Search results for: specific learning disability

Authors: Dike Felix Okechukwu

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Studies and reports from authoritative sources such as the Intergovernmental Panel on Climate Change (IPCC) have stated that to effectively solve environmental sustainability challenges such as pollution, inappropriate waste disposal, and unsustainable consumption, there is a need for more research to seek solutions towards environmentally sustainable behavior. However, literature thus far reports only sporadic developments of TL in Environmental Sustainability because there are scarce reports showing the reliable process(es) to produce TL - for sustainability projects or otherwise. Nonetheless, a recently published article demonstrates how TL can be used to help young adults gain transformed mindsets and habits toward environmental sustainability behaviors and practices. This study, however, does not demonstrate, on a repeated basis, the dependability of the method or reliability of the procedures in using its proposed methodology to help young adults achieve transformed habits towards environmental sustainability behaviors, especially in diverse contexts. In this study, it is demonstrated, through repeated measures, a reliable process that can be used to achieve transformations in habits and mindsets toward environmental sustainability behaviors. To achieve this, the design adopted is multiple case studies and a thematic analysis techniques. Five cases in diverse contexts were used to analyze pieces of evidence of Transformative Learning Outcomes toward environmentally sustainable behaviors. Results from the study offer fresh perspectives on a reliable methodology that can be adopted to achieve Transformations in Habits and mindsets toward environmental sustainability behaviors.

Keywords: environmental sustainability, transformative learning, behaviour, learning, education

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Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

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The escalating adoption of electric vehicles (EVs) across the globe has underscored the critical importance of advancing battery system technologies. This has catalyzed a shift towards the design and development of battery systems that not only exhibit higher energy efficiency but also boast enhanced thermal performance and sophisticated multi-material enclosures. A significant leap in this domain has been the incorporation of simulation-based design optimization for battery packs and Battery Management Systems (BMS), a move further enriched by integrating artificial intelligence/machine learning (AI/ML) approaches. These strategies are pivotal in refining the design, manufacturing, and operational processes for electric vehicles and energy storage systems. By leveraging AI/ML, stakeholders can now predict battery performance metrics—such as State of Health, State of Charge, and State of Power—with unprecedented accuracy. Furthermore, as Li-ion batteries (LIBs) become more prevalent in urban settings, the imperative for bolstering thermal and fire resilience has intensified. This has propelled Battery Thermal Management Systems (BTMs) to the forefront of energy storage research, highlighting the role of machine learning and AI not just as tools for enhanced safety management through accurate temperature forecasts and diagnostics but also as indispensable allies in the early detection and warning of potential battery fires.

Keywords: electric vehicles, battery thermal management, industrial engineering, machine learning, artificial intelligence, manufacturing

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Authors: Satendra Pal Singh, Dalip Kr. Kakru, Jyoti Mishra, Rajesh Thakur, Tarana Sarwat

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COVID-19 is still an intrigue as far as morbidity or mortality is concerned. The rate of recovery varies from person to person, & it depends upon the accessibility of the healthcare system and the roles played by the physicians and caregivers. It is envisaged that with the passage of time, people would become immune to this virus, and those who are vulnerable would sustain themselves with the help of vaccines. The proposed study deals with the severeness of COVID-19 is associated with some specific biomarkers linked to correlate age and gender. We will be assessing the overall homeostasis of the persons who were affected by the coronavirus infection and also of those who recovered from it. Some people show more severe effects, while others show very mild symptoms, however, they show low CT values. Thus far, it is unclear why the new strain of Covid has different effects on different people in terms of age, gender, and ABO blood typing. According to data, the fatality rate with heart disease was 10.5 percent, 7.3 percent were diabetic, and 6 percent who are already infected from other comorbidities. However, some COVID-19 cases are worse than others & it is not fully explainable as of date. Overall data show that the ABO blood group is effective or prone to the risk of SARS-COV2 infection, while another study also shows the phenotypic effects of the blood group related to covid. It is an accepted fact that females have more strong immune systems than males, which may be related to the fact that females have two ‘X’ chromosomes, which might contain a more effective immunity booster gene on the X chromosome, and are capable to protect the female. Also specific sex hormones also induce a better immune response in a specific gender. This calls for in-depth analysis to be able to gain insight into this dilemma. COVID-19 is still not fully characterized, and thus we are not very familiar with its biology, mode of infection, susceptibility, and overall viral load in the human body. How many virus particles are needed to infect a person? How, then, comorbidity contribute to coronavirus infection? Since the emergence of this virus in 2020, a large number of papers have been published, and seemingly, vaccines have been prepared. But still, a large number of questions remain unanswered. The proneness of humans for infection by covid-19 needs to be established to be able to develop a better strategy to fight this virus. Our study will be on the Impact of demography on the Severity of covid-19 infection & at the same time, will look into gender-specific sensitivity of Covid-19 and the Operational variation of different biochemical markers in Covid-19 positive patients. Besides, we will be studying the co-relation, if any, of COVID severity & ABO Blood group type and the occurrence of the most common blood group type amongst positive patience.

Keywords: coronavirus, ABO blood group, age, gender

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Ayesha Selwyn, Annapoorni Chandrashekar, Kumar Ashwarya, Nishant Baghel

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Project-based learning (PBL) activities are typically implemented in technology-enabled schools by highly trained teachers. In rural India, students have limited access to technology and quality education. Implementing typical PBL activities is challenging. This study details how Pratham Education Foundation’s Hybrid Learning model was used to implement two PBL activities related to music in 900 remote Indian villages with 46,000 students aged 10-14. The activities were completed by 69% of groups that submitted a total of 15,000 videos (completed projects). Pratham’s H-Learning model reaches 100,000 students aged 3-14 in 900 Indian villages. The community-driven model engages students in 20,000 self-organized groups outside of school. The students are guided by 6,000 youth volunteers and 100 facilitators. The students partake in learning activities across subjects with the support of community stakeholders and offline digital content on shared Android tablets. A training and implementation toolkit for PBL activities is designed by subject experts. This toolkit is essential in ensuring efficient implementation of activities as facilitators aren’t highly skilled and have limited access to training resources. The toolkit details the activity at three levels of student engagement - enrollment, participation, and completion. The subject experts train project leaders and facilitators who train youth volunteers. Volunteers need to be trained on how to execute the activity and guide students. The training is focused on building the volunteers’ capacity to enable students to solve problems, rather than developing the volunteers’ subject-related knowledge. This structure ensures that continuous intervention of subject matter experts isn’t required, and the onus of judging creativity skills is put on community members. 46,000 students in the H-Learning program were engaged in two PBL activities related to Music from April-June 2019. For one activity, students had to conduct a “musical survey” in their village by designing a survey and shooting and editing a video. This activity aimed to develop students’ information retrieval, data gathering, teamwork, communication, project management, and creativity skills. It also aimed to identify talent and document local folk music. The second activity, “Pratham Idol”, was a singing competition. Students participated in performing, producing, and editing videos. This activity aimed to develop students’ teamwork and creative skills and give students a creative outlet. Students showcased their completed projects at village fairs wherein a panel of community members evaluated the videos. The shortlisted videos from all villages were further evaluated by experts who identified students and adults to participate in advanced music workshops. The H-Learning framework enables students in low resource settings to engage in PBL and develop relevant skills by leveraging community support and using video creation as a tool. In rural India, students do not have access to high-quality education or infrastructure. Therefore designing activities that can be implemented by community members after limited training is essential. The subject experts have minimal intervention once the activity is initiated, which significantly reduces the cost of implementation and allows the activity to be implemented at a massive scale.

Keywords: community supported learning, project-based learning, self-organized learning, education technology

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Authors: Anne E. Goodenough

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One of the most important roles of higher education professionals is to ensure that graduates have excellent employment prospects. This means providing students with the skills necessary to be immediately effective in the workplace. Increasingly, universities are seeking to achieve this by moving from lecture-based and campus-delivered curricula to more varied delivery, which takes students out of their academic comfort zone and allows them to engage with, and be challenged by, real world issues. One popular approach is integration of problem-based learning (PBL) projects into curricula. However, although the potential benefits of PBL are considerable, it can be difficult to devise projects that are meaningful, such that they can be regarded as mere ‘hoop jumping’ exercises. This study examines three-way partnerships between academics, students, and external link organizations. It studied the experiences of all partners involved in different collaborative projects to identify how benefits can be maximized and challenges overcome. Focal collaborations included: (1) development of real-world modules with novel assessment whereby the organization became the ‘client’ for student consultancy work; (2) frameworks where students collected/analyzed data for link organizations in research methods modules; (3) placement-based internships and dissertations; (4) immersive fieldwork projects in novel locations; and (5) students working as partners on staff-led research with link organizations. Focus groups, questionnaires and semi-structured interviews were used to identify opportunities and barriers, while quantitative analysis of students’ grades was used to determine academic effectiveness. Common challenges identified by academics were finding suitable link organizations and devising projects that simultaneously provided education opportunities and tangible benefits. There was no ‘one size fits all’ formula for success, but careful planning and ensuring clarity of roles/responsibilities were vital. Students were very positive about collaboration projects. They identified benefits to confidence, time-keeping and communication, as well as conveying their enthusiasm when their work was of benefit to the wider community. They frequently highlighted employability opportunities that collaborative projects opened up and analysis of grades demonstrated the potential for such projects to increase attainment. Organizations generally recognized the value of project outputs, but often required considerable assistance to put the right scaffolding in place to ensure projects worked. Benefits were maximized by ensuring projects were well-designed, innovative, and challenging. Co-publication of projects in peer-reviewed journals sometimes gave additional benefits for all involved, being especially beneficial for student curriculum vitae. PBL and student projects are by no means new pedagogic approaches: the novelty here came from creating meaningful three-way partnerships between academics, students, and link organizations at all undergraduate levels. Such collaborations can allow students to make a genuine contribution to knowledge, answer real questions, solve actual problems, all while providing tangible benefits to organizations. Because projects are actually needed, students tend to engage with learning at a deep level. This enhances student experience, increases attainment, encourages development of subject-specific and transferable skills, and promotes networking opportunities. Such projects frequently rely upon students and staff working collaboratively, thereby also acting to break down the traditional teacher/learner division that is typically unhelpful in developing students as advanced learners.

Keywords: higher education, employability, link organizations, innovative teaching and learning methods, interactions between enterprise and education, student experience

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Authors: Angkana Tungkasamit, Ladda Silanoi , Teerachai Nethanomsak, Sitthipon Art-in, Siribhong Bhiasiri

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As the date for the commencement of the ASEAN Community in Year 2015 is approaching, it has become apparent to all that there is an urgent need to get Thai people ready to meet the challenge of entering into the Community confidently. Our research team has been organized by the Faculty of Education, Khon Kaen University with the task of training administrators and teachers of the schools along the borders with Laos People’s Democratic Republic and the Kingdom of Cambodia to be able to develop supplementary courses on ASEAN Community. The course to be developed is based on the essential elements of the Community, i.e. general backgrounds of the member countries, the education, social and economic life in the Community and social skills needed for a good citizen of the ASEAN Community. The study, based on learning outcome and learning management process as a basis for inquiry, was a research and development in nature using participative action research as a means to achieve the goal of helping school administrators and teachers to learn how to develop supplementary courses to be used in their schools. A post-workshop evaluation of the outcome was made and found that, besides the successfully completed supplementary course, the participants were satisfied with their participation in the workshop because they had participated in every step of the development activity, from the beginning to the end.

Keywords: development of supplementary course, ASEAN community, social studies, northeastern border area of Thailand

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Authors: Mahmoud Huleihel, George Abu-Aqil, Manal Suleiman, Klaris Riesenberg, Itshak Lapidot, Ahmad Salman

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Urinary tract infections (UTIs) are considered to be the most common bacterial infections worldwide, which are caused mainly by Escherichia (E.) coli (about 80%). Klebsiella pneumoniae (about 10%) and Pseudomonas aeruginosa (about 6%). Although antibiotics are considered as the most effective treatment for bacterial infectious diseases, unfortunately, most of the bacteria already have developed resistance to the majority of the commonly available antibiotics. Therefore, it is crucial to identify the infecting bacteria and to determine its susceptibility to antibiotics for prescribing effective treatment. Classical methods are time consuming, require ~48 hours for determining bacterial susceptibility. Thus, it is highly urgent to develop a new method that can significantly reduce the time required for determining both infecting bacterium at the species level and diagnose its susceptibility to antibiotics. Fourier-Transform Infrared (FTIR) spectroscopy is well known as a sensitive and rapid method, which can detect minor molecular changes in bacterial genome associated with the development of resistance to antibiotics. The main goal of this study is to examine the potential of FTIR spectroscopy, in tandem with machine learning algorithms, to identify the infected bacteria at the species level and to determine E. coli susceptibility to different antibiotics directly from patients' urine in about 30minutes. For this goal, 1600 different E. coli isolates were isolated for different patients' urine sample, measured by FTIR, and analyzed using different machine learning algorithm like Random Forest, XGBoost, and CNN. We achieved 98% success in isolate level identification and 89% accuracy in susceptibility determination.

Keywords: urinary tract infections (UTIs), E. coli, Klebsiella pneumonia, Pseudomonas aeruginosa, bacterial, susceptibility to antibiotics, infrared microscopy, machine learning

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Authors: Jimena Alarcon, Andrea Llorens, Gabriel Hernandez, Maritza Palma, Lucia Navarrete

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The research has funding from the Government of Chile and is focused on defining the design of rural primary classroom that stimulates creativity. The relevance of the study consists of its capacity to define adequate educational spaces for the implementation of the design-based learning (DBL) methodology. This methodology promotes creativity and teamwork, generating a meaningful learning experience for students, based on the appreciation of their environment and the generation of projects that contribute positively to their communities; also, is an inquiry-based form of learning that is based on the integration of design thinking and the design process into the classroom. The main goal of the study is to define the design characteristics of rural primary school classrooms, associated with the implementation of the DBL methodology. Along with the change in learning strategies, it is necessary to change the educational spaces in which they develop. The hypothesis indicates that a change in the space and equipment of the classrooms based on the emotions of the students will motivate better learning results based on the implementation of a new methodology. In this case, the pedagogical dynamics require an important interaction between the participants, as well as an environment favorable to creativity. Methodologies from Kansei engineering are used to know the emotional variables associated with their definition. The study is done to 50 students between 6 and 10 years old (average age of seven years), 48% of men and 52% women. Virtual three-dimensional scale models and semantic differential tables are used. To define the semantic differential, self-applied surveys were carried out. Each survey consists of eight separate questions in two groups: question A to find desirable emotions; question B related to emotions. Both questions have a maximum of three alternatives to answer. Data were tabulated with IBM SPSS Statistics version 19. Terms referred to emotions are grouped into twenty concepts with a higher presence in surveys. To select the values obtained as part of the implementation of Semantic Differential, a number expected of 'chi-square test (x2)' frequency calculated for classroom space is considered lower limit. All terms over the N expected a cut point, are included to prepare tables for surveys to find a relation between emotion and space. Statistic contrast (Chi-Square) represents significance level ≥ 0, indicator that frequencies appeared are not random. Then, the most representative terms depend on the variable under study: a) definition of textures and color of vertical surfaces is associated with emotions such as tranquility, attention, concentration, creativity; and, b) distribution of the equipment of the rooms, with emotions associated with happiness, distraction, creativity, freedom. The main findings are linked to the generation of classrooms according to diverse DBL team dynamics. Kansei engineering is the appropriate methodology to know the emotions that students want to feel in the classroom space.

