Search results for: Student Learning Center

Authors: A. Vahanyan

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The paper touches upon the problem of revision and modernization of the current curriculum on translation studies at the Armenian Higher Education Institutions (HEIs). In the contemporary world where quality and speed of services provided are mostly valued, certain higher education centers in Armenia though do not demonstrate enough flexibility in terms of the revision and amendment of courses taught. This issue is present for various curricula at the university level and Translation Studies related curriculum, in particular. Technological innovations that are of great help for translators have been long ago smoothly implemented into the global Translation Industry. According to the European Master's in Translation (EMT) framework, translation service provision comprises linguistic, intercultural, information mining, thematic, and technological competencies. Therefore, to form the competencies mentioned above, the curriculum should be seriously restructured to meet the modern education and job market requirements, relevant courses should be proposed. New courses, in particular, should focus on the formation of technological competences. These suggestions have been made upon the author’s research of the problem across various HEIs in Armenia. The updated curricula should include courses aimed at familiarization with various computer-assisted translation (CAT) tools (MemoQ, Trados, OmegaT, Wordfast, etc.) in the translation process, creation of glossaries and termbases compatible with different platforms), which will ensure consistency in translation of similar texts and speeding up the translation process itself. Another aspect that may be strengthened via curriculum modification is the introduction of interdisciplinary and Project-Based Learning courses, which will enable info mining and thematic competences, which are of great importance as well. Of course, the amendment of the existing curriculum with the mentioned courses will require corresponding faculty development via training, workshops, and seminars. Finally, the provision of extensive internship with translation agencies is strongly recommended as it will ensure the synthesis of theoretical background and practical skills highly required for the specific area. Summing up, restructuring and modernization of the existing curricula on Translation Studies should focus on three major aspects, i.e., introduction of new courses that meet the global quality standards of education, professional development for faculty, and integration of extensive internship supervised by experts in the field.

Keywords: competencies, curriculum, modernization, technical literacy, translation studies

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Authors: Jonathan Sohn

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Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

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Authors: Jhiamluka Zservando Solano Velasquez, Raul Palma, Alejandro Calderon, Servio Paguada, Erick Marin, Kellyn Funes, Hana Sandoval, Oscar Hernandez

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Background: Screening cardiac conditions in primary care in developing countries can be challenging, and Honduras is not the exception. One of the main limitations is the underfunding of the Healthcare System in general, causing conventional ECG acquisition to become a secondary priority. Objective: Development of a low-cost ECG to improve screening of arrhythmias in primary care and communication with a specialist in secondary and tertiary care. Methods: Design a portable, pocket-size low-cost 3 lead ECG (Handy EKG). The device is autonomous and has Wi-Fi/Bluetooth connectivity options. A mobile app was designed which can access online servers with machine learning, a subset of artificial intelligence to learn from the data and aid clinicians in their interpretation of readings. Additionally, the device would use the online servers to transfer patient’s data and readings to a specialist in secondary and tertiary care. 50 randomized patients volunteer to participate to test the device. The patients had no previous cardiac-related conditions, and readings were taken. One reading was performed with the conventional ECG and 3 readings with the Handy EKG using different lead positions. This project was possible thanks to the funding provided by the National Autonomous University of Honduras. Results: Preliminary results show that the Handy EKG performs readings of the cardiac activity similar to those of a conventional electrocardiograph in lead I, II, and III depending on the position of the leads at a lower cost. The wave and segment duration, amplitude, and morphology of the readings were similar to the conventional ECG, and interpretation was possible to conclude whether there was an arrhythmia or not. Two cases of prolonged PR segment were found in both ECG device readings. Conclusion: Using a Frugal innovation approach can allow lower income countries to develop innovative medical devices such as the Handy EKG to fulfill unmet needs at lower prices without compromising effectiveness, safety, and quality. The Handy EKG provides a solution for primary care screening at a much lower cost and allows for convenient storage of the readings in online servers where clinical data of patients can then be accessed remotely by Cardiology specialists.

