien

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Over the past decade, the authors have undertaken applied research aimed at enabling transformation within the prison service to improve conditions and outcomes for those living, working and visiting in prisons in the UK and the communities they serve. The research has taken place against a context of reducing resources and public discontent at increasing levels of violence, deteriorating conditions and persistently high levels of re-offending. Top-down governmental policies have mainly been ineffectual and in some cases counter-productive. The prison service is characterised by hierarchical organisation, and the research has applied design thinking at multiple levels to challenge and precipitate change: top-down, middle-out and bottom-up. The research employs three distinct but related approaches, system design (top-down): working at the national policy level to analyse the changing policy context, identifying opportunities and challenges; engaging with the Ministry of Justice commissioners and sector organisations to facilitate debate, introducing new evidence and provoking creative thinking, place-based design (middle-out): working with individual prison establishments as pilots to illustrate and test the potential for local empowerment, creative change, and improved architecture within place-specific contexts and organisational hierarchies, everyday design (bottom-up): working with individuals in the system to explore the potential for localised, significant, demonstrator changes; including collaborative design, capacity building and empowerment in skills, employment, communication, training, and other activities. The research spans a series of projects, through which the methodological approach has developed responsively. The projects include a place-based model for the re-purposing of Ministry of Justice land assets for the purposes of rehabilitation; an evidence-based guide to improve prison design for health and well-being; capacity-based employment, skills and self-build project as a template for future open prisons. The overarching research has enabled knowledge to be developed and disseminated through policy and academic networks. Whilst the research remains live and continuing; key findings are emerging as a basis for a new methodological approach to effecting change in the UK prison service. An interdisciplinary approach is necessary to overcome the barriers between distinct areas of the prison service. Sometimes referred to as total environments, prisons encompass entire social and physical environments which themselves are orchestrated by institutional arms of government, resulting in complex systems that cannot be meaningfully engaged through narrow disciplinary lenses. A scalar approach is necessary to connect strategic policies with individual experiences and potential, through the medium of individual prison establishments, operating as discrete entities within the system. A reflexive process is necessary to connect research with action in a responsive mode, learning to adapt as the system itself is changing. The role of individuals in the system, their latent knowledge and experience and their ability to engage and become agents of change are essential. Whilst the specific characteristics of the UK prison system are unique, the approach is internationally applicable.

Keywords: architecture, design, policy, prison, system, transformation

Procedia PDF Downloads 102
44 Use of Artificial Intelligence and Two Object-Oriented Approaches (k-NN and SVM) for the Detection and Characterization of Wetlands in the Centre-Val de Loire Region, France

Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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43 Becoming a Good-Enough White Therapist: Experiences of International Students in Psychology Doctoral Programs

Authors: Mary T. McKinley

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As socio-economic globalization impacts education and turns knowledge into a commodity, institutions of higher education are becoming more intentional about infusing a global and intercultural perspective into education via the recruitment of international students. Coming from dissimilar cultures, many of these students are evaluated and held accountable to Euro-American values of independence, self-reliance, and autonomy. Not surprisingly, these students often experience culture shock with deleterious effects on their mental health and academic functioning. Thus, it is critical to understand the experiences of international students with the hope that such knowledge will keep the field of psychology from promulgating Eurocentric ideals and values and prevent the training of these students as good-enough White therapists. Using a critical narrative inquiry framework, this study elicits stories about the challenges encountered by international students as they navigate their clinical training in the presence of acculturative stress and potentially different worldviews. With its emphasis on story-telling as meaning making, narrative research design is hinged on the assumption that people are interpretive beings who make meaning of themselves and their world through the language of stories. Also, dominant socially-constructed narratives play a central role in creating and maintaining hegemonic structures that privilege certain individuals and ideologies at the expense of others. On this premise, narrative inquiry begins with an exploration of the experiences of participants in their lived stories. Bounded narrative segments were read, interpreted, and analyzed using a critical events approach. Throughout the process, issues of reliability and researcher bias were addressed by keeping a reflective analytic memo, as well as triangulating the data using peer-reviewers and check-ins with participants. The findings situate culture at the epicenter of international students’ acculturation challenges as well as their resiliency in psychology doctoral programs. It was not uncommon for these international students to experience ethical dilemmas inherent in learning content that conflicted with their cultural beliefs and values. Issues of cultural incongruence appear to be further exacerbated by visible markers for differences like speech accent and clothing attire. These stories also link the acculturative stress reported by international students to the experiences of perceived racial discrimination and lack of support from the faculty, administration, peers, and the society at large. Beyond the impact on the international students themselves, there are implications for internationalization in psychology with the goal of equipping doctoral programs to be better prepared to meet the needs of their international students. More than ever before, programs need to liaise with international students’ services and work in tandem to meet the unique needs of this population of students. Also, there exists a need for multiculturally competent supervisors working with international students with varying degrees of acculturation. In addition to making social justice and advocacy salient in students’ multicultural training, it may be helpful for psychology doctoral programs to be more intentional about infusing cross-cultural theories, indigenous psychotherapies, and/or when practical, the possibility for geographically cross-cultural practicum experiences in the home countries of international students while taking into consideration the ethical issues for virtual supervision.

Keywords: decolonizing pedagogies, international students, multiculturalism, psychology doctoral programs

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42 Childhood Sensory Sensitivity: A Potential Precursor to Borderline Personality Disorder

Authors: Valerie Porr, Sydney A. DeCaro

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TARA for borderline personality disorder (BPD), an education and advocacy organization, helps families to compassionately and effectively deal with troubling BPD behaviors. Our psychoeducational programs focus on understanding underlying neurobiological features of BPD and evidence-based methodology integrating dialectical behavior therapy (DBT) and mentalization based therapy (MBT,) clarifying the inherent misunderstanding of BPD behaviors and improving family communication. TARA4BPD conducts online surveys, workshops, and topical webinars. For over 25 years, we have collected data from BPD helpline callers. This data drew our attention to particular childhood idiosyncrasies that seem to characterize many of the children who later met the criteria for BPD. The idiosyncrasies we observed, heightened sensory sensitivity and hypervigilance, were included in Adolf Stern’s 1938 definition of “Borderline.” This aspect of BPD has not been prioritized by personality disorder researchers, presently focused on emotion processing and social cognition in BPD. Parents described sleep reversal problems in infants who, early on, seem to exhibit dysregulation in circadian rhythm. Families describe children as supersensitive to sensory sensations, such as specific sounds, heightened sense of smell, taste, textures of foods, and an inability to tolerate various fabrics textures (i.e., seams in socks). They also exhibit high sensitivity to particular words and voice tones. Many have alexithymia and dyslexia. These children are either hypo- or hypersensitive to sensory sensations, including pain. Many suffer from fibromyalgia. BPD reactions to pain have been studied (C. Schmahl) and confirm the existence of hyper and hypo-reactions to pain stimuli in people with BPD. To date, there is little or no data regarding what comprises a normative range of sensitivity in infants and children. Many parents reported that their children were tested or treated for sensory processing disorder (SPD), learning disorders, and ADHD. SPD is not included in the DSM and is treated by occupational therapists. The overwhelming anecdotal data from thousands of parents of children who later met criteria for BPD led TARA4BPD to develop a sensitivity survey to develop evidence of the possible role of early sensory perception problems as a pre-cursor to BPD, hopefully initiating new directions in BPD research. At present, the research community seems unaware of the role supersensory sensitivity might play as an early indicator of BPD. Parents' observations of childhood sensitivity obtained through family interviews and results of an extensive online survey on sensory responses across various ages of development will be presented. People with BPD suffer from a sense of isolation and otherness that often results in later interpersonal difficulties. Early identification of supersensitive children while brain circuits are developing might decrease the development of social interaction deficits such as rejection sensitivity, self-referential processes, and negative bias, hallmarks of BPD, ultimately minimizing the maladaptive methods of coping with distress that characterizes BPD. Family experiences are an untapped resource for BPD research. It is hoped that this data will give family observations the critical credibility to inform future treatment and research directions.

Keywords: alexithymia, dyslexia, hypersensitivity, sensory processing disorder

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41 Female Entrepreneurship in the Creative Industry: The Antecedents of Their Ventures' Performance

Authors: Naoum Mylonas, Eugenia Petridou

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Objectives: The objectives of this research are firstly, to develop an integrated model of predicting factors to new ventures performance, taking into account certain issues and specificities related to creative industry and female entrepreneurship based on the prior research; secondly, to determine the appropriate measures of venture performance in a creative industry context, drawing upon previous surveys; thirdly, to illustrate the importance of entrepreneurial orientation, networking ties, environment dynamism and access to financial capital on new ventures performance. Prior Work: An extant review of the creative industry literature highlights the special nature of entrepreneurship in this field. Entrepreneurs in creative industry share certain specific characteristics and intensions, such as to produce something aesthetic, to enrich their talents and their creativity, and to combine their entrepreneurial with their artistic orientation. Thus, assessing venture performance and success in creative industry entails an examination of how creative people or artists conceptualize success. Moreover, female entrepreneurs manifest more positive attitudes towards sectors primarily based on creativity, rather than innovation in which males outbalance. As creative industry entrepreneurship based mainly on the creative personality of the creator / artist, a high interest is accrued to examine female entrepreneurship in the creative industry. Hypotheses development: H1a: Female entrepreneurs who are more entrepreneurially-oriented show a higher financial performance. H1b: Female entrepreneurs who are more artistically-oriented show a higher creative performance. H2: Female entrepreneurs who have personality that is more creative perform better. H3: Female entrepreneurs who participate in or belong to networks perform better. H4: Female entrepreneurs who have been consulted by a mentor perform better. Η5a: Female entrepreneurs who are motivated more by pull-factors perform better. H5b: Female entrepreneurs who are motivated more by push-factors perform worse. Approach: A mixed method triangulation design has been adopted for the collection and analysis of data. The data are collected through a structured questionnaire for the quantitative part and through semi-structured interviews for the qualitative part as well. The sample is 293 Greek female entrepreneurs in the creative industry. Main findings: All research hypotheses are accepted. The majority of creative industry entrepreneurs evaluate themselves in creative performance terms rather than financial ones. The individuals who are closely related to traditional arts sectors have no EO but also evaluate themselves highly in terms of venture performance. Creative personality of creators is appeared as the most important predictor of venture performance. Pull factors in accordance with our hypothesis lead to higher levels of performance compared to push factors. Networking and mentoring are viewed as very important, particularly now during the turbulent economic environment in Greece. Implications-Value: Our research provides an integrated model with several moderating variables to predict ventures performance in the creative industry, taking also into account the complicated nature of arts and the way artists and creators define success. At the end, the findings may be used for the appropriate design of educational programs in creative industry entrepreneurship. This research has been co-financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: Heracleitus II. Investing in knowledge society through the European Social Fund.

Keywords: venture performance, female entrepreneurship, creative industry, networks

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40 Technological Transference Tools to Diffuse Low-Cost Earthquake Resistant Construction with Adobe in Rural Areas of the Peruvian Andes

