Search results for: collaboration learning

Authors: Marwa Hanafy

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The objective of linking the museum with school curriculum is to focus on the values and principles of the educational standards of the fourth grade as "equality, cooperation, allegiance, belonging, participation, peace, tolerance, pride and patriotism, etc." through activities, discussion, exhibits, etc., which can help the students to develop their characters and be useful for their society. For example, there is a lesson in Module 3 assess the role of women as mothers and queens, here this research will focus on the value of women and respect them through statues or images of women which support and affect positively on the students who will apply these Morals to themselves and to the community by dependency. It cannot be denied that the students have to be a part of the museum educational programs which have designed for them, by giving them the opportunity to participate, talk, discuss and express their opinions and hear them in the museums, this may be an effective way to confirm that the interests of children are taken into account.

Keywords: museum education, primary school education, school curriculum, informal learning

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Anna K. Johnson

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Technology can provide endless opportunities for students with special needs. Virtual learning, particularly virtual charter schools in the US, provides opportunities for students with special needs for alternative education besides Brick and Mortar schools. Virtual schools have proven to be successful in the way they are able to provide quality education for their students. Virtual schools, just like Brick and Mortar schools, are not for everybody. This research is designed to look at the effectiveness of online charter schools, so parents can make decisions based on data. This article explains what inclusion is and how inclusion is addressed in the virtual environment. Often, students with special needs have limited options for schooling, and new charter schools provide that alternative education for students who don’t fit in the local brick-and-mortar school.

Keywords: special education, virtual school, online, inclusion

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Authors: Aicha Zohbie

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The purpose of this paper is to critically compare two teaching methods: the communicative method and the grammar-translation method. The paper presents the importance of language awareness as an approach to teaching and learning language and some challenges that language teachers face. In addition, the paper strives to determine whether the adoption of communicative teaching methods or the grammar teaching method would be more effective to teach a language. A variety of features are considered for comparing the two methods: the purpose of each method, techniques used, teachers’ and students’ roles, the use of L1, the skills that are emphasized, the correction of students’ errors, and the students’ assessments. Finally, the paper includes suggestions and recommendations for implementing an approach that best meets the students’ needs in a classroom.

Keywords: language teaching methods, language awareness, communicative method grammar translation method, advantages and disadvantages

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Authors: Kilari Nikhil, Ankur Tibrewal, Srinivas Kruthiventi S. S.

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Conventional speaker identification systems often fall short of capturing the diverse variations present in speech data due to fixed-scale architectures. In this research, we propose a CNN-based architecture, USENet, designed to overcome these limitations. Leveraging two key techniques, our approach achieves superior performance on the VoxCeleb 1 Dataset without any pre-training. Firstly, we adopt a U-net-inspired design to extract features at multiple scales, empowering our model to capture speech characteristics effectively. Secondly, we introduce the squeeze and excitation block to enhance spatial feature learning. The proposed architecture showcases significant advancements in speaker identification, outperforming existing methods, and holds promise for future research in this domain.

Keywords: multi-scale feature extraction, squeeze and excitation, VoxCeleb1 speaker identification, mel-spectrograms, USENet

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Authors: CA Kishore S. Peshori

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Introduction: India, a country with vast diversity and huge population is going to have largest young population by 2020. Higher education has and will always be the basic requirement for making a developing nation to a developed nation. To improve any system it needs to be bench-marked. There have been various tools for bench-marking the systems. Education is delivered in India by universities which are mainly funded by government. This universities for delivering the education sets up colleges which are again funded mainly by government. Recently however there has also been autonomy given to universities and colleges. Moreover foreign universities are waiting to enter Indian boundaries. With a large number of universities and colleges it has become more and more necessary to measure this institutes for bench-marking. There have been various tools for measuring the institute. In India college assessments have been made compulsory by UGC. Naac has been offically recognised as the accrediation criteria. The Naac criteria has been based on seven criterias namely: 1. Curricular assessments, 2. Teaching learning and evaluation, 3. Research Consultancy and Extension, 4. Infrastructure and learning resources, 5. Student support and progression, 6. Governance leadership and management, 7. Innovation and best practices. The Naac tries to bench mark the institution for identification, sustainability, dissemination and adaption of best practices. It grades the institution according to this seven criteria and the funding of institution is based on these grades. Many of the colleges are struggling to get best of grades but they have not come across a systematic tool to achieve the results. Balanced Scorecard developed by Kaplan has been a successful tool for corporates to develop best of practices so as to increase their financial performance and also retain and increase their customers so as to grow the organization to next level.It is time to test this tool for an educational institute. Methodology: The paper tries to develop a prototype for college based on the secondary data. Once a prototype is developed the researcher based on questionnaire will try to test this tool for successful implementation. The success of this research will depend on its implementation of BSC on an institute and its grading improved due to this successful implementation. Limitation of time is a major constraint in this research as Naac cycle takes minimum 4 years for accreditation and reaccreditation the methodology will limit itself to secondary data and questionnaire to be circulated to colleges along with the prototype model of BSC. Conclusion: BSC is a successful tool for enhancing growth of an organization. Educational institutes are no exception to these. BSC will only have to be realigned to suit the Naac criteria. Once this prototype is developed the success will be tested only on its implementation but this research paper will be the first step towards developing this tool and will also initiate the success by developing a questionnaire and getting and evaluating the responses for moving to the next level of actual implementation

Keywords: balanced scorecard, bench marking, Naac, UGC

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Authors: Joseph Ndegwa

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Changes are required if energy systems are to foster long-term growth. The main problems are increasing access to inexpensive, dependable, and sufficient energy supply while addressing environmental implications at all levels. Policies can help to promote sustainable development by providing adequate and inexpensive energy sources to underserved regions, such as liquid and gaseous fuels for cooking and electricity for household and commercial usage. Promoting energy efficiency. Increased utilization of new renewables. Spreading and implementing additional innovative energy technologies. Markets can achieve many of these goals with the correct policies, pricing, and regulations. However, if markets do not work or fail to preserve key public benefits, tailored government policies, programs, and regulations can achieve policy goals. The main strategies for promoting sustainable energy systems are simple. However, they need a broader recognition of the difficulties we confront, as well as a firmer commitment to specific measures. Making markets operate better by minimizing pricing distortions, boosting competition, and removing obstacles to energy efficiency are among the measures. Complementing the reform of the energy industry with policies that promote sustainable energy. Increasing investments in renewable energy. Increasing the rate of technical innovation at each level of the energy innovation chain. Fostering technical leadership in underdeveloped nations by transferring technology and enhancing institutional and human capabilities. promoting more international collaboration. Governments, international organizations, multilateral financial institutions, and civil society—including local communities, business and industry, non-governmental organizations (NGOs), and consumers—all have critical enabling roles to play in the problem of sustainable energy. Partnerships based on integrated and cooperative approaches and drawing on real-world experience will be necessary. Setting the required framework conditions and ensuring that public institutions collaborate effectively and efficiently with the rest of society are common themes across all industries and geographical areas in order to achieve sustainable development. Powerful tools for sustainable development include energy. However, significant policy adjustments within the larger enabling framework will be necessary to refocus its influence in order to achieve that aim. Many of the options currently accessible will be lost or the price of their ultimate realization (where viable) will grow significantly if such changes don't take place during the next several decades and aren't started right enough. In any case, it would seriously impair the capacity of future generations to satisfy their demands.

Keywords: sustainable development, reliable, price, policy

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Authors: Rochelle Yun Ge

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University has played an active role in the country’s development in China. There has been an increasing research interest on the development of higher education cooperation, talent cultivation and attraction, and innovation in the regional development. The Triple Helix model, which indicates that regional innovation and development can be engendered by collaboration among university, industry and government, is often adopted as research framework. The research using triple helix model emphasizes the active and often leading role of university in knowledge-based economy. Within this framework, universities are conceptualized as key institutions of knowledge production, transmission and transference potentially making critical contributions to regional development. Recent research almost uniformly consistent in indicating the high-level research labours (i.e., doctoral, post-doctoral researchers and academics) as important actors in the innovation ecosystem with their cross-geographical human capital and resources presented. In 2019, the development of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was officially launched as an important strategy by the Chinese government to boost the regional development of the Pearl River Delta and to support the realization of “One Belt One Road” strategy. Human Capital formation is at the center of this plan. One of the strategic goals of the GBA development is set to evolve into an international educational hub and innovation center with high-level talents. A number of policies have been issued to attract and cultivate human resources in different GBA cities, in particular for the high-level R&D (research and development) talents such as doctoral and post-doctoral researchers. To better understand the development of high-level talents hub in the GBA, more empirical considerations should be given to explore the approaches of talents cultivation and attraction in the GBA. What remains to explore is the ways to better attract, train, support and retain these talents in the cross-systems context. This paper aims to investigate the role of university in human capital development under China’s national agenda of GBA integration through the lens of universities and actors. Two flagship comprehensive universities are selected to be the cases and 30 interviews with university officials, research leaders, post-doctors and doctoral candidates are used for analysis. In particular, we look at in what ways have universities aligned their strategies and practices to the Chinese government’s GBA development strategy? What strategies and practices have been developed by universities for the cultivation and attraction of high-level research labor? And what impacts the universities have made for the regional development? The main arguments of this research highlights the specific ways in which universities in smaller sub-regions can collaborate in high-level human capital formation and the role policy can play in facilitating such collaborations.

