Search results for: computational machine learning

Authors: Ruslan Safarov, Zhanat Shomanova, Yuri Nossenko, Zhandos Mussayev, Ayana Baltabek

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Geochemical maps of distribution of polluting elements V, Cr, Mn, Co, Ni, Cu, Zn, Mo, Cd, Pb on the territory of the Pavlodar city (Kazakhstan), which is an industrial hub were designed. The samples of soil were taken from 100 locations. Elemental analysis has been performed using XRF. The obtained data was used for training of the computational model with gradient boosting algorithm. The optimal parameters of model as well as the loss function were selected. The computational model was used for prediction of polluting elements concentration for 1000 evenly distributed points. Based on predicted data geochemical maps were created. Additionally, the total pollution index Zc was calculated for every from 1000 point. The spatial distribution of the Zc index was visualized using GIS (QGIS). It was calculated that the maximum coverage area of the territory of the Pavlodar city belongs to the moderately hazardous category (89.7%). The visualization of the obtained data allowed us to conclude that the main source of contamination goes from the industrial zones where the strategic metallurgical and refining plants are placed.

Keywords: Pavlodar, geochemical map, gradient boosting, CatBoost, QGIS, spatial distribution, heavy metals

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Authors: Eylem Tas

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This empirical study aims to explore the development of students' entrepreneurial skills through problem-based learning within the context of university-industry collaborations (UICs) in curriculum co-design and co-delivery (CDD). The research question guiding this study is: "How do problem-based learning and university-industry collaborations influence the development of students' entrepreneurial skills in the context of curriculum co-design and co-delivery?” To address this question, the study was conducted in a big city in Germany and involved interviews with stakeholders from various industries, including the private sector, government agencies (govt), and non-governmental organizations (NGOs). These stakeholders had established collaborative partnerships with the targeted university for projects encompassing entrepreneurial development aspects in CDD. The study sought to gain insights into the intricacies and subtleties of UIC dynamics and their impact on fostering entrepreneurial skills. Qualitative content analysis, based on Mayring's guidelines, was employed to analyze the interview transcriptions. Through an iterative process of manual coding, 442 codes were generated, resulting in two main sections: "the role of problem-based learning and UIC in fostering entrepreneurship" and "challenges and requirements of problem-based learning within UIC for systematical entrepreneurship development.” The chosen experimental approach of semi-structured interviews was justified by its capacity to provide in-depth perspectives and rich data from stakeholders with firsthand experience in UICs in CDD. By enlisting participants with diverse backgrounds, industries, and company sizes, the study ensured a comprehensive and heterogeneous sample, enhancing the credibility of the findings. The first section of the analysis delved into problem-based learning and entrepreneurