Search results for: self-regulated learning strategies

Authors: Ersin Bozkurt

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The aim of the study is to develop materials for understanding image formations through virtual objects in geometric optics. The images in physics course books are formed by using real objects. This results in mistakes in the features of images because of generalizations which leads to conceptual misunderstandings in learning. In this study it was intended to identify pre-service physics teachers misunderstandings arising from false generalizations. Focused group interview was used as a qualitative method. The findings of the study show that students have several misconceptions such as "the image in a plain mirror is always virtual". However a real image can be formed in a plain mirror. To explain a virtual object's image formation in a more understandable way an overhead projector and episcope and their design was illustrated. The illustrations are original and several computer simulations will be suggested.

Keywords: computer simulations, geometric optics, physics education, students' misconceptions in physics

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Authors: Annie Gedion, Johan Severinus Tati, Jacinta Caroline Peter

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Syntax error analysis studies have a significant role in English language teaching especially in the second language. This study investigates the syntax errors in written composition by 50 multilingual ESL learners in Politeknik Kota Kinabalu Sabah, Malaysia. The subjects speak their own dialect, Malay as their second language and English as their third or foreign language. Data were collected from the written discourse in the form of descriptive essays. The subjects were asked to write in the classroom within 45 minutes. 15 categories of errors were classified into a set of syntactic categories and were analysed based on the five steps of the syntactic analysis procedure. The findings of the study showed that the mother tongue interference, as well as lack of vocabulary and grammar knowledge, were the major sources of syntax errors in the learners’ written composition. Learners should be exposed to the differentiation of Malay and English grammar to avoid interference and effective learning of second language writing.

Keywords: errors analysis, syntactic analysis, English as a second language, ESL writing

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Authors: Robin Gengan

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The film industry is one of the most impactful creative sectors in modern social influence. It has relational effects on knowledge and psychological impact on the youth. Much focus in current filmmaking is either in fictional drama or documentary. The purpose of this article is to combine the two into a third genre; edutainment in which film is approached as a visual educational text. Similar to language text, cinema can be applied to semiotic reading. Film interpretation is a phenomenological order, unique to each viewer. There are cultural norms and tropes that are more universal between the practice of semiotic reading, symbolism and interpretation. Film semiotics and narration are a juxtaposition of moving visual texts and sound to create meaning through film codes and social conventions to form an educational narrative that makes the medium effective for learning and teaching. The aim of this article is to explore and set precedence for more creative building-blocks into future research on edutainment cinema. This will further stimulate and benefit innovative entrepreneurial filmmaking and future academic research.

Keywords: cinema, edutainment, epistemology, multimodality, semiotics, structuralism

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Authors: Behdokht Mall-Amiri, Sara Farzaminejad

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The purpose of the present study was to discover which of the two writing activities, a self-assessment questioner or a critical thinking skills handout, is more effective on Iranian EFL learners’ writing ability. To fulfill the purpose of the study, a sample of 120 undergraduate students of English SAT for a standardized sample of PET. Eighty-two students whose scores fell one standard deviation above and below the sample mean were selected and randomly divided into two equal groups. One group practiced self-assessment and the other group practiced critical thinking skills while they were learning process writing. A writing posttest was finally administered to the students in both groups and the mean rank scores were compared by t-test. The result led to the rejection of the null hypothesis, indicating that practicing critical thinking skills had a significantly higher effect on the writing ability. The implications of the study for students and teachers as well as course book designers are discussed.

