Search results for: Learning materials

Authors: Jurijs Salijevs, Katrina Bolocko

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The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

Procedia PDF Downloads 78

Authors: Mazyar Ahrari, Ramin Khajavi, Mehdi Kamali Dolatabadi, Tayebeh Toliyat, Abosaeed Rashidi

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Fabric as the first and most common layer that is in permanent contact with human skin is a very good interface to provide coverage, as well as heat and cold insulation. Phase change materials (PCMs) are organic and inorganic compounds which have the capability of absorbing and releasing noticeable amounts of latent heat during phase transitions between solid and liquid phases at a low temperature range. PCMs come across phase changes (liquid-solid and solid-liquid transitions) during absorbing and releasing thermal heat; so, in order to use them for a long time, they should have been encapsulated in polymeric shells, so-called microcapsules. Microencapsulation and nanoencapsulation methods have been developed in order to reduce the reactivity of a PCM with outside environment, promoting the ease of handling, decreasing the diffusion and evaporation rates. Methods of incorporation of PCMs in textiles such as electrospinning and determining thermal properties had been summarized. Paraffin waxes catch a lot of attention due to their high thermal storage density, repeatability of phase change, thermal stability, small volume change during phase transition, chemical stability, non-toxicity, non-flammability, non-corrosive and low cost and they seem to play a key role in confronting with climate change and global warming. In this article, we aimed to review the researches concentrating on the characteristics of PCMs and new materials and methods of microencapsulation.

Keywords: thermoregulation, microencapsulation, phase change materials, thermal energy storage, nanoencapsulation

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Authors: Pratheesh Jakkala

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This paper addresses the use of breakout sessions to conduct successful weekly physics recitations for College Physics I and II at a large University in remote teaching method during COVID-19 pandemic. All breakout sessions are synchronous, conducted live, and handled by teaching assistants. A two-prong approach is used to maintain the integrity of recitations. Three different conference platforms WebEx, Zoom, and Canvas conferences, were tested, and BigBlue button using Canvas was adopted. The results and experiences of all three learning platforms are presented in this paper. Recitation questions were assigned on WebAssign learning platform and a standard five-question template developed by the instructor was used for group discussions and active peer-peer engagement. Breakout sessions feature of BigBlueButton in Canvas conferences was successfully implemented. Each breakout session consists of a team of 4 students. An online whiteboard, chat window options were used for live teamwork. Student peer-peer interactions, Teaching Assistants’ interaction with students were video and audio recorded. A total of 72 students in College Physics II and 55 students in College Physics I was enrolled. 82% of students agreed that method under study is better than previous methods. The study addressed the quality of student teamwork, student attitude towards problem-solving, and student performance in the exams.

Keywords: recitations, breakout rooms, online learning platforms, COVID pandemic

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Authors: Samia Moulebhar, Chahrazed Bendenia, Souhila Bendenia, Hanaa Merad-dib, Sarra Merabet, Sid Ahmed Khantar, Baghdad Hadri

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The photovoltaic solar field is today experiencing exponential advancement with the exploitation of new technological sectors of nanoparticles, namely the field of solar cells based on organic polymer materials. These cells are flexible, easy to process and low cost. This work includes a presentation of the conjugated polymer materials used in the design of photovoltaic technology devices while determining their properties and then the models used for the modeling of thin film photovoltaic cells heterojunction.

Keywords: photovoltaic, cells, nanoparticles, organic

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Authors: Tarek Ninouh, Ahmed Rouili

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The Roman paths or roads offer a very interesting archaeological material, because they allow us to understand the history of human settlement and are also factors that increase territorial identity. Roman roads are one of the hallmarks of the Roman empire, which extends to North Africa. The objective of this investigation is to attract the attention of researchers to the importance of Roman roads and paths, which are found in Algeria, according to the quality of the materials and techniques used in this period of our history, and to encourage other decision makers to protect and enhance these routes because the current urbanization, intensive agricultural practices, or simply forgotten, decreases the sustainability of this important historical heritage.

Keywords: Roman paths, quality of materials, property, valuation

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Authors: Dike Felix Okechukwu

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

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

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Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

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

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

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

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

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

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

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

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

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

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

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

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Authors: E. A. Asabina, V. I. Pet'kov, P. A. Mayorov, A. V. Markin, N. N. Smirnova, A. M. Kovalskii, A. A. Usenko

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The purpose of this work was to synthesize and investigate phase formation, structure and thermophysical properties of the phosphates M_0.5+xM'_xZr_2–x(PO₄)₃ (M – Cd, Sr, Pb; M' – Mg, Co, Mn). The compounds were synthesized by sol-gel method. The results showed formation of limited solid solutions of NZP/NASICON type. The crystal structures of triple phosphates of the compositions MMg_0.5Zr_1.5(PO₄)₃ were refined by the Rietveld method using XRD data. Heat capacity (8–660 K) of the phosphates Pb_0.5+xMg_xZr_2-x(PO₄)₃ (x = 0, 0.5) was measured, and reversible polymorphic transitions were found at temperatures, close to the room temperature. The results of Rietveld structure refinement showed the polymorphism caused by disordering of lead cations in the cavities of NZP/NASICON structure. Thermal expansion (298−1073 K) of the phosphates MMg_0.5Zr_1.5(PO₄)₃ was studied by XRD method, and the compounds were found to belong to middle and low-expanding materials. Thermal diffusivity (298–573 K) of the ceramic samples of phosphates slightly decreased with temperature increasing. As was demonstrated, the studied phosphates are characterized by the better thermophysical characteristics than widespread fire-resistant materials, such as zirconia and etc.

Keywords: NASICON, NZP, phosphate, structure, synthesis, thermophysical properties

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

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

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

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Authors: Omnia F. Elkommos

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

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

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Authors: R Palson Kennedy, P.Kiran Sai

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

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

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Authors: Kadda Boumediene, Mohamed Ziani

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Mainly because of their good ratio stiffness/mass, and in addition to adjustable mechanical properties, composite materials are more and more often used as an alternative to traditional materials in several domains. Before using these materials in practical application, a detailed and precise characterization of their mechanical properties is necessary. In the present work, we will find a dynamic analyze of composite beam (natural frequencies and mode shape), an experimental vibration technique, which presents a powerful tool for the estimation of mechanical characteristics, is used to characterize a dissimilar beam of a Mortar/ natural mineral fiber. The study is completed by an analytic (Rayleigh & Rayleigh-Ritz), experimental and numerical application for non-uniform composite beam of a Mortar/ natural mineral fiber. The study is supported by a comparison between numerical and analytic results as well as a comparison between experimental and numerical results.

Keywords: composite beam, mortar/ natural mineral fiber, mechanical characteristics, natural frequencies, mode shape

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Authors: Ahmed Negm, George Aggidis, Xiandong Ma

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

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

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Authors: Brian J. Kozak, Joshua D. Shipman, Peng Hao Wang, Blake Shipp

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The unmanned aerial system (UAS) industry is growing at a rapid pace. This growth has increased the demand for low cost, custom made and high strength unmanned aerial vehicles (UAV). The area of most growth is in the area of 25 kg to 200 kg vehicles. Vehicles this size are beyond the size and scope of simple wood and fabric designs commonly found in hobbyist aircraft. These high end vehicles require stronger materials to complete their mission. Traditional aircraft construction materials such as aluminum are difficult to use without machining or advanced computer controlled tooling. However, by using general aviation composite aircraft homebuilding techniques and materials, a large scale UAV can be constructed cheaply and easily. Furthermore, these techniques could be used to easily manufacture cost made composite shapes and airfoils that would be cost prohibitive when using metals. These homebuilt aircraft techniques are being demonstrated by the researchers in the construction of a 75 kg aircraft.

Keywords: composite aircraft, homebuilding, unmanned aerial system industry, UAS, unmanned aerial vehicles, UAV

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

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

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

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Authors: B. Chen, F. Kuznik, M. Horgnies, K. Johannes, V. Morin, E. Gengembre

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More attention on renewable energy has been done after the achievement of Paris Agreement against climate change. Solar-based technology is supposed to be one of the most promising green energy technologies for residential buildings since its widely thermal usage for hot water and heating. However, the seasonal mismatch between its production and consumption makes buildings need an energy storage system to improve the efficiency of renewable energy use. Indeed, there exist already different kinds of energy storage systems using sensible or latent heat. With the consideration of energy dissipation during storage and low energy density for above two methods, thermochemical energy storage is then recommended. Recently, ettringite (3CaO∙Al₂O₃∙3CaSO₄∙32H₂O) based materials have been reported as potential thermochemical storage materials because of high energy density (~500 kWh/m³), low material cost (700 €/m³) and low storage temperature (~60-70°C), compared to reported salt hydrates like SrBr₂·6H₂O (42 k€/m³, ~80°C), LaCl₃·7H₂O (38 k€/m³, ~100°C) and MgSO₄·7H₂O (5 k€/m³, ~150°C). Therefore, they have the possibility to be largely used in building sector with being coupled to normal solar panel systems. On the other side, the lack in terms of extensive examination leads to poor knowledge on their thermal properties and limit maturity of this technology. The aim of this work is to develop a modular reactor adapting to thermal characterizations of ettringite-based material particles of different sizes. The filled materials in the reactor can be self-compacted vertically to ensure hot air or humid air goes through homogenously. Additionally, quick assembly and modification of reactor, like LEGO™ plastic blocks, make it suitable to distinct thermochemical energy storage material samples with different weights (from some grams to several kilograms). In our case, quantity of stored and released energy, best work conditions and even chemical durability of ettringite-based materials have been investigated.