Authors: Marcial Blondet, Malena Serrano, Álvaro Rubiños, Elin Mattsson

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In Peru, there are more than two million houses made of adobe (sun dried mud bricks) or rammed earth (35% of the total houses), in which almost 9 million people live, mainly because they cannot afford to purchase industrialized construction materials. Although adobe houses are cheap to build and thermally comfortable, their seismic performance is very poor, and they usually suffer significant damage or collapse with tragic loss of life. Therefore, over the years, researchers at the Pontifical Catholic University of Peru and other institutions have developed many reinforcement techniques as an effort to improve the structural safety of earthen houses located in seismic areas. However, most rural communities live under unacceptable seismic risk conditions because these techniques have not been adopted massively, mainly due to high cost and lack of diffusion. The nylon rope mesh reinforcement technique is simple and low-cost, and two technological transference tools have been developed to diffuse it among rural communities: 1) Scale seismic simulations using a portable shaking table have been designed to prove its effectiveness to protect adobe houses; 2) A step-by-step illustrated construction manual has been developed to guide the complete building process of a nylon rope mesh reinforced adobe house. As a study case, it was selected the district of Pullo: a small rural community in the Peruvian Andes where more than 80% of its inhabitants live in adobe houses and more than 60% are considered to live in poverty or extreme poverty conditions. The research team carried out a one-day workshop in May 2015 and a two-day workshop in September 2015. Results were positive: First, the nylon rope mesh reinforcement procedure was proven simple enough to be replicated by adults, both young and seniors, and participants handled ropes and knots easily as they use them for daily livestock activity. In addition, nylon ropes were proven highly available in the study area as they were found at two local stores in variety of color and size.. Second, the portable shaking table demonstration successfully showed the effectiveness of the nylon rope mesh reinforcement and generated interest on learning about it. On the first workshop, more than 70% of the participants were willing to formally subscribe and sign up for practical training lessons. On the second workshop, more than 80% of the participants returned the second day to receive introductory practical training. Third, community members found illustrations on the construction manual simple and friendly but the roof system illustrations led to misinterpretation so they were improved. The technological transfer tools developed in this project can be used to train rural dwellers on earthquake-resistant self-construction with adobe, which is still very common in the Peruvian Andes. This approach would allow community members to develop skills and capacities to improve safety of their households on their own, thus, mitigating their high seismic risk and preventing tragic losses. Furthermore, proper training in earthquake-resistant self-construction with adobe would prevent rural dwellers from depending on external aid after an earthquake and become agents of their own development.

Keywords: adobe, Peruvian Andes, safe housing, technological transference

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39 Generating Individualized Wildfire Risk Assessments Utilizing Multispectral Imagery and Geospatial Artificial Intelligence

Authors: Gus Calderon, Richard McCreight, Tammy Schwartz

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Forensic analysis of community wildfire destruction in California has shown that reducing or removing flammable vegetation in proximity to buildings and structures is one of the most important wildfire defenses available to homeowners. State laws specify the requirements for homeowners to create and maintain defensible space around all structures. Unfortunately, this decades-long effort had limited success due to noncompliance and minimal enforcement. As a result, vulnerable communities continue to experience escalating human and economic costs along the wildland-urban interface (WUI). Quantifying vegetative fuels at both the community and parcel scale requires detailed imaging from an aircraft with remote sensing technology to reduce uncertainty. FireWatch has been delivering high spatial resolution (5” ground sample distance) wildfire hazard maps annually to the community of Rancho Santa Fe, CA, since 2019. FireWatch uses a multispectral imaging system mounted onboard an aircraft to create georeferenced orthomosaics and spectral vegetation index maps. Using proprietary algorithms, the vegetation type, condition, and proximity to structures are determined for 1,851 properties in the community. Secondary data processing combines object-based classification of vegetative fuels, assisted by machine learning, to prioritize mitigation strategies within the community. The remote sensing data for the 10 sq. mi. community is divided into parcels and sent to all homeowners in the form of defensible space maps and reports. Follow-up aerial surveys are performed annually using repeat station imaging of fixed GPS locations to address changes in defensible space, vegetation fuel cover, and condition over time. These maps and reports have increased wildfire awareness and mitigation efforts from 40% to over 85% among homeowners in Rancho Santa Fe. To assist homeowners fighting increasing insurance premiums and non-renewals, FireWatch has partnered with Black Swan Analytics, LLC, to leverage the multispectral imagery and increase homeowners’ understanding of wildfire risk drivers. For this study, a subsample of 100 parcels was selected to gain a comprehensive understanding of wildfire risk and the elements which can be mitigated. Geospatial data from FireWatch’s defensible space maps was combined with Black Swan’s patented approach using 39 other risk characteristics into a 4score Report. The 4score Report helps property owners understand risk sources and potential mitigation opportunities by assessing four categories of risk: Fuel sources, ignition sources, susceptibility to loss, and hazards to fire protection efforts (FISH). This study has shown that susceptibility to loss is the category residents and property owners must focus their efforts. The 4score Report also provides a tool to measure the impact of homeowner actions on risk levels over time. Resiliency is the only solution to breaking the cycle of community wildfire destruction and it starts with high-quality data and education.