Keywords: writing ability, process writing, critical thinking skills, self-assessment

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Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

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In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

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Authors: Chia-li Wang

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The surge of service and commerce platforms, such as e-commerce and internet-of-things, have rapidly changed our lives. How to avoid the congestion and get the job done in the platform is now a common problem that many people encounter every day. This requires platform users to make decisions about when to enter the platform. To that end, we investigate the strategic entering time of a simple platform containing random numbers of buyers and sellers of some item. Upon a trade, the buyer and the seller gain respective profits, yet they pay the cost of waiting in the platform. To maximize their expected payoffs from trading, both buyers and sellers can choose their entering times. This creates an interesting and practical framework of a game that is played among buyers, among sellers, and between them. That is, a strategy employed by a player is not only against players of its type but also a response to those of the other type, and, thus, a strategy profile is composed of strategies of buyers and sellers. The players' best response, the Nash equilibrium (NE) strategy profile, is derived by a pair of differential equations, which, in turn, are used to establish its existence and uniqueness. More importantly, its structure sheds valuable insights of how the entering strategy of one side (buyers or sellers) is affected by the entering behavior of the other side. These results provide a base for the study of dynamic pricing for stochastic demand-supply imbalances. Finally, comparisons between the social welfares (the sum of the payoffs incurred by individual participants) obtained by the optimal strategy and by the NE strategy are conducted for showing the efficiency loss relative to the socially optimal solution. That should help to manage the platform better.

Keywords: double-sided queue, non-cooperative game, nash equilibrium, price of anarchy

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Authors: Mostafa Gabr, Rania Abdul Galil, Nihal Salim

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Various interventions are applied in cities with the aim to improve living and acoustic environmental conditions. Noise is one of the most influential and critical factors in the environment that has an effect on the QOL (quality of life) and urban environment. It ranks second among environmental pollution issues according to EEAA. Traffic noise is a major source of noise. Noise barriers are one of the physical techniques in landscape design used to reduce the impact of noise pollution in urban areas. Roadways noise pollution can be best controlled by a noise barrier. The aim of this paper is to consider all facets of sustainability when designing a comfortable acoustic environment in roadways, through different strategies related to planning and the design process. The study focuses on the relation between the design of noise barriers as a landscape noise mitigation installation and their materiality in so far as it influences the sustainability of the open space and the acceptability of users. According to previous studies, design of noise barrier mainly depends on cost as a decisive factor. This study asserts that environmental and socioeconomic costs associated are equally important. Hence, the paper presents a strategy for sustainable soundscape design. It builds a framework focusing on materiality considering the environmental and socioeconomic impact of noise barriers shaping urban open space around the road ways, and the different academic and market positions on noise barrier types and materials. Finally, it concludes with a matrix of the relation between the noise barrier design consideration and the three pillars of sustainability (social, economic and environmental).

Keywords: traffic noise level, acoustic sustainability, noise barrier, noise reduction, noise control, acoustical level

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Authors: A. Arjomand Kermani, N. Charbgoo, M. Alalhesabi

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In the situation of great acceleration of changes and the need for new developments in the cities on one hand and conservation and regeneration approaches on the other hand, place identity and its relation with heritage context have taken on new importance. This relation is generally mutual and complex one. The significant point in this relation is that the process of identifying something as heritage rather than just historical  phenomena, brings that which may be inherited into the realm of identity. In planning and urban design as well as environmental psychology and phenomenology domain, place identity and its attributes and components were studied and discussed. However, the relation between physical environment (especially heritage) and identity has been neglected in the planning literature. This article aims to review the knowledge on this field and develop a model on the influence and relation of these two major concepts (heritage and identity). To build this conceptual model, we draw on available literature in environmental psychology as well as planning on place identity and heritage environment using a descriptive-analytical methodology to understand how they can inform the planning strategies and governance policies. A cross-disciplinary analysis is essential to understand the nature of place identity and heritage context and develop a more holistic model of their relationship in order to be employed in planning process and decision making. Moreover, this broader and more holistic perspective would enable both social scientists and planners to learn from one another’s expertise for a fuller understanding of community dynamics. The result indicates that a combination of these perspectives can provide a richer understanding—not only of how planning impacts our experience of place, but also how place identity can impact community planning and development.