Keywords: university, human capital, regional development, triple-helix model

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Authors: Kyna Elliott

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The COVID-19 global pandemic has changed the shape, design, and delivery of education. As communities continue to fight the pandemic, research suggests the coronavirus is leaving an indelible mark on education which will last long after the pandemic has ended. Faculty and students bring more than their textbooks into the classroom. They bring their lived experiences into the classroom, and it is through these lived experiences that interactions and learning filter through. The COVID-19 pandemic has proved to be a traumatic experience for many. Leaders will need to have the tools and skills to mitigate trauma's impact on faculty and students. This presentation will explore research-based trauma-informed leadership practices, pedagogy, and mitigation strategies within secondary school environments.

Keywords: COVID-19, compassion fatigue, educational leadership, the science of trauma, trauma-informed leadership, trauma-informed pedagogy

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Authors: Dahia Chibouti, Benoit Trouette, Eric Chenier

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With the development of micro-electro-mechanical systems (MEMS), understanding fluid flow and heat transfer at the micrometer scale is crucial. In the case where the flow characteristic length scale is narrowed to around ten times the mean free path of gas molecules, the classical fluid mechanics and energy equations are still valid in the bulk flow, but particular attention must be paid to the gas/solid interface boundary conditions. Indeed, in the vicinity of the wall, on a thickness of about the mean free path of the molecules, called the Knudsen layer, the gas molecules are no longer in local thermodynamic equilibrium. Therefore, macroscopic models based on the continuity of velocity, temperature and heat flux jump conditions must be applied at the fluid/solid interface to take this non-equilibrium into account. Although these macroscopic models are widely used, the assumptions on which they depend are not necessarily verified in realistic cases. In order to get rid of these assumptions, simulations at the molecular scale are carried out to study how molecule interaction with walls can change the fluid flow and heat transfers at the vicinity of the walls. The developed approach is based on a kind of heterogeneous multi-scale method: micro-domains overlap the continuous domain, and coupling is carried out through exchanges of information between both the molecular and the continuum approaches. In practice, molecular dynamics describes the fluid flow and heat transfers in micro-domains while the Navier-Stokes and energy equations are used at larger scales. In this framework, two kinds of micro-simulation are performed: i) in bulk, to obtain the thermo-physical properties (viscosity, conductivity, ...) as well as the equation of state of the fluid, ii) close to the walls to identify the relationships between the slip velocity and the shear stress or between the temperature jump and the normal temperature gradient. The coupling strategy relies on an implicit formulation of the quantities extracted from micro-domains. Indeed, using the results of the molecular simulations, a Bayesian regression is performed in order to build continuous laws giving both the behavior of the physical properties, the equation of state and the slip relationships, as well as their uncertainties. These latter allow to set up a learning strategy to optimize the number of micro simulations. In the present contribution, the first results regarding this coupling associated with the learning strategy are illustrated through parametric studies of convergence criteria, choice of basis functions and noise of input data. Anisothermic flows of a Lennard Jones fluid in micro-channels are finally presented.

Keywords: multi-scale, microfluidics, micro-channel, hybrid approach, coupling

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Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Arthur Ricardo Deps Miguel Ferreira, John Buchanan, Amarnath Banerjee

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This paper describes the development of a virtual-reality system ARWED, which will be used in physical rehabilitation of patients with reduced upper extremity mobility to increase limb Active Range of Motion (AROM). The ARWED system performs a symmetric reflection and real-time mapping of the patient’s healthy limb on to their most affected limb, tapping into the mirror neuron system and facilitating the initial learning phase. Using the ARWED, future experiments will test the extension of the action-observation priming effect linked to the mirror-neuron system on healthy subjects and then stroke patients.

Keywords: physical rehabilitation, mirror neuron, virtual reality, stroke therapy

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Authors: Jaiden X. Schraut

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Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

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Authors: Sławomir Lasota, Tomasz Kajdanowicz

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This paper delves into adapting the Tweeting Factory paradigm to achieve universal production optimization under the Industry 5.0 framework. The proposed system creates a dynamic decision-making environment by collecting and analyzing structured telemetry data (”tweets”) from production lines. A hybrid recommendation engine combines rule-based systems with machine learning models to enhance real-time responsiveness and operator engagement. The research evaluates the system’s ability to optimize diverse industrial processes through predictive KPIs and real-time feedback loops. Results indicate significant advancements in eco-efficiency and operator productivity, showcasing the versatility of the Tweeting Factory approach in meeting the demands of human-centric and sustainable production.

Keywords: tweeting factory, production optimization, industry 5.0, recommendation

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Authors: R. Simide, T. Miard

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Integrated multi-trophic aquaculture (IMTA) is used to reduce waste from aquaculture and increase productivity by co-cultured species. In this study, we designed a recirculating multi-trophic aquaculture system which requires low energy consumption, low water renewal and easy-care. European seabass (Dicentrarchus labrax) were raised with co-cultured sea urchin (Paracentrotus lividus), deteritivorous polychaete fed on settled particulate matter, mussels (Mytilus galloprovincialis) used to extract suspended matters, macroalgae (Ulva sp.) used to uptake dissolved nutrients and gastropod (Phorcus turbinatus) used to clean the series of 4 tanks from fouling. Experiment was performed in triplicate during one month in autumn under an experimental greenhouse at the Institute Océanographique Paul Ricard (IOPR). Thanks to the absence of a physical filter, any pomp was needed to pressure water and the water flow was carried out by a single air-lift followed by gravity flow.Total suspended solids (TSS), biochemical oxygen demand (BOD5), turbidity, phytoplankton estimation and dissolved nutrients (ammonium NH₄, nitrite NO₂⁻, nitrate NO₃⁻ and phosphorus PO₄³⁻) were measured weekly while dissolved oxygen and pH were continuously recorded. Dissolved nutrients stay under the detectable threshold during the experiment. BOD5 decreased between fish and macroalgae tanks. TSS highly increased after 2 weeks and then decreased at the end of the experiment. Those results show that bioremediation can be well used for aquaculture system to keep optimum growing conditions. Fish were the only feeding species by an external product (commercial fish pellet) in the system. The others species (extractive species) were fed from waste streams from the tank above or from Ulva produced by the system for the sea urchin. In this way, between the fish aquaculture only and the addition of the extractive species, the biomass productivity increase by 5.7. In other words, the food conversion ratio dropped from 1.08 with fish only to 0.189 including all species. This experimental recirculating multi-trophic aquaculture system was efficient enough to reduce waste and increase productivity. In a second time, this technology has been reproduced at a commercial scale. The IOPR in collaboration with Les 4 Marais company run for 6 month a recirculating IMTA in 8000 m² of water allocate between 4 marsh ponds. A similar air-lift and gravity recirculating system was design and only one feeding species of shrimp (Palaemon sp.) was growth for 3 extractive species. Thanks to this joint work at the laboratory and commercial scales we will be able to challenge IMTA system and discuss about this sustainable aquaculture technology.

Keywords: bioremediation, integrated multi-trophic aquaculture (IMTA), laboratory and commercial scales, recirculating aquaculture, sustainable