Keywords: low-cost hardware, portable electrocardiograph, prototype, remote healthcare

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Authors: Hsiu-Ling Hsu, En-Minh (John) Lan

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Pronunciation has received more and more language researchers’ and teachers’ attention because it is important for effective or even successful communication. How to consistently and correctly orally produce verbal morphology, such as English regular past tense inflection, has been a big challenge and troublesome for FL learners. The research aims to explore EFL (English as a foreign language) learners’ developmental trajectory of the inflectional morphology, that is, what mediating processes and strategies EFL learners use, to attain native-like prosodic structure of inflectional morphemes (e.g., –ed and –s suffixes) by comparing the differences among EFL learners at different English levels. This research adopted a self-repair analysis and Prosodic Transfer Hypothesis with three developmental stages as a theoretical framework. To answer the research questions, we conducted two experiments, grammatical tense test written production (Experiment 1) and read-aloud oral production (Experiment 2), and recruited 30 participants who were divided into three groups, low-, middle-, and advanced EFL learners. Experiment 1 was conducted to ensure that participants had learned the knowledge of forming the English regular past tense rules and Experiment 2 was carried out to compare the data across FL English learner groups at different English levels. The EFL learners’ self-repair data showed at least four interesting findings. First, low achievers were more sensitive to the plural suffix -s than the past tense suffix -ed. Middle achievers exhibited a greater responsiveness to the past tense suffix, while high achievers demonstrated equal sensitivity to both suffixes. Additionally, two strategies used by EFL English learners to produce verbs and nouns with inflectional morphemes were to delete internal syllable and to divide a four-syllable verb (e.g., ‘graduated’) into two prosodic structures (e.g., ‘gradu’ and ‘ated’ or ‘gradua’ and ‘ted’). Third, true vowel epenthesis was found only in the low EFL achievers. Moreover fortition (native-like sound) was observed in the low and middle EFL achievers. These findings and self-repair data disclosed mediating processes between the developmental stages and provided insight on how Taiwan EFL learners attained the adjunction prosodic structures of inflectional Morphemes in English.

Keywords: inflectional morphology, prosodic structure, developmental trajectory, strategies and mediating processes, English as a foreign language

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Authors: A. Kouloumpis, P. Zygouri, G. Potsi, K. Spyrou, D. Gournis

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Much of the research effort on graphene focuses on its use as building block for the development of new hybrid nanostructures with well-defined dimensions and behavior suitable for applications among else in gas storage, heterogeneous catalysis, gas/liquid separations, nanosensing and biology. Towards this aim, here we describe a new bottom-up approach, which combines the self-assembly with the Langmuir Schaefer technique, for the production of fullerene-intercalated graphene hybrid materials. This new method uses graphene nanosheets as a template for the grafting of various fullerene C60 molecules (pure C60, bromo-fullerenes, C60Br24, and fullerols, C60(OH)24) in a bi-dimensional array, and allows for perfect layer-by-layer growth with control at the molecular level. Our film preparation approach involves a bottom-up layer-by-layer process that includes the formation of a hybrid organo-graphene Langmuir film hosting fullerene molecules within its interlayer spacing. A dilute water solution of chemically oxidized graphene (GO) was used as subphase on the Langmuir-Blodgett deposition system while an appropriate amino surfactant (that binds covalently with the GO) was applied for the formation of hybridized organo-GO. After the horizontal lift of a hydrophobic substrate, a surface modification of the GO platelets was performed by bringing the surface of the transferred Langmuir film in contact with a second amino surfactant solution (capable to interact strongly with the fullerene derivatives). In the final step, the hybrid organo-graphene film was lowered in the solution of the appropriate fullerene derivative. Multilayer films were constructed by repeating this procedure. Hybrid fullerene-based thin films deposited on various hydrophobic substrates were characterized by X-ray diffraction (XRD) and X-ray reflectivity (XRR), FTIR, and Raman spectroscopies, Atomic Force Microscopy, and optical measurements. Acknowledgments. This research has been co‐financed by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF)‐Research Funding Program: THALES. Investing in knowledge society through the European Social Fund (no. 377285).

Keywords: hybrids, graphene oxide, fullerenes, langmuir-blodgett, intercalated structures

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Sajedah Al Yaari, Adham Al Yaari, Ayman Al Yaari, Montaha Al Yaari, Ayah Al Yaari, Fatehi Eissa