Keywords: heritage, inter-disciplinary study, place identity, planning

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Authors: Julia Wimmers Klick

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

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

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Authors: Frederik Calsius, Mirela Popa, Alexia Briassouli

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In the field of machine learning, it is common practice to use benchmark datasets to prove the working of a method. The domain of action recognition in videos often uses datasets like Kinet-ics, Something-Something, UCF-101 and HMDB-51 to report results. Considering the properties of the datasets, there are no datasets that focus solely on very short clips (2 to 3 seconds), and on highly-similar fine-grained actions within one specific domain. This paper researches how current state-of-the-art action recognition methods perform on a dataset that consists of highly similar, fine-grained actions. To do so, a dataset of skateboarding tricks was created. The performed analysis highlights both benefits and limitations of state-of-the-art methods, while proposing future research directions in the activity recognition domain. The conducted research shows that the best results are obtained by fusing RGB data with OpenPose data for the Temporal Shift Module.

Keywords: activity recognition, fused deep representations, fine-grained dataset, temporal modeling

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Authors: Szu Mei Hsiao

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This study explores the spiritual needs of inpatients with advanced cancer and their family caregivers in one southern regional teaching hospital in Taiwan and elucidates the differences and similarities of spiritual needs between them. Little research reports the different phases of spiritual needs and the potential impact of Chinese cultural values on the spiritual needs. Qualitative inquiry was used. Twenty-one patients with advanced cancer and twenty-two family caregivers were recruited. During hospitalization, all participants identified spiritual needs both the palliative phase and the dying phase: (a) the need to foster faith/confidence and hope for medicine and/or God; (b) to understand the meaning and values of life; (c) to experience more reciprocal human love and forgiveness; and (d) to obey God’s/Heaven will. Furthermore, the differences of spiritual needs between patients with advanced cancer and their family caregivers are as follows: (a) family caregivers emphasized the need to inform relatives and say goodbye in order to die peacefully; (b) patients highlighted a need to maintain a certain physical appearance in order to preserve their dignity; nurture one’s willpower; learn about the experiences of cancer survivors; and identify one’s own life experience for understanding the meaning and values of life. Moreover, the dissimilarity of spiritual needs is that the patients pointed out the need to understand God’s will during the palliative treatment phase. However, the family caregivers identified the need to forgive each other, and inform relatives and say goodbye to patients in the dying phase. This research has shown that the needs of meaning/values of life and facing death peacefully are different between two groups. Health professionals will be encouraged to detect and to develop individualized care strategies to meet spiritual needs.

Keywords: advanced cancer, Chinese culture, family caregivers, qualitative research, spiritual needs

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Authors: Zhao Gao, Eran Edirisinghe

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

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

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Authors: Dominika Collett

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AI applications, such as machine learning, require access to a vast amount of data in the training phase, which can often be the subject of copyright protection. During later usage, the various content with which the application works can be recorded or made available on the basis of which it produces the resulting output. The EU has recently adopted new legislation to secure machine access to protected works under the DSM Directive; but, the issue of machine use of copyright works is not clearly addressed. However, such clarity is needed regarding the increasing importance of AI and its development. Therefore, this paper provides a basic background of the technology used in the development of applications in the field of computer creativity. The second part of the paper then will focus on a legal analysis of machine use of the authors' works from the perspective of existing European and Czech legislation. The main results of the paper discuss the potential collision of existing legislation in regards to machine use of works with special focus on exceptions and limitations. The legal regulation of machine use of copyright work will impact the development of AI technology.