Keywords: creativity, design-based learning, education spaces, emotions

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Authors: Tajudeen Yusuf

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Arabic language and its instruction occupy a prominent status in the contemporary world, especially in academic and research institutions. Arabic, like other international languages, consolidates understanding among people of different nations and societies. It is a promising medium of sharing thoughts and feelings. As a means of communication and interaction, the language has gained its outstanding status since ancient times, especially because of the relationship it maintains with Islam and its heritage. Adding to its importance is the rapid growth and advancement of Science and Technology in the contemporary Era which has eventually made communication between human societies all over the world inevitable. Despite, the Arabic language still experiences many challenges especially in some area such as irrelevant textbooks and other teaching materials, old versions of teaching methods and inadequate teachers who professionally trained. Eventually, these have resulted in difficulties in the teaching and learning of the language. Therefore, urgent and necessary measures to enhance the teaching and learning of Arabic language within and outside Arab countries are therefore needed to be taken.

Keywords: Arabic, language, challenges, modern era

Procedia PDF Downloads 597

Authors: Omnia F. Elkommos

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In the course of teaching stylistics to undergraduate students of the Department of English Language and Literature, Faculty of Arts and Humanities, the linguistic tool kit of theories comes in handy and useful for the better understanding of the different literary genres: Poetry, drama, and short stories. In the present paper, a model of teaching of stylistics is compiled and suggested. It is a collaborative group project technique for use in the undergraduate diverse specialisms (Literature, Linguistics and Translation tracks) class. Students initially are introduced to the different linguistic tools and theories suitable for each literary genre. The second step is to apply these linguistic tools to texts. Students are required to watch videos performing the poems or play, for example, and search the net for interpretations of the texts by other authorities. They should be using a template (prepared by the researcher) that has guided questions leading students along in their analysis. Finally, a practical analysis would be written up using the practical analysis essay template (also prepared by the researcher). As per collaborative learning, all the steps include activities that are student-centered addressing differentiation and considering their three different specialisms. In the process of selecting the proper tools, the actual application and analysis discussion, students are given tasks that request their collaboration. They also work in small groups and the groups collaborate in seminars and group discussions. At the end of the course/module, students present their work also collaboratively and reflect and comment on their learning experience. The module/course uses a drama play that lends itself to the task: ‘The Bond’ by Amy Lowell and Robert Frost. The project results in an interpretation of its theme, characterization and plot. The linguistic tools are drawn from pragmatics, and discourse analysis among others.

Keywords: applied linguistic theories, collaborative learning, cooperative principle, discourse analysis, drama analysis, group project, online acting performance, pragmatics, speech act theory, stylistics, technology enhanced learning

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Authors: R Palson Kennedy, P.Kiran Sai

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This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

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Authors: Ahmed Negm, George Aggidis, Xiandong Ma

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With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

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Authors: Miriam I. Jimenez-Perez, Mariana C. Orellana-Haro, Carolina Guzman-Brambila

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As part of microbiology and dietetics courses, students of medicine and nutrition analyze the main pathogenic microorganisms and perform dietary analyzes. The course of microbiology describes in a general way the main pathogens including bacteria, viruses, fungi, and parasites, as well as their interaction with the human species. We hypothesize that lack of practical application of the course causes the students not to find the value and the clinical application of it when in reality it is a matter of great importance for healthcare in our country. The courses of the medical microbiology and dietetics are mostly theoretical and only a few hours of laboratory practices. Therefore, it is necessary the incorporation of new innovative techniques that involve more practices and community fieldwork, real cases analysis and real-life situations. The purpose of this intervention was to incorporate real-world learning experiences in the instruction of medical microbiology and dietetics courses, in order to improve the learning process, understanding and the application in the field. During a period of 6 months, medicine and nutrition students worked in a community of urban poverty. We worked with 90 children between 4 and 6 years of age from low-income families with no access to medical services, to give an infectious diagnosis related to nutritional status in these children. We expect that this intervention would give a different kind of context to medical microbiology and dietetics students improving their learning process, applying their knowledge and laboratory practices to help a needed community. First, students learned basic skills in microbiology diagnosis test during laboratory sessions. Once, students acquired abilities to make biochemical probes and handle biological samples, they went to the community and took stool samples from children (with the corresponding informed consent). Students processed the samples in the laboratory, searching for enteropathogenic microorganism with RapID™ ONE system (Thermo Scientific™) and parasites using Willis and Malloy modified technique. Finally, they compared the results with the nutritional status of the children, previously measured by anthropometric indicators. The anthropometric results were interpreted by the OMS Anthro software (WHO, 2011). The microbiological result was interpreted by ERIC® Electronic RapID™ Code Compendium software and validated by a physician. The results were analyses of infectious outcomes and nutritional status. Related to fieldwork community learning experiences, our students improved their knowledge in microbiology and were capable of applying this knowledge in a real-life situation. They found this kind of learning useful when they translate theory to a real-life situation. For most of our students, this is their first contact as health caregivers with real population, and this contact is very important to help them understand the reality of many people in Mexico. In conclusion, real-world or fieldwork learning experiences empower our students to have a real and better understanding of how they can apply their knowledge in microbiology and dietetics and help a much- needed population, this is the kind of reality that many people live in our country.

Keywords: real-world learning experiences, medical microbiology, dietetics, nutritional status, infectious status.