Keywords: dehydration, ettringite, hydration, modular reactor, thermochemical energy storage

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Authors: Arianna Nativio, Zoran Kapelan, Jan Peter van der Hoek

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Bio-composite materials are becoming increasingly popular in various applications, such as the automotive industry. Usually, bio-composite materials are made from natural resources recovered from plants, now, a new type of bio-composite material has begun to be produced in the Netherlands. This material is made from resources recovered from drinking water treatments (calcite), wastewater treatment (cellulose), and material from surface water management (aquatic plants). Surface water, raw drinking water, and wastewater can be contaminated with pathogens and chemical compounds. Therefore, it would be valuable to develop a framework to assess, monitor, and control the potential risks. Indeed, the goal is to define the major risks in terms of human health, quality of materials, and environment associated with the production and application of these new materials. This study describes the general risk assessment framework, starting with a qualitative risk assessment. The qualitative risk analysis was carried out by using the HAZOP methodology for the hazard identification phase. The HAZOP methodology is logical and structured and able to identify the hazards in the first stage of the design when hazards and associated risks are not well known. The identified hazards were analyzed to define the potential associated risks, and then these were evaluated by using the qualitative Event Tree Analysis. ETA is a logical methodology used to define the consequences for a specific hazardous incidents, evaluating the failure modes of safety barriers and dangerous intermediate events that lead to the final scenario (risk). This paper shows the effectiveness of combining of HAZOP and qualitative ETA methodologies for hazard identification and risk mapping. Then, key risks were identified, and a quantitative framework was developed based on the type of risks identified, such as QMRA and QCRA. These two models were applied to assess human health risks due to the presence of pathogens and chemical compounds such as heavy metals into the bio-composite materials. Thus, due to these contaminations, the bio-composite product, during its application, might release toxic substances into the environment leading to a negative environmental impact. Therefore, leaching tests are going to be planned to simulate the application of these materials into the environment and evaluate the potential leaching of inorganic substances, assessing environmental risk.

Keywords: bio-composite, risk assessment, water reuse, resource recovery

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

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

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

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Authors: Salsabila Meutia Meutia

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

Keywords: Youtube, Nihongo, Mantappu, SDG's

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Authors: Yaojun Wang, Yaoqing Wang

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

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

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Authors: Sameerah A. Al-Hariri Al-Zahrani

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The current study aims at getting acquainted with the impact of the use of some multiple intelligence-based teaching strategies on developing moral intelligence and inferential jurisprudential thinking among secondary school female students. The study has endeavored to answer the following questions: What is the impact of the use of some multiple intelligence-based teaching strategies on developing inferential jurisprudential thinking and moral intelligence among first-year secondary school female students? In the frame of this main research question, the study seeks to answer the following sub-questions: (i) What are the inferential jurisprudential thinking skills among first-year secondary school female students? (ii) What are the components of moral intelligence among first year secondary school female students? (iii) What is the impact of the use of some multiple intelligence‐based teaching strategies (such as the strategies of analyzing values, modeling, Socratic discussion, collaborative learning, peer collaboration, collective stories, building emotional moments, role play, one-minute observation) on moral intelligence among first-year secondary school female students? (iv) What is the impact of the use of some multiple intelligence‐based teaching strategies (such as the strategies of analyzing values, modeling, Socratic discussion, collaborative learning, peer collaboration, collective stories, building emotional moments, role play, one-minute observation) on developing the capacity for inferential jurisprudential thinking of juristic rules among first-year secondary school female students? The study has used the descriptive-analytical methodology in surveying, analyzing, and reviewing the literature on previous studies in order to benefit from them in building the tools of the study and the materials of experimental treatment. The study has also used the experimental method to study the impact of the independent variable (multiple intelligence strategies) on the two dependent variables (moral intelligence and inferential jurisprudential thinking) in first-year secondary school female students’ learning. The sample of the study is made up of 70 female students that have been divided into two groups: an experimental group consisting of 35 students who have been taught through multiple intelligence strategies, and a control group consisting of the other 35 students who have been taught normally. The two tools of the study (inferential jurisprudential thinking test and moral intelligence scale) have been implemented on the two groups as a pre-test. The female researcher taught the experimental group and implemented the two tools of the study. After the experiment, which lasted eight weeks, was over, the study showed the following results: (i) The existence of significant statistical differences (0.05) between the mean average of the control group and that of the experimental group in the inferential jurisprudential thinking test (recognition of the evidence of jurisprudential rule, recognition of the motive for the jurisprudential rule, jurisprudential inferencing, analogical jurisprudence) in favor of the experimental group. (ii) The existence of significant statistical differences (0.05) between the mean average of the control group and that of the experimental group in the components of the moral intelligence scale (sympathy, conscience, moral wisdom, tolerance, justice, respect) in favor of the experimental group. The study has, thus, demonstrated the impact of the use of some multiple intelligence-based teaching strategies on developing moral intelligence and inferential jurisprudential thinking.

Keywords: moral intelligence, teaching, inferential jurisprudential thinking, secondary school

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Authors: Tamal Roy, Anuradha Bhat

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

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

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Authors: Stephen J. Mitchual, Kwasi Frimpong-Mensah, Nicholas A. Darkwa

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The fuel potential of six tropical hardwood species namely: Triplochiton scleroxylon, Ceiba pentandra, Aningeria robusta, Terminalia superba, Celtis mildbreadii and Piptadenia africana were studied. Properties studied include the species density, gross calorific value, volatile matter, ash, organic carbon, N, H, S, Cu, Pb, As and Cd content. Fuel properties were determined using standard laboratory methods. The result indicates that the Gross Calorific Value (GCV) of the species ranged from 20.16 to 22.22 MJ/kg and they slightly varied from each other. Additionally, the GCV of the biomass materials were higher than that of other biomass materials like; wheat straw, rice straw, maize straw and sugar cane. The ash and volatile matter content varied from 0.6075 to 5.0407%, and 75.23% to 83.70% respectively. The overall rating of the properties of the six biomass materials suggest that Piptadenia africana has the best fuel property to be used as briquettes and Aningeria robusta the worse. This study therefore suggests that a holistic assessment of a biomass material needs to be done before selecting it for fuel purpose.

Keywords: ash content, briquette, calorific value, elemental composition, species, volatile matter

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Authors: D. K. Kumador, E. A. Muthivhi

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Historically, reforms in early childhood education in Ghana have focused narrowly on structural and pedagogical aspects with little attention paid to the broader sociocultural framework within which schooling and child development systems interact. This preliminary study investigates inclusive early childhood education within rapidly changing Ghanaian socio-cultural context, and its consequences for the development of children with learning disabilities. The study addresses an important topic, which is largely under-researched outside of Europe, North America, and Australasia. While inclusive education has been widely accepted globally at the level of policy, its implementation is uneven, as is shown in numerous studies across an array of countries and education systems. Despite this burgeoning area of research internationally, there have been far fewer studies conducted in African settings and fewer still that use cultural-historical activity theory as an investigative approach. More so, specific literature on the subject in the Ghanaian context is non-existent and, as such, coming to a deeper understanding of the sociocultural practices that shape, and possibly impede, inclusive early childhood education in an African country, Ghana, is a worthwhile research endeavour. Using cultural-historical activity theory as a methodological framework, this study employed classroom observations, and in-depth interviews and focus group discussions of preschool teachers in three kindergarten centres in the Greater Accra Region of Ghana to qualitatively explore inclusive early childhood education and the development of children with learning disabilities. The findings showed that literature from Ghana rarely discusses child informed consent as an on-going process that must be articulated throughout the research process from data collection to analysis, reporting and dissemination. Further, the study showed that the introduction and implementation of inclusive education framework – with its concomitant revisions in the curriculum, policies, and school rules, as well as enhanced community and parent involvement – into existing schooling practices, generated contradictions in inclusive teachers’ approaches to teaching and learning, and classroom management. Generally, contradictions in the understanding and acceptability of approaches to teaching and learning occur when a new way of doing things is incorporated into existing practices. These contradictions are thought to be a source of change and development. Thus, they guide teachers to unlearn outmoded practices, relearn or learn new approaches that are beneficial to the development of all children. Nonetheless, the findings of the current study showed that preschool teachers’ belief systems and perceptions of disabilities mediated the outcomes of such contradictions. Also, that was evidenced in the way they engaged children with learning disabilities compared to their typically developing counterparts, showing disregard for what was prescribed by new policies and school rules. The findings have implications for research with young children and the development outcomes of children with learning disabilities in inclusive early childhood education settings.

Keywords: CHAT, classroom management, cultural-historical activity theory, ghana, inclusive early childhood education, schooling practices, young children with learning disabilities

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Authors: Eunice H. Li

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

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

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Authors: Zory Marantz

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

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

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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

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

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