Keywords: copyright, artificial intelligence, legal use, infringement, Czech law, EU law, text and data mining

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Authors: Upasana Bhumbla

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Background: Hepatitis C virus is a major cause of chronic hepatitis, which can further lead to cirrhosis of the liver and hepatocellular carcinoma. Worldwide the burden of Hepatitis C infection has become a serious threat to the human race. Hepatitis C virus (HCV) has population-specific genotypes and provides valuable epidemiological and therapeutic information. Genotyping and assessment of viral load in HCV patients are important for planning the therapeutic strategies. The aim of the study is to study the changing trends of prevalence and genotypic distribution of hepatitis C virus in a tertiary care hospital in Western India. Methods: It is a retrospective study; blood samples were collected and tested for anti HCV antibodies by ELISA in Dept. of Microbiology. In seropositive Hepatitis C patients, quantification of HCV-RNA was done by real-time PCR and in HCV-RNA positive samples, genotyping was conducted. Results: A total of 114 patients who were seropositive for Anti HCV were recruited in the study, out of which 79 (69.29%) were HCV-RNA positive. Out of these positive samples, 54 were further subjected to genotype determination using real-time PCR. Genotype was not detected in 24 samples due to low viral load; 30 samples were positive for genotype. Conclusion: Knowledge of genotype is crucial for the management of HCV infection and prediction of prognosis. Patients infected with HCV genotype 1 and 4 will have to receive Interferon and Ribavirin for 48 weeks. Patients with these genotypes show a poor sustained viral response when tested 24 weeks after completion of therapy. On the contrary, patients infected with HCV genotype 2 and 3 are reported to have a better response to therapy.

Keywords: hepatocellular, genotype, ribavarin, seropositive

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Authors: Syhalath Xaphakdy, Toshio Nagata, Saykham Phommathat, Pavy Souwannavong, Vilayvanh Srithilat, Phoxay Sengdala, Bounaom Phetarnousone, Boualay Siharath, Xaya Chemcheng

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The National University of Laos (NUOL) invited a group of volunteers from the Japan International Cooperation Agency (JICA) to revise the physics experiments to utilize the materials that were already available to students. The intension was to review and revise the materials regularly utilized in physics class. The project had access to limited materials and a small budget for the class in the unit; however, by developing experimental textbooks related to mechanics, electricity, and wave and vibration, the group found a way to apply them in the classroom and enhance the students teaching activities. The aim was to introduce a way to incorporate the materials and practices in the classroom to enhance the students learning and teaching skills, particularly when they graduate and begin working as high school teachers.

Keywords: NUOL, JICA, physics experiment materials, small budget, mechanics, electricity

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Authors: Samuel Olugbenga King

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This review article, which is a synthesis of the relevant research literature, focuses on the capabilities of digital video to support, facilitate and enhance faculty development. Based on the literature review, faculty development (i.e., academic or educational development) requires the continued adoption of cohesive, theoretical frameworks to guide research and practice; incorporation of relevant tools from analogous fields, such as teacher professional development; systematic program evaluations; and detailed descriptions of practice to further practice and creative development. A cohesive, five-heuristic framework is subsequently outlined to inform the design and evaluation of the use of digital video, so as to address the barriers to advancing faculty development, as identified through the literature review. Alternative impact evaluation approaches are also described, while the limitations of using digital video for faculty development are highlighted. This paper is therefore conceived as one way to meaningfully leverage the educational affordances of digital video to address some lingering gaps in faculty development.

Keywords: digital video, faculty/educational development, evaluation, scholarship of teaching and learning (SoTL)

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Authors: B. Chandra

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In Association Rule Mining, much attention has been paid for developing algorithms for large (frequent/closed/maximal) itemsets but very little attention has been paid to improve the performance of rule generation algorithms. Rule generation is an important part of Association Rule Mining. In this paper, a novel approach named NARG (Association Rule using Antecedent Support) has been proposed for rule generation that uses memory resident data structure named FCET (Frequent Closed Enumeration Tree) to find frequent/closed itemsets. In addition, the computational speed of NARG is enhanced by giving importance to the rules that have lower antecedent support. Comparative performance evaluation of NARG with fast association rule mining algorithm for rule generation has been done on synthetic datasets and real life datasets (taken from UCI Machine Learning Repository). Performance analysis shows that NARG is computationally faster in comparison to the existing algorithms for rule generation.

