Search results for: compensation tool
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5293

Search results for: compensation tool

193 A Rural Journey of Integrating Interprofessional Education to Foster Trust

Authors: Julia Wimmers Klick

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Interprofessional Education (IPE) is widely recognized as a valuable approach in healthcare education, despite the challenges it presents. This study explores IP surface anatomy lab sessions, with a focus on fostering trust and collaboration among healthcare students. The research is conducted within the context of rural healthcare settings in British Columbia (BC), where a medical school and a physical therapy (PT) program operate under the Faculty of Medicine at the University of British Columbia (UBC). While IPE sessions addressing soft skills have been implemented, the integration of hard skills, such as Anatomy, remains limited. To address this gap, a pilot feasibility study was conducted with a positive outcome, a follow-up study involved these IPE sessions aimed at exploring the influence of bonding and trust between medical and PT students. Data were collected through focus groups comprising participating students and faculty members, and a structured SWOC (Strengths, Weaknesses, Opportunities, and Challenges) analysis was conducted. The IPE sessions, 3 in total, consisted of a 2.5-hour lab on surface anatomy, where PT students took on the teaching role, and medical students were newly exposed to surface anatomy. The focus of the study was on the relationship-building process and trust development between the two student groups, rather than assessing the acquisition of surface anatomy skills. Results indicated that the surface anatomy lab served as a suitable tool for the application and learning of soft skills. Faculty members observed positive outcomes, including productive interaction between students, reversed hierarchy with PT students teaching medical students, practicing active listening skills, and using a mutual language of anatomy. Notably, there was no grade assessment or external pressure to perform. The students also reported an overall positive experience; however, the specific impact on the development of soft skill competencies could not be definitively determined. Participants expressed a sense of feeling respected, welcomed, and included, all of which contributed to feeling safe. Within the small group environment, students experienced becoming a part of a community of healthcare providers that bonded over a shared interest in health professions education. They enjoyed sharing diverse experiences related to learning across their varied contexts, without fear of judgment and reprisal that were often intimidating in single professional contexts. During a joint Christmas party for both cohorts, faculty members observed students mingling, laughing, and forming bonds. This emphasized the importance of early bonding and trust development among healthcare colleagues, particularly in rural settings. In conclusion, the findings emphasize the potential of IPE sessions to enhance trust and collaboration among healthcare students, with implications for their future professional lives in rural settings. Early bonding and trust development are crucial in rural settings, where healthcare professionals often rely on each other. Future research should continue to explore the impact of content-concentrated IPE on the development of soft skill competencies.

Keywords: interprofessional education, rural healthcare settings, trust, surface anatomy

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192 Deep Learning Based Text to Image Synthesis for Accurate Facial Composites in Criminal Investigations

Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

Procedia PDF Downloads 164
191 Non-Invasive Evaluation of Patients After Percutaneous Coronary Revascularization. The Role of Cardiac Imaging

Authors: Abdou Elhendy

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Numerous study have shown the efficacy of the percutaneous intervention (PCI) and coronary stenting in improving left ventricular function and relieving exertional angina. Furthermore, PCI remains the main line of therapy in acute myocardial infarction. Improvement of procedural techniques and new devices have resulted in an increased number of PCI in those with difficult and extensive lesions, multivessel disease as well as total occlusion. Immediate and late outcome may be compromised by acute thrombosis or the development of fibro-intimal hyperplasia. In addition, progression of coronary artery disease proximal or distal to the stent as well as in non-stented arteries is not uncommon. As a result, complications can occur, such as acute myocardial infarction, worsened heart failure or recurrence of angina. In a stent, restenosis can occur without symptoms or with atypical complaints rendering the clinical diagnosis difficult. Routine invasive angiography is not appropriate as a follow up tool due to associated risk and cost and the limited functional assessment. Exercise and pharmacologic stress testing are increasingly used to evaluate the myocardial function, perfusion and adequacy of revascularization. Information obtained by these techniques provide important clues regarding presence and severity of compromise in myocardial blood flow. Stress echocardiography can be performed in conjunction with exercise or dobutamine infusion. The diagnostic accuracy has been moderate, but the results provide excellent prognostic stratification. Adding myocardial contrast agents can improve imaging quality and allows assessment of both function and perfusion. Stress radionuclide myocardial perfusion imaging is an alternative to evaluate these patients. The extent and severity of wall motion and perfusion abnormalities observed during exercise or pharmacologic stress are predictors of survival and risk of cardiac events. According to current guidelines, stress echocardiography and radionuclide imaging are considered to have appropriate indication among patients after PCI who have cardiac symptoms and those who underwent incomplete revascularization. Stress testing is not recommended in asymptomatic patients, particularly early after revascularization, Coronary CT angiography is increasingly used and provides high sensitive for the diagnosis of coronary artery stenosis. Average sensitivity and specificity for the diagnosis of in stent stenosis in pooled data are 79% and 81%, respectively. Limitations include blooming artifacts and low feasibility in patients with small stents or thick struts. Anatomical and functional cardiac imaging modalities are corner stone for the assessment of patients after PCI and provide salient diagnostic and prognostic information. Current imaging techniques cans serve as gate keeper for coronary angiography, thus limiting the risk of invasive procedures to those who are likely to benefit from subsequent revascularization. The determination of which modality to apply requires careful identification of merits and limitation of each technique as well as the unique characteristic of each individual patient.

Keywords: coronary artery disease, stress testing, cardiac imaging, restenosis

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190 Psychogeographic Analysis of Spatial Appropriation within Walking Practice: The City Centre versus University Campus in the Case of Van, Turkey

Authors: Yasemin Ilkay

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Urban spatial pattern interacts with the minds and bodies of citizens and influences their perception and attitudes, which leads to a two-folded map of the same space: physical and Psychogeographic maps. Psychogeography is a field of inquiry (rooted in literature and fiction) investigating how the environment affects the feelings and behaviors of individuals. This term was posed by Situationist International Movement in the 1950s by Guy Debord; in the course of time, the artistic framework evolved into a political issue, especially with the term Dérive, which indicates ‘deviation’ and ‘resistance’ to the existing spatial reality. The term Dérive appeared on the track of Flânéur after one hundred years; and turned out to be a political tool to transform everyday urban life. The three main concepts of psychogeography [walking, dérive, and palimpsest] construct the epistemological framework for a psychogeographic spatial analysis. Mental representations investigating this framework would provide a designer to capture the invisible layers of the gap between ‘how a space is conceived’ and ‘how the same space is perceived and experienced.’ This gap is a neglected but critical issue to discuss in the planning discipline, and psychogeography provides methodological inputs to cover the interrelation among top-down designs of urban patterning and bottom-up reproductions of ‘the soul’ of urban space at the intersection of geography and psychology. City centers and university campuses exemplify opposite poles of spatial organization and walking practice, which may result in differentiated spatial appropriation forms. There is a traditional city center in Van, located at the core of the city with a dense population and several activities, but not connected to Van Lake, which is the largest lake in the country. On the other hand, the university campus is located at the periphery, and although it has a promenade along the lake’s coast and a regional hospital, it presents a limited walking experience with ambiguous forms of spatial appropriation. The city center draws a vivid urban everyday life; however, the campus presents a relatively natural life far away from the center. This paper aims to reveal the differentiated psychogeographic maps of spatial appropriation at the city center vs. the university campus, which is located at the periphery of the city and along the coast of the largest lake in Turkey. The main question of the paper is, “how do the psychogeographic maps of spatial appropriation differentiate at the city center and university campus in Van within the walking experience with reference to the two-folded map assumption.” The experiential maps of a core group of 15 planning students will be created with the techniques of mental mapping, photographing, and narratives through attentive walks conducted together on selected routes; in addition to these attentive walks, 30 more in-depth interviews will be conducted by the core group. The narrative of psychogeographic mapping of spatial appropriation at the two spatial poles would display the conflicting soul of the city with reference to sub-behavioural regions of walking, differentiated forms of derive and layers of palimpsest.

Keywords: attentive walk, body, cognitive geography, derive, experiential maps, psychogeography, Van, Turkey

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189 The Evaluation of Child Maltreatment Severity and the Decision-Making Processes in the Child Protection System

Authors: Maria M. Calheiros, Carla Silva, Eunice Magalhães

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Professionals working in child protection services (CPS) need to have common and clear criteria to identify cases of maltreatment and to differentiate levels of severity in order to determine when CPS intervention is required, its nature and urgency, and, in most countries, the service that will be in charge of the case (community or specialized CPS). Actually, decision-making process is complex in CPS, and, for that reason, such criteria are particularly important for who significantly contribute to that decision-making in child maltreatment cases. The main objective of this presentation is to describe the Maltreatment Severity Assessment Questionnaire (MSQ), specifically designed to be used by professionals in the CPS, which adopts a multidimensional approach and uses a scale of severity within subtypes. Specifically, we aim to provide evidence of validity and reliability of this tool, in order to improve the quality and validity of assessment processes and, consequently, the decision making in CPS. The total sample was composed of 1000 children and/or adolescents (51.1% boys), aged between 0 and 18 years old (M = 9.47; DP = 4.51). All the participants were referred to official institutions of the children and youth protective system. Children and adolescents maltreatment (abuse, neglect experiences and sexual abuse) were assessed with 21 items of the Maltreatment Severity Questionnaire (MSQ), by professionals of CPS. Each item (sub-type) was composed of four descriptors of increasing severity. Professionals rated the level of severity, using a 4-point scale (1= minimally severe; 2= moderately severe; 3= highly severe; 4= extremely severe). The construct validity of the Maltreatment Severity Questionnaire was assessed with a holdout method, performing an Exploratory Factor Analysis (EFA) followed by a Confirmatory Factor Analysis (CFA). The final solution comprised 18 items organized in three factors 47.3% of variance explained. ‘Physical neglect’ (eight items) was defined by parental omissions concerning the insurance and monitoring of the child’s physical well-being and health, namely in terms of clothing, hygiene, housing conditions and contextual environmental security. ‘Physical and Psychological Abuse’ (four items) described abusive physical and psychological actions, namely, coercive/punitive disciplinary methods, physically violent methods or verbal interactions that offend and denigrate the child, with the potential to disrupt psychological attributes (e.g., self-esteem). ‘Psychological neglect’ (six items) involved omissions related to children emotional development, mental health monitoring, school attendance, development needs, as well as inappropriate relationship patterns with attachment figures. Results indicated a good reliability of all the factors. The assessment of child maltreatment cases with MSQ could have a set of practical and research implications: a) It is a valid and reliable multidimensional instrument to measure child maltreatment, b) It is an instrument integrating the co-occurrence of various types of maltreatment and a within-subtypes scale of severity; c) Specifically designed for professionals, it may assist them in decision-making processes; d) More than using case file reports to evaluate maltreatment experiences, researchers could guide more appropriately their research about determinants and consequences of maltreatment.

Keywords: assessment, maltreatment, children and youth, decision-making

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188 Improving Road Infrastructure Safety Management Through Statistical Analysis of Road Accident Data. Case Study: Streets in Bucharest

Authors: Dimitriu Corneliu-Ioan, Gheorghe FrațIlă

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Romania has one of the highest rates of road deaths among European Union Member States, and there is a concern that the country will not meet its goal of "zero deaths" by 2050. The European Union also aims to halve the number of people seriously injured in road accidents by 2030. Therefore, there is a need to improve road infrastructure safety management in Romania. The aim of this study is to analyze road accident data through statistical methods to assess the current state of road infrastructure safety in Bucharest. The study also aims to identify trends and make forecasts regarding serious road accidents and their consequences. The objective is to provide insights that can help prioritize measures to increase road safety, particularly in urban areas. The research utilizes statistical analysis methods, including exploratory analysis and descriptive statistics. Databases from the Traffic Police and the Romanian Road Authority are analyzed using Excel. Road risks are compared with the main causes of road accidents to identify correlations. The study emphasizes the need for better quality and more diverse collection of road accident data for effective analysis in the field of road infrastructure engineering. The research findings highlight the importance of prioritizing measures to improve road safety in urban areas, where serious accidents and their consequences are more frequent. There is a correlation between the measures ordered by road safety auditors and the main causes of serious accidents in Bucharest. The study also reveals the significant social costs of road accidents, amounting to approximately 3% of GDP, emphasizing the need for collaboration between local and central administrations in allocating resources for road safety. This research contributes to a clearer understanding of the current road infrastructure safety situation in Romania. The findings provide critical insights that can aid decision-makers in allocating resources efficiently and institutionally cooperating to achieve sustainable road safety. The data used for this study are collected from the Traffic Police and the Romanian Road Authority. The data processing involves exploratory analysis and descriptive statistics using the Excel tool. The analysis allows for a better understanding of the factors contributing to the current road safety situation and helps inform managerial decisions to eliminate or reduce road risks. The study addresses the state of road infrastructure safety in Bucharest and analyzes the trends and forecasts regarding serious road accidents and their consequences. It studies the correlation between road safety measures and the main causes of serious accidents. To improve road safety, cooperation between local and central administrations towards joint financial efforts is important. This research highlights the need for statistical data processing methods to substantiate managerial decisions in road infrastructure management. It emphasizes the importance of improving the quality and diversity of road accident data collection. The research findings provide a critical perspective on the current road safety situation in Romania and offer insights to identify appropriate solutions to reduce the number of serious road accidents in the future.

Keywords: road death rate, strategic objective, serious road accidents, road safety, statistical analysis

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187 Using Business Simulations and Game-Based Learning for Enterprise Resource Planning Implementation Training

Authors: Carin Chuang, Kuan-Chou Chen

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An Enterprise Resource Planning (ERP) system is an integrated information system that supports the seamless integration of all the business processes of a company. Implementing an ERP system can increase efficiencies and decrease the costs while helping improve productivity. Many organizations including large, medium and small-sized companies have already adopted an ERP system for decades. Although ERP system can bring competitive advantages to organizations, the lack of proper training approach in ERP implementation is still a major concern. Organizations understand the importance of ERP training to adequately prepare managers and users. The low return on investment, however, for the ERP training makes the training difficult for knowledgeable workers to transfer what is learned in training to the jobs at workplace. Inadequate and inefficient ERP training limits the value realization and success of an ERP system. That is the need to call for a profound change and innovation for ERP training in both workplace at industry and the Information Systems (IS) education in academia. The innovated ERP training approach can improve the users’ knowledge in business processes and hands-on skills in mastering ERP system. It also can be instructed as educational material for IS students in universities. The purpose of the study is to examine the use of ERP simulation games via the ERPsim system to train the IS students in learning ERP implementation. The ERPsim is the business simulation game developed by ERPsim Lab at HEC Montréal, and the game is a real-life SAP (Systems Applications and Products) ERP system. The training uses the ERPsim system as the tool for the Internet-based simulation games and is designed as online student competitions during the class. The competitions involve student teams with the facilitation of instructor and put the students’ business skills to the test via intensive simulation games on a real-world SAP ERP system. The teams run the full business cycle of a manufacturing company while interacting with suppliers, vendors, and customers through sending and receiving orders, delivering products and completing the entire cash-to-cash cycle. To learn a range of business skills, student needs to adopt individual business role and make business decisions around the products and business processes. Based on the training experiences learned from rounds of business simulations, the findings show that learners have reduced risk in making mistakes that help learners build self-confidence in problem-solving. In addition, the learners’ reflections from their mistakes can speculate the root causes of the problems and further improve the efficiency of the training. ERP instructors teaching with the innovative approach report significant improvements in student evaluation, learner motivation, attendance, engagement as well as increased learner technology competency. The findings of the study can provide ERP instructors with guidelines to create an effective learning environment and can be transferred to a variety of other educational fields in which trainers are migrating towards a more active learning approach.

Keywords: business simulations, ERP implementation training, ERPsim, game-based learning, instructional strategy, training innovation

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186 Comparative Studies on the Needs and Development of Autotronic Maintenance Training Modules for the Training of Automobile Independent Workshop Service Technicians in North – Western Region, Nigeria

Authors: Muhammad Shuaibu Birniwa

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Automobile Independent Workshop Service Technicians (popularly called roadside mechanics) are technical personals that repairs most of the automobile vehicles in Nigeria. Majority of these mechanics acquired their skills through apprenticeship training. Modern vehicle imported into the country posed greater challenges to the present automobile technicians particularly in the area of carrying out maintenance repairs of these latest automobile vehicles (autotronics vehicle) due to their inability to possessed autotronic skills competency. To source for solution to the above mentioned problems, therefore a research is carried out in North – Western region of Nigeria to produce a suitable maintenance training modules that can be used to train the technicians for them to upgrade/acquire the needed competencies for successful maintenance repair of the autotronic vehicles that were running everyday on the nation’s roads. A cluster sampling technique is used to obtain a sample from the population. The population of the study is all autotronic inclined lecturers, instructors and independent workshop service technicians that are within North – Western region of Nigeria. There are seven states (Jigawa, Kaduna, Kano, Katsina, Kebbi, Sokoto and Zamfara) in the study area, these serves as clusters in the population. Five (5) states were randomly selected to serve as the sample size. The five states are Jigawa, Kano, Katsina, Kebbi and Zamfara, the entire population of the five states which serves as clusters is (183), lecturers (44), instructors (49) and autotronic independent workshop service technicians (90), all of them were used in the study because of their manageable size. 183 copies of autotronic maintenance training module questionnaires (AMTMQ) with 174 and 149 question items respectively were administered and collected by the researcher with the help of an assistants, they are administered to 44 Polytechnic lecturers in the department of mechanical engineering, 49 instructors in skills acquisition centres/polytechnics and 90 master craftsmen of an independent workshops that are autotronic inclined. Data collected for answering research questions 1, 3, 4 and 5 were analysed using SPSS software version 22, Grand Mean and standard deviation were used to answer the research questions. Analysis of Variance (ANOVA) was used to test null hypotheses one (1) to three (3) and t-test statistical tool is used to analyzed hypotheses four (4) and five (5) all at 0.05 level of significance. The research conducted revealed that; all the objectives, contents/tasks, facilities, delivery systems and evaluation techniques contained in the questionnaire were required for the development of the autotronic maintenance training modules for independent workshop service technicians in the north – western zone of Nigeria. The skills upgrade training conducted by federal government in collaboration with SURE-P, NAC and SMEDEN was not successful because the educational status of the target population was not considered in drafting the needed training modules. The mode of training used does not also take cognizance of the theoretical aspect of the trainees, especially basic science which rendered the programme ineffective and insufficient for the tasks on ground.

Keywords: autotronics, roadside, mechanics, technicians, independent

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185 Rapid Building Detection in Population-Dense Regions with Overfitted Machine Learning Models

Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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184 A Flipped Learning Experience in an Introductory Course of Information and Communication Technology in Two Bachelor's Degrees: Combining the Best of Online and Face-to-Face Teaching

Authors: Begona del Pino, Beatriz Prieto, Alberto Prieto

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Two opposite approaches to teaching can be considered: in-class learning (teacher-oriented) versus virtual learning (student-oriented). The most known example of the latter is Massive Online Open Courses (MOOCs). Both methodologies have pros and cons. Nowadays there is an increasing trend towards combining both of them. Blending learning is considered a valuable tool for improving learning since it combines student-centred interactive e-learning and face to face instruction. The aim of this contribution is to exchange and share the experience and research results of a blended-learning project that took place in the University of Granada (Spain). The research objective was to prove how combining didactic resources of a MOOC with in-class teaching, interacting directly with students, can substantially improve academic results, as well as student acceptance. The proposed methodology is based on the use of flipped learning technics applied to the subject ‘Fundamentals of Computer Science’ of the first course of two degrees: Telecommunications Engineering, and Industrial Electronics. In this proposal, students acquire the theoretical knowledges at home through a MOOC platform, where they watch video-lectures, do self-evaluation tests, and use other academic multimedia online resources. Afterwards, they have to attend to in-class teaching where they do other activities in order to interact with teachers and the rest of students (discussing of the videos, solving of doubts and practical exercises, etc.), trying to overcome the disadvantages of self-regulated learning. The results are obtained through the grades of the students and their assessment of the blended experience, based on an opinion survey conducted at the end of the course. The major findings of the study are the following: The percentage of students passing the subject has grown from 53% (average from 2011 to 2014 using traditional learning methodology) to 76% (average from 2015 to 2018 using blended methodology). The average grade has improved from 5.20±1.99 to 6.38±1.66. The results of the opinion survey indicate that most students preferred blended methodology to traditional approaches, and positively valued both courses. In fact, 69% of students felt ‘quite’ or ‘very’ satisfied with the classroom activities; 65% of students preferred the flipped classroom methodology to traditional in-class lectures, and finally, 79% said they were ‘quite’ or ‘very’ satisfied with the course in general. The main conclusions of the experience are the improvement in academic results, as well as the highly satisfactory assessments obtained in the opinion surveys. The results confirm the huge potential of combining MOOCs in formal undergraduate studies with on-campus learning activities. Nevertheless, the results in terms of students’ participation and follow-up have a wide margin for improvement. The method is highly demanding for both students and teachers. As a recommendation, students must perform the assigned tasks with perseverance, every week, in order to take advantage of the face-to-face classes. This perseverance is precisely what needs to be promoted among students because it clearly brings about an improvement in learning.

Keywords: blended learning, educational paradigm, flipped classroom, flipped learning technologies, lessons learned, massive online open course, MOOC, teacher roles through technology

Procedia PDF Downloads 182
183 Small Town Big Urban Issues the Case of Kiryat Ono, Israel

Authors: Ruth Shapira

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Introduction: The rapid urbanization of the last century confronts planners, regulatory bodies, developers and most of all – the public with seemingly unsolved conflicts regarding values, capital, and wellbeing of the built and un-built urban space. This is reflected in the quality of the urban form and life which has known no significant progress in the last 2-3 decades despite the on-growing urban population. It is the objective of this paper to analyze some of these fundamental issues through the case study of a relatively small town in the center of Israel (Kiryat-Ono, 100,000 inhabitants), unfold the deep structure of qualities versus disruptors, present some cure that we have developed to bridge over and humbly suggest a practice that may be generic for similar cases. Basic Methodologies: The OBJECT, the town of Kiryat Ono, shall be experimented upon in a series of four action processes: De-composition, Re-composition, the Centering process and, finally, Controlled Structural Disintegration. Each stage will be based on facts, analysis of previous multidisciplinary interventions on various layers – and the inevitable reaction of the OBJECT, leading to the conclusion based on innovative theoretical and practical methods that we have developed and that we believe are proper for the open ended network, setting the rules for the contemporary urban society to cluster by. The Study: Kiryat Ono, was founded 70 years ago as an agricultural settlement and rapidly turned into an urban entity. In spite the massive intensification, the original DNA of the old small town was still deeply embedded, mostly in the quality of the public space and in the sense of clustered communities. In the past 20 years, the recent demand for housing has been addressed to on the national level with recent master plans and urban regeneration policies mostly encouraging individual economic initiatives. Unfortunately, due to the obsolete existing planning platform the present urban renewal is characterized by pressure of developers, a dramatic change in building scale and widespread disintegration of the existing urban and social tissue. Our office was commissioned to conceptualize two master plans for the two contradictory processes of Kiryat Ono’s future: intensification and conservation. Following a comprehensive investigation into the deep structures and qualities of the existing town, we developed a new vocabulary of conservation terms thus redefying the sense of PLACE. The main challenge was to create master plans that should offer a regulatory basis to the accelerated and sporadic development providing for the public good and preserving the characteristics of the PLACE consisting of a tool box of design guidelines that will have the ability to reorganize space along the time axis in a coherent way. In Conclusion: The system of rules that we have developed can generate endless possible patterns making sure that at each implementation fragment an event is created, and a better place is revealed. It takes time and perseverance but it seems to be the way to provide a healthy framework for the accelerated urbanization of our chaotic present.

Keywords: housing, architecture, urban qualities, urban regeneration, conservation, intensification

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182 Geophysical Methods and Machine Learning Algorithms for Stuck Pipe Prediction and Avoidance

Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

Procedia PDF Downloads 235
181 An Online Space for Practitioners in the Water, Sanitation and Hygiene Sector

Authors: Olivier Mills, Bernard McDonell, Laura A. S. MacDonald

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The increasing availability and quality of internet access throughout the developing world provides an opportunity to utilize online spaces to disseminate water, sanitation and hygiene (WASH) knowledge to practitioners. Since 2001, CAWST has provided in-person education, training and consulting services to thousands of WASH practitioners all over the world, supporting them to start, troubleshoot, improve and expand their WASH projects. As CAWST continues to grow, the organization faces challenges in meeting demand from clients and in providing consistent, timely technical support. In 2012, CAWST began utilizing online spaces to expand its reach by developing a series of resources websites and webinars. CAWST has developed a WASH Education and Training resources website, a Biosand Filter (BSF) Knowledge Base, a Household Water Treatment and Safe Storage Knowledge Base, a mobile app for offline users, a live chat support tool, a WASH e-library, and a series of webinar-style online training sessions to complement its in-person capacity development services. In order to determine the preliminary outcomes of providing these online services, CAWST has monitored and analyzed registration to the online spaces, downloads of the educational materials, and webinar attendance; as well as conducted user surveys. The purpose of this analysis was to find out who was using the online spaces, where users came from, and how the resources were being used. CAWST’s WASH Resources website has served over 5,800 registered users from 3,000 organizations in 183 countries. Additionally, the BSF Knowledge Base has served over 1000 registered users from 68 countries, and over 540 people from 73 countries have attended CAWST’s online training sessions. This indicates that the online spaces are effectively reaching a large numbers of users, from a range of countries. A 2016 survey of the Biosand Filter Knowledge Base showed that approximately 61% of users are practitioners, and 39% are either researchers or students. Of the respondents, 46% reported using the BSF Knowledge Base to initiate a BSF project and 43% reported using the information to train BSF technicians. Finally, 61% indicated they would like even greater support from CAWST’s Technical Advisors going forward. The analysis has provided an encouraging indication that CAWST’s online spaces are contributing to its objective of engaging and supporting WASH practitioners to start, improve and expand their initiatives. CAWST has learned several lessons during the development of these online spaces, in particular related to the resources needed to create and maintain the spaces, and respond to the demand created. CAWST plans to continue expanding its online spaces, improving user experience of the sites, and involving new contributors and content types. Through the use of online spaces, CAWST has been able to increase its global reach and impact without significantly increasing its human resources by connecting WASH practitioners with the information they most need, in a practical and accessible manner. This paper presents on CAWST’s use of online spaces through the CAWST-developed platforms discussed above and the analysis of the use of these platforms.

Keywords: education and training, knowledge sharing, online resources, water and sanitation

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180 Bio-Psycho-Social Consequences and Effects in Fall-Efficacy Scale in Seniors Using Exercise Intervention of Motor Learning According to Yoga Techniques

Authors: Milada Krejci, Martin Hill, Vaclav Hosek, Dobroslava Jandova, Jiri Kajzar, Pavel Blaha

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The paper declares effects of exercise intervention of the research project “Basic research of balance changes in seniors”, granted by the Czech Science Foundation. The objective of the presented study is to define predictors, which influence bio-psycho-social consequences and effects of balance ability in senior 65 years old and above. We focused on the Fall-Efficacy Scale changes evaluation in seniors. Comprehensive hypothesis of the project declares, that motion uncertainty (dyskinesia) can negatively affect the well-being of a senior in bio-psycho-social context. In total, random selection and testing of 100 seniors (30 males, 70 females) from Prague and Central Bohemian region was provided. The sample was divided by stratified random selection into experimental and control groups, who underwent input and output testing. For diagnostics the methods of Medical Anamnesis, Functional anthropological examinations, Tinetti Balance Assessment Tool, SF-36 Health Survey, Anamnestic comparative self-assessment scale were used. Intervention method called "Life in Balance" based on yoga techniques was applied in four-week cycle. Results of multivariate regression were verified by repeated measures ANOVA: subject factor, phase of intervention (between-subject factor), body fluid (within-subject factor) and phase of intervention × body fluid interaction). ANOVA was performed with a repetition involving the factors of subjects, experimental/control group, phase of intervention (independent variable), and x phase interaction followed by Bonferroni multiple comparison assays with a test strength of at least 0.8 on the probability level p < 0.05. In the paper results of the first-year investigation of the three years running project are analysed. Results of balance tests confirmed no significant difference between females and males in pre-test. Significant improvements in balance and walking ability were observed in experimental group in females comparing to males (F = 128.4, p < 0.001). In the females control group, there was no significant change in post- test, while in the female experimental group positive changes in posture and spine flexibility in post-tests were found. It seems that females even in senior age react better to incentives of intervention in balance and spine flexibility. On the base of results analyses, we can declare the significant improvement in social balance markers after intervention in the experimental group (F = 10.5, p < 0.001). In average, seniors are used to take four drugs daily. Number of drugs can contribute to allergy symptoms and balance problems. It can be concluded that static balance and walking ability of seniors according Tinetti Balance scale correlate significantly with psychic and social monitored markers.

Keywords: exercises, balance, seniors 65+, health, mental and social balance

Procedia PDF Downloads 139
179 Identifying Risk Factors for Readmission Using Decision Tree Analysis

Authors: Sıdıka Kaya, Gülay Sain Güven, Seda Karsavuran, Onur Toka

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This study is part of an ongoing research project supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 114K404, and participation to this conference was supported by Hacettepe University Scientific Research Coordination Unit under Project Number 10243. Evaluation of hospital readmissions is gaining importance in terms of quality and cost, and is becoming the target of national policies. In Turkey, the topic of hospital readmission is relatively new on agenda and very few studies have been conducted on this topic. The aim of this study was to determine 30-day readmission rates and risk factors for readmission. Whether readmission was planned, related to the prior admission and avoidable or not was also assessed. The study was designed as a ‘prospective cohort study.’ 472 patients hospitalized in internal medicine departments of a university hospital in Turkey between February 1, 2015 and April 30, 2015 were followed up. Analyses were conducted using IBM SPSS Statistics version 22.0 and SPSS Modeler 16.0. Average age of the patients was 56 and 56% of the patients were female. Among these patients 95 were readmitted. Overall readmission rate was calculated as 20% (95/472). However, only 31 readmissions were unplanned. Unplanned readmission rate was 6.5% (31/472). Out of 31 unplanned readmission, 24 was related to the prior admission. Only 6 related readmission was avoidable. To determine risk factors for readmission we constructed Chi-square automatic interaction detector (CHAID) decision tree algorithm. CHAID decision trees are nonparametric procedures that make no assumptions of the underlying data. This algorithm determines how independent variables best combine to predict a binary outcome based on ‘if-then’ logic by portioning each independent variable into mutually exclusive subsets based on homogeneity of the data. Independent variables we included in the analysis were: clinic of the department, occupied beds/total number of beds in the clinic at the time of discharge, age, gender, marital status, educational level, distance to residence (km), number of people living with the patient, any person to help his/her care at home after discharge (yes/no), regular source (physician) of care (yes/no), day of discharge, length of stay, ICU utilization (yes/no), total comorbidity score, means for each 3 dimensions of Readiness for Hospital Discharge Scale (patient’s personal status, patient’s knowledge, and patient’s coping ability) and number of daycare admissions within 30 days of discharge. In the analysis, we included all 95 readmitted patients (46.12%), but only 111 (53.88%) non-readmitted patients, although we had 377 non-readmitted patients, to balance data. The risk factors for readmission were found as total comorbidity score, gender, patient’s coping ability, and patient’s knowledge. The strongest identifying factor for readmission was comorbidity score. If patients’ comorbidity score was higher than 1, the risk for readmission increased. The results of this study needs to be validated by other data–sets with more patients. However, we believe that this study will guide further studies of readmission and CHAID is a useful tool for identifying risk factors for readmission.

Keywords: decision tree, hospital, internal medicine, readmission

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178 The Recommended Summary Plan for Emergency Care and Treatment (ReSPECT) Process: An Audit of Its Utilisation on a UK Tertiary Specialist Intensive Care Unit

Authors: Gokulan Vethanayakam, Daniel Aston

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Introduction: The ReSPECT process supports healthcare professionals when making patient-centered decisions in the event of an emergency. It has been widely adopted by the NHS in England and allows patients to express thoughts and wishes about treatments and outcomes that they consider acceptable. It includes (but is not limited to) cardiopulmonary resuscitation decisions. ReSPECT conversations should ideally occur prior to ICU admission and should be documented in the eight sections of the nationally-standardised ReSPECT form. This audit evaluated the use of ReSPECT on a busy cardiothoracic ICU in an NHS Trust where established policies advocating its use exist. Methods: This audit was a retrospective review of ReSPECT forms for a sample of high-risk patients admitted to ICU at the Royal Papworth Hospital between January 2021 and March 2022. Patients all received one of the following interventions: Veno-Venous Extra-Corporeal Membrane Oxygenation (VV-ECMO) for severe respiratory failure (retrieved via the national ECMO service); cardiac or pulmonary transplantation-related surgical procedures (including organ transplants and Ventricular Assist Device (VAD) implantation); or elective non-transplant cardiac surgery. The quality of documentation on ReSPECT forms was evaluated using national standards and a graded ranking tool devised by the authors which was used to assess narrative aspects of the forms. Quality was ranked as A (excellent) to D (poor). Results: Of 230 patients (74 VV-ECMO, 104 transplant, 52 elective non-transplant surgery), 43 (18.7%) had a ReSPECT form and only one (0.43%) patient had a ReSPECT form completed prior to ICU admission. Of the 43 forms completed, 38 (88.4%) were completed due to the commencement of End of Life (EoL) care. No non-transplant surgical patients included in the audit had a ReSPECT form. There was documentation of balance of care (section 4a), CPR status (section 4c), capacity assessment (section 5), and patient involvement in completing the form (section 6a) on all 43 forms. Of the 34 patients assessed as lacking capacity to make decisions, only 22 (64.7%) had reasons documented. Other sections were variably completed; 29 (67.4%) forms had relevant background information included to a good standard (section 2a). Clinical guidance for the patient (section 4b) was given in 25 (58.1%), of which 11 stated the rationale that underpinned it. Seven forms (16.3%) contained information in an inappropriate section. In a comparison of ReSPECT forms completed ahead of an EoL trigger with those completed when EoL care began, there was a higher number of entries in section 3 (considering patient’s values/fears) that were assessed at grades A-B in the former group (p = 0.014), suggesting higher quality. Similarly, forms from the transplant group contained higher quality information in section 3 than those from the VV-ECMO group (p = 0.0005). Conclusions: Utilisation of the ReSPECT process in high-risk patients is yet to be well-adopted in this trust. Teams who meet patients before hospital admission for transplant or high-risk surgery should be encouraged to engage with the ReSPECT process at this point in the patient's journey. VV-ECMO retrieval teams should consider ReSPECT conversations with patients’ relatives at the time of retrieval.

Keywords: audit, critical care, end of life, ICU, ReSPECT, resuscitation

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177 An Eco-Systemic Typology of Fashion Resale Business Models in Denmark

Authors: Mette Dalgaard Nielsen

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The paper serves the purpose of providing an eco-systemic typology of fashion resale business models in Denmark while pointing to possibilities to learn from its wisdom during a time when a fundamental break with the dominant linear fashion paradigm has become inevitable. As we transgress planetary boundaries and can no longer continue the unsustainable path of over-exploiting the Earth’s resources, the global fashion industry faces a tremendous need for change. One of the preferred answers to the fashion industry’s sustainability crises lies in the circular economy, which aims to maximize the utilization of resources by keeping garments in use for longer. Thus, in the context of fashion, resale business models that allow pre-owned garments to change hands with the purpose of being reused in continuous cycles are considered to be among the most efficient forms of circularity. Methodologies: The paper is based on empirical data from an ongoing project and a series of qualitative pilot studies that have been conducted on the Danish resale market over a 2-year time period from Fall 2021 to Fall 2023. The methodological framework is comprised of (n) ethnography and fieldwork in selected resale environments, as well as semi-structured interviews and a workshop with eight business partners from the Danish fashion and textiles industry. By focusing on the real-world circulation of pre-owned garments, which is enabled by the identified resale business models, the research lets go of simplistic hypotheses to the benefit of dynamic, vibrant and non-linear processes. As such, the paper contributes to the emerging research field of circular economy and fashion, which finds itself in a critical need to move from non-verified concepts and theories to empirical evidence. Findings: Based on the empirical data and anchored in the business partners, the paper analyses and presents five distinct resale business models with different product, service and design characteristics. These are 1) branded resale, 2) trade-in resale, 3) peer-2-peer resale, 4) resale boutiques and consignment shops and 5) resale shelf/square meter stores and flea markets. Together, the five business models represent a plurality of resale-promoting business model design elements that have been found to contribute to the circulation of pre-owned garments in various ways for different garments, users and businesses in Denmark. Hence, the provided typology points to the necessity of prioritizing several rather than single resale business model designs, services and initiatives for the resale market to help reconfigure the linear fashion model and create a circular-ish future. Conclusions: The article represents a twofold research ambition by 1) presenting an original, up-to-date eco-systemic typology of resale business models in Denmark and 2) using the typology and its eco-systemic traits as a tool to understand different business model design elements and possibilities to help fashion grow out of its linear growth model. By basing the typology on eco-systemic mechanisms and actual exemplars of resale business models, it becomes possible to envision the contours of a genuine alternative to business as usual that ultimately helps bend the linear fashion model towards circularity.

Keywords: circular business models, circular economy, fashion, resale, strategic design, sustainability

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176 Where do Pregnant Women Miss Out on Nutrition? Analysis of Survey Data from 22 Countries

Authors: Alexis D'Agostino, Celeste Sununtunasuk, Jack Fiedler

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Background: Iron-folic acid (IFA) supplementation during antenatal care (ANC) has existed in many countries for decades. Despite this, low national coverage persists and women do not often consume appropriate amounts during pregnancy. USAID’s SPRING Project investigated pregnant women’s access to, and consumption of, IFA tablets through ANC. Cross-country analysis provided a global picture of the state of IFA-supplementation, while country-specific results noted key contextual issues, including geography, wealth, and ANC attendance. The analysis can help countries prioritize strategies for systematic performance improvements within one of the most common micronutrient supplementation programs aimed at reducing maternal anemia. Methodology: Using falter point analysis on Demographic and Health Survey (DHS) data collected from 162,958 women across 22 countries, SPRING identified four sequential falter points (ANC attendance, IFA receipt or purchase, IFA consumption, and number of tablets taken) where pregnant women fell out of the IFA distribution structure. SPRING analyzed data on IFA intake from DHS surveys with women of reproductive age. SPRING disaggregated these data by ANC participation during the most recent pregnancy, residency, and women’s socio-economic status. Results: Average sufficient IFA tablet use across all countries was only eight percent. Even in the best performing countries, only about one-third of pregnant women consumed 180 or more IFA tablets during their most recent pregnancy. ANC attendance was an important falter point for a quarter of women across all countries (with highest falter rates in Democratic Republic of the Congo, Nigeria, and Niger). Further analysis reveals patterns, with some countries having high ANC coverage but low IFA provision during ANC (DRC and Haiti), others having high ANC coverage and IFA provision but few women taking any tablets (Nigeria and Liberia), and countries that perform well in ANC, supplies, and initial consumption but where very few women consume the recommended 180 tablets (Malawi and Cambodia). Country-level analysis identifies further patterns of supplementation. In Indonesia, for example, only 62% of women in the poorest quintile took even one IFA tablet, while 86% of the wealthiest women did. This association between socioeconomic status and IFA intake held across nearly all countries where these data are available and was also visible in rural/urban comparisons. Analysis of ANC attendance data also suggests that higher numbers of ANC visits are associated with higher tablet intake. Conclusions: While it is difficult to disentangle which specific aspects of supply or demand cause the low rates of consumption, this tool allows policy-makers to identify major bottlenecks to scaling-up IFA supplementation during ANC. In turn, each falter point provides possible explanations of program performance and helps strategically identify areas for improved IFA supplementation. For example, improving the delivery of IFA supplementation in Ethiopia relies on increasing access to ANC, but also on identifying and addressing program gaps in IFA supply management and health workers’ practices in order to provide quality ANC services. While every country requires a customized approach to improving IFA supplementation, the multi-country analysis conducted by SPRING is a helpful first step in identifying country bottlenecks and prioritizing interventions.

Keywords: iron and folic acid, supplementation, antenatal care, micronutrient

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175 Development of the Drug Abuse Health Information System in Thai Community

Authors: Waraporn Boonchieng, Ekkarat Boonchieng, Sivaporn Aungwattana, Decha Tamdee, Wongamporn Pinyavong

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Drug addiction represents one of the most important public health issues in both developed and developing countries. The purpose of this study was to develop a drug abuse health information in a community in Northern Thailand using developmental research design. The developmental researchers performed four phases to develop drug abuse health information, including 1) synthesizing knowledge related to drug abuse prevention and identifying the components of drug abuse health information; 2) developing the system in mobile application and website; 3) implementing drug abuse health information in the rural community; and 4) evaluating the feasibility of drug abuse health information. Data collection involved both qualitative and quantitative procedures. The qualitative data and quantitative data were analyzed using content analysis and descriptive statistics, respectively. The findings of this study showed that drug abuse health information consisted of five sections, including drug-related prevention knowledge for teens, drug-related knowledge for adults and professionals, the database for drug dependence treatment centers, self-administered questionnaires, and supportive counseling sections. First, in drug-related prevention knowledge for teens, the developmental researchers designed four infographics and animation to provide drug-related prevention knowledge, including types of illegal drugs, causes of drug abuse, consequences of drug abuse, drug abuse diagnosis and treatment, and drug abuse prevention. Second, in drug-related knowledge for adults and professionals, the developmental researchers developed many documents in a form of PDF file to provide drug-related knowledge, including types of illegal drugs, causes of drug abuse, drug abuse prevention, and relapse prevention guideline. Third, database for drug dependence treatment centers included the place, direction map, operation time, and the way for contacting all drug dependence treatment centers in Thailand. Fourth, self-administered questionnaires comprised preventive drugs behavior questionnaire, drug abuse knowledge questionnaire, the stages of change readiness and treatment eagerness to drug use scale, substance use behaviors questionnaire, tobacco use behaviors questionnaire, stress screening, and depression screening. Finally, for supportive counseling, the developmental researchers designed chatting box through which each user could write and send their concerns to counselors individually. Results from evaluation process showed that 651 participants used drug abuse health information via mobile application and website. Among all users, 48.8% were males and 51.2% were females. More than half (55.3%) were 15-20 years old and most of them (88.0%) were Buddhists. Most users reported ever getting knowledge related to drugs (86.1%), and drinking alcohol (94.2%) while some of them (6.9%) reported ever using tobacco. For satisfaction with using the drug abuse health information, more than half of users reflected that the contents of drug abuse health information were interesting (59%), up-to date (61%), and highly useful to their self-study (59%) at high level. In addition, half of them were satisfied with the design in terms of infographics (54%) and animation (51%). Thus, this drug abuse health information can be adopted to explore drug abuse situation and serves as a tool to prevent drug abuse and addiction among Thai community people.