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Authors: Shaleeza Sohail

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Self, and peer evaluations are some of the main components in almost all group assignments and projects in higher education institutes. These evaluations provide students an opportunity to better understand the learning outcomes of the assignment and/or project. A number of online systems have been developed for this purpose that provides automated assessment and feedback of students’ contribution in a group environment based on self and peer evaluations. All these systems lack a progressive aspect of these assessments and feedbacks which is the most crucial factor for ongoing improvement and life-long learning. In addition, a number of assignments and projects are designed in a manner that smaller or initial assessment components lead to a final assignment or project. In such cases, the evaluation and feedback may provide students an insight into their performance as a group member for a particular component after the submission. Ideally, it should also create an opportunity to improve for next assessment component as well. Self and Peer Progressive Assessment and Feedback System encourages students to perform better in the next assessment by providing a comparative analysis of the individual’s contribution score on an ongoing basis. Hence, the student sees the change in their own contribution scores during the complete project based on smaller assessment components. Self-Assessment Factor is calculated as an indicator of how close the self-perception of the student’s own contribution is to the perceived contribution of that student by other members of the group. Peer-Assessment Factor is calculated to compare the perception of one student’s contribution as compared to the average value of the group. Our system also provides a Group Coherence Factor which shows collectively how group members contribute to the final submission. This feedback is provided for students and teachers to visualize the consistency of members’ contribution perceived by its group members. Teachers can use these factors to judge the individual contributions of the group members in the combined tasks and allocate marks/grades accordingly. This factor is shown to students for all groups undertaking same assessment, so the group members can comparatively analyze the efficiency of their group as compared to other groups. Our System provides flexibility to the instructors for generating their own customized criteria for self and peer evaluations based on the requirements of the assignment. Students evaluate their own and other group members’ contributions on the scale from significantly higher to significantly lower. The preliminary testing of the prototype system is done with a set of predefined cases to explicitly show the relation of system feedback factors to the case studies. The results show that such progressive feedback to students can be used to motivate self-improvement and enhanced team skills. The comparative group coherence can promote a better understanding of the group dynamics in order to improve team unity and fair division of team tasks.

Keywords: effective group work, improvement of team skills, progressive feedback, self and peer assessment system

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Authors: Aakriti Chetan Shah, Elle Sein

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Background/purpose: Group B Streptococcus(GBS) is the leading cause of severe early onset infection in newborns, with the incidence of Early Onset Group B Streptococcus (EOGBS) in the UK and Ireland rising from 0.48 to 0.57 per 1000 births from 2000 to 2015. A WHO study conducted in 2017, has shown that 38.5% of cases can result in stillbirth and infant deaths. This is an important problem to consider as 20% of women worldwide have GBS colonisation and can suffer from these detrimental effects. Current Royal College of Obstetricians and Midwives (RCOG) guidelines do not recommend bacteriological screening for pregnant women due to its low sensitivity in antenatal screening correlating with the neonate having GBS but advise a patient information leaflet be given to pregnant women. However, a Healthcare Safety Investigation Branch (HSIB) 2019 learning report found that only 50% of trusts and health boards reported giving GBS information leaflets to all pregnant mothers. Therefore, this audit aimed to assess current practices of information dissemination about GBS at Chelsea & Westminster (C&W) Hospital. Methodology: A quantitative cross-sectional study was carried out using a questionnaire based on the RCOG GBS guidelines and the HSIB Learning report. The study was conducted in antenatal clinics at Chelsea & Westminster Hospital, from 29th January 2021 to 14th February 2021, with twenty-two practicing obstetricians and midwives participating in the survey. The main outcome measure was the proportion of obstetricians and midwives who disseminate information about GBS to pregnant women, and the reasons behind why they do or do not. Results: 22 obstetricians and midwives responded with 18 complete responses. Of which 12 were obstetricians and 6 were midwives. Only 17% of clinical staff routinely inform all pregnant women about GBS, and do so at varying timeframes of the pregnancy, with an equal split in the first, second and third trimester. The primary reason for not informing women about GBS was influenced by three key factors: Deemed relevant only for patients at high risk of GBS, lack of time in clinic appointments and no routine NHS screening available. Interestingly 58% of staff in the antenatal clinic believe it is necessary to inform all women about GBS and its importance. Conclusion: It is vital for obstetricians and midwives to inform all pregnant women about GBS due to the high prevalence of incidental carriers in the population, and the harmful effects it can cause for neonates. Even though most clinicians believe it is important to inform all pregnant women about GBS, most do not. To ensure that RCOG and HSIB recommendations are followed, we recommend that women should be given this information at 28 weeks gestation in the antenatal clinic. Proposed implementations include an information leaflet to be incorporated into the Mum and Baby app, an informative video and end-to-end digital clinic documentation to include this information sharing prompt.