Keywords: knowledge discovery, association rule mining, antecedent support, rule generation

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Authors: Sadia Suri Kashif, Raheeda Fatima, Maqsood Ahmed Khan

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Purpose of the study: The objective of this research was to determine the perception of Pakistani physicians (whether primary care, specialists or residents) in Karachi, being one of the largest and highly populated cities of Pakistan, regarding clinical approaches towards diet, exercise, and therapy in obese patients. This research determines their understanding of obesity and employability of obesity management in their daily practices. Research methodology: This is a questionnaire-based survey. A minimum of 300 questionnaires (N=300) were distributed and filled by practicing physicians in a random selection of medical setups in Karachi. Randomly 246 physicians responded to the survey. The survey tested their views regarding weight management, importance of general awareness and their strategies to control weight. Results: In the first part of survey the physicians responded to almost 66% regarding the seriousness of obesity management with advising diet modification, physical exercise and decreasing calorie intake; 57% failed to employ Body Mass Index and Waist Hip Ratio as weight measurement tools in their daily practice; 50% disagreed on using pharmacotherapy as an option; 67% were not sure about the proper dosage and indication of anti-obesity medication while almost same disagreed on using surgical options for management of obesity; 83.3% physicians agreed on the increased obesity pandemic in Pakistan. Conclusion: The findings indicate that there is a gap between awareness and knowledge among Pakistani practicing physicians regarding pharmacotherapy for obesity. There is a need to frequently update latest guidelines to help manage this condition, which is becoming more prevalent in our country day by day. Physicians should be obligated to use updated knowledge for managing obesity.

Keywords: obesity, physicians, BMI, weight management, obesity awareness

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Emmanuel Ademola Anigilaje, Ibraheem Ishola

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Background: Childhood steroid-sensitive idiopathic nephrotic syndrome (SSINS) is plagued with relapses that contribute to its morbidity and the cost of treatment. Materials and Methods: This is a retrospective review of relapses among children with SSINS at the University of Abuja Teaching Hospital from January 2016 to July 2020. Triggers related to relapse incidents were noted. Chi-square test was deployed for predictors (factors at the first clinical presentations that associate with subsequent relapses) of relapses. Predictors with p-values of less than 0.05 were considered significant and 95% confidence intervals (CI) and odd ratio (OR) were described. Results: Sixty SSINS comprising 52 males (86.7%), aged 23 months to 18 years, with a mean age of 7.04±4.16 years were studied. Thirty-eight (63.3%) subjects had 126 relapses including infrequent relapses in 30 (78.9%) and frequent relapses in 8 (21.1%). The commonest triggers were acute upper respiratory tract infections (68, 53.9%) and urinary tract infections (UTIs) in 25 (19.8%) relapses. In 4 (3.2%) relapses, no trigger was identified. The time-to-first relapse ranged 14 days to 365 days with a median time of 60 days. The significant predictors were hypertension (OR=3.4, 95% CI; 1.04-11.09, p=0.038), UTIs (OR=9.9, 95% CI; 1.16-80.71, p= 0.014), malaria fever (OR=8.0, 95% CI; 2.45-26.38, p˂0.001), micro-haematuria (OR=4.9, 95% CI; 11.58-15.16, p=0.004), elevated serum creatinine (OR=12.3, 95%CI; 1.48-101.20, p=0.005) and hypercholesterolaemia (OR=4.1, 95%CI; 1.35-12.63, p=0.011). Conclusion: While the pathogenesis of relapses remains unknown, it is prudent to consider relapse-specific preventive strategies against triggers and predictors of relapses in our setting.