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Dysgraphia is a neurological disorder of written expression that impairs writing ability and fine motor skills, resulting primarily in problems relating not only to handwriting but also to writing coherence and cohesion. We investigate the properties of smart writing technology to highlight some unique features of the effects they cause on the academic performance of pupils with dysgraphia. In Amis, dysgraphics undergo writing problems to express their ideas due to ordinary writing aids, as the default strategy. The Amis data suggests a possible connection between available writing aids and pupils’ writing improvement; therefore, texts’ expression and comprehension. A group of thirteen dysgraphic pupils were placed in a regular classroom of primary school, with twenty-one pupils being recruited in the study as a control group. To ensure validity, reliability and accountability to the research, both groups studied writing courses for two semesters, of which the first was equipped with smart writing aids while the second took place in an ordinary classroom. Two pre-tests were undertaken at the beginning of the first two semesters, and two post-tests were administered at the end of both semesters. Tests examined pupils’ ability to write coherent, cohesive and expressive texts. The dysgraphic group received the treatment of a writing course in the first semester in classes with smart technology and produced significantly greater increases in writing expression than in an ordinary classroom, and their performance was better than that of the control group in the second semester. The current study concludes that using smart teaching aids is a ‘MUST’, both for teaching and learning dysgraphia. Furthermore, it is demonstrated that for young dysgraphia, expressive tasks are more challenging than coherent and cohesive tasks. The study, therefore, supports the literature suggesting a role for smart educational aids in writing and that smart writing techniques may be an efficient addition to regular educational practices, notably in special educational institutions and speech-language therapeutic facilities. However, further research is needed to prompt the adults with dysgraphia more often than is done to the older adults without dysgraphia in order to get them to finish the other productive and/or written skills tasks.

Keywords: smart technology, writing aids, pupils with dysgraphia, hands’ movement

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Authors: Matthew Baucum

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With the increasing popularity of fMRI as an experimental method, psychology and neuroscience can greatly benefit from advanced techniques for summarizing and synthesizing large amounts of data from brain imaging studies. One promising avenue is automated meta-analyses, in which natural language processing methods are used to identify the brain regions consistently associated with certain semantic concepts (e.g. “social”, “reward’) across large corpora of studies. This study builds on this approach by demonstrating how, in fMRI meta-analyses, individual voxels can be treated as vectors in a semantic space and evaluated for their “proximity” to terms of interest. In this technique, a low-dimensional semantic space is built from brain imaging study texts, allowing words in each text to be represented as vectors (where words that frequently appear together are near each other in the semantic space). Consequently, each voxel in a brain mask can be represented as a normalized vector sum of all of the words in the studies that showed activation in that voxel. The entire brain mask can then be visualized in terms of each voxel’s proximity to a given term of interest (e.g., “vision”, “decision making”) or collection of terms (e.g., “theory of mind”, “social”, “agent”), as measured by the cosine similarity between the voxel’s vector and the term vector (or the average of multiple term vectors). Analysis can also proceed in the opposite direction, allowing word cloud visualizations of the nearest semantic neighbors for a given brain region. This approach allows for continuous, fine-grained metrics of voxel-term associations, and relies on state-of-the-art “open vocabulary” methods that go beyond mere word-counts. An analysis of over 11,000 neuroimaging studies from an existing meta-analytic fMRI database demonstrates that this technique can be used to recover known neural bases for multiple psychological functions, suggesting this method’s utility for efficient, high-level meta-analyses of localized brain function. While automated text analytic methods are no replacement for deliberate, manual meta-analyses, they seem to show promise for the efficient aggregation of large bodies of scientific knowledge, at least on a relatively general level.

Keywords: FMRI, machine learning, meta-analysis, text analysis

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Authors: Peter Hajnal

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The need to combine serious training in disciplinary/scholarly approaches to problems of general significance with an educational experience that engages students with these very same problems on a personal level is one of the key challenges facing modern liberal education in the West. The typical approach to synthesizing these two goals, one highly abstract, the other elusively practical, proceeds by invoking ideals traditionally associated with Enlightenment and 19th century “humanism”. These ideas are in turn rooted in an approach to reality codified by Cartesianism and the rise of modern science. Articulating this connection of the modern humanist tradition with Cartesianism allows for demonstrating how the central problem of modern liberal education is rooted in the strict separation of knowledge and personal experience inherent in the dualism of Descartes. The question about the shape of contemporary liberal education is, therefore, the same as asking whether an anti-Cartesian version of liberal education is possible at all. Although the formulation of a general answer to this question is a tall order (whether in abstract or practical terms), and might take different forms (nota bene in Eastern and Western contexts), a key inspiration may be provided by a certain shift of attitude towards the Cartesian conception of the relationship of knowledge and experience required by discussion based close-reading of works of visual art. Taking the work of Stanley Cavell as its central inspiration, my paper argues that this shift of attitude in question is best described as a form of “second naïveté”, and that it provides a useful model of conceptualizing in more concrete terms the appeal for such a “second naïveté” expressed in recent writings on the role of various disciplines in organizing learning by philosophers of such diverse backgrounds and interests as Hilary Putnam and Bruno Latour. The adoption of naïveté so identified as an educational ideal may be seen as a key instrument in thinking of the educational context as itself a medium of synthesis of the contemplative and the practical. Moreover, it is helpful in overcoming the bad dilemma of ideological vs. conservative approaches to liberal education, as well as in correcting a certain commonly held false view of the historical roots of liberal education in the Renaissance, which turns out to offer much more of a sui generis approach to practice rather than represent a mere precursor to the Cartesian conception.