Keywords: group B Streptococcus, early onset sepsis, Antenatal care, Neonatal morbidity, GBS

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Authors: Ujjwall Sai Sunder Uppuluri

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Group theory is a powerful tool that researchers can use to provide a structural foundation for their Agent Based Models. These Agent Based models are argued by this paper to be the future of the Social Science Disciplines. More specifically, researchers can use them to apply evolutionary theory to the study of complex social systems. This paper illustrates one such example of how theoretically an Agent Based Model can be formulated from the application of Group Theory, Systems Dynamics, and Evolutionary Biology to analyze the strategies pursued by states to mitigate risk and maximize usage of resources to achieve the objective of economic growth. This example can be applied to other social phenomena and this makes group theory so useful to the analysis of complex systems, because the theory provides the mathematical formulaic proof for validating the complex system models that researchers build and this will be discussed by the paper. The aim of this research, is to also provide researchers with a framework that can be used to model political entities such as states on a 3-dimensional plane. The x-axis representing resources (tangible and intangible) available to them, y the risks, and z the objective. There also exist other states with different constraints pursuing different strategies to climb the mountain. This mountain’s environment is made up of risks the state faces and resource endowments. This mountain is also layered in the sense that it has multiple peaks that must be overcome to reach the tallest peak. A state that sticks to a single strategy or pursues a strategy that is not conducive to the climbing of that specific peak it has reached is not able to continue advancement. To overcome the obstacle in the state’s path, it must innovate. Based on the definition of a group, we can categorize each state as being its own group. Each state is a closed system, one which is made up of micro level agents who have their own vectors and pursue strategies (actions) to achieve some sub objectives. The state also has an identity, the inverse being anarchy and/or inaction. Finally, the agents making up a state interact with each other through competition and collaboration to mitigate risks and achieve sub objectives that fall within the primary objective. Thus, researchers can categorize the state as an organism that reflects the sum of the output of the interactions pursued by agents at the micro level. When states compete, they employ a strategy and that state which has the better strategy (reflected by the strategies pursued by her parts) is able to out-compete her counterpart to acquire some resource, mitigate some risk or fulfil some objective. This paper will attempt to illustrate how group theory combined with evolutionary theory and systems dynamics can allow researchers to model the long run development, evolution, and growth of political entities through the use of a bottom up approach.

Keywords: complex systems, evolutionary theory, group theory, international political economy

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Authors: Troels Bo Jørgensen, Preben Hagh Strunge Holm, Henrik Gordon Petersen, Norbert Kruger

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This paper presents a simulation framework for using machine learning techniques to determine robust robotic motions for handling deformable objects. The main focus is on applications in the meat sector, which mainly handle three-dimensional objects. In order to optimize the robotic handling, the robot motions have been parameterized in terms of grasp points, robot trajectory and robot speed. The motions are evaluated based on a dynamic simulation environment for robotic control of deformable objects. The evaluation indicates certain parameter setups, which produce robust motions in the simulated environment, and based on a visual analysis indicate satisfactory solutions for a real world system.

Keywords: deformable objects, robotic manipulation, simulation, real world system

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Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

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Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

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Authors: Belkacem Benadda, Adil Benabdellah, Boutheyna Souna

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The Internet of Things (IoT) is an unprecedented creation. Electronics objects are now able to interact, share, respond and adapt to their environment on a much larger basis. Actual spread of these modern means of connectivity and solutions with high data volume exchange are affecting our ways of life. Accommodation is becoming an intelligent living space, not only suited to the people circumstances and desires, but also to systems constraints to make daily life simpler, cheaper, increase possibilities and achieve a higher level of services and luxury. In this paper we are as Internet access, teleworking, consumption monitoring, information search, etc.). This paper addresses the design and integration of a smart home, it also purposes an IoT solution that allows smart power consumption based on measurements from power-grid and deep learning analysis.

Keywords: array sensors, IoT, power grid, FPGA, embedded

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Authors: Violeta Juanico

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While there was a statement made by the RVM Education Ministry Commission that its strength is its Ignacian identity, shaped by the Ignacian spirituality that permeates the school community leading to a more defined RVM school culture, there has been no empirical study made in terms of a clear and convincing conceptual framework on how the RVM Educational mission is lived in the Religious of the Virgin Mary (RVM) learning institutions to the best of author’s knowledge. This dissertation is an attempt to come up with a substantive theory that supports and explains the stakeholders’ experiences with the RVM educational mission in the Philippines. Participants that represent the different stakeholders ranging from students to administrators were interviewed. The expressions and thoughts of the participants were initially coded and analyzed using the Barney Glaser’s original grounded theory methodology to find out how the RVM mission is lived in the field of education.