Keywords: Patterns, triggers, predictors, steroid-sensitive idiopathic nephrotic syndrome, relapses, Nigeria

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Authors: Amit Kumar, Davide Lionetti, Victor Day, James Blakemore

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Capture and activation of the water-soluble uranyl dication (UO22+) remains a challenging problem, as few rational approaches are available for modulating the reactivity of this species. Here, we report the divergent synthesis of heterobimetallic complexes in which UO22+ is held in close proximity to a range of redox-inactive metals by tailored macrocyclic ligands. Crystallographic and spectroscopic studies confirm assembly of homologous UVI(μ-OAr)2Mn+ cores with a range of mono-, di-, and trivalent Lewis acids (Mn+). X-ray diffraction (XRD) and cyclic voltammetry (CV) data suggest preferential binding of K+ in an 18-crown-6-like cavity and Na+ in a 15-crown-5-like cavity, both appended to Schiff-base type sites that selectively bind UO22+. CV data demonstrate that the UVI/UV reduction potential in these complexes shifts positive and the rate of electron transfer decreases with increasing Lewis acidity of the incorporated redox-inactive metals. Moreover, spectroelectrochemical studies confirm the formation of [UV] species in the case of monometallic UO22+ complex, consistent with results from prior studies. However, unique features were observed during spectroelectrochemical studies in the presence of the K+ ion, suggesting new insights into electronic structure may be accessible with the heterobimetallic complexes. Overall, these findings suggest that interactions with Lewis acids could be effectively leveraged for rational tuning of the electronic and thermochemical properties of the 5f elements, reminiscent of strategies more commonly employed with 3d transition metals.

Keywords: electrochemistry, Lewis acid, macrocycle, uranyl

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Authors: Humara Bano, Nyla Anjum

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Disability in any form has great impact not only for the person facing it but also for its family members too. This effect may be so severe that may lead to mal adjustment of any member of the family in society as well. This impact has also been multiplied due to negative attitudes of the society, unawareness about the needs of special needs and no legislation for the parents of children with special needs. As a result not only the separations among the parents have been reported but also the normal siblings in the home are also badly affected in their daily lives. The situation is more challenging when more than one child with disability is present in the family. The main objectives of this paper are to unfold the relationship of variety of disabilities (hearing, visual or physical impairment, mental retardation, speech impairment) in i) developing depression in home setting, ii) social exclusion, iii) anxiety and aggression and iv) development of insecure feelings among family members of the persons with disabilities, as well as, v) to identify coping strategies to manage the special needs by family members too. To reach on conclusion about fifty families (having any sort of disability in their homes) have been interviewed on basis of convenient sampling. Correlation, ANOVA and different analysis have been used to identify the relationship of disability in developing depression among family members in line of above mentioned problems. Results revealed that depression due to disability among families is a common phenomenon and adversely have affected their lives in daily routines as well as in following their life achievements. Coping with the situation and recommending various remedies by parents is the positive reflection of this study too that can help to families in managing their mental health.

Keywords: depression, anxiety and aggression, social exclusion, parents of children with special needs

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Authors: Zasha Romero, Joe Paschall

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This poster will detail the importance of physical activity for the Visually Impaired students and how to promote inclusion in fitness through way of social gatherings and jogging. Furthermore, it will demonstrate how a Health & Kinesiology University Club cooperated in the journey of visually impaired students from participating in physical activity to completing their first 10K fun run. Purpose: The poster will detail how a university’s Health & Kinesiology Club developed a program to promote participation in fitness activities for visually impaired individuals. Also, it will detail their journey from participation in physical activity to completing a 10K fun run. Methods: In an effort to promote inclusion of all into physical activity, a university’s Health & Kinesiology Club developed a non-profit program to challenge visually impaired students to train and complete a 10 kilometer fun run in a South Texas town. The idea was to promote physical fitness through way of social interaction. In order to maintain runners interested, Club students developed training plans and strategies to be able to navigate in a race that was attended by over 18,000 runners. The idea was to promote interaction and life-long fitness amongst participants. Implications: This strategy was done in collaboration with different non-profit institutions to create awareness and provide opportunities for physical fitness, social interaction and life-long fitness skills associated with the jogging. The workshop provided collaboration amongst different entities and novel ideas to create opportunities for a typically underserved population.