Keywords: drug addiction, health informatics, big data, development research

Procedia PDF Downloads 113
174 An Odyssey to Sustainability: The Urban Archipelago of India

Authors: B. Sudhakara Reddy

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This study provides a snapshot of the sustainability of selected Indian cities by employing 70 indicators in four dimensions to develop an overall city sustainability index. In recent years, the concept of ‘urban sustainability’ has become prominent due to its complexity. Urban areas propel growth and at the same time poses a lot of ecological, social and infrastructural problems and risks. In case of developing countries, the high population density of and the continuous in-migration run the highest risk in natural and man-made disasters. These issues combined with the inability of policy makers in providing basic services makes the cities unsustainable. To assess whether any given policy is moving towards or against urban sustainability it is necessary to consider the relationships among its various dimensions. Hence, in recent years, while preparing the sustainability index, an integral approach involving indicators of different dimensions such as ‘economic’, ‘environmental’ and 'social' is being used. It is also important for urban planners, social analysts and other related institutions to identify and understand the relationships in this complex system. The objective of the paper is to develop a city performance index (CPI) to measure and evaluate the urban regions in terms of sustainable performances. The objectives include: i) Objective assessment of a city’s performance, ii) setting achievable goals iii) prioritise relevant indicators for improvement, iv) learning from leaders, iv) assessment of the effectiveness of programmes that results in achieving high indicator values, v) Strengthening of stakeholder participation. Using the benchmark approach, a conceptual framework is developed for evaluating 25 Indian cities. We develop City Sustainability index (CSI) in order to rank cities according to their level of sustainability. The CSI is composed of four dimensions: Economic, Environment, Social, and Institutional. Each dimension is further composed of multiple indicators: (1) Economic that considers growth, access to electricity, and telephone availability; (2) environmental that includes waste water treatment, carbon emissions, (3) social that includes, equity, infant mortality, and 4) institutional that includes, voting share of population, urban regeneration policies. The CSI, consisting of four dimensions disaggregate into 12 categories and ultimately into 70 indicators. The data are obtained from public and non-governmental organizations, and also from city officials and experts. By ranking a sample of diverse cities on a set of specific dimensions the study can serve as a baseline of current conditions and a marker for referencing future results. The benchmarks and indices presented in the study provide a unique resource for the government and the city authorities to learn about the positive and negative attributes of a city and prepare plans for a sustainable urban development. As a result of our conceptual framework, the set of criteria we suggest is somewhat different to any already in the literature. The scope of our analysis is intended to be broad. Although illustrated with specific examples, it should be apparent that the principles identified are relevant to any monitoring that is used to inform decisions involving decision variables. These indicators are policy-relevant and, hence they are useful tool for decision-makers and researchers.

Keywords: benchmark, city, indicator, performance, sustainability

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173 MEIOSIS: Museum Specimens Shed Light in Biodiversity Shrinkage

Authors: Zografou Konstantina, Anagnostellis Konstantinos, Brokaki Marina, Kaltsouni Eleftheria, Dimaki Maria, Kati Vassiliki

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Body size is crucial to ecology, influencing everything from individual reproductive success to the dynamics of communities and ecosystems. Understanding how temperature affects variations in body size is vital for both theoretical and practical purposes, as changes in size can modify trophic interactions by altering predator-prey size ratios and changing the distribution and transfer of biomass, which ultimately impacts food web stability and ecosystem functioning. Notably, a decrease in body size is frequently mentioned as the third "universal" response to climate warming, alongside shifts in distribution and changes in phenology. This trend is backed by ecological theories like the temperature-size rule (TSR) and Bergmann's rule, which have been observed in numerous species, indicating that many species are likely to shrink in size as temperatures rise. However, the thermal responses related to body size are still contradictory, and further exploration is needed. To tackle this challenge, we developed the MEIOSIS project, aimed at providing valuable insights into the relationship between the body size of species, species’ traits, environmental factors, and their response to climate change. We combined a digitized collection of butterflies from the Swiss Federal Institute of Technology in Zürich with our newly digitized butterfly collection from Goulandris Natural History Museum in Greece to analyse trends in time. For a total of 23868 images, the length of the right forewing was measured using ImageJ software. Each forewing was measured from the point at which the wing meets the thorax to the apex of the wing. The forewing length of museum specimens has been shown to have a strong correlation with wing surface area and has been utilized in prior studies as a proxy for overall body size. Temperature data corresponding to the years of collection were also incorporated into the datasets. A second dataset was generated when a custom computer vision tool was implemented for the automated morphological measuring of samples for the digitized collection in Zürich. Using the second dataset, we corrected manual measurements with ImageJ, and a final dataset containing 31922 samples was used for analysis. Setting time as a smoother variable, species identity as a random factor, and the length of right-wing size (a proxy for body size) as the response variable, we ran a global model for a maximum period of 110 years (1900 – 2010). Then, we investigated functional variability between different terrestrial biomes in a second model. Both models confirmed our initial hypothesis and resulted in a decreasing trend in body size over the years. We expect that this first output can be provided as basic data for the next challenge, i.e., to identify the ecological traits that influence species' temperature-size responses, enabling us to predict the direction and intensity of a species' reaction to rising temperatures more accurately.

Keywords: butterflies, shrinking body size, museum specimens, climate change

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172 The Influence of Human Movement on the Formation of Adaptive Architecture

Authors: Rania Raouf Sedky

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Adaptive architecture relates to buildings specifically designed to adapt to their residents and their environments. To design a biologically adaptive system, we can observe how living creatures in nature constantly adapt to different external and internal stimuli to be a great inspiration. The issue is not just how to create a system that is capable of change but also how to find the quality of change and determine the incentive to adapt. The research examines the possibilities of transforming spaces using the human body as an active tool. The research also aims to design and build an effective dynamic structural system that can be applied on an architectural scale and integrate them all into the creation of a new adaptive system that allows us to conceive a new way to design, build and experience architecture in a dynamic manner. The main objective was to address the possibility of a reciprocal transformation between the user and the architectural element so that the architecture can adapt to the user, as the user adapts to architecture. The motivation is the desire to deal with the psychological benefits of an environment that can respond and thus empathize with human emotions through its ability to adapt to the user. Adaptive affiliations of kinematic structures have been discussed in architectural research for more than a decade, and these issues have proven their effectiveness in developing kinematic structures, responsive and adaptive, and their contribution to 'smart architecture'. A wide range of strategies have been used in building complex kinetic and robotic systems mechanisms to achieve convertibility and adaptability in engineering and architecture. One of the main contributions of this research is to explore how the physical environment can change its shape to accommodate different spatial displays based on the movement of the user’s body. The main focus is on the relationship between materials, shape, and interactive control systems. The intention is to develop a scenario where the user can move, and the structure interacts without any physical contact. The soft form of shifting language and interaction control technology will provide new possibilities for enriching human-environmental interactions. How can we imagine a space in which to construct and understand its users through physical gestures, visual expressions, and response accordingly? How can we imagine a space whose interaction depends not only on preprogrammed operations but on real-time feedback from its users? The research also raises some important questions for the future. What would be the appropriate structure to show physical interaction with the dynamic world? This study concludes with a strong belief in the future of responsive motor structures. We imagine that they are developing the current structure and that they will radically change the way spaces are tested. These structures have obvious advantages in terms of energy performance and the ability to adapt to the needs of users. The research highlights the interface between remote sensing and a responsive environment to explore the possibility of an interactive architecture that adapts to and responds to user movements. This study ends with a strong belief in the future of responsive motor structures. We envision that it will improve the current structure and that it will bring a fundamental change to the way in which spaces are tested.

