Search results for: learning and memory

Authors: Marion G. Ben-Jacob, David Wang

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There is a mathematics requirement for entry level college and university students, especially those who plan to study STEM (Science, Technology, Engineering and Mathematics). Most of them take College Algebra, and to continue their studies, they need to succeed in this course. Different pedagogical strategies are employed to promote the success of our students. There is, of course, the Traditional Method of teaching- lecture, examples, problems for students to solve. The Emporium Model, another pedagogical approach, replaces traditional lectures with a learning resource center model featuring interactive software and on-demand personalized assistance. This presentation will compare these two methods of pedagogy and the study done with its results on this comparison. Math is the foundation for science, technology, and engineering. Its work is generally used in STEM to find patterns in data. These patterns can be used to test relationships, draw general conclusions about data, and model the real world. In STEM, solutions to problems are analyzed, reasoned, and interpreted using math abilities in a assortment of real-world scenarios. This presentation will examine specific examples of how math is used in the different STEM disciplines. Math becomes practical in science when it is used to model natural and artificial experiments to identify a problem and develop a solution for it. As we analyze data, we are using math to find the statistical correlation between the cause of an effect. Scientists who use math include the following: data scientists, scientists, biologists and geologists. Without math, most technology would not be possible. Math is the basis of binary, and without programming, you just have the hardware. Addition, subtraction, multiplication, and division is also used in almost every program written. Mathematical algorithms are inherent in software as well. Mechanical engineers analyze scientific data to design robots by applying math and using the software. Electrical engineers use math to help design and test electrical equipment. They also use math when creating computer simulations and designing new products. Chemical engineers often use mathematics in the lab. Advanced computer software is used to aid in their research and production processes to model theoretical synthesis techniques and properties of chemical compounds. Mathematics mastery is crucial for success in the STEM disciplines. Pedagogical research on formative strategies and necessary topics to be covered are essential.

Keywords: emporium model, mathematics, pedagogy, STEM

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Authors: Dona Shaini Abhilasha Nanayakkara, Kurugamage Jude Pravinda Gregory Perera

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E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. The Analyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling The Analyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: data clustering, data standardization, dimensionality reduction, human computer interaction, user profiling

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Authors: Matt Stichter

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Moral development requires learning from one’s failures, but that turnsout to be especially challenging when dealing with moral failures. The distress prompted by moral failure can cause responses ofdefensiveness or disengagement rather than attempts to make amends and work on self-change. The most potentially distressing response to moral failure is a shame. However, there appears to be two different senses of “shame” that are conflated in the literature, depending on whether the failure is appraised as the result of a global and unalterable self-defect, or a local and alterable self-defect. One of these forms of shame does prompt self-improvement in response to moral failure. This occurs if one views the failure as indicating only a specific (local) defect in one’s identity, where that’s something repairable, rather than asanoverall(orglobal)defectinyouridentity that can’t be fixed. So, if the whole of one’s identity as a morally good person isn’t being called into question, but only a part, then that is something one could work on to improve. Shame, in this sense, provides motivation for self-improvement to fix this part oftheselfinthe long run, and this would be important for moral development. One factor that looks to affect these different self-attributions in the wake of moral failure can be found in mindset theory, as reactions to moral failure in these two forms of shame are similar to how those with a fixed or growth mindset of their own abilities, such as intelligence, react to failure. People fall along a continuum with respect to how they view abilities – it is more of a fixed entity that you cannot do much to change, or it is malleable such that you can train to improve it. These two mindsets, ‘fixed’ versus ‘growth’, have different consequences for how we react to failure – a fixed mindset leads to maladaptive responses because of feelings of helplessness to do better; whereas a growth mindset leads to adaptive responses where a person puts forth effort to learn how to act better the next time. Here we can see the parallels between a fixed mindset of one’s own (im)morality, as the way people respond to shame when viewed as indicating a global and unalterable self-defect parallels the reactions people have to failure when they have a fixed mindset. In addition, it looks like there may be a similar structure to pride. Pride is, like shame, a self-conscious emotion that arises from internal attributions about the self as being the cause of some event. There are also paradoxical results from research on pride, where pride was found to motivate pro-social behavior in some cases but aggression in other cases. Research suggests that there may be two forms of pride, authentic and hubristic, that are also connected to different self-attributions, depending on whether one is feeling proud about a particular (local) aspect of the self versus feeling proud about the whole of oneself (global).

Keywords: emotion, mindset, moral development, moral psychology, pride, shame, self-regulation

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Authors: E. Happ, Zs. Ivancsone Horvath

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With the development of the information technology, IT, sector, all industry of the world has a new path, dealing with digitalisation. Tourism is the most rapidly increasing industry in the world. Without digitalisation, tourism operators would not be competitive enough with foreign destinations or other experience-based service providers. Digitalisation is also necessary to enable organizations, which are interested in tourism to meet the growing expectations of consumers. With the help of digitalisation, tourism providers can also obtain information about tourists, changes in consumer behaviour, and the use of online services. The degree of digitalisation in tourism is different for different services. The research is based on a questionnaire survey conducted in 2018 in Hungary. The sample with more than 500 respondents was processed by the SPSS program, using a variety of analysis methods. The following two variables were observed from more aspects: frequency of travel and the importance of services related to online travel. With the help of these variables, a cluster analysis was performed among the participants. The sample can be divided into two groups using K-mean cluster analysis. Cluster ‘1’ is a positive group; they can be called the “most digital tourists.” They agree in most things, with low standard deviation, and for them, digitalisation is a starting point. To the members of Cluster ‘2’, digitalisation is important, too. The results show what is important (accommodation, information gathering) to them, but also what they are not interested in at all within the digital world (e.g., car rental or online sharing). Interestingly, there is no third negative cluster. This result (that there is no result) proves that tourism uses digitalisation, and the question is only the extent of the use of online tools and methods. With the help of the designed consumer groups, the characteristics of digital tourism segments can be identified. The help of different variables characterised these groups. One of them is the frequency of travel, where there is a significant correlation between travel frequency and cluster membership. The shift is clear towards Cluster ‘1’, which means, those who find services related to online travel more important, are more likely to travel as well. By learning more about digital tourists’ consumer behaviour, the results of this research can help the providers in what kind of marketing tools could be used to influence the consumer choices of the different consumer groups created using digital devices, furthermore how to conduct more detailed and effective marketing activities. The main finding of the research was that most of the people have digital tools which are important to be able to participate in e-tourism. Of these, mobile devices are increasingly preferred. That means the challenge for service providers is no longer the digital presence but having optimised application for different devices.