Keywords: inclusion, participation, management, disability, fitness

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Authors: Matthew B. Davis, Amit Kumar

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With potentially dangerous impacts of climate change on the horizon, Canada has an opportunity to take a lead role on the international stage to demonstrate how energy use intensity and greenhouse gas emission intensity may be effectively reduced. Through bottom-up modelling of Canada’s energy sector using Long-range Energy Alternative Planning (LEAP) software, it can be determined where efforts should to be concentrated to produce the most positive energy management results. By analyzing a provincially integrated Canada, one can develop strategies to minimize the country’s economic downfall while transitioning to lower-emission energy technologies. Canada’s electricity sector plays an important role in accommodating these transitionary technologies as fossil-fuel based power production is prevalent in many parts of the country and is responsible for a large portion (17%) of Canada’s greenhouse gas emissions. Current findings incorporate an in-depth model of Canada’s current energy supply and demand sectors, as well as a business-as-usual scenario up to the year 2035. This allows for in-depth analysis of energy flow from resource potential, to extraction, to fuel and electricity production, to energy end use and emissions in Canada’s residential, transportation, commercial, institutional, industrial, and agricultural sectors. Bottom-up modelling techniques such as these are useful to critically analyze and compare the various possible scenarios of implementing sustainable energy measures. This work can aid government in creating effective energy and environmental policies, as well as guide industry to what technology or process changes would be most worthwhile to pursue.

Keywords: energy management, LEAP, energy end-use, GHG emissions

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Authors: Mostafa Refat Ismail, Hazem Eldaly

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The adaptation of architecture design to building function is getting highly needed in contemporary designs, especially with the great progression in design methods and tools. This, in turn, requires great flexibility in design strategies, as well as a wider spectrum of space settings to achieve the required environment that special activities imply. Acoustics is an essential factor influencing cognitive acts and behavior as well as, on the extreme end, the physical well-being inside a space. The complexity of this constrain is fueled up by the extended geometric dimensions of multipurpose halls, making acoustic adequateness a great concern that could not easily be achieved for each purpose. To achieve a performance oriented acoustic environment, various parametric shaped false ceilings based on origami folded notion are simulated. These parametric origami shapes are able to fold and unfold forming an interactive structure that changes the mutual acoustic environment according to the geometric shapes' position and its changing exposed surface areas. The mobility of the facets in the origami surface can stretch up the range from a complete plain surface to an unfolded element where a considerable amount of absorption is added to the space. The behavior of the parametric origami shapes are being modeled employing a ray tracing computer simulation package for various shapes topology. The conclusion shows a great variation in the acoustical performance due to the variation in folding faces of the origami surfaces, which cause different reflections and consequently large variations in decay curves.

Keywords: parametric, origami, acoustics, architecture

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Authors: Hao Zhang, Hongyang Yu

Abstract:

Scale uncertainty is a well-known challenging problem in visual SLAM. Because RGB-D sensor provides depth information, RGB-D SLAM improves this scale uncertainty problem. However, due to the limitation of physical hardware, the depth map output by RGB-D sensor usually contains a large area of missing depth values. These missing depth information affect the accuracy and robustness of RGB-D SLAM. In order to reduce these effects, this paper completes the missing area of the depth map output by RGB-D sensor and then fuses the completed dense depth map into ORB SLAM2. By adding the process of obtaining pixel-level dense depth maps, a better RGB-D visual SLAM algorithm is finally obtained. In the process of obtaining dense depth maps, a deep learning model of indoor scenes is adopted. Experiments are conducted on public datasets and real-world environments of indoor scenes. Experimental results show that the proposed SLAM algorithm has better robustness than ORB SLAM2.