Keywords: adaptive architecture, interactive architecture, responsive architecture, tensegrity

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171 Towards a Measuring Tool to Encourage Knowledge Sharing in Emerging Knowledge Organizations: The Who, the What and the How

Authors: Rachel Barker

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The exponential velocity in the truly knowledge-intensive world today has increasingly bombarded organizations with unfathomable challenges. Hence organizations are introduced to strange lexicons of descriptors belonging to a new paradigm of who, what and how knowledge at individual and organizational levels should be managed. Although organizational knowledge has been recognized as a valuable intangible resource that holds the key to competitive advantage, little progress has been made in understanding how knowledge sharing at individual level could benefit knowledge use at collective level to ensure added value. The research problem is that a lack of research exists to measure knowledge sharing through a multi-layered structure of ideas with at its foundation, philosophical assumptions to support presuppositions and commitment which requires actual findings from measured variables to confirm observed and expected events. The purpose of this paper is to address this problem by presenting a theoretical approach to measure knowledge sharing in emerging knowledge organizations. The research question is that despite the competitive necessity of becoming a knowledge-based organization, leaders have found it difficult to transform their organizations due to a lack of knowledge on who, what and how it should be done. The main premise of this research is based on the challenge for knowledge leaders to develop an organizational culture conducive to the sharing of knowledge and where learning becomes the norm. The theoretical constructs were derived and based on the three components of the knowledge management theory, namely technical, communication and human components where it is suggested that this knowledge infrastructure could ensure effective management. While it is realised that it might be a little problematic to implement and measure all relevant concepts, this paper presents effect of eight critical success factors (CSFs) namely: organizational strategy, organizational culture, systems and infrastructure, intellectual capital, knowledge integration, organizational learning, motivation/performance measures and innovation. These CSFs have been identified based on a comprehensive literature review of existing research and tested in a new framework adapted from four perspectives of the balanced score card (BSC). Based on these CSFs and their items, an instrument was designed and tested among managers and employees of a purposefully selected engineering company in South Africa who relies on knowledge sharing to ensure their competitive advantage. Rigorous pretesting through personal interviews with executives and a number of academics took place to validate the instrument and to improve the quality of items and correct wording of issues. Through analysis of surveys collected, this research empirically models and uncovers key aspects of these dimensions based on the CSFs. Reliability of the instrument was calculated by Cronbach’s a for the two sections of the instrument on organizational and individual levels.The construct validity was confirmed by using factor analysis. The impact of the results was tested using structural equation modelling and proved to be a basis for implementing and understanding the competitive predisposition of the organization as it enters the process of knowledge management. In addition, they realised the importance to consolidate their knowledge assets to create value that is sustainable over time.

Keywords: innovation, intellectual capital, knowledge sharing, performance measures

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170 Advertising Campaigns for a Sustainable Future: The Fight against Plastic Pollution in the Ocean

Authors: Mokhlisur Rahman

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Ocean inhibits one of the most complex ecosystems on the planet that regulates the earth's climate and weather by providing us with compatible weather to live. Ocean provides food by extending various ways of lifestyles that are dependent on it, transportation by accommodating the world's biggest carriers, recreation by offering its beauty in many moods, and home to countless species. At the essence of receiving various forms of entertainment, consumers choose to be close to the ocean while performing many fun activities. Which, at some point, upsets the stomach of the ocean by threatening marine life and the environment. Consumers throw the waste into the ocean after using it. Most of them are plastics that float over the ocean and turn into thousands of micro pieces that are hard to observe with the naked eye but easily eaten by the sea species. Eventually, that conflicts with the natural consumption process of any living species, making them sick. This information is not known by most consumers who go to the sea or seashores occasionally to spend time, nor is it widely discussed, which creates an information gap among consumers. However, advertising is a powerful tool to educate people about ocean pollution. This abstract analyzes three major ocean-saving advertisement campaigns that use innovative and advanced technology to get maximum exposure. The study collects data from the selected campaigns' websites and retrieves all available content related to messages, videos, and images. First, the SeaLegacy campaign uses stunning images to create awareness among the people; they use social media content, videos, and other educational content. They create content and strategies to build an emotional connection among the consumers that encourage them to move on an action. All the messages in their campaign empower consumers by using powerful words. Second, Ocean Conservancy Campaign uses social media marketing, events, and educational content to protect the ocean from various pollutants, including plastics, climate change, and overfishing. They use powerful images and videos of marine life. Their mission is to create evidence-based solutions toward a healthy ocean. Their message includes the message regarding the local communities along with the sea species. Third, ocean clean-up is a campaign that applies strategies using innovative technologies to remove plastic waste from the ocean. They use social media, digital, and email marketing to reach people and raise awareness. They also use images and videos to evoke an emotional response to take action. These tree advertisements use realistic images, powerful words, and the presence of living species in the imagery presentation, which are eye-catching and can grow emotional connection among the consumers. Identifying the effectiveness of the messages these advertisements carry and their strategies highlights the knowledge gap of mass people between real pollution and its consequences, making the message more accessible to the mass of people. This study aims to provide insights into the effectiveness of ocean-saving advertisement campaigns and their impact on the public's awareness of ocean conservation. The findings from this study help shape future campaigns.

Keywords: advertising-campaign, content-creation, images ocean-saving technology, videos

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169 Computer Aided Design Solution Based on Genetic Algorithms for FMEA and Control Plan in Automotive Industry

Authors: Nadia Belu, Laurenţiu Mihai Ionescu, Agnieszka Misztal

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The automotive industry is one of the most important industries in the world that concerns not only the economy, but also the world culture. In the present financial and economic context, this field faces new challenges posed by the current crisis, companies must maintain product quality, deliver on time and at a competitive price in order to achieve customer satisfaction. Two of the most recommended techniques of quality management by specific standards of the automotive industry, in the product development, are Failure Mode and Effects Analysis (FMEA) and Control Plan. FMEA is a methodology for risk management and quality improvement aimed at identifying potential causes of failure of products and processes, their quantification by risk assessment, ranking of the problems identified according to their importance, to the determination and implementation of corrective actions related. The companies use Control Plans realized using the results from FMEA to evaluate a process or product for strengths and weaknesses and to prevent problems before they occur. The Control Plans represent written descriptions of the systems used to control and minimize product and process variation. In addition Control Plans specify the process monitoring and control methods (for example Special Controls) used to control Special Characteristics. In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorithms to find optimum between RPN risk factor and cost of production. A feature of Genetic Algorithms is that they are used as a means of finding solutions for multi criteria optimization problems. In our case, along with three specific FMEA risk factors is considered and reduce production cost. Analysis tool will generate final reports for all FMEA processes. The data obtained in FMEA reports are automatically integrated with other entered parameters in Control Plan. Implementation of the solution is in the form of an application running in an intranet on two servers: one containing analysis and plan generation engine and the other containing the database where the initial parameters and results are stored. The results can then be used as starting solutions in the synthesis of other projects. The solution was applied to welding processes, laser cutting and bending to manufacture chassis for buses. Advantages of the solution are efficient elaboration of documents in the current project by automatically generating reports FMEA and Control Plan using multiple criteria optimization of production and build a solid knowledge base for future projects. The solution which we propose is a cheap alternative to other solutions on the market using Open Source tools in implementation.

Keywords: automotive industry, FMEA, control plan, automotive technology

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168 Deep Learning-Based Classification of 3D CT Scans with Real Clinical Data; Impact of Image format

Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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167 Formulation and Optimization of Self Nanoemulsifying Drug Delivery System of Rutin for Enhancement of Oral Bioavailability Using QbD Approach

Authors: Shrestha Sharma, Jasjeet K. Sahni, Javed Ali, Sanjula Baboota

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Introduction: Rutin is a naturally occurring strong antioxidant molecule belonging to bioflavonoid category. Due to its free radical scavenging properties, it has been found to be beneficial in the treatment of various diseases including inflammation, cancer, diabetes, allergy, cardiovascular disorders and various types of microbial infections. Despite its beneficial effects, it suffers from the problem of low aqueous solubility which is responsible for low oral bioavailability. The aim of our study was to optimize and characterize self-nanoemulsifying drug delivery system (SNEDDS) of rutin using Box-Behnken design (BBD) combined with a desirability function. Further various antioxidant, pharmacokinetic and pharmacodynamic studies were performed for the optimized rutin SNEDDS formulation. Methodologies: Selection of oil, surfactant and co-surfactant was done on the basis of solubility/miscibility studies. Sefsol+ Vitamin E, Solutol HS 15 and Transcutol P were selected as oil phase, surfactant and co-surfactant respectively. Optimization of SNEDDS formulations was done by a three-factor, three-level (33)BBD. The independent factors were Sefsol+ Vitamin E, Solutol HS15, and Transcutol P. The dependent variables were globule size, self emulsification time (SEF), % transmittance and cumulative percentage drug released. Various response surface graphs and contour plots were constructed to understand the effect of different factor, their levels and combinations on the responses. The optimized Rutin SNEDDS formulation was characterized for various parameters such as globule size, zeta potential, viscosity, refractive index , % Transmittance and in vitro drug release. Ex vivo permeation studies and pharmacokinetic studies were performed for optimized formulation. Antioxidant activity was determined by DPPH and reducing power assays. Anti-inflammatory activity was determined by using carrageenan induced rat paw oedema method. Permeation of rutin across small intestine was assessed using confocal laser scanning microscopy (CLSM). Major findings:The optimized SNEDDS formulation consisting of Sefsol+ Vitamin E - Solutol HS15 -Transcutol HP at proportions of 25:35:17.5 (w/w) was prepared and a comparison of the predicted values and experimental values were found to be in close agreement. The globule size and PDI of optimized SNEDDS formulation was found to be 16.08 ± 0.02 nm and 0.124±0.01 respectively. Significant (p˂0.05) increase in percentage drug release was achieved in the case of optimized SNEDDS formulation (98.8 %) as compared to rutin suspension. Furthermore, pharmacokinetic study showed a 2.3-fold increase in relative oral bioavailability compared with that of the suspension. Antioxidant assay results indicated better efficacy of the developed formulation than the pure drug and it was found to be comparable with ascorbic acid. The results of anti-inflammatory studies showed 72.93 % inhibition for the SNEDDS formulation which was significantly higher than the drug suspension 46.56%. The results of CLSM indicated that the absorption of SNEDDS formulation was considerably higher than that from rutin suspension. Conclusion: Rutin SNEDDS have been successfully prepared and they can serve as an effective tool in enhancing oral bioavailability and efficacy of Rutin.

