Search results for: Neal Wade

Authors: Christine C. Neal

Abstract:

A veritable world citizen, Nanyang painter Georgette Chen (1906-1993) melded artistic influences from both the East and West. Much has been written about her contribution to the art of Singapore, her role in the establishment of the Nanyang Style, the lasting influence that she exerted on younger artists, and her considerable artistic achievements. Never before examined is the development of her oeuvre that reflects this mixture, to the best of the author’s knowledge. The works selected for this investigation reveal her artistic development from student to teacher, the range of her thematic interests, and the stimuli that she absorbed from a life ensconced in eastern and western cultures where she felt, as she wrote, “at home in this world.”

Keywords: art, China, Georgette Chen, Nanyang, Paris, Singapore

Procedia PDF Downloads 249

Authors: Mansoureh Zangiabadi, Shamil Velji, Rajendra Kelkar, Neal Wade, Volker Pickert

Abstract:

The EU has set itself a long-term goal of reducing greenhouse gas emissions by 80-95% of the 1990 levels by 2050 as set in the Energy Roadmap 2050. This paper reports on the European Union H2020 funded E-Lobster project which demonstrates tools and technologies, software and hardware in integrating the grid distribution, and the railway power systems with power electronics technologies (Smart Soft Open Point - sSOP) and local energy storage. In this context this paper describes the existing policies and regulatory frameworks of the energy market at European level with a special focus then at National level, on the countries where the members of the consortium are located, and where the demonstration activities will be implemented. By taking into account the disciplinary approach of E-Lobster, the main policy areas investigated includes electricity, energy market, energy efficiency, transport and smart cities. Energy storage will play a key role in enabling the EU to develop a low-carbon electricity system. In recent years, Energy Storage System (ESSs) are gaining importance due to emerging applications, especially electrification of the transportation sector and grid integration of volatile renewables. The need for storage systems led to ESS technologies performance improvements and significant price decline. This allows for opening a new market where ESSs can be a reliable and economical solution. One such emerging market for ESS is R+G management which will be investigated and demonstrated within E-Lobster project. The surplus of energy in one type of power system (e.g., due to metro braking) might be directly transferred to the other power system (or vice versa). However, it would usually happen at unfavourable instances when the recipient does not need additional power. Thus, the role of ESS is to enhance advantages coming from interconnection of the railway power systems and distribution grids by offering additional energy buffer. Consequently, the surplus/deficit of energy in, e.g. railway power systems, is not to be immediately transferred to/from the distribution grid but it could be stored and used when it is really needed. This will assure better energy management exchange between the railway power systems and distribution grids and lead to more efficient loss reduction. In this framework, to identify the existing policies and regulatory frameworks is crucial for the project activities and for the future development of business models for the E-Lobster solutions. The projections carried out by the European Commission, the Member States and stakeholders and their analysis indicated some trends, challenges, opportunities and structural changes needed to design the policy measures to provide the appropriate framework for investors. This study will be used as reference for the discussion in the envisaged workshops with stakeholders (DSOs and Transport Managers) in the E-Lobster project.

Keywords: light railway, electrical distribution network, Electrical Energy Storage, policy

Procedia PDF Downloads 104

Authors: Mamadou I. Wade, Henry C. Ogworonjo, Madiha Gul, Mandoye Ndoye, Mohamed Chouikha, Wayne Patterson

Abstract:

In this paper, we present a novel application of the Paillier cryptographic system to the encryption of RGB (Red Green Blue) images. In this method, an RGB image is first separated into its constituent channel images, and the Paillier encryption function is applied to each of the channels pixel intensity values. Next, the encrypted image is combined and compressed if necessary before being transmitted through an unsecured communication channel. The transmitted image is subsequently recovered by a decryption process. We performed a series of security and performance analyses to the recovered images in order to verify their robustness to security attack. The results show that the proposed image encryption scheme produces highly secured encrypted images.

Keywords: image encryption, Paillier cryptographic system, RBG image encryption, Paillier

Procedia PDF Downloads 201

Authors: Qiongzi Zheng, Lewis Cornwell, Neal Peres Da Costa

Abstract:

Drawn on Confucian and Taoist philosophy and long-established tradition of aesthetic ideals, the Art of the Chinese Zither (Xishan Qinkuang), a classic work by Chinese music scholar Xu Shangyin in 1643, distilled twenty-four practicing principles for the Chinese zither. This work has influenced the practice of guzheng to the present day. Whilst the principles were described in detail, how they can actually be achieved on a technical level remains to be explored. This study focuses on three key practicing principles: yuan (roundness), liu (fluidness), and su (swiftness), and examines how the playing techniques developed by Master Zhao Manqin contribute to the implementation of the principles. The study concludes that knowledge of the technicality of fingering positioning before and after plucking motion is critical to the realization of these principles.