Keywords: catholic education, grounded theory, lived experience, RVM educational mission

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Authors: Nada Souissi, Mourad Mroua

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The main purpose of this study is to examine the interaction between financial asset volatility, economic factors and investor's behavioral indicators related to both the company's and the markets stocks for the period from January 2000 to January2020. Using multiple linear regression and Bayesian Networks modeling, results show a positive and negative relationship between investor's psychology index, economic factors and predicted stock market return. We reveal that the application of the Bayesian Discrete Network contributes to identify the different cause and effect relationships between all economic, financial variables and psychology index.

Keywords: Financial asset return predictability, Economic factors, Investor's psychology index, Bayesian approach, Probabilistic networks, Parametric learning

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Authors: Sunidhi Sood, Drashti Narendrakumar Shah, Aakarsh Sharma, Nirali Harsh Panchal, Maria Karizhenskaia

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Cancer is a global health concern, causing a significant number of deaths, with chemotherapy being a standard treatment method. However, chemotherapy often induces side effects that profoundly impact the physical and emotional well-being of patients, lowering their overall quality of life (QoL). This research aims to investigate the potential of music and art therapy as holistic adjunctive therapy for cancer patients undergoing chemotherapy, offering non-pharmacological support. This is achieved through a comprehensive review of existing literature with a focus on the following themes, including stress and anxiety alleviation, emotional expression and coping skill development, transformative changes, and pain management with mood upliftment. A systematic search was conducted using Medline, Google Scholar, and St. Lawrence College Library, considering original, peer-reviewed research papers published from 2014 to 2023. The review solely incorporated studies focusing on the impact of music and art therapy on the health and overall well-being of cancer patients undergoing chemotherapy in North America. The findings from 16 studies involving pediatric oncology patients, females affected by breast cancer, and general oncology patients show that music and art therapies significantly reduce anxiety (standardized mean difference: -1.10) and improve perceived stress (median change: -4.0) and overall quality of life in cancer patients undergoing chemotherapy. Furthermore, music therapy has demonstrated the potential to decrease anxiety, depression, and pain during infusion treatments (average changes in resilience scale: 3.4 and 4.83 for instrumental and vocal music therapy, respectively). This data calls for consideration of the integration of music and art therapy into supportive care programs for cancer patients undergoing chemotherapy. Moreover, it provides guidance to healthcare professionals and policymakers, facilitating the development of patient-centered strategies for cancer care in Canada. Further research is needed in collaboration with qualified therapists to examine its applicability and explore and evaluate patients' perceptions and expectations in order to optimize the therapeutic benefits and overall patient experience. In conclusion, integrating music and art therapy in cancer care promises to substantially enhance the well-being and psychosocial state of patients undergoing chemotherapy. However, due to the small population size considered in existing studies, further research is needed to bridge the knowledge gap and ensure a comprehensive, patient-centered approach, ultimately enhancing the quality of life (QoL) for individuals facing the challenges of cancer treatment.

Keywords: anxiety, cancer, chemotherapy, depression, music and art therapy, pain management, quality of life

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Authors: Shah Muhammad Butt, Ahmed Masaud Ansari

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Present Financial crisis in Higher Educational Institutes (HEIs) facing lots of problems considerable budget cuts, make difficult to meet the ever growing IT-based research and learning needs, institutions are rapidly planning and promoting cloud-based approaches for their academic and research needs. A cost effective Hybrid Cloud framework for HEI’s will provide educational services for campus or intercampus communication. Hybrid Cloud Framework comprises Private and Public Cloud approaches. This paper will propose the framework based on the Open Source Cloud (OpenNebula for Virtualization, Eucalyptus for Infrastructure, and Aneka for programming development environment) combined with CSP’s services which are delivered to the end-user via the Internet from public clouds.

Keywords: educational services, hybrid campus cloud, open source, electrical and systems sciences

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Authors: Pengchao Wei, Xiangzhong Fang

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Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.

Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise

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Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

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Authors: Fabrizio Logiurato

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Light Polarization has many technological applications, and its discovery was crucial to reveal the transverse nature of the electromagnetic waves. However, despite its fundamental and practical importance, in high school, this property of light is often neglected. This is a pity not only for its conceptual relevance, but also because polarization gives the possibility to perform many brilliant experiments with low cost materials. Moreover, the treatment of this matter lends very well to an interdisciplinary approach between art, biology and technology, which usually makes things more interesting to students. For these reasons, we have developed, and in this work, we introduce a laboratory on light polarization for high school and undergraduate students. They can see beautiful pictures when birefringent materials are set between two crossed polarizing filters. Pupils are very fascinated and drawn into by what they observe. The colourful images remind them of those ones of abstract painting or alien landscapes. With this multidisciplinary teaching method, students are more engaged and participative, and also, the learning process of the respective physics concepts is more effective.