Keywords: rutin, oral bioavilability, pharamacokinetics, pharmacodynamics

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166 Documentary Filmmaking as Activism: Case Studies in Advocacy and Social Justice

Authors: Babatunde Kolawole

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This paper embarks on an exploration of the compelling interplay between documentary filmmaking and activism, delving into their symbiotic relationship and profound impact on advocacy and social justice causes. Through an in-depth analysis of diverse case studies, it seeks to illuminate the instances where documentary films have emerged as potent tools for effecting social change and advancing the principles of justice. This research underscores the vital role played by documentary filmmakers in harnessing the medium's unique capacity to engage, educate, and mobilize audiences while advocating for societal transformation. The primary focus of this study is on a selection of compelling case studies spanning various topics and causes, each exemplifying the marriage between documentary filmmaking and activism. These case studies encompass a broad spectrum of subjects, from environmental conservation and climate change to civil rights movements and human rights struggles. By examining these real-world instances, this paper endeavors to provide a comprehensive understanding of the strategies, challenges, and ethical considerations that underpin the practice of documentary filmmaking as a form of activism. Throughout the paper, it becomes evident that the potency of documentary filmmaking lies in its ability to blend artistry with social impact. The selected case studies vividly demonstrate how documentary filmmakers, armed with cameras and a passion for change, have emerged as critical agents of societal transformation. Whether it be exposing environmental atrocities, shedding light on systemic inequalities, or giving voice to marginalized communities, these documentaries have played a pivotal role in pushing the boundaries of advocacy and social justice. One of the key themes explored in this paper is the evolving nature of documentary filmmaking as a tool for activism. It delves into the shift from traditional observational documentaries to more participatory and immersive approaches, highlighting the dynamic ways in which filmmakers engage with their subjects and audiences. This evolution is exemplified in case studies where filmmakers have collaborated with the communities they document, fostering a sense of agency and empowerment among those whose stories are being told. Furthermore, this research underscores the ethical considerations inherent in the intersection of documentary filmmaking and activism. It scrutinizes questions surrounding representation, objectivity, and the responsibility of filmmakers in portraying complex social issues. By dissecting ethical dilemmas faced by documentary filmmakers in these case studies, this paper encourages a critical examination of the ethical boundaries and obligations in the realm of advocacy-driven filmmaking. In conclusion, this paper aims to shed light on the remarkable potential of documentary filmmaking as a catalyst for activism and social justice. Through the lens of compelling case studies, it illustrates the transformative power of the medium in effecting change, amplifying underrepresented voices, and mobilizing global audiences. It is hoped that this research will not only inform the discourse on documentary activism but also inspire filmmakers, scholars, and advocates to continue leveraging the cinematic art form as a formidable force for a more just and equitable world.

Keywords: film, filmmaker, documentary, human right

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165 Towards Sustainable Evolution of Bioeconomy: The Role of Technology and Innovation Management

Authors: Ronald Orth, Johanna Haunschild, Sara Tsog

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The bioeconomy is an inter- and cross-disciplinary field covering a large number and wide scope of existing and emerging technologies. It has a great potential to contribute to the transformation process of industry landscape and ultimately drive the economy towards sustainability. However, bioeconomy per se is not necessarily sustainable and technology should be seen as an enabler rather than panacea to all our ecological, social and economic issues. Therefore, to draw and maximize benefits from bioeconomy in terms of sustainability, we propose that innovative activities should encompass not only novel technologies and bio-based new materials but also multifocal innovations. For multifocal innovation endeavors, innovation management plays a substantial role, as any innovation emerges in a complex iterative process where communication and knowledge exchange among relevant stake holders has a pivotal role. The knowledge generation and innovation are although at the core of transition towards a more sustainable bio-based economy, to date, there is a significant lack of concepts and models that approach bioeconomy from the innovation management approach. The aim of this paper is therefore two-fold. First, it inspects the role of transformative approach in the adaptation of bioeconomy that contributes to the environmental, ecological, social and economic sustainability. Second, it elaborates the importance of technology and innovation management as a tool for smooth, prompt and effective transition of firms to the bioeconomy. We conduct a qualitative literature study on the sustainability challenges that bioeconomy entails thus far using Science Citation Index and based on grey literature, as major economies e.g. EU, USA, China and Brazil have pledged to adopt bioeconomy and have released extensive publications on the topic. We will draw an example on the forest based business sector that is transforming towards the new green economy more rapidly as expected, although this sector has a long-established conventional business culture with consolidated and fully fledged industry. Based on our analysis we found that a successful transition to sustainable bioeconomy is conditioned on heterogenous and contested factors in terms of stakeholders , activities and modes of innovation. In addition, multifocal innovations occur when actors from interdisciplinary fields engage in intensive and continuous interaction where the focus of innovation is allocated to a field of mutually evolving socio-technical practices that correspond to the aims of the novel paradigm of transformative innovation policy. By adopting an integrated and systems approach as well as tapping into various innovation networks and joining global innovation clusters, firms have better chance of creating an entire new chain of value added products and services. This requires professionals that have certain capabilities and skills such as: foresight for future markets, ability to deal with complex issues, ability to guide responsible R&D, ability of strategic decision making, manage in-depth innovation systems analysis including value chain analysis. Policy makers, on the other hand, need to acknowledge the essential role of firms in the transformative innovation policy paradigm.

Keywords: bioeconomy, innovation and technology management, multifocal innovation, sustainability, transformative innovation policy

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164 Sustainable Strategies for Managing Rural Tourism in Abyaneh Village, Isfahan

Authors: Hoda Manafian, Stephen Holland

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Problem statement: Rural areas in Iran are one of the most popular tourism destinations. Abyaneh Village is one of them with a long history behind it (more than 1500 years) which is a national heritage site and also is nominated as a world heritage site in UNESCO tentative list from 2007. There is a considerable foundation of religious-cultural heritage and also agricultural history and activities. However, this heritage site suffers from mass tourism which is beyond its social and physical carrying capacity, since the annual number of tourists exceed 500,000. While there are four adjacent villages around Abyaneh which can benefit from advantages of tourism. Local managers also can at the same time prorate the tourists’ flux of Abyaneh on those other villages especially in high-season. The other villages have some cultural and natural tourism attractions as well. Goal: The main goal of this study is to identify a feasible development strategy according to the current strengths, weaknesses, opportunities and threats of rural tourism in this area (Abyaneh Village and four adjacent villages). This development strategy can lead to sustainable management of these destinations. Method: To this end, we used SWOT analysis as a well-established tool for conducting a situational analysis to define a sustainable development strategy. The procedures included following steps: 1) Extracting variables of SWOT chart based on interviewing tourism experts (n=13), local elites (n=17) and personal observations of researcher. 2) Ranking the extracted variables from 1-5 by 13 tourism experts in Isfahan Cultural Heritage, Handcrafts and Tourism Organization (ICHTO). 3) Assigning weights to the ranked variables using Expert Choice Software and the method of Analytical Hierarchical Process (AHP). 4) Defining the Total Weighted Score (TWS) for each part of SWOT chart. 5) Identifying the strategic position according to the TWS 6) Selecting the best development strategy based on the defined position using the Strategic Position and Action Evaluation (SPACE) matrix. 7) Assessing the Probability of Strategic Success (PSS) for the preferred strategy using relevant formulas. 8) Defining two feasible alternatives for sustainable development. Results and recommendations: Cultural heritage attractions were first-ranked variable in strength chart and also lack of sufficient amenities for one-day tourists (catering, restrooms, parking, and accommodation) was firs-ranked weakness. The strategic position was in ST (Strength-Threat) quadrant which is a maxi-mini position. According this position we would suggest ‘Competitive Strategy’ as a development strategy which means relying on strengths in order to neutralization threats. The result of Probability of Strategic Success assessment which was 0.6 shows that this strategy could be successful. The preferred approach for competitive strategy could be rebranding the market of tourism in this area. Rebranding the market can be achieved by two main alternatives which are based on the current strengths and threats: 1) Defining a ‘Heritage Corridor’ from first adjacent village to Abyaneh as a final destination. 2) Focus on ‘educational tourism’ versus mass tourism and also green tourism by developing agritourism in that corridor.

Keywords: Abyaneh village, rural tourism, SWOT analysis, sustainable strategies

Procedia PDF Downloads 388