Keywords: cluster analysis, digital tourism, marketing tool, tourist behaviour

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Authors: Naziema Jappie

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There is a wealth of knowledge about JEDI (Justice Equity Diversity Inclusion), but unfortunately this remains at a discrete initiative level at universities. South African universities are committed to social justice by promoting inclusive teaching, learning and research environments, diversity and equity in access and participation of students and staff regardless of age; disability; gender; sexual orientation; nationality, ethnic or national origin; religion; and socioeconomic background in all aspects of higher education at a national level. Universities strive to promote and protect equal rights and equity of access is safeguarded for international students by recognizing the foreign policies and practices. Nevertheless, many international students remain underrepresented, alienated and often without employment. Universities see internationalisation as a commercial venture, but where does JEDI fit into this plan? Given the focus on diversity in higher education institutions, one would assume that JEDI should have a broader compass rather than a narrow scope. Over the past decades, national trends have emerged in the commitment to international diversification by admitting students and recruiting staff, mainly from the African continent. Most importantly, emergence of statements of broader diversity and equity plans across the campuses, included in the strategic plans of institutions are counterproductive to the statements of the Employment Equity plans and targets when aligned to the recruitment processes. These trends are certainly significant and relevant given the increasing diverse populations in higher education. What is missing in JEDI initiatives is the lack of global perspective and situating JEDI within a larger and inclusive context to embrace institutional internationalization. It is not a separate construct but internationalization framework takes the JEDI vision from local to global. Embracing JEDI and internationalization are fundamental for future economic growth. JEDI creates diverse perspectives and builds a team of top diverse and international talent that will gives a competitive edge. Increasing internationalization efforts and creating a knowledge platform will affect the innovation performance of the economy. Transforming South African policies require a comprehensive educational strategy on justice, equity, diversity, and inclusion (JEDI).

Keywords: equity, diversity, inclusion, internationalization, justice, higher education

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Authors: Irma Wani Othman

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The internationalization of higher education in Malaysia mainly focuses to place the implementation of the strategic, comprehensive and integrated range of stakeholders in order to highlight the visibility of Malaysia as a hub of academic excellence. While the concept of 'global citizenship' is used as a two-pronged strategy of aggressive marketing by universities which includes; (i) the involvement of the academic expatriates in stimulating international activities of higher education and (ii) an increase in international student enrollment capacity for the enculturation of science and the development of first class mentality. In this aspect, aspirations for a transnational social movement through global citizenship status to establish the identity of the university community without borders (borderless universities) - regardless of skin colour, thus rationalize and liberalize the universal principles of life and cultural traditions of a nation. The education system earlier referred by the spirit of nationalism is now progressing due to globalization, hence forming a system of higher education that is relevant and generated by the need of all time. However, debates arose when the involvement of global citizenship is said to threaten the ultimate university autonomy in determining the direction of academic affairs and governance of their human resources. Stemming from this debate, this study aims to explore the experience of 'global citizenship' that the academic expatriates and international students in shaping the university's strategic needs and interests which are in line with the transition of contemporary higher education. The objective of this study is to examine the acculturation experience of the global citizen in the form of transnational higher education system and suggest policy and policing IHE which refers directly to the experience of the global citizen. This study offers a detailed understanding of how the university communities assess their expatriation experience, thus becoming useful information for learning and transforming education. The findings also open an advanced perspective on the international mobility of human resources and the implications on the implementation of the policy of internationalization of higher education. The contribution of this study is expected to give new input, thus shift the focus of contextual literature for the internationalization of the education system. Instead of focusing on the purpose of generating income of a university, to a greater understanding of subjective experience in utilizing international human resources hence contributing to the prominent transnational character of higher education.

Keywords: internationalization, global citizens, Malaysia higher education, academic expatriate, international students

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Authors: Kritchakhris Na-Wattanaprasert

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The objective of this research is to design and develop a prototype of a key performance indicator system this is suitable for warehouse management in a case study and use requirement. In this study, we design a prototype of key performance indicator system (KPI) for warehouse case study of furniture business by methodology in step of identify scope of the research and study related papers, gather necessary data and users requirement, develop key performance indicator base on balance scorecard, design pro and database for key performance indicator, coding the program and set relationship of database and finally testing and debugging each module. This study use Balance Scorecard (BSC) for selecting and grouping key performance indicator. The system developed by using Microsoft SQL Server 2010 is used to create the system database. In regard to visual-programming language, Microsoft Visual C# 2010 is chosen as the graphic user interface development tool. This system consists of six main menus: menu login, menu main data, menu financial perspective, menu customer perspective, menu internal, and menu learning and growth perspective. Each menu consists of key performance indicator form. Each form contains a data import section, a data input section, a data searches – edit section, and a report section. The system generates outputs in 5 main reports, the KPI detail reports, KPI summary report, KPI graph report, benchmarking summary report and benchmarking graph report. The user will select the condition of the report and period time. As the system has been developed and tested, discovers that it is one of the ways to judging the extent to warehouse objectives had been achieved. Moreover, it encourages the warehouse functional proceed with more efficiency. In order to be useful propose for other industries, can adjust this system appropriately. To increase the usefulness of the key performance indicator system, the recommendations for further development are as follows: -The warehouse should review the target value and set the better suitable target periodically under the situation fluctuated in the future. -The warehouse should review the key performance indicators and set the better suitable key performance indicators periodically under the situation fluctuated in the future for increasing competitiveness and take advantage of new opportunities.