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Authors: Zahra Asgharpour, Eric Renteria, Sebastian De Boodt

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There is a growing trend towards personalization of medical care, as evidenced by the emphasis on outcomes based medicine, the latest developments in CT and MR imaging and personalized treatment in a variety of surgical disciplines. 3D Printing has been introduced and applied in the medical field since 2000. The first applications were in the field of dental implants and custom prosthetics. According to recent publications, 3D printing in the medical field has been used in a wide range of applications which can be organized into several categories including implants, prosthetics, anatomical models and tissue bioprinting. Some of these categories are still in their infancy stage of the concept of proof while others are in application phase such as the design and manufacturing of customized implants and prosthesis. The approach of 3D printing in this category has been successfully used in the health care sector to make both standard and complex implants within a reasonable amount of time. In this study, some of the clinical applications of 3D printing in design and manufacturing of a patient-specific hip implant would be explained. In cases where patients have complex bone geometries or are undergoing a complex revision on hip replacement, the traditional surgical methods are not efficient, and hence these patients require patient-specific approaches. There are major advantages in using this new technology for medical applications, however, in order to get this technology widely accepted in medical device industry, there is a need for gaining more acceptance from the medical device regulatory offices. This is a challenge that is moving onward and will help the technology find its way at the end as an accepted manufacturing method for medical device industry in an international scale. The discussion will conclude with some examples describing the future directions of 3D Medical Printing.

Keywords: CT/MRI, image processing, 3D printing, medical devices, patient specific implants

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Authors: Christopher Leung, Tony Kim, Rebecca Lendzion, Scott Mackenzie

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Retroperitoneal abscesses are a rare but serious condition with often delayed diagnosis, non-specific symptoms, multiple causes and high morbidity/mortality. With the advent of more readily available cross-sectional imaging, retroperitoneal abscesses are treated earlier and better outcomes are achieved. Occasionally, a retroperitoneal abscess is present as a huge retroperitoneal abscess, as evident in this 53-year-old male. With a background of chronic renal disease and left partial nephrectomy, this gentleman presented with a one-month history of left flank pain without any other symptoms, including fevers or abdominal pain. CT abdomen and pelvis demonstrated a huge retroperitoneal abscess spanning from the diaphragm, abutting the spleen, down to the iliopsoas muscle and abutting the iliac vessels at the pelvic brim. This large retroperitoneal abscess required open drainage as well as drainage by interventional radiology. A long course of intravenous antibiotics and multiple drainages was required to drain the abscess. His blood culture and fluid culture grew Proteus species suggesting a urinary source, likely from his non-functioning kidney, which had a partial nephrectomy. Such a huge retroperitoneal abscess has rarely been described in the literature. The learning point here is that the basic principle of source control and antibiotics is paramount in treating retroperitoneal abscesses regardless of the size of the abscess.

Keywords: retroperitoneal abscess, retroperitoneal mass, sepsis, genitourinary infection

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Authors: Mustafa Tevfik Hebebci, Ismail Sahin, Sirin Kucuk, Ismail Celik, Ahmet Oguz Akturk

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ADDIE is an instructional design model which has the five core elements: analyze, design, develop, implement, and evaluate. The ADDIE approach provides a systematic process for the analysis of instructional needs, the design and development of instructional programs and materials, implementation of a program, and the evaluation of the effectiveness of an instruction. The case-based study is an instructional design model that is a variant of project-oriented learning. Collecting and analyzing stories can be used in two primary ways -perform task analysis and as a learning support during instruction- by instructional designers. Besides, teachers use technology to develop students’ thinking, enriching the learning environment and providing permanent learning. The purpose of this paper is to introduce an interactive online case-study library website developed in a national project. The design goal of the website is to provide interactive, enhanced, case-based and online educational resource for educators through the purpose and within the scope of a national project. The ADDIE instructional design model was used in the development of the website for the interactive case-based library. This web-based library contains the navigation menus as the follows: “Homepage”, "Registration", "Branches", "Aim of The Research", "About TPACK", "National Project", "Contact Us", etc. This library is developed on a web-based platform, which is important in terms of manageability, accessibility, and updateability of data. Users are able to sort the displayed case-studies by their titles, dates, ratings, view counts, etc. In addition, they encouraged to rate and comment on the case-studies. The usability test is used and the expert opinion is taken for the evaluation of the website. This website is a tool to integrate technology in education. It is believed that this website will be beneficial for pre-service and in-service teachers in terms of their professional developments.

Keywords: design, ADDIE, case based library, technology integration

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Authors: Rodrigo S. Piera, Jailson Sales Ara´ujo, Gabriela B. Lemos, Matthew B. Weiss, John B. DeBrota, Gabriel H. Aguilar, Jacques L. Pienaar

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The Born rule was historically viewed as an independent axiom of quantum mechanics until Gleason derived it in 1957 by assuming the Hilbert space structure of quantum measurements [1]. In subsequent decades there have been diverse proposals to derive the Born rule starting from even more basic assumptions [2]. In this work, we demonstrate that a simple reinforcement-learning algorithm, having no pre-programmed assumptions about quantum theory, will nevertheless converge to a behaviour pattern that accords with the Born rule, when tasked with predicting the output of a quantum optical implementation of a symmetric informationally-complete measurement (SIC). Our findings support a hypothesis due to QBism (the subjective Bayesian approach to quantum theory), which states that the Born rule can be thought of as a normative rule for making decisions in a quantum world [3].