Keywords: defensible space, geospatial data, multispectral imaging, Rancho Santa Fe, susceptibility to loss, wildfire risk.

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38 Accountability of Artificial Intelligence: An Analysis Using Edgar Morin’s Complex Thought

Authors: Sylvie Michel, Sylvie Gerbaix, Marc Bidan

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Artificial intelligence (AI) can be held accountable for its detrimental impacts. This question gains heightened relevance given AI's pervasive reach across various domains, magnifying its power and potential. The expanding influence of AI raises fundamental ethical inquiries, primarily centering on biases, responsibility, and transparency. This encompasses discriminatory biases arising from algorithmic criteria or data, accidents attributed to autonomous vehicles or other systems, and the imperative of transparent decision-making. This article aims to stimulate reflection on AI accountability, denoting the necessity to elucidate the effects it generates. Accountability comprises two integral aspects: adherence to legal and ethical standards and the imperative to elucidate the underlying operational rationale. The objective is to initiate a reflection on the obstacles to this "accountability," facing the challenges of the complexity of artificial intelligence's system and its effects. Then, this article proposes to mobilize Edgar Morin's complex thought to encompass and face the challenges of this complexity. The first contribution is to point out the challenges posed by the complexity of A.I., with fractional accountability between a myriad of human and non-human actors, such as software and equipment, which ultimately contribute to the decisions taken and are multiplied in the case of AI. Accountability faces three challenges resulting from the complexity of the ethical issues combined with the complexity of AI. The challenge of the non-neutrality of algorithmic systems as fully ethically non-neutral actors is put forward by a revealing ethics approach that calls for assigning responsibilities to these systems. The challenge of the dilution of responsibility is induced by the multiplicity and distancing between the actors. Thus, a dilution of responsibility is induced by a split in decision-making between developers, who feel they fulfill their duty by strictly respecting the requests they receive, and management, which does not consider itself responsible for technology-related flaws. Accountability is confronted with the challenge of transparency of complex and scalable algorithmic systems, non-human actors self-learning via big data. A second contribution involves leveraging E. Morin's principles, providing a framework to grasp the multifaceted ethical dilemmas and subsequently paving the way for establishing accountability in AI. When addressing the ethical challenge of biases, the "hologrammatic" principle underscores the imperative of acknowledging the non-ethical neutrality of algorithmic systems inherently imbued with the values and biases of their creators and society. The "dialogic" principle advocates for the responsible consideration of ethical dilemmas, encouraging the integration of complementary and contradictory elements in solutions from the very inception of the design phase. Aligning with the principle of organizing recursiveness, akin to the "transparency" of the system, it promotes a systemic analysis to account for the induced effects and guides the incorporation of modifications into the system to rectify deviations and reintroduce modifications into the system to rectify its drifts. In conclusion, this contribution serves as an inception for contemplating the accountability of "artificial intelligence" systems despite the evident ethical implications and potential deviations. Edgar Morin's principles, providing a lens to contemplate this complexity, offer valuable perspectives to address these challenges concerning accountability.

Keywords: accountability, artificial intelligence, complexity, ethics, explainability, transparency, Edgar Morin

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37 Industrial Production of the Saudi Future Dwelling: A Saudi Volumetric Solution for Single Family Homes, Leveraging Industry 4.0 with Scalable Automation, Hybrid Structural Insulated Panels Technology and Local Materials