Keywords: RGB-D, SLAM, dense depth, depth map

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Authors: Somayeh Sharifi

Abstract:

The purpose of this study is to investigate the effects of collaborative reflection and class observation on improving the quality of teacher training courses and the students reading comprehension skills. 13 inexperienced English teachers teaching elementary courses that were at the same level of proficiency were chosen. Thirteen participants were allocated in two groups, with 7 teachers in the experimental group and the other 6 teachers in the control group. Since two groups were not selected randomly, this study is a form of quasi-experimental research. In addition to a 3-day teacher training course for both groups, teachers in experimental group recorded and observed 20 sessions of their own classes and 30 sessions of experienced teachers’ class and participated in 12 meetings -3 month once a week- in which teachers shared any event that they found interesting during observations and their own teaching and compare it with strategies that they learned in teacher training courses. In contrast, the control group did not engage in any process of observation and collaboration. In order to test students' performance in English before and after the treatment, a Key English Test (KET) was employed to check students' reading skill. The result of the test shows that there is not a significant difference in mean of scores in KET pretest in and, since they are close to each other. However by considering mean and median of posttest in both classes we perceive that although both control and experimental group students' proficiency in English enhanced, there was a significant difference in experimental group students' final scores before and after treatment.

Keywords: collaborative reflection, reading comprehension, teacher training courses, key English test (KET)

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Authors: M. Panidou, F. Kilipiris, E. Christou, K. Alexandris

Abstract:

This study focuses on Generation Z, the next generation of tourists born between 1996 and 2012. Given their significant population size, Generation Z is expected to have a substantial impact on the travel and tourism sector. Therefore, understanding their travel preferences is crucial for businesses in the hospitality and tourism industry. By examining their travel preferences, this research aims to identify the unique characteristics and motivations of this generation when it comes to travel. This study used a quantitative method, and primary data was collected through a survey (online questionnaire), while secondary data was gathered from academic literature, industry reports, and online sources to provide a comprehensive analysis of the topic. The sample of the study was 100 Greek individuals aged between 18-26 years old. The data was analyzed with the support of SPSS software. The findings of the research indicated that technology, sustainability, and budget-friendly options are essential components for attracting and retaining Generation Z tourists. These preferences highlight the importance of incorporating innovative technologies, promoting sustainable practices, and offering affordable travel options to effectively engage this market niche. This research contributes to the field of hospitality and tourism businesses by providing valuable insights into the travel preferences of Generation Z. By understanding their distinct features and preferences; businesses can tailor their strategies and marketing efforts to effectively engage and retain this market segment. Considering the limitations of the sample size, future studies could aim for a larger and more diverse sample to enhance the generalizability of the findings.

Keywords: gen Z, technology, travel preferences, sustainability

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Authors: Ali Asheibi

Abstract:

The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters.

Keywords: data mining, harmonic data, clustering, classification

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Authors: Mohamed Mokhtar, Mostafa F. Shaaban

Abstract:

Among the challenges facing solar photovoltaic (PV) systems in the United Arab Emirates (UAE), dust accumulation on solar panels is considered the most severe problem that faces the growth of solar power plants. The accumulation of dust on the solar panels significantly degrades output from these panels. Hence, solar PV panels have to be cleaned manually or using costly automated cleaning methods. This paper focuses on initiating cleaning actions when required to reduce maintenance costs. The cleaning actions are triggered only when the dust level exceeds a threshold value. The amount of dust accumulated on the PV panels is estimated using an artificial neural network (ANN). Experiments are conducted to collect the required data, which are used in the training of the ANN model. Then, this ANN model will be fed by the output power from solar panels, ambient temperature, and solar irradiance, and thus, it will be able to estimate the amount of dust accumulated on solar panels at these conditions. The model was tested on different case studies to confirm the accuracy of the developed model.

Keywords: machine learning, dust, PV panels, renewable energy

Procedia PDF Downloads 127