Keywords: key performance indicator, warehouse management, warehouse operation, logistics management

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Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi

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Background:-Due to the essential role of the foot in movement, foot disorders (FDs) have significant impacts on activity and quality of life. Many studies confirmed the association between FDs and demographic characteristics. On the other hand, recent advances in data collection and statistical analysis led to an increase in the volume of databases. Analysis of patient’s data through the decision tree can be used to explore the relationship between demographic characteristics and FDs. Significance of the study: This study aimed to investigate the relationship between demographic characteristics with common FDs. The second purpose is to better inform foot intervention, we classify FDs based on demographic variables. Methodologies: We analyzed 2323 subjects with pes-planus (PP), pes-cavus (PC), hallux-valgus (HV) and plantar-fasciitis (PF) who were referred to a foot therapy clinic between 2015 and 2021. Subjects had to fulfill the following inclusion criteria: (1) weight between 14 to 150 kilogram, (2) height between 30 to 220, (3) age between 3 to 100 years old, and (4) BMI between 12 to 35. Medical archives of 2323 subjects were recorded retrospectively and all the subjects examined by an experienced physician. Age and BMI were classified into five and four groups, respectively. 80% of the data were randomly selected as training data and 20% tested. We build a decision tree model to classify FDs using demographic characteristics. Findings: Results demonstrated 981 subjects from 2323 (41.9%) of people who were referred to the clinic with FDs were diagnosed as PP, 657 (28.2%) PC, 628 (27%) HV and 213 (9%) identified with PF. The results revealed that the prevalence of PP decreased in people over 18 years of age and in children over 7 years. In adults, the prevalence depends first on BMI and then on gender. About 10% of adults and 81% of children with low BMI have PP. There is no relationship between gender and PP. PC is more dependent on age and gender. In children under 7 years, the prevalence was twice in girls (10%) than boys (5%) and in adults over 18 years slightly higher in men (62% vs 57%). HV increased with age in women and decreased in men. Aging and obesity have increased the prevalence of PF. We conclude that the accuracy of our approach is sufficient for most research applications in FDs. Conclusion:-The increased prevalence of PP in children is probably due to the formation of the arch of the foot at this age. Increasing BMI by applying high pressure on the foot can increase the prevalence of this disorder in the foot. In PC, the Increasing prevalence of PC from women to men with age may be due to genetics and innate susceptibility of men to this disorder. HV is more common in adult women, which may be due to environmental reasons such as shoes, and the prevalence of PF in obese adult women may also be due to higher foot pressure and housekeeping activities.

Keywords: decision tree, demographic characteristics, foot disorders, machine learning

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Authors: Naseer Ahmad

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This research investigates the intricate dynamics of language policy, ideology, and the choice of educational language as a medium of instruction in rural Pakistan. Focused on addressing the complexities of language practices in underexplored educational contexts, the study employed a case study approach, analyzing interviews with education authorities, teachers, and students, alongside classroom observations in English-medium and Urdu-medium rural schools. The research underscores the significance of understanding linguistic diversity within rural communities. The analysis of interviews and classroom observations revealed that language policies in rural schools are influenced by multiple factors, including historical legacies, societal language ideologies, and government directives. The dominance of Urdu and English as the preferred languages of instruction reflected a broader language hierarchy, where regional languages are often marginalized. This language ideology perpetuates a sense of linguistic inferiority among students who primarily speak regional languages. The impact of language choices on students' learning experiences and outcomes is a central focus of the research. It became evident that while policies advocate for specific language practices, the implementation often diverges due to multifarious socio-cultural, economic, and institutional factors. This disparity significantly impacts the effectiveness of educational processes, influencing pedagogical approaches, student engagement, academic outcomes, social mobility, and language choices. Based on the findings, the study concluded that due to policy and practice gap, rural people have complex perceptions and language choices. They perceived Urdu as a national, lingua franca, cultural, easy, or low-status language. They perceived English as an international, lingua franca, modern, difficult, or high-status language. They perceived other languages as mother tongue, local, religious, or irrelevant languages. This research provided insights that are crucial for theory, policy, and practice, addressing educational inequities and inclusive language policies. It set the stage for further research and advocacy efforts in the realm of language policies in diverse educational settings.

Keywords: language-in-education policy, language ideology, educational language choice, pakistan

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Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo

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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.

Keywords: anomaly detection, digital twin, generalised additive model, GAM, power consumption, supervised learning

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Authors: Carlos V. Gonzalez

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Background: Providers of in-home and community based services strive for the elimination of preventable harm to the people under their care as well as to the employees who support them. Traditional models of safety and protection from harm have assumed that the absence of incidents of harm is a good indicator of safe practices. However, this model creates an illusion of safety that is easily shaken by sudden and inadvertent harmful events. As an alternative, we have developed and implemented an evidence-based resilient model of safety known as C.O.P.E. (Caring, Observing, Predicting and Evaluating). Within this model, safety is not defined by the absence of harmful incidents, but by the presence of continuous monitoring, anticipation, learning, and rapid response to events that may lead to harm. Objective: The objective was to evaluate the effectiveness of the C.O.P.E. model for the reduction of harm to individuals with mental disabilities who receive home and community based services. Methods: Over the course of 2 years we counted the number of incidents of harm and near misses. We trained employees on strategies to eliminate incidents before they fully escalated. We trained employees to track different levels of patient status within a scale from 0 to 10. Additionally, we provided direct support professionals and supervisors with customized smart phone applications to track and notify the team of changes in that status every 30 minutes. Finally, the information that we collected was saved in a private computer network that analyzes and graphs the outcome of each incident. Result and conclusions: The use of the COPE model resulted in: A reduction in incidents of harm. A reduction the use of restraints and other physical interventions. An increase in Direct Support Professional’s ability to detect and respond to health problems. Improvement in employee alertness by decreasing sleeping on duty. Improvement in caring and positive interaction between Direct Support Professionals and the person who is supported. Developing a method to globally measure and assess the effectiveness of prevention from harm plans. Future applications of the COPE model for the reduction of harm to people who receive home and community based services are discussed.

Keywords: harm, patients, resilience, safety, mental illness, disability

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Authors: Olivera Lupescu, Taina Elena Avramescu, Mihail Nagea, Alexandru Dimitriu

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Acetabular fractures represent a real challenge due to their impact upon the long term function of the hip joint, and due to the risk of intra- and peri-operative complications especially that they affect young, active people. That is why treating these fractures require certain skills which must be exercised, regarding the pre-operative planning, as well as the execution of surgery.The authors retrospectively analyse 38 cases with acetabular fractures operated using the posterior approach in our hospital between 01.01.2013- 01.01.2015 for which complete medical records ensure a follow-up of 24 months, in order to establish the main causes of potential errors and to underline the methods for preventing them. This target is included in the Erasmus + project ‘Collaborative learning for enhancing practical skills for patient-focused interventions in gait rehabilitation after orthopedic surgery COR-skills’. This paper analyses the pitfalls revealed by these cases, as well as the measures necessary to enhance the practical skills of the surgeons who perform acetabular surgery. Pre-op planning matched the intra and post-operative outcome in 88% of the analyzed points, from 72% at the beginning to 94% in the last case, meaning that experience is very important in treating this injury. The main problems detected for the posterior approach were: nervous complications - 3 cases, 1 of them a complete paralysis of the sciatic nerve, which recovered 6 months after surgery, and in other 2 cases intra-articular position of the screws was demonstrated by post-operative CT scans, so secondary screw removal was necessary in these cases. We analysed this incident, too, due to lack of information about the relationship between the screws and the joint secondary to this approach. Septic complications appeared in 3 cases, 2 superficial and 1 profound (requiring implant removal). The most important problems were the reduction of the fractures and the positioning of the screws so as not to interfere with the the articular space. In posterior acetabular fractures, pre-op complex planning is important in order to achieve maximum treatment efficacy with minimum of risk; an optimal training of the surgeons insisting on the main points of potential mistakes ensure the success of the procedure, as well as a favorable outcome for the patient.

Keywords: acetabular fractures, articular congruency, surgical skills, vocational training

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Authors: Hazel P. Atilano

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In this age of AI-assisted teaching and learning, there seems to be a dearth of research literature on the linguistic analysis of English as a Second Language (ESL) student-generated paraphrased academic texts. This study sought to examine the lexico-semantic, morphosyntactic features of paraphrased academic texts generated by ESL students. Employing a descriptive qualitative design, specifically linguistic analysis, the study involved a total of 85 students from senior high school, college, and graduate school enrolled in research courses. Data collection consisted of a 60-minute real-time, on-site paraphrasing practice exercise using excerpts from discipline-specific literature reviews of 150 to 200 words. A focus group discussion (FGD) was conducted to probe into the challenges experienced by the participants. The writing exercise yielded a total of 516 paraphrase pairs. A total of 176 paraphrase units (PUs) and 340 non-paraphrase pairs (NPPs) were detected. Findings from the linguistic analysis of PUs reveal that the modifications made to the original texts are predominantly syntax-based (Diathesis Alterations and Coordination Changes) and a combination of Miscellaneous Changes (Change of Order, Change of Format, and Addition/Deletion). Results of the analysis of paraphrase extremes (PE) show that Identical Structures resulting from the use of synonymous substitutions, with no significant change in the structural features of the original, is the most frequently occurring instance of PE. The analysis of paraphrase errors reveals that synonymous substitutions resulting in identical structures are the most frequently occurring error that leads to PE. Another type of paraphrasing error involves semantic and content loss resulting from the deletion or addition of meaning-altering content. Three major themes emerged from the FGD: (1) The Challenge of Preserving Semantic Content and Fidelity; (2) The Best Words in the Best Order: Grappling with the Lexico-semantic and Morphosyntactic Demands of Paraphrasing; and (3) Contending with Limited Vocabulary, Poor Comprehension, and Lack of Practice. A pedagogical paradigm was designed based on the major findings of the study for a sustainable instructional intervention.

Keywords: academic text, lexico-semantic analysis, linguistic analysis, morphosyntactic analysis, paraphrasing

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Authors: Julius Oluwayomi Oluwadamilare, Michael Olutayo Olatunji

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In the African traditional societies, women have always played the role of a teacher, albeit informally. This is evident in the upbringing of their babies. As mothers, they also serve as the first teachers to teach their wards lessons through day-to-day activities. Furthermore, women always play the role of a musician during naming ceremonies, in the singing of lullabies, during initiation rites of adolescent boys and girls into adulthood, and in preparing their children especially daughters (and sons) for marriage. They also perform this role during religious and cultural activities, chieftaincy title/coronation ceremonies, singing of dirges during funeral ceremonies, and so forth. This traditional role of the African/Nigerian women puts them at a vantage point to contribute maximally to the teaching and learning of music at every level of education. The need for more women in the field of music education in Nigeria cannot be overemphasized. Today, gender equality is a major discourse in most countries of the world, Nigeria inclusive. Statistical data in the field of education and music education reveal the high ratio of male teachers/lecturers over their female counterparts in Nigerian tertiary institutions. The percentage is put at 80% Male and a distant 20% Female! This paper, therefore, examines feminine gender in Nigerian music education by tracing the involvement of women in musical practice from the pre-colonial to the post-colonial periods. The study employed both primary and secondary sources of data collection. The primary source included interviews conducted with 19 music lecturers from 8 purposively selected tertiary institutions from 4 geo-political zones of Nigeria. In addition, observation method was employed in the selected institutions. The results show, inter alia, that though there is a remarkable improvement in the rate of admission of female students into the music programme of Nigerian tertiary institutions, there is still an imbalance in the job placement in these institutions especially in the Colleges of Education which is the main focus of this research. Religious and socio-cultural factors are highly traceable to this development. This paper recommends the need for more female music teachers to be employed in the Nigerian tertiary institutions in line with the provisions stated in the Millennium Development Goals (MDGs) of the Federal Republic of Nigeria.

Keywords: gender, education, music, women

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Authors: Yvonne Howard

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This project currently under development is centered around current learning processes, including a thorough literature review and ongoing practical experiences gained as a deputy head in a school. These daily experiences with students engaging in animal-assisted interventions and the school therapy dog form a strong base for this research. The primary objective of this research is to comprehensively explore the impact of dog-assisted well-being interventions on student motivation and affective engagement within primary and secondary school settings. The educational domain currently encounters a significant challenge due to the lack of substantial research in this area. Despite the perceived positive outcomes of such interventions being acknowledged and shared in various settings, the evidence supporting their effectiveness in an educational context remains limited. This study aims to bridge the gap in the research and shed light on the potential benefits of dog-assisted well-being interventions in promoting student motivation and affective engagement. The significance of this topic recognizes that education is not solely confined to academic achievement but encompasses the overall well-being and emotional development of students. Over recent years, there has been a growing interest in animal-assisted interventions, particularly in healthcare settings. This interest has extended to the educational context. While the effectiveness of these interventions in these areas has been explored in other fields, the educational sector lacks comprehensive research in this regard. Through a systematic and thorough research methodology, this study seeks to contribute valuable empirical data to the field, providing evidence to support informed decision-making regarding the implementation of dog-assisted well-being interventions in schools. This research will utilize a mixed-methods design, combining qualitative and quantitative measures to assess the research objectives. The quantitative phase will include surveys and standardized scales to measure student motivation and affective engagement, while the qualitative phase will involve interviews and observations to gain in-depth insights from students, teachers, and other stakeholders. The findings will contribute evidence-based insights, best practices, and practical guidelines for schools seeking to incorporate dog-assisted interventions, ultimately enhancing student well-being and improving educational outcomes.

Keywords: therapy dog, wellbeing, engagement, motivation, AAI, intervention, school

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Authors: Madhura Yadav

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Urban redevelopment planning initiatives in developing countries have been largely criticised due to top-down planning approach and lack of involvement of the targeted beneficiaries which have led to a challenging situation which is contrary to the perceived needs of beneficiaries. Urban renewal projects improve the lives of people and meaningful participation of community plays a pivotal role. Public perceptions on satisfaction and participation have been given less priority in the investigation, which hinders effective planning and implementation of urban renewal projects. Moreover, challenges of community participation in urban renewal projects are less documented, particularly in relation to public participation and satisfaction. There is a need for new paradigm shift focusing on community participatory approach in urban renewal projects. The over 125-year-old Bhendi Bazar in Mumbai, India is the country’s first ever cluster redevelopment project, popularly known as Bhendi Bazaar redevelopment and it will be one of the largest projects for urban rejuvenation of one of Mumbai’s oldest and dying inner city areas. The project is led by the community trust, inputs were taken from various stakeholders, including residents, commercial tenants and expert consultants to shape the master plan and design of the project. The project started in 2016 but there is a significant delay in implementing the project. The study aimed at studying and assessing public perceptions on satisfaction and the relationship between community participation and community satisfaction in Bhendi Bazaar of Mumbai, India. Furthermore, the study will outline the challenges and problems of community participation in urban renewal projects and it suggests recommendations for the future. The qualitative and quantitative methods such as reconnaissance survey, key informant interviews, focus group discussions, walking interviews, a narrative inquiry is used for analysis of data. Preliminary findings revealed that all tenants are satisfied for the redevelopment of an area but the willingness of residential tenants to move in transit accommodation has made the projects successful and reductant of some residential and commercial tenants, regulatory provisions rising to face challenges in implementation. Experiences from the case study can help to understand dynamics behind public participation and government. At the same time, they serve as an inspiration and learning opportunity for future projects to ensure that they are sustainable not only from an economic standpoint but also, a social perspective.

Keywords: urban renewal, Bhendi Bazaar, community participation, satisfaction, social perspective

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Authors: Kai-Chieh Lin, Chih-Fu Wu, Hsiang Ling Hsu, Yung-Hsiang Tu, Chia-Chen Wu

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With the rapid development of computer technology, the design of computers and keyboards moves towards a trend of slimness. The change of mobile input devices directly influences users’ behavior. Although multi-touch applications allow entering texts through a virtual keyboard, the performance, feedback, and comfortableness of the technology is inferior to traditional keyboard, and while manufacturers launch mobile touch keyboards and projection keyboards, the performance has not been satisfying. Therefore, this study discussed the design factors of slim pressure-sensitive keyboards. The factors were evaluated with an objective (accuracy and speed) and a subjective evaluation (operability, recognition, feedback, and difficulty) depending on the shape (circle, rectangle, and L-shaped), thickness (flat, 3mm, and 6mm), and force (35±10g, 60±10g, and 85±10g) of the keyboard. Moreover, MANOVA and Taguchi methods (regarding signal-to-noise ratios) were conducted to find the optimal level of each design factor. The research participants, by their typing speed (30 words/ minute), were divided in two groups. Considering the multitude of variables and levels, the experiments were implemented using the fractional factorial design. A representative model of the research samples were established for input task testing. The findings of this study showed that participants with low typing speed primarily relied on vision to recognize the keys, and those with high typing speed relied on tactile feedback that was affected by the thickness and force of the keys. In the objective and subjective evaluation, a combination of keyboard design factors that might result in higher performance and satisfaction was identified (L-shaped, 3mm, and 60±10g) as the optimal combination. The learning curve was analyzed to make a comparison with a traditional standard keyboard to investigate the influence of user experience on keyboard operation. The research results indicated the optimal combination provided input performance to inferior to a standard keyboard. The results could serve as a reference for the development of related products in industry and for applying comprehensively to touch devices and input interfaces which are interacted with people.

Keywords: input performance, mobile device, slim keyboard, tactile feedback

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Authors: Asadullah Sheikh, Kerry Barnett, Paul Ayres

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Despite significant progress in access, equity and public examination success, poor student performance in mathematics in secondary schools has become a major concern in Bangladesh. A substantial body of research has emphasised the important contribution of teaching practices to student achievement. However, this has not been investigated in Bangladesh. Therefore, the study sought to find out the effectiveness of mathematics teaching practices as a means of improving secondary school mathematics in Dhaka Municipality City (DMC) area, Bangladesh. The purpose of this study was twofold, first, to identify the 20 highest performing secondary schools in mathematics in DMC, and second, to investigate the teaching practices of mathematics teachers in these schools. A two-phase mixed method approach was adopted. In the first phase, secondary source data were obtained from the Board of Intermediate and Secondary Education (BISE), Dhaka and value-added measures used to identify the 20 highest performing secondary schools in mathematics. In the second phase, a concurrent mixed method design, where qualitative methods were embedded within a dominant quantitative approach was utilised. A purposive sampling strategy was used to select fifteen teachers from the 20 highest performing secondary schools. The main sources of data were classroom teaching observations, and teacher interviews. The data from teacher observations were analysed with descriptive and nonparametric statistics. The interview data were analysed qualitatively. The main findings showed teachers adopt a direct teaching approach which incorporates orientation, structuring, modelling, practice, questioning and teacher-student interaction that creates an individualistic learning environment. The variation in developmental levels of teaching skill indicate that teachers do not necessarily use the qualitative (i.e., focus, stage, quality and differentiation) aspects of teaching behaviours effectively. This is the first study to investigate teaching behaviours of effective secondary mathematics teachers within Dhaka, Bangladesh. It contributes in an international dimension to the field of educational effectiveness and raise questions about existing constructivist approaches. Further, it contributes to important insights about teaching behaviours that can be used to inform the development of evidence-based policy and practice on quality teaching in Bangladesh.

Keywords: effective teaching, mathematics, secondary schools, student achievement, value-added measures

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Authors: Tayyab Ahmad, Gerard Healey

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Sustainability in built environment sector is subject to many development constraints. Building projects are developed under different requirements of deliverables which makes each project unique. For an owner organization, i.e., a higher-education institution, involved in a significant building stock, it is important to prioritize some of the sustainability initiatives over the others in order to align the sustainable building development with organizational goals. The point-based green building rating tools i.e. Green Star, LEED, BREEAM are becoming increasingly popular and are well-acknowledged worldwide for verifying a sustainable development. It is imperative to synthesize a multi-criteria decision-making tool that can capitalize on the point-based methodology of rating systems while customizing the sustainable development of building projects according to the individual requirements and constraints of the client organization. A multi-criteria decision-making tool for the University of Melbourne is developed that builds on the action-learning and experience of implementing Green Buildings at the University of Melbourne. The tool evaluates the different sustainable building initiatives based on the framework of Green Star rating tool of Green Building Council of Australia. For each different sustainability initiative the decision-making tool makes an assessment based on at least five performance criteria including the ease with which a sustainability initiative can be achieved and the potential of a sustainability initiative to enhance project objectives, reduce life-cycle costs, enhance University’s reputation, and increase the confidence in quality construction. The use of a weighted aggregation mathematical model in the proposed tool can have a considerable role in the decision-making process of a Green Building project by indexing the Green Building initiatives in terms of organizational priorities. The index value of each initiative will be based on its alignment with some of the key performance criteria. The usefulness of the decision-making tool is validated by conducting structured interviews with some of the key stakeholders involved in the development of sustainable building projects at the University of Melbourne. The proposed tool is realized to help a client organization in deciding that within limited resources which sustainability initiatives and practices are more important to be pursued than others.

Keywords: higher education institution, multi-criteria decision-making tool, organizational values, prioritizing sustainability initiatives, weighted aggregation model

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Authors: Zeta Dooly, Aidan Duane

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The collaborative European funded research and development landscape provides prime environmental conditions for multi-disciplinary teams to learn and enhance their knowledge beyond the capability of training and learning within their own organisation cocoons. Whilst the emergence of the academic entrepreneur has changed the focus of educational institutions to that of quasi-businesses, the training and professional development of lecturers and academic staff are often not formalised to the same level as industry. This research focuses on industry and academic collaborative research funded by the European Commission. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness, the nature of relationships, links, and nodes within a research network, and the enhancement of the network’s knowledge. The contribution of this paper extends our understanding of establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. This research provides evidence to support the impact collaborative research has on the disparate individuals toward their innovative contributions to their organisations and their own professional development. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, intra-network challenges in relation to open data, competition, friendships, and competency enhancement. The network capability is enhanced by the adoption of the relevant theories; network theory, open innovation, and social exchange, with the understanding that the network structure has an impact on innovation and social exchange in research networks. The research concludes that there is an opportunity to deepen our understanding of the impact of network reuse and network hoping that provides scaffolding for the network members to enhance and build upon their knowledge using a progressive approach.

Keywords: research networks, competency building, network theory, case study

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Authors: Alicia Yanadira Nava Fuentes, Ilse Cervantes Camacho, Amadeo José Argüelles Cruz, Ana María Balboa Verduzco

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Augmented reality promises being present in future driving, with its immersive technology let to show directions and maps to identify important places indicating with graphic elements when the car driver requires the information. On the other side, driving is considered a multitasking activity and, for some people, a complex activity where different situations commonly occur that require the immediate attention of the car driver to make decisions that contribute to avoid accidents; therefore, the main aim of the project is the instrumentation of a platform with biometric sensors that allows evaluating the performance in driving vehicles with the influence of augmented reality devices to detect the level of attention in drivers, since it is important to know the effect that it produces. In this study, the physiological sensors EPOC X (EEG), ECG06 PRO and EMG Myoware are joined in the driving test platform with a Logitech G29 steering wheel and the simulation software City Car Driving in which the level of traffic can be controlled, as well as the number of pedestrians that exist within the simulation obtaining a driver interaction in real mode and through a MSP430 microcontroller achieves the acquisition of data for storage. The sensors bring a continuous analog signal in time that needs signal conditioning, at this point, a signal amplifier is incorporated due to the acquired signals having a sensitive range of 1.25 mm/mV, also filtering that consists in eliminating the frequency bands of the signal in order to be interpretative and without noise to convert it from an analog signal into a digital signal to analyze the physiological signals of the drivers, these values are stored in a database. Based on this compilation, we work on the extraction of signal features and implement K-NN (k-nearest neighbor) classification methods and decision trees (unsupervised learning) that enable the study of data for the identification of patterns and determine by classification methods different effects of augmented reality on drivers. The expected results of this project include are a test platform instrumented with biometric sensors for data acquisition during driving and a database with the required variables to determine the effect caused by augmented reality on people in simulated driving.

Keywords: augmented reality, driving, physiological signals, test platform

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Authors: Lee Rui, Rajeev Ramachandran

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The approach to recurrent fevers in the paediatric or adolescent age group is not a straightforward one. Causes range from infectious diseases to rheumatological conditions to endocrinopathies, and are usually accompanied by weight loss rather than weight gain. We present an interesting case of a 16-year-old girl brought by her mother to the General Pediatrics Clinic for concerns of recurrent fever paired with significant weight gain over 1.5 years, with no identifiable cause found despite extensive work-up by specialists ranging from Rheumatologists to Oncologists. This case provides a learning opportunity on the approach to weight gain paired with persistent fevers in a paediatric population, one which is not commonly encountered and prompts further evaluation and consideration of less common diagnoses. In a span of 2 years, the girl’s weight had increased from 55 kg at 13 years old (75th centile) to 73.9 kg at 16 years old (>97th centile). About 1 year into her rapid weight gain, she started developing recurrent fevers of documented temperatures > 37.5 – 38.6 every 2-3 days, resulting in school absenteeism when she was sent home after temperature-taking in school found her to be febrile. The rapid onset of weight gain paired with unexplained fevers prompted the treating physician to consider the diagnosis of ROHHAD syndrome. Rapid onset obesity with hypoventilation, hypothalamic dysfunction and autonomic dysregulation (ROHHAD) syndrome is a rare disorder first described in 2007. It is characterized by dysfunction of the autonomic and endocrine system, characterized by hyperphagia and rapid-onset weight gain. This rapid weight gain is classically followed by hypothalamic manifestations with neuroendocrine deficiencies, hypo-ventilatory breathing abnormalities, and autonomic dysregulation. ROHHAD is challenging to diagnose with and diagnosis is made based mostly on clinical judgement. However if truly diagnosed, the condition is characterized by high morbidity and mortality rates. Early recognition of sleep disorders breathing and targeted therapeutic interventions helps limit morbidity and mortality associated with ROHHAD syndrome. This case poses an interesting diagnostic challenge and a diagnosis of ROHHAD has to be considered, given the serious complications that can come with disease progression while conditions such as Munchausen’s or drug fever remain as diagnoses of exclusion until we have exhausted all other possible conditions.

Keywords: pediatrics, endocrine, weight gain, recurrent fever, adolescent

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Authors: Seval Kula-Kartal

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Developing students’ reading comprehension skills is an aim that is difficult to accomplish and requires to follow long-term and systematic teaching and assessment processes. In these processes, teachers need tools to provide guidance to them on what reading comprehension is and which comprehension skills they should develop. Due to a lack of clear and evidence-based frameworks defining reading comprehension skills, especially in Turkiye, teachers and students mostly follow various processes in the classrooms without having an idea about what their comprehension goals are and what those goals mean. Since teachers and students do not have a clear view of comprehension targets, strengths, and weaknesses in students’ comprehension skills, the formative feedback processes cannot be managed in an effective way. It is believed that detecting and defining influential comprehension skills may provide guidance both to teachers and students during the feedback process. Therefore, in the current study, some of the reading comprehension frameworks that define comprehension skills operationally were examined. The aim of the study is to develop a simple and clear framework that can be used by teachers and students during their teaching, learning, assessment, and feedback processes. The current study is qualitative research in which documents related to reading comprehension skills were analyzed. Therefore, the study group consisted of recourses and frameworks which made big contributions to theoretical and operational definitions of reading comprehension. A content analysis was conducted on the resources included in the study group. To determine the validity of the themes and sub-categories revealed as the result of content analysis, three educational assessment experts were asked to examine the content analysis results. The Fleiss’ Cappa coefficient revealed that there is consistency among themes and categories defined by three different experts. The content analysis of the reading comprehension frameworks revealed that comprehension skills could be examined under four different themes. The first and second themes focus on understanding information given explicitly or implicitly within a text. The third theme includes skills used by the readers to make connections between their personal knowledge and the information given in the text. Lastly, the fourth theme focus on skills used by readers to examine the text with a critical view. The results suggested that fundamental reading comprehension skills can be examined under four themes. Teachers are recommended to use these themes in their reading comprehension teaching and assessment processes. Acknowledgment: This research is supported by Pamukkale University Scientific Research Unit within the project, whose title is Developing A Reading Comprehension Rubric.

Keywords: reading comprehension, assessing reading comprehension, comprehension taxonomies, educational assessment

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have an important role in controlling illness associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing like disk diffusion are time-consuming and other method including E-test, genotyping are relatively expensive. Fourier transform infrared (FTIR) microscopy is rapid, safe, and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 550 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 85% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E. coli, FTIR, multivariate analysis, susceptibility

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Authors: Xiaoyu Sun

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In recent years, the rapid development of Artificial Intelligence (AI) has extensively promoted medicine, pharmaceutical, and other related fields. The medical research and development of artificial intelligence by scientific and commercial organizations are on the fast track. The ethics review is one of the critical procedures of registration to get the products approved and launched. However, the SOPs for ethics review is not enough to guide the healthy and rapid development of artificial intelligence in healthcare in China. Ethical Review Measures for Biomedical Research Involving Human Beings was enacted by the National Health Commission of the People's Republic of China (NHC) on December 1st, 2016. However, from a legislative design perspective, it was neither updated timely nor in line with the trends of AI international development. Therefore, it was great that NHC published a consultation paper on the updated version on March 16th, 2021. Based on the most updated laws and regulations in the States and EU, and in-depth-interviewed 11 subject matter experts in China, including lawmakers, regulators, and key members of ethics review committees, heads of Regulatory Affairs in SaMD industry, and data scientists, several suggestions were proposed on top of the updated version. Although the new version indicated that the Ethics Review Committees need to be created by National, Provincial and individual institute levels, the review authorities of different levels were not clarified. The suggestion is that the precise scope of review authorities for each level should be identified based on Risk Analysis and Management Model, such as the complicated leading technology, gene editing, should be reviewed by National Ethics Review Committees, it will be the job of individual institute Ethics Review Committees to review and approve the clinical study with less risk such as an innovative cream to treat acne. Furthermore, to standardize the research and development of artificial intelligence in healthcare in the age of AI, more clear guidance should be given to data security in the layers of data, algorithm, and application in the process of ethics review. In addition, transparency and responsibility, as two of six principles in the Rome Call for AI Ethics, could be further strengthened in the updated version. It is the shared goal among all countries to manage well and develop AI to benefit human beings. Learned from the other countries who have more learning and experience, China could be one of the most advanced countries in artificial intelligence in healthcare.

Keywords: biomedical research involving human beings, data security, ethics committees, ethical review, medical artificial intelligence

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Authors: Sheillah Hlamalani Mboweni, Lufuno Makhado

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Background: The increasing number of people who tested HIV positive and who demand antiretroviral therapy (ART) prompted the National Department of Health to adopt WHO recommendations of task shifting where Professional Nurses(PNs) initiate ART rather than doctors in the hospital. This resulted in the decentralization of services to primary health care(PHC), generating a need to capacitate PNs on NIMART. After years of training, the impact of NIMART was assessed where it was established that even though there was an increased number who accessed ART, the quality of care is of serious concern. The study aims to answer the following question: What are the challenges influencing NIMART implementation in primary health care. Objectives: This study explores challenges influencing NIMART training and implementation and makes recommendations to improve patient and HIV program outcomes. Methods: A qualitative explorative program evaluation research design. The study was conducted in the rural districts of North West province. Purposive sampling was used to sample PNs trained on NIMART. FGDs were used to collect data with 6-9 participants and data was analysed using ATLAS ti. Results: Five FGDs, n=28 PNs and three program managers were interviewed. The study results revealed two themes: inadequacy in NIMART training and the health care system challenges. Conclusion: The deficiency in NIMART training and health care system challenges is a public health concern as it compromises the quality of HIV management resulting in poor patients’ outcomes and retard the goal of ending the HIV epidemic. These should be dealt with decisively by all stakeholders. Recommendations: The national department of health should improve NIMART training and HIV management: standardization of NIMART training curriculum through the involvement of all relevant stakeholders skilled facilitators, the introduction of pre-service NIMART training in institutions of higher learning, support of PNs by district and program managers, plan on how to deal with the shortage of staff, negative attitude to ensure compliance to guidelines. There is a need to develop a conceptual framework that provides guidance and strengthens NIMART implementation in PHC facilities.

Keywords: antiretroviral therapy, nurse initiated management of retroviral therapy, primary health care, professional nurses

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Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

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Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

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Authors: Elissavet Feloni, Ioannis Kourtis, Konstantinos Kotsifakis, Evangelos Baltas

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Water inadequacy in small dry islands scattered in the Aegean Sea (Greece) is a major problem regarding Water Resources Management (WRM), especially during the summer period due to tourism. In the present work, various WRM schemes are designed and presented. The WRM schemes take into account current infrastructure and include Rainwater Harvesting tanks and Reverse Osmosis Desalination Units. The energy requirements are covered mainly by wind turbines and/or a seawater pumped storage system. Sizing is based on the available data for population and tourism per island, after taking into account a slight increase in the population (up to 1.5% per year), and it guarantees at least 80% reliability for the energy supply and 99.9% for potable water. Evaluation of scenarios is carried out from a financial perspective, after calculating the Life Cycle Cost (LCC) of each investment for a lifespan of 30 years. The wind-powered desalination plant was found to be the most cost-effective practice, from an economic point of view. Finally, in order to estimate the Climate Change (CC) impact, six different CC scenarios were investigated. The corresponding rate of on-grid versus off-grid energy required for ensuring the targeted reliability for the zero and each climatic scenario was investigated per island. The results revealed that under CC the grid-on energy required would increase and as a result, the reduction in wind turbines and seawater pumped storage systems’ reliability will be in the range of 4 to 44%. However, the range of this percentage change does not exceed 22% per island for all examined CC scenarios. Overall, CC is proposed to be incorporated into the design process for WRM-related projects. Acknowledgements: This research is co-financed by Greece and the European Union (European Social Fund - ESF) through the Operational Program «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Development of a combined rain harvesting and renewable energy-based system for covering domestic and agricultural water requirements in small dry Greek Islands” (MIS 5004775).

Keywords: small dry islands, water resources management, climate change, desalination, RES, seawater pumped storage system, rainwater harvesting

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Authors: Evan Lowhorn, Rocio Alba-Flores

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Traditional classification Convolutional Neural Networks (CNN) attempt to classify an image in its entirety. This becomes problematic when trying to perform classification with a drone’s camera in real-time due to unpredictable backgrounds. Object detectors with bounding boxes can be used to isolate individuals and other items, but the original backgrounds remain within these boxes. These basic detectors have been regularly used to determine what type of object an item is, such as “person” or “dog.” Recent advancement in computer vision, particularly with human imaging, is keypoint detection. Human keypoint detection goes beyond bounding boxes to fully isolate humans and plot points, or Regions of Interest (ROI), on their bodies within an image. ROIs can include shoulders, elbows, knees, heads, etc. These points can then be related to each other and used in deep learning methods such as pose estimation. For drone control based on human motions, poses, or signals using the onboard camera, it is important to have a simple method for pilot identification among multiple individuals while also giving the pilot fine control options for the drone. To achieve this, the OpenPose keypoint detection network was used with body and hand keypoint detection enabled. OpenPose supports the ability to combine multiple keypoint detection methods in real-time with a single network. Body keypoint detection allows simple poses to act as the pilot identifier. The hand keypoint detection with ROIs for each finger can then offer a greater variety of signal options for the pilot once identified. For this work, the individual must raise their non-control arm to be identified as the operator and send commands with the hand on their other arm. The drone ignores all other individuals in the onboard camera feed until the current operator lowers their non-control arm. When another individual wish to operate the drone, they simply raise their arm once the current operator relinquishes control, and then they can begin controlling the drone with their other hand. This is all performed mid-flight with no landing or script editing required. When using a desktop with a discrete NVIDIA GPU, the drone’s 2.4 GHz Wi-Fi connection combined with OpenPose restrictions to only body and hand allows this control method to perform as intended while maintaining the responsiveness required for practical use.

Keywords: computer vision, drone control, keypoint detection, openpose

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Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

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