Keywords: Chinese music aesthetics, practicing principles of the Chinese zither, guzheng playing techniques, Zhao Manqin’s fingering techniques, Xishan Qinkuang

Procedia PDF Downloads 142

Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

Abstract:

Synthetic data generated by Generative Adversarial Networks and Autoencoders is becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and Mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic GAN, such as the Gaussian copula. We present the results from two synthetic data sets (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the ROC and AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: synthetic data generation, generative adversarial networks, conditional tabular GAN, Gaussian copula

Procedia PDF Downloads 29

Authors: Mohammed Hasan Salahat, Stave Wade

Abstract:

This paper presents an application of a “Systematic Soft Domain Driven Design Framework” as a soft systems approach to domain-driven design of information systems development. The framework combining techniques from Soft Systems Methodology (SSM), the Unified Modeling Language (UML), and an implementation pattern knows as ‘Naked Objects’. This framework have been used in action research projects that have involved the investigation and modeling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, and a real case study ‘Information Retrieval System for Academic Research’ is used, in this paper, to show further practice and evaluation of the framework in different business domain. We argue that there are advantages from combining and using techniques from different methodologies in this way for business domain modeling. The framework is overviewed and justified as multi-methodology using Mingers Multi-Methodology ideas.

Keywords: SSM, UML, domain-driven design, soft domain-driven design, naked objects, soft language, information retrieval, multimethodology

Procedia PDF Downloads 529

Authors: Mohammed Salahat, Steve Wade

Abstract:

This paper presents and compares the SSDDD “Systematic Soft Domain Driven Design Framework” to DDD “Domain Driven Design Framework” as a soft system approach of information systems development. The framework use SSM as a guiding methodology within which we have embedded a sequence of design tasks based on the UML leading to the implementation of a software system using the Naked Objects framework. This framework has been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, a comparison between SSDDD and DDD is presented in this paper, to show how SSDDD improved DDD as an approach to modelling and implementing business domain perspectives for Information Systems Development. The comparison process, the results, and the improvements are presented in the following sections of this paper.

Keywords: domain-driven design, soft domain-driven design, naked objects, soft language

Procedia PDF Downloads 262

Authors: Chandra Prayaga, Lakshmi Prayaga, Aaron Wade, Kyle Rank, Gopi Shankar Mallu, Sri Satya, Harsha Pola

Abstract:

In today's tech-driven world, where connectivity shapes our daily lives, maintaining physical and emotional health is crucial. Athletic trainers play a vital role in optimizing athletes' performance and preventing injuries. However, a shortage of trainers impacts the quality of care. This study introduces a vision-based exercise monitoring system leveraging Google's MediaPipe library for precise tracking of bicep curl exercises and simultaneous posture monitoring. We propose a three-stage methodology: landmark detection, side detection, and angle computation. Our system calculates angles at the elbow, wrist, neck, and torso to assess exercise form. Experimental results demonstrate the system's effectiveness in distinguishing between good and partial repetitions and evaluating body posture during exercises, providing real-time feedback for precise fitness monitoring.

Keywords: physical health, athletic trainers, fitness monitoring, technology driven solutions, Google’s MediaPipe, landmark detection, angle computation, real-time feedback

Procedia PDF Downloads 24

Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

Abstract:

This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

Procedia PDF Downloads 13

Authors: Evelyne Nguegwouo, Raoul Fonkem Sonfack Tsakem, Abel Wade, Gabriel Nama Medoua, Kamgaing Theophile

Abstract:

Fresh and smoked fish are widely consumed in Cameroon. The traditional nature of smoking, the lack of hygiene in production, the poor preservation of stocks and the long storage time for certain types of fish considerably favor the contamination of products by molds, which secrete toxic molecules called mycotoxins. Today there are more than 400 types of mycotoxins, Aflatoxins being the most formidable. These toxins are considered carcinogenic in humans. It is in this perspective that we proposed to evaluate the total Aflatoxins in the fish marketed and consumed by the populations of the city of Yaoundé in Cameroon. On the one hand, it was a question of conducting a survey of fish consumers and sellers in points of sale, sampling fish of three species [Marquereau (Scomber scombrus), Cod (Gadus morhua) and Bifaka (Ethmalosa fimbriata)], randomly in some markets of the city to evaluate the total Aflatoxins contents (B1, B2, G1, G2) by the quantitative ELISA method and finally to estimate the level of exposure of the populations. It emerges from this study that of the 30 samples analyzed, 96.1% contained total Aflatoxins and two samples had total Aflatoxins levels above the standard, which is 20 ppb. These first results show that the risk is present in Cameroon and in order to improve the quality of marketed fish in terms of mycotoxins, a more thorough control must be done from the production chain to the consumer.