Keywords: quantum Bayesianism, quantum theory, quantum information, quantum measurement

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Authors: Salsabila Meutia Meutia

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Indonesia as one of the countries that agreed to SDG's must commit to achieve this SDG's goal until the deadline of 2030. The government has tried hard to realize all the goals in the SDG’s, but there is still something that has not been achieved, especially the goal in number 4 which is to ensure that every human being has a decent and inclusive education and encourages lifelong learning opportunities for everyone. Teenagers who are the golden generation for Indonesia are starting to feel dependent on Youtube. The addictive virus of teenagers about using YouTube is both good news and bad news for the sustainability of government programs in achieving goals in SDG’s, especially in term of education. One popular YouTube channel among high school teenagers is Nihongo Mantappu which has 1.8 million followers. This channel contains interesting but quality content that can have a positive influence for the audience. This research was conducted to determine the effectiveness of the Nihongo Mantappu channel on Youtube as a means of fostering enthusiasm and awareness of learning in tenth graders of SMA Muhammadiyah 10 GKB, as well as how it affected in achieving quality educational goals as an effort to succeed in the Sustainable Development Goals of 2030. The objectives of this study were carried out with distributing questionnaires to tenth graders of SMA Muhammadiyah 10 GKB and observing objects in the real life. Then the data obtained are analyzed and described properly so that this research is a descriptive study. The results of the study mentioned that YouTube as one of the websites for viewing and sharing videos is a very effective media for disseminating information, especially among teenagers. The Nihongo Mantappu channel is also considered to be a very effective channel in building enthusiasm and awareness of learning in tenth graders of SMA Muhammadiyah 10 GKB. Students as the main subject of education have a great influence on the achievement of one of SDG’s fourth goals, named quality education. Students who are always on fire in the spirit and awareness of learning will greatly help the achievement of quality education goals in the Sustainable Development Goals by 2030.

Keywords: Youtube, Nihongo, Mantappu, SDG's

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Tamal Roy, Anuradha Bhat

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Cognitive abilities aid fishes in foraging, avoiding predators & locating mates. Factors like predation pressure & habitat complexity govern learning & memory in fishes. This study aims to compare spatial learning & memory across four natural populations of zebrafish. Zebrafish, a small cyprinid inhabits a diverse range of freshwater habitats & this makes it amenable to studies investigating role of native environment in spatial cognitive abilities. Four populations were collected across India from waterbodies with contrasting ecological conditions. Habitat complexity of the water-bodies was evaluated as a combination of channel substrate diversity and diversity of vegetation. Experiments were conducted on populations under controlled laboratory conditions. A square shaped spatial testing arena (maze) was constructed for testing the performance of adult zebrafish. The square tank consisted of an inner square shaped layer with the edges connected to the diagonal ends of the tank-walls by connections thereby forming four separate chambers. Each of the four chambers had a main door in the centre. Each chamber had three sections separated by two windows. A removable coloured window-pane (red, yellow, green or blue) identified each main door. A food reward associated with an artificial plant was always placed inside the left-hand section of the red-door chamber. The position of food-reward and plant within the red-door chamber was fixed. A test fish would have to explore the maze by taking turns and locate the food inside the right-side section of the red-door chamber. Fishes were sorted from each population stock and kept individually in separate containers for identification. At a time, a test fish was released into the arena and allowed 20 minutes to explore in order to find the food-reward. In this way, individual fishes were trained through the maze to locate the food reward for eight consecutive days. The position of red door, with the plant and the reward, was shuffled every day. Following training, an intermission of four days was given during which the fishes were not subjected to trials. Post-intermission, the fishes were re-tested on the 13th day following the same protocol for their ability to remember the learnt task. Exploratory tendencies and latency of individuals to explore on 1st day of training, performance time across trials, and number of mistakes made each day were recorded. Additionally, mechanism used by individuals to solve the maze each day was analyzed across populations. Fishes could be expected to use algorithm (sequence of turns) or associative cues in locating the food reward. Individuals of populations did not differ significantly in latencies and tendencies to explore. No relationship was found between exploration and learning across populations. High habitat-complexity populations had higher rates of learning & stronger memory while low habitat-complexity populations had lower rates of learning and much reduced abilities to remember. High habitat-complexity populations used associative cues more than algorithm for learning and remembering while low habitat-complexity populations used both equally. The study, therefore, helped understand the role of natural ecology in explaining variations in spatial learning abilities across populations.

Keywords: algorithm, associative cue, habitat complexity, population, spatial learning

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Authors: Eunice H. Li

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This paper discusses and analyses a small portion of the literature that has been reviewed for research work in Distance Education (DE) pedagogies that I am currently undertaking. It begins by presenting a brief overview of Taylor's (2001) five-generation models of Distance Education. The focus of the discussion will be on the 5th generation, Intelligent Flexible Learning Model. For this generation, educational and other institutions make portal access and interactive multi-media (IMM) an integral part of their operations. The paper then takes a brief look at current trends in technologies – for example smart-watch wearable technology such as Apple Watch. The emergent trends in technologies carry many new features. These are compared to former DE generational features. Also compared is the time span that has elapsed between the generations that are referred to in Taylor's model. This paper is a work in progress. The paper therefore welcome new insights, comparisons and critique of the issues discussed.