Authors: Bandar Alkahlan

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The King Abdulaziz City for Science and Technology (KACST) created the Saudi Future Dwelling (SFD) initiative to identify, localize and commercialize a scalable home manufacturing technology suited to deployment across the Kingdom of Saudi Arabia (KSA). This paper outlines the journey, the creation of the international project delivery team, the product design, the selection of the process technologies, and the outcomes. A target was set to remove 85% of the construction and finishing processes from the building site as these activities could be more efficiently completed in a factory environment. Therefore, integral to the SFD initiative is the successful industrialization of the home building process using appropriate technologies, automation, robotics, and manufacturing logistics. The technologies proposed for the SFD housing system are designed to be energy efficient, economical, fit for purpose from a Saudi cultural perspective, and will minimize the use of concrete, relying mainly on locally available Saudi natural materials derived from the local resource industries. To this end, the building structure is comprised of a hybrid system of structural insulated panels (SIP), combined with a light gauge steel framework manufactured in a large format panel system. The paper traces the investigative process and steps completed by the project team during the selection process. As part of the SFD Project, a pathway was mapped out to include a proof-of-concept prototype housing module and the set-up and commissioning of a lab-factory complete with all production machinery and equipment necessary to simulate a full-scale production environment. The prototype housing module was used to validate and inform current and future product design as well as manufacturing process decisions. A description of the prototype design and manufacture is outlined along with valuable learning derived from the build and how these results were used to enhance the SFD project. The industrial engineering concepts and lab-factory detailed design and layout are described in the paper, along with the shop floor I.T. management strategy. Special attention was paid to showcase all technologies within the lab-factory as part of the engagement strategy with private investors to leverage the SFD project with large scale factories throughout the Kingdom. A detailed analysis is included in the process surrounding the design, specification, and procurement of the manufacturing machinery, equipment, and logistical manipulators required to produce the SFD housing modules. The manufacturing machinery was comprised of a combination of standardized and bespoke equipment from a wide range of international suppliers. The paper describes the selection process, pre-ordering trials and studies, and, in some cases, the requirement for additional research and development by the equipment suppliers in order to achieve the SFD objectives. A set of conclusions is drawn describing the results achieved thus far, along with a list of recommended ongoing operational tests, enhancements, research, and development aimed at achieving full-scale engagement with private sector investment and roll-out of the SFD project across the Kingdom.

Keywords: automation, dwelling, manufacturing, product design

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36 i2kit: A Tool for Immutable Infrastructure Deployments

Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservice architectures are increasingly in distributed cloud applications due to the advantages on the software composition, development speed, release cycle frequency and the business logic time to market. On the other hand, these architectures also introduce some challenges on the testing and release phases of applications. Container technology solves some of these issues by providing reproducible environments, easy of software distribution and isolation of processes. However, there are other issues that remain unsolved in current container technology when dealing with multiple machines, such as networking for multi-host communication, service discovery, load balancing or data persistency (even though some of these challenges are already solved by traditional cloud vendors in a very mature and widespread manner). Container cluster management tools, such as Kubernetes, Mesos or Docker Swarm, attempt to solve these problems by introducing a new control layer where the unit of deployment is the container (or the pod — a set of strongly related containers that must be deployed on the same machine). These tools are complex to configure and manage and they do not follow a pure immutable infrastructure approach since servers are reused between deployments. Indeed, these tools introduce dependencies at execution time for solving networking or service discovery problems. If an error on the control layer occurs, which would affect running applications, specific expertise is required to perform ad-hoc troubleshooting. As a consequence, it is not surprising that container cluster support is becoming a source of revenue for consulting services. This paper presents i2kit, a deployment tool based on the immutable infrastructure pattern, where the virtual machine is the unit of deployment. The input for i2kit is a declarative definition of a set of microservices, where each microservice is defined as a pod of containers. Microservices are built into machine images using linuxkit —- a tool for creating minimal linux distributions specialized in running containers. These machine images are then deployed to one or more virtual machines, which are exposed through a cloud vendor load balancer. Finally, the load balancer endpoint is set into other microservices using an environment variable, providing service discovery. The toolkit i2kit reuses the best ideas from container technology to solve problems like reproducible environments, process isolation, and software distribution, and at the same time relies on mature, proven cloud vendor technology for networking, load balancing and persistency. The result is a more robust system with no learning curve for troubleshooting running applications. We have implemented an open source prototype that transforms i2kit definitions into AWS cloud formation templates, where each microservice AMI (Amazon Machine Image) is created on the fly using linuxkit. Even though container cluster management tools have more flexibility for resource allocation optimization, we defend that adding a new control layer implies more important disadvantages. Resource allocation is greatly improved by using linuxkit, which introduces a very small footprint (around 35MB). Also, the system is more secure since linuxkit installs the minimum set of dependencies to run containers. The toolkit i2kit is currently under development at the IMDEA Software Institute.

Keywords: container, deployment, immutable infrastructure, microservice

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