Keywords: aflatoxins, evaluation, exposure, mycotoxins, fish

Procedia PDF Downloads 42

Authors: Sinead Impey, Damon Berry, Selma Furtado, Miriam Galvin, Loretto Grogan, Orla Hardiman, Lucy Hederman, Mark Heverin, Vincent Wade, Linda Douris, Declan O'Sullivan, Gaye Stephens

Abstract:

Healthcare is a knowledge-rich environment. This knowledge, while valuable, is not always accessible outside the borders of individual clinics. This research aims to address part of this problem (at a study site) by constructing a maximal data set (knowledge artefact) for motor neurone disease (MND). This data set is proposed as an initial knowledge base for a concurrent project to develop an MND patient data platform. It represents the domain knowledge at the study site for the duration of the research (12 months). A knowledge elicitation method was also developed from the lessons learned during this process - the WICKED method. WICKED is an anagram of the words: eliciting and confirming data, information, knowledge, wisdom. But it is also a reference to the concept of wicked problems, which are complex and challenging, as is eliciting expert knowledge. The method was evaluated at a second site, and benefits and limitations were noted. Benefits include that the method provided a systematic way to manage data, information, knowledge and wisdom (DIKW) from various sources, including healthcare specialists and existing data sets. Limitations surrounded the time required and how the data set produced only represents DIKW known during the research period. Future work is underway to address these limitations.

Keywords: healthcare, knowledge acquisition, maximal data sets, action design science

Procedia PDF Downloads 265

Authors: Desmond Wade, Alfredo Ormazabal

Abstract:

Background: Ever since it commenced its registration process of pre-hospital practitioners in the year 2000 through the Irish Government Statute Instrument (SI 109 of 2000) process, the approach to education of its professionals has changed drastically. The progression from the traditional behaviouristic to the current constructivist approach has been based on experiences from other sectors and industries, nationally and internationally. Today, the delivery of a safe and efficient ambulance service heavily depends on its practitioners’ range of technical skills, academic knowledge, and overall competences. As these increase, so does the level of complexity of paramedics’ everyday practice. This has made it inevitable to consider the 'Human Factor' as a source of potential risk and made formative institutions like the National Ambulance Service College to include it in their curriculum. Methods: This paper used a mixed-method approach, where both, an online questionnaire and a set of semi-structured interviews were the source of primary data. An analysis of this data was carried out using qualitative and quantitative data analysis. Conclusions: The evidence presented leads to the conclusion that in the National Ambulance Service there is a considerable lack of education of Human Factors and the levels in understanding of how to manage Human Factors in practice vary across its spectrum. Paramedic Practitioners in Ireland seem to understand that the responsibility of patient care lies on the team, rather than on the most hierarchically senior practitioner present in the scene.

Keywords: human factors, ergonomics, stress, decision making, pre-hospital care, paramedic, education

Procedia PDF Downloads 117

Authors: Carla O'Connor, Shanta' Robinson, Alaina Neal, Elan Hope, Adam Hengen, Samantha Drotar

Abstract:

In this paper, we provide a preliminary analysis of the stories teachers tell about their Black students in their efforts to make sense of and professionally resolve the underperformance of Black students in their district. The teachers themselves hail from three demographically distinct districts that participate in the state coordinated inter-district school choice system. The districts are Varuna Hills (a pseudonym, as are all other names in this manuscript), a district that serves a predominantly White and affluent community; Newport, a district that serves a socioeconomically diverse but still majority White population; and Aspen, a district in which the student body is predominantly Black and predominantly working to lower middle class. Relying upon teacher focus group interviews in each of these districts which share a common reform context, we show how teachers’ everyday and narrative discourse makes meaning of the bodies and achievement of Black students and their families. More specifically, we show that these discourses construct Black students as interlopers, as suffering from extraordinary neediness, and in dire need of proper parenting. Our analysis reveals that there are nuances by which the teachers articulate these discourses with the nuances being a function of how the schools of choice reform context intersects with the demographics of each school and beliefs about the demographics of the schools of choice population. We unpack the racialized and classed nature of these narratives and the implications for teachers’ personal practical knowledge.

Keywords: black achievement, educational access and opportunity, race and schooling, teacher knowledge and education

Procedia PDF Downloads 393

Authors: Alan Berman, Mark Brady

Abstract:

The phenomenon of homophobia and transphobia in the United States detrimentally impacts the health, wellbeing, and dignity of school students who identify with the LGBTQ+ community. These negative impacts also compromise the participation of LGBTQ+ individuals in the wider life of educational domains and endanger the potential economic, social and cultural contribution this community can make to American society. The recent 6:3 majority decision of the US Supreme Court in Dobbs v Jackson Women’s Health Organization expressly overruled the 1973 decision in Roe v Wade and the 1992 Planned Parenthood v Casey decision. This study will canvass the bases upon which the court in Dobbs overruled longstanding precedent established in Roe and Casey. It will examine the potential implications for the LGBTQ community of the result in Dobbs. The potential far-reaching consequences of this case are foreshadowed in a concurring opinion by Justice Clarence Thomas, suggesting the Court should revisit all substantive due process cases. This includes notably the Lawrence v Texas case (invalidating sodomy laws criminalizing same-sex relations) and the Obergefellcase (upholding same-sex marriage). Finally, the study will examine the likely impact of the uncertainty brought about by the decision in Doddsfor LGBTQ students in US educational institutions. The actions of several states post-Dobbs, reflects and exacerbates the problems facing LGBTQ+ students and uncovers and highlights societal homophobia and transphobia.

Keywords: human rights, LGBT rights, right to personal dignity and autonomy, substantive due process rights

Procedia PDF Downloads 65

Authors: Fergus Wade, Jasmine Makker, Matthew Jankinson, Aminah Qamar, Gemma Morrelli, Shayan Shah

Abstract:

Background: Ambulance offload delays (AODs) affect patient outcomes. At baseline, the average AOD at Princess Royal University Hospital (PRUH) was 41 minutes, in breach of the 15-minute target. Aims: By February 2023, we aimed to reduce: the average AOD to 30 minutes percentage of AOD >30 minutes (PA30) to 25% and >60 minutes (PA60) to 10% Methods: Following a root-cause analysis, we implemented 2 Plan, Do, Study, Act (PDSA) cycles. PDSA-1 ‘Drop-and-run’: ambulances waiting >15 minutes for a handover left the patients in the Emergency Department (ED) and returned to the community. PDSA-2: Booking in the patients before the handover, allowing direct updates to online records, eliminating the need for handwritten notes. Outcome measures: AOD, PA30, and PA60, and process measures: total ambulances and patients in the ED were recorded for 16 weeks. Results: In PDSA-1, all parameters increased slightly despite unvarying ED crowding. In PDSA-2, two shifts in data were seen: initially, a sharp increase in the outcome measures consistent with increased ED crowding, followed by a downward shift when crowding returned to baseline (p<0.01). Within this interval, the AOD reduced to 29.9 minutes, and PA30 and PA60 were 31.2% and 9.2% respectively. Discussion/conclusion: PDSA-1 didn’t result in any significant changes; lack of compliance was a key cause. The initial upward shift in PDSA-2 is likely associated with NHS staff strikes. However, during the second interval, the AOD and the PA60 met our targets of 30 minutes and 10%, respectively, improving patient flow in the ED. This was sustained without further input and if maintained, saves 2 paramedic shifts every 3 days.

Keywords: ambulance offload, district general hospital, handover, quality improvement

Procedia PDF Downloads 65

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

Abstract:

In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

Procedia PDF Downloads 72

Authors: Kumudini Apsara Munasinghe, Devin Gregory Lissau, Ryan Thomas Wade

Abstract:

Fresh fruits and vegetables are rich in vitamins, minerals, and fibers and help maintain a healthy weight over high-calorie food. Eating fruits and vegetables protects us from free radicals produced by metabolic reactions and safeguards us from cardiovascular disease and cancer. However, there has been an increased concern about foodborne diseases tied to contaminated farmers’ market produce. In addition, very little information is available about the contribution of eating raw fruits and vegetables to human exposure to antibiotic-resistant bacteria. This research aims to identify bacteria isolated from farmers’ market fruits and vegetables and understand their antibiotic resistance. Vegetables and fruits were collected from farmers’ markets around Frostburg and Cumberland areas in Maryland and transported to the microbiology lab at Frostburg State University for the isolation of bacteria. Bacteria were extracted from tomatoes, cucumber, strawberry, and lettuce using Tryptic soy broth overnight at 37°C, and Tryptic Soy agar was used for the streak plate technique to isolate bacteria. Pure cultures were used to identify bacteria using biochemical reactions after conducting Gram staining technique. The research used many biochemical reactions, including Mannitol Salt agar, MacConkey agar, and Eosin Methylene blue agar, for identification. Antibiotic sensitivity was tested for many different types of antibiotics, including amoxicillin, penicillin, tetracycline, ampicillin, and erythromycin. Most prevalent bacteria in the isolates were Staphylococcus, Bacillus, Micrococcus, Enterococcus, Enterobacter, Citrobacter, and other bacteria from the family Enterobacteriaceae. The data obtained from this research will be useful to educate and train farmers and individuals involved in post-harvest processes such as transportation and selling in farmers’ markets. Further results for bacterial antibiotic resistance will be obtained, and unculturable bacteria will be identified by next-generation DNA sequencing.

Keywords: antibiotic resistance, farmers markets, fruits, bacteria, vegetables

Procedia PDF Downloads 35

Authors: Lara Dutil-Fafard, Caroline Rhéaume, Patrick Archambault, Daniel Lafond, Neal W. Pollock

Abstract:

Improving resources for medical autonomy of astronauts in prolonged space missions, such as a Mars mission, requires not only technology development, but also decision-making support systems. The Advanced Crew Medical System - Medical Condition Requirements study, funded by the Canadian Space Agency, aimed to create knowledge content and a scenario-based query capability to support medical autonomy of astronauts. The key objective of this study was to create a prototype tool for identifying medical infrastructure requirements in terms of medical knowledge, skills and materials. A multicriteria decision-making method was used to prioritize the highest risk medical events anticipated in a long-term space mission. Starting with those medical conditions, event sequence diagrams (ESDs) were created in the form of decision trees where the entry point is the diagnosis and the end points are the predicted outcomes (full recovery, partial recovery, or death/severe incapacitation). The ESD formalism was adapted to characterize and compare possible outcomes of medical conditions as a function of available medical knowledge, skills, and supplies in a given mission scenario. An extensive literature review was performed and summarized in a medical condition database. A PostgreSQL relational database was created to allow query-based evaluation of health outcome metrics with different medical infrastructure scenarios. Critical decision points, skill and medical supply requirements, and probable health outcomes were compared across chosen scenarios. The three medical conditions with the highest risk rank were acute coronary syndrome, sepsis, and stroke. Our efforts demonstrate the utility of this approach and provide insight into the effort required to develop appropriate content for the range of medical conditions that may arise.

Keywords: decision support system, event-sequence diagram, exploration mission, medical autonomy, scenario-based queries, space medicine

Procedia PDF Downloads 96

Authors: Neal Rupani

Abstract:

Background: A surgical trainee has limited learning opportunities in the operating room in order to gain an ever-increasing standard of surgical skill, competency, and proficiency. These opportunities continue to decline due to numerous factors such as the European Working Time Directive and increasing requirement for service provision. It is therefore imperative to obtain the highest educational value from each educational opportunity. A measure that has yet to be validated in England on surgical trainees called the Operating Room Educational Environment Measure (OREEM) has been developed to identify and evaluate each component of the educational environment with a view to steer future change in optimising educational events in theatre. Aims: The aims of the study are to assess the reliability of the OREEM within England and to evaluate the surgical trainee’s objective perspective of the current operating room educational environment within one region within England. Methods: Using a quantitative study approach, data was collected over one month from surgical trainees within Health Education Thames Valley (Oxford) using an online questionnaire consisting of demographic data, the OREEM, a global satisfaction score. Results: 140 surgical trainees were invited to the study, with an online response of 54 participants (response rate = 38.6%). The OREEM was shown to have good internal consistency (α = 0.906, variables = 40) and unidimensionality, along with all four of its subgroups. The mean OREEM score was 79.16%. The areas highlighted for improvement predominantly focused on improving learning opportunities (average subscale score = 72.9%) and conducting pre- and post-operative teaching (average score = 70.4%). The trainee perception is most satisfactory for the level of supervision and workload (average subscale score = 82.87%). There was no differences found between gender (U = 191.5, p = 0.535) or type of hospital (U = 258.0, p = 0.099), but the learning environment was favoured towards senior trainees (U = 223.5, p = 0.017). There was strong correlation between OREEM and the global satisfaction score (r = 0.755, p<0.001). Conclusions: The OREEM was shown to be reliable in measuring the educational environment in the operating room. This can be used to identify potentially modifiable components for improvement and as an audit tool to ensure high standards are being met. The current perception of the education environment in Health Education Thames Valley is satisfactory, and modifiable internal and external factors such as reducing service provision requirements, empowering trainees to plan lists, creating a team-working ethic between all personnel, and using tools that maximise learning from each operation have been identified to improve learning in the future. There is a favourable attitude to use of such improvement tools, especially for those currently dissatisfied.

Keywords: education environment, surgery, post-graduate education, OREEM

Procedia PDF Downloads 149

Authors: Avi Shrivastava

Abstract:

Our world continues to grapple with a lot of social issues. Economic growth and scientific advancements have not completely eradicated poverty, homelessness, discrimination and bias, gender inequality, health issues, mental illness, addiction, and other social issues. So, how do we improve the human condition in a world driven by advanced technology? The answer is simple: we will have to leverage technology to address some of the most important social challenges of the day. AI, or artificial intelligence, has emerged as a critical tool in the battle against issues that deprive marginalized and disadvantaged groups of the right to enjoy benefits that a society offers. Social work professionals can transform their lives by harnessing it. The lack of reliable data is one of the reasons why a lot of social work projects fail. Social work professionals continue to rely on expensive and time-consuming primary data collection methods, such as observation, surveys, questionnaires, and interviews, instead of tapping into AI-based technology to generate useful, real-time data and necessary insights. By leveraging AI’s data-mining ability, we can gain a deeper understanding of how to solve complex social problems and change lives of people. We can do the right work for the right people and at the right time. For example, AI can enable social work professionals to focus their humanitarian efforts on some of the world’s poorest regions, where there is extreme poverty. An interdisciplinary team of Stanford scientists, Marshall Burke, Stefano Ermon, David Lobell, Michael Xie, and Neal Jean, used AI to spot global poverty zones – identifying such zones is a key step in the fight against poverty. The scientists combined daytime and nighttime satellite imagery with machine learning algorithms to predict poverty in Nigeria, Uganda, Tanzania, Rwanda, and Malawi. In an article published by Stanford News, Stanford researchers use dark of night and machine learning, Ermon explained that they provided the machine-learning system, an application of AI, with the high-resolution satellite images and asked it to predict poverty in the African region. “The system essentially learned how to solve the problem by comparing those two sets of images [daytime and nighttime].” This is one example of how AI can be used by social work professionals to reach regions that need their aid the most. It can also help identify sources of inequality and conflict, which could reduce inequalities, according to Nature’s study, titled The role of artificial intelligence in achieving the Sustainable Development Goals, published in 2020. The report also notes that AI can help achieve 79 percent of the United Nation’s (UN) Sustainable Development Goals (SDG). AI is impacting our everyday lives in multiple amazing ways, yet some people do not know much about it. If someone is not familiar with this technology, they may be reluctant to use it to solve social issues. So, before we talk more about the use of AI to accomplish social work objectives, let’s put the spotlight on how AI and social work can complement each other.

Keywords: social work, artificial intelligence, AI based social work, machine learning, technology

Procedia PDF Downloads 72

Authors: Teng Teng, Christos Tsinopoulos

Abstract:

The purpose of this research is to explore the link between IS capabilities, customer connection, and quality performance in the service context, with investigation of the impact of firm’s stable and dynamic environments. The application of Information Systems (IS) has become a significant effect on contemporary service operations. Firms invest in IS with the presumption that they will facilitate operations processes so that their performance will improve. Yet, IS resources by themselves are not sufficiently 'unique' and thus, it would be more useful and theoretically relevant to focus on the processes they affect. One such organisational process, which has attracted a lot of research attention by supply chain management scholars, is the integration of customer connection, where IS-enabled customer connection enhances communication and contact processes, and with such customer resources integration comes greater success for the firm in its abilities to develop a good understanding of customer needs and set accurate customer. Nevertheless, prior studies on IS capabilities have focused on either one specific type of technology or operationalised it as a highly aggregated concept. Moreover, although conceptual frameworks have been identified to show customer integration is valuable in service provision, there is much to learn about the practices of integrating customer resources. In this research, IS capabilities have been broken down into three dimensions based on the framework of Wade and Hulland: IT for supply chain activities (ITSCA), flexible IT infrastructure (ITINF), and IT operations shared knowledge (ITOSK); and focus on their impact on operational performance of firms in services. With this background, this paper addresses the following questions: -How do IS capabilities affect the integration of customer connection and service quality? -What is the relationship between environmental dynamism and the relationship of customer connection and service quality? A survey of 156 service establishments was conducted, and the data analysed to determine the role of customer connection in mediating the effects of IS capabilities on firms’ service quality. Confirmatory factor analysis was used to check convergent validity. There is a good model fit for the structural model. Moderating effect of environmental dynamism on the relationship of customer connection and service quality is analysed. Results show that ITSCA, ITINF, and ITOSK have a positive influence on the degree of the integration of customer connection. In addition, customer connection positively related to service quality; this relationship is further emphasised when firms work in a dynamic environment. This research takes a step towards quelling concerns about the business value of IS, contributing to the development and validation of the measurement of IS capabilities in the service operations context. Additionally, it adds to the emerging body of literature linking customer connection to the operational performance of service firms. Managers of service firms should consider the strength of the mediating role of customer connection when investing in IT-related technologies and policies. Particularly, service firms developing IS capabilities should simultaneously implement processes that encourage supply chain integration.

Keywords: customer connection, environmental dynamism, information systems capabilities, service quality, service supply chain

Procedia PDF Downloads 109

Authors: Bronwen Wade

Abstract:

Over the last half-century, child welfare systems have increasingly relied on quantitative risk assessment tools, such as actuarial or predictive risk tools. These tools are developed by performing statistical analysis of how attributes captured in administrative data are related to future child maltreatment. Some scholars argue that attributes in administrative data can serve as proxies for race and that quantitative risk assessment tools reify racial bias in decision-making. Others argue that these tools provide more “objective” and “scientific” guides for decision-making instead of subjective social worker judgment. This study performs a systematic review of the literature on the impact of quantitative risk assessment tools on racial disproportionality; it examines methodological biases in work on this topic, summarizes key findings, and provides suggestions for further work. A search of CINAHL, PsychInfo, Proquest Social Science Premium Collection, and the ProQuest Dissertations and Theses Collection was performed. Academic and grey literature were included. The review includes studies that use quasi-experimental methods and development, validation, or re-validation studies of quantitative risk assessment tools. PROBAST (Prediction model Risk of Bias Assessment Tool) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) were used to assess the risk of bias and guide data extraction for risk development, validation, or re-validation studies. ROBINS-I (Risk of Bias in Non-Randomized Studies of Interventions) was used to assess for bias and guide data extraction for the quasi-experimental studies identified. Due to heterogeneity among papers, a meta-analysis was not feasible, and a narrative synthesis was conducted. 11 papers met the eligibility criteria, and each has an overall high risk of bias based on the PROBAST and ROBINS-I assessments. This is deeply concerning, as major policy decisions have been made based on a limited number of studies with a high risk of bias. The findings on racial disproportionality have been mixed and depend on the tool and approach used. Authors use various definitions for racial equity, fairness, or disproportionality. These concepts of statistical fairness are connected to theories about the reason for racial disproportionality in child welfare or social definitions of fairness that are usually not stated explicitly. Most findings from these studies are unreliable, given the high degree of bias. However, some of the less biased measures within studies suggest that quantitative risk assessment tools may worsen racial disproportionality, depending on how disproportionality is mathematically defined. Authors vary widely in their approach to defining and addressing racial disproportionality within studies, making it difficult to generalize findings or approaches across studies. This review demonstrates the power of authors to shape policy or discourse around racial justice based on their choice of statistical methods; it also demonstrates the need for improved rigor and transparency in studies of quantitative risk assessment tools. Finally, this review raises concerns about the impact that these tools have on child welfare systems and racial disproportionality.

Keywords: actuarial risk, child welfare, predictive risk, racial disproportionality

Procedia PDF Downloads 16

Authors: Annalise Weckesser, Alex Wade, Clara Joergensen, Jerome Turner

Abstract:

Introduction: Digital mobile technologies afford Generation M a number of opportunities in terms of communication, creativity and connectivity in their social interactions. Yet these young people’s use of such technologies is often the source of moral panic with accordant social anxiety especially prevalent in media representations of teen ‘sexting,’ or the sending of sexually explicit images via smartphones. Thus far, most responses to youth sexting have largely been ineffective or unjust with adult authorities sometimes blaming victims of non-consensual sexting, using child pornography laws to paradoxically criminalise those they are designed to protect, and/or advising teenagers to simply abstain from the practice. Prevention strategies are further skewed, with sex education initiatives often targeted at girls, implying that they shoulder the responsibility of minimising the risks associated with sexting (e.g. revenge porn and sexual predation). Purpose of Study: Despite increasing public interest and concern about ‘teen sexting,’ there remains a dearth of research with young people regarding their experiences of navigating sex and relationships in the current digital media landscape. Furthermore, young people's views on sexting are rarely solicited in the policy and educational strategies aimed at them. To address this research-policy-education gap, an interdisciplinary team of four researchers (from anthropology, media, sociology and education) have undertaken a peer-to-peer research project to co-create a sexual health intervention. Methods: In the winter of 2015-2016, the research team conducted serial group interviews with four cohorts of students (aged 13 to 15) from a secondary school in the West Midlands, UK. To facilitate open dialogue, girls and boys were interviewed separately, and each group consisted of no more than four pupils. The team employed a range of participatory techniques to elicit young people’s views on sexting, its consequences, and its interventions. A final focus group session was conducted with all 14 male and female participants to explore developing a peer-to-peer ‘safe sexting’ education intervention. Findings: This presentation will highlight the ongoing, ‘old school’ sexual double standards at work within this new digital frontier. In the sharing of ‘nudes’ (teens’ preferred term to ‘sexting’) via social media apps (e.g. Snapchat and WhatsApp), girls felt sharing images was inherently risky and feared being blamed and ‘slut-shamed.’ In contrast, boys were seen to gain in social status if they accumulated nudes of female peers. Further, if boys had nudes of themselves shared without consent, they felt they were expected to simply ‘tough it out.’ The presentation will also explore what forms of supports teens desire to help them in their day-to-day navigation of these digitally mediated, heteronormative performances of teen femininity and masculinity expected of them. Conclusion: This is the first research project, within UK, conducted with rather than about teens and the phenomenon of sexting. It marks a timely and important contribution to the nascent, but growing body of knowledge on gender, sexual politics and the digital mobility of sexual images created by and circulated amongst young people.

Keywords: teens, sexting, gender, sexual politics

Procedia PDF Downloads 202

Authors: Ozgul Kartal, Wade Tillett, Lyn D. English

Abstract:

Despite its global significance in curricula, mathematical modeling encounters persistent disparities in recognition and emphasis within regular mathematics classrooms and teacher education across countries with diverse educational and cultural traditions, including variations in the perceived role of mathematical modeling. Over the past two decades, increased attention has been given to the integration of mathematical modeling into national curriculum standards in the U.S. and other countries. Therefore, the mathematics education research community has dedicated significant efforts to investigate various aspects associated with the teaching and learning of mathematical modeling, primarily focusing on exploring the applicability of modeling in schools and assessing students', teachers', and preservice teachers' (PTs) competencies and engagement in modeling cycles and processes. However, limited attention has been directed toward examining potential resistance hindering teachers and PTs from effectively implementing mathematical modeling. This study focuses on how PTs, without prior modeling experience, resist and/or embrace mathematical modeling and its pedagogy as they learn about models and modeling perspectives, navigate the modeling process, design and implement their modeling activities and lesson plans, and experience the pedagogy enabling modeling. Model eliciting activities (MEAs) were employed due to their high potential to support the development of mathematical modeling pedagogy. The mathematical modeling module was integrated into a mathematics methods course to explore how PTs embraced or resisted mathematical modeling and its pedagogy. The module design included reading, reflecting, engaging in modeling, assessing models, creating a modeling task (MEA), and designing a modeling lesson employing an MEA. Twelve senior undergraduate students participated, and data collection involved video recordings, written prompts, lesson plans, and reflections. An open coding analysis revealed acceptance and resistance toward teaching mathematical modeling. The study identified four overarching themes, including both acceptance and resistance: pedagogy, affordance of modeling (tasks), modeling actions, and adjusting modeling. In the category of pedagogy, PTs displayed acceptance based on potential pedagogical benefits and resistance due to various concerns. The affordance of modeling (tasks) category emerged from instances when PTs showed acceptance or resistance while discussing the nature and quality of modeling tasks, often debating whether modeling is considered mathematics. PTs demonstrated both acceptance and resistance in their modeling actions, engaging in modeling cycles as students and designing/implementing MEAs as teachers. The adjusting modeling category captured instances where PTs accepted or resisted maintaining the qualities and nature of the modeling experience or converted modeling into a typical structured mathematics experience for students. While PTs displayed a mix of acceptance and resistance in their modeling actions, limitations were observed in embracing complexity and adhering to model principles. The study provides valuable insights into the challenges and opportunities of integrating mathematical modeling into teacher education, emphasizing the importance of addressing pedagogical concerns and providing support for effective implementation. In conclusion, this research offers a comprehensive understanding of PTs' engagement with modeling, advocating for a more focused discussion on the distinct nature and significance of mathematical modeling in the broader curriculum to establish a foundation for effective teacher education programs.

Keywords: mathematical modeling, model eliciting activities, modeling pedagogy, secondary teacher education

Procedia PDF Downloads 28