Keywords: distance education, e-learning technologies, pedagogy, generational models

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Authors: Zory Marantz

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Hybrid flexible (HyFlex) is a pedagogical methodology whereby an instructor delivers content in three modalities, i.e. live in-person (LIP), live online synchronous (LOS), and non-live online asynchronous (nLOaS). HyFlex is focused on providing the largest level of flexibility needed to achieve a cohesive environment across all modalities and incorporating four basic principles – learner’s choice, reusability, accessibility, and equivalency. Much literature has focused on the advantages of this methodology in providing students with the flexibility to choose their learning modality as best suits their schedules and learning styles. Initially geared toward graduate-level students, the concept has been applied to undergraduate studies, particularly during our national pedagogical response to the COVID19 pandemic. There is still little literature about the practicality and feasibility of HyFlex for hardware laboratory intensive engineering technology programs, particularly in dense, urban commuter institutions of higher learning. During a semester of engineering, a lab-based course was taught in the HyFlex modality, and students were asked to complete a survey about their experience. The data demonstrated that there is no single mode that is preferred by a majority of students and the usefulness of any modality is limited to how familiar the student and instructor are with the technology being applied. The technology is only as effective as our understanding and comfort with its functionality. For HyFlex to succeed in its implementation in an engineering technology environment within an urban commuter institution, faculty and students must be properly introduced to the technology being used.

Keywords: education, HyFlex, technology, urban, commuter, pedagogy

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Jill Steel

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Introduction: Animal-assisted learning (AAL) interventions are increasing exponentially, yet a paucity of quality research in the field exists. The aim of this study was to evaluate how the promotion of emotional wellbeing, through AAL, in this case, a dog, may support children’s engagement with reading in a Primary 1 classroom. Research indicates that dogs can provide emotional support to children; by forming a trusting attachment with a non-critical ‘friend’ who confers unconditional positive regard on the child, confidence may be boosted and anxiety reduced. By promoting emotional wellbeing through interactions with the dog, it is hoped that children begin to associate reading with feelings of wellbeing, which then results in increased engagement with reading. Methodology: A review of the literature was conducted. The relationship between emotional wellbeing and learning was explored, followed by an examination of the literature relating to Animal-Assisted Therapy and AAL. Scottish educational policy and legislation were analysed to establish the extent to which AAL might be suitable for the Scottish pedagogical context. An empirical study was conducted in a mainstream Primary 1 classroom over a four-week period. An inclusive approach was adopted whereby all children that wanted to interact with the dog were given the opportunity to do so, and all 25 children subsequently chose to participate. Children were not withdrawn from the classroom. Primary methods included interviews, observations, and questionnaires. Three focus children were selected for closer study. Main Results: Results were remarkably close to previous research and literature. Children’s emotional wellbeing was boosted, and engagement in reading improved. Principal Conclusions and Implications for Field: It was concluded that AAL could support emotional wellbeing and, in turn, promote children’s engagement with reading. The main limitation of the study was its short-term nature, and a longer randomised controlled trial with a larger sample, currently being undertaken by the author, would provide a fuller answer to the research question. Barriers to AAL include health and safety concerns and steps to ensure the welfare of the dog.

Keywords: animal-assisted learning, emotional wellbeing, reading, reading to dogs

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Authors: Jothilakshmy Nagammal

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This research paper deals with the different case studies, where the Form-Based Codes are adopted in general and the different implementation methods in particular are discussed to develop a method for formulating a new planning model. The organizing principle of the Form-Based Codes, the transect is used to zone the city into various context specific transects. An approach is adopted to develop the new planning model, city Specific Planning Model (CSPM), as a tool to achieve sustainability for any city in general. A case study comparison method in terms of the planning tools used, the code process adopted and the various control regulations implemented in thirty two different cities are done. The analysis shows that there are a variety of ways to implement form-based zoning concepts: Specific plans, a parallel or optional form-based code, transect-based code /smart code, required form-based standards or design guidelines. The case studies describe the positive and negative results from based zoning, Where it is implemented. From the different case studies on the method of the FBC, it is understood that the scale for formulating the Form-Based Code varies from parts of the city to the whole city. The regulating plan is prepared with the organizing principle as the transect in most of the cases. The various implementation methods adopted in these case studies for the formulation of Form-Based Codes are special districts like the Transit Oriented Development (TOD), traditional Neighbourhood Development (TND), specific plan and Street based. The implementation methods vary from mandatory, integrated and floating. To attain sustainability the research takes the approach of developing a regulating plan, using the transect as the organizing principle for the entire area of the city in general in formulating the Form-Based Codes for the selected Special Districts in the study area in specific, street based. Planning is most powerful when it is embedded in the broader context of systemic change and improvement. Systemic is best thought of as holistic, contextualized and stake holder-owned, While systematic can be thought of more as linear, generalisable, and typically top-down or expert driven. The systemic approach is a process that is based on the system theory and system design principles, which are too often ill understood by the general population and policy makers. The system theory embraces the importance of a global perspective, multiple components, interdependencies and interconnections in any system. In addition, the recognition that a change in one part of a system necessarily alters the rest of the system is a cornerstone of the system theory. The proposed regulating plan taking the transect as an organizing principle and Form-Based Codes to achieve sustainability of the city has to be a hybrid code, which is to be integrated within the existing system - A Systemic Approach with a Systematic Process. This approach of introducing a few form based zones into a conventional code could be effective in the phased replacement of an existing code. It could also be an effective way of responding to the near-term pressure of physical change in “sensitive” areas of the community. With this approach and method the new Context Specific Planning Model is created towards achieving sustainability is explained in detail this research paper.

Keywords: context based planning model, form based code, transect, systemic approach

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Authors: Eva Tolmeijer, Emmanuelle Peters, Veena Kumari, Liam Mason

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Cognitive behavioral therapy for psychosis (CBTp) is effective in many but not all patients, making it important to better understand the factors that determine treatment outcomes. To date, no studies have examined whether neuroimaging can make clinically useful predictions about who will respond to CBTp. To this end, we used machine learning methods that make predictions about symptom improvement at the individual patient level. Prior to receiving CBTp, 22 patients with a diagnosis of schizophrenia completed a social-affective processing task during functional MRI. Multivariate pattern analysis assessed whether treatment response could be predicted by brain activation responses to facial affect that was either socially threatening or prosocial. The resulting models did significantly predict symptom improvement, with distinct multivariate signatures predicting psychotic (r=0.54, p=0.01) and affective (r=0.32, p=0.05) symptoms. Psychotic symptom improvement was accurately predicted from relatively focal threat-related activation across hippocampal, occipital, and temporal regions; affective symptom improvement was predicted by a more dispersed profile of responses to prosocial affect. These findings enrich our understanding of the neurobiological underpinning of treatment response. This study provides a foundation that will hopefully lead to greater precision and tailoring of the interventions offered to patients.

Keywords: cognitive behavioral therapy, machine learning, psychosis, schizophrenia

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Authors: Lamia Bouzgarrou, Amira Omrane, Malika Azzouzi, Asma Kheder, Amira Saadallah, Ilhem Boussarsar, Kamel Rejeb

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Introduction: Increasing the women’s labor force participation is a political issue in countries with developed economies and those with low growth prospects. However, in the labor market, women continue to face several obstacles, either for the integration or for the maintenance at work. This study aims to assess the prevalence of premature withdrawal from working life -due to invalidity or medical justified early retirement- among active women in the Tunisian center and to identify its determinants. Material and methods: We conducted a cross-sectional study, over one year, focusing on the agreement for invalidity or early retirement for premature usury of the body- delivered by the medical commission of the National Health Insurance Fund (CNAM) in the central Tunisian district. We exhaustively selected women's files. Data related to Socio-demographic characteristics, professional and medical ones, were collected from the CNAM's administrative and medical files. Results: During the period of one year, 222 women have had an agreement for premature departure of their professional activity. Indeed, 149 women (67.11%) benefit of from invalidity agreement and 20,27% of them from favorable decision for early retirement. The average age was 50 ± 6 years with extremes of 23 and 62 years, and 18.9% of women were under 45 years. Married women accounted for 69.4% and 59.9% of them had at least one dependent child in charge. The average professional seniority in the sector was 23 ± 8 years. The textile-clothing sector was the most affected, with 70.7% of premature departure. Medical reasons for withdrawal from working life were mainly related to neuro-degenerative diseases in 46.8% of cases, rheumatic ones in 35.6% of cases and cardiovascular diseases in 22.1% of them. Psychiatric and endocrine disorders motivated respectively 17.1% and 13.5% of these departures. The evaluation of the sequels induced by these pathologies concluded to an average permanent partial disability equal to 61.4 ± 17.3%. The analytical study concluded that the agreement of disability or early retirement was correlated with the insured ‘age (p = 10-3), the professional seniority (p = 0.003) and the permanent partial incapacity (PPI) rate assessed by the expert physician (p = 0.04). No other social or professional factors were correlated with this decision. Conclusion: Despite many advances in labour law and Tunisian legal text on employability, women still exposed to several social and professional inequalities (payment inequality, precarious work ...). Indeed, women are often pushed to accept working in adverse conditions, thus they are more vulnerable to develop premature wear on the body and being forced to premature departures from the world of work. These premature withdrawals from active life are not only harmful to the concerned women themselves, but also associated with considerable costs for the insurance organism and the society. In order to ensure maintenance at work for women, a political commitment is imperative in the implementation of global prevention strategies and the improvement of working conditions, particularly in our socio-cultural context.

Keywords: Active Women , Early Retirement , Invalidity , Maintenance at Work

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Authors: Anshika Kankane, Dongshik Kang

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Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.

Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching

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Authors: Catherine Equey Balzli

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Old age retirement pensions are an important concern among the Swiss but estimating one’s income after retirement is difficult due to the Swiss insurance system’s complexity. This project’s aim is to prepare for developing a digital platform that will allow individuals to plan for retirement in a simplified manner. The main objective of the platform will be to give individuals the tools to check that their savings and retirement benefits will allow them to continue the lifestyle to which they are accustomed once they are retired. The research results from qualitative (focus group) and quantitative (survey) methodologies, recommend the scope and functionalities for a digital platform to be developed. A main outcome is the need to limit the platform’s scope to old-age pension only (excluding survivors’ or disability pensions, for instance). Furthermore, an outcome regarding the functionalities is the proposition of scenarios such as early retirement, changes to income, or modifications to personal status. The development of the digital platform will be a subsequent project.

Keywords: benefit statement, digital platform, retirement financial planning, social insurance

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