Keywords: light polarization, optical activity, multidisciplinary education, science and art

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Authors: Doni Dermawan

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Modern sports competition as a consequence of the increase in the value of the business and entertainment in the field of sport has been demanding athletes to always have excellent physical endurance performance. Physical exercise is done in a long time, and intensive may pose a risk of muscle tissue damage caused by the increase of the enzyme creatine kinase. Branched Chain Amino Acids (BCAA) is an essential amino acid that is composed of leucine, isoleucine, and valine which serves to maintain muscle tissue, keeping the immune system, and prevent further loss of coordination and muscle pain. Pea (Pisum sativum L.) is a kind of leguminous plants that are rich in Branched Chain Amino Acids (BCAA) where every one gram of protein pea contains 82.7 mg of leucine; 56.3 mg isoleucine; and 56.0 mg of valine. This research aims to develop Branched Chain Amino Acids (BCAA) from pea extract is applied in dosage forms Gel PVP Kinesio Tape technology using Ultrasound-assisted Extraction. The method used in the writing of this paper is the Cochrane Collaboration Review that includes literature studies, testing the quality of the study, the characteristics of the data collection, analysis, interpretation of results, and clinical trials as well as recommendations for further research. Extraction of BCAA in pea done using ultrasound-assisted extraction technology with optimization variables includes the type of solvent extraction (NaOH 0.1%), temperature (20-250C), time (15-30 minutes) power (80 watt) and ultrasonic frequency (35 KHz). The advantages of this extraction method are the level of penetration of the solvent into the membrane of the cell is high and can increase the transfer period so that the BCAA substance separation process more efficient. BCAA extraction results are then applied to the polymer PVP (Polyvinylpyrrolidone) Gel powder composed of PVP K30 and K100 HPMC dissolved in 10 mL of water-methanol (1: 1) v / v. Preparations Kinesio Tape Gel PVP is the BCAA in the gel are absorbed into the muscle tissue, and joints through tensile force then provides stimulation to the muscle circulation with variable pressure so that the muscle can increase the biomechanical movement and prevent damage to the muscle enzyme creatine kinase. Analysis and evaluation of test preparation include interaction, thickness, weight uniformity, humidity, water vapor permeability, the levels of the active substance, content uniformity, percentage elongation, stability testing, release profile, permeation in vitro and in vivo skin irritation testing.

Keywords: branched chain amino acid, BCAA, Kinesio tape, pea, PVP gel, ultrasound-assisted extraction

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Authors: Ashenafi Sileshi Etefa, Bezawit Worku Yenealem

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Micro-insurance is a relatively new concept that is just being introduced in Ethiopia. For an agrarian economy dominated by small holder farming and vulnerable to natural disasters, mainly drought, the need for an Index-Based Micro Insurance (IBMI) is crucial. Since IBMI solves moral hazard, adverse selection, and access issues to poor clients, it is preferable over traditional insurance products. IBMI is being piloted in drought prone areas of Ethiopia with the aim of learning and expanding the service across the country. This article analyses the demand of IBMI and the barriers to demand and finds that the demand for IBMI has so far been constrained by lack of awareness, trust issues, costliness, and the level of basis risk; and recommends reducing the basis risk and increasing the role of government and farmer cooperatives.

Keywords: agriculture, index based micro-insurance (IBMI), drought, micro-finance institution (MFI)

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Authors: Aadya Kaktikar

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The role of a traditional dance teacher in India revolves around teaching movements and postures that have been a part of the movement vocabulary of dancers from before the 2nd century BC. These movements inscribe on the mind and body of the dancer a complex web of philosophy, culture history, and religion. However, this repository of tradition sits in a fast globalizing India creating a cultural space which is in a constant flux, where identities and meanings are being constantly challenged. The guru-shishya parampara, the traditional way of learning dance, sits uneasily with a modern education space in India. The traditional dance teacher is caught in the cross-currents of tradition and modernity, of preservation and exploration. This paper explores conflicting views on what dance ought to mean and how it should be taught. The paper explores the tensions of the social, economic and cultural spaces that the traditional dance teacher navigates.

Keywords: pedagogy, dance education, dance curriculum, teacher training

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