Keywords: liberal arts, philosophy, education, Descartes, naivete

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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: 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: 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: Svetlana Kostrubina, Anastasia Prokopeva

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This research presents a comprehensive study of the word formation processes in computer terminology within English and Russian languages and provides listeners with a system of exercises for training these skills. The originality is that this study focuses on a comparative approach, which shows both general patterns and specific features of English and Russian computer terms word formation. The key point is the system of exercises development for training computer terminology based on Bloom’s taxonomy. Data contain 486 units (228 English terms from the Glossary of Computer Terms and 258 Russian terms from the Terminological Dictionary-Reference Book). The objective is to identify the main affixation models in the English and Russian computer terms formation and to develop exercises. To achieve this goal, the authors employed Bloom’s Taxonomy as a methodological framework to create a systematic exercise program aimed at enhancing students’ cognitive skills in analyzing, applying, and evaluating computer terms. The exercises are appropriate for various levels of learning, from basic recall of definitions to higher-order thinking skills, such as synthesizing new terms and critically assessing their usage in different contexts. Methodology also includes: a method of scientific and theoretical analysis for systematization of linguistic concepts and clarification of the conceptual and terminological apparatus; a method of nominative and derivative analysis for identifying word-formation types; a method of word-formation analysis for organizing linguistic units; a classification method for determining structural types of abbreviations applicable to the field of computer communication; a quantitative analysis technique for determining the productivity of methods for forming abbreviations of computer vocabulary based on the English and Russian computer terms, as well as a technique of tabular data processing for a visual presentation of the results obtained. a technique of interlingua comparison for identifying common and different features of abbreviations of computer terms in the Russian and English languages. The research shows that affixation retains its productivity in the English and Russian computer terms formation. Bloom’s taxonomy allows us to plan a training program and predict the effectiveness of the compiled program based on the assessment of the teaching methods used.

Keywords: word formation, affixation, computer terms, Bloom's taxonomy

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Authors: Rizalito B. Javier

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Research has shown that foreign students with higher levels of cultural awareness and intercultural communication competence tend to have better academic performance outcomes. This study aimed to find out the cultural awareness, intercultural communication competence, and academic performance of foreign students and its relationships among variables. Methods used were descriptive-comparative and correlational research design, quota purposive sampling technique while frequency counts and percentages, mean and standard deviation, T, and F-test and chi-square were utilized to analyze the data. The results revealed that the majority of the respondents were under the age bracket of 21-25 years old, mostly males, all single, and mostly citizens of Papua New Guinea, Angolan, Vanuatu, Tanzanian, Nigerian, Korean, Rwanda, and Myanmar. Most language spoken was English, many of them were born again Christians, the majority took BS business management degree program, their studies mainly supported by their parents, they had stayed in the Philippines for 3-4 years, and most of them attended five to six times of cultural awareness/competence workshop-seminars, majority of their parent’s occupations were family own business, and had been earning a family monthly income of P61,0000 and above. The respondents were highly aware of their culture in terms of clients’ issues. The intercultural communication competence of the respondents was slightly aware in terms of intercultural awareness, while the foreign students performed good remarks in their average academic performance. However, the profiles of the participants in terms of age, gender, civil status, nationality, course/degree program taken, support to the study, length of stay, workshop attended, and parents’ occupation have significant differences in the academic performance except for the type of family, language spoken, religion and family monthly income. Moreover, cultural awareness was significantly related to intercultural communication competence, and both were not related to academic performance. It is recommended that foreign students be provided with cultural orientation programs, offered language support services, promoted intercultural exchange activities, and implemented inclusive teaching practices to allow students to effectively navigate and interact with people from different cultural backgrounds, fostering a more inclusive and collaborative learning environment.

Keywords: cultural competence, communication competence, intercultural competence, and culture-academic performance.

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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: 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: 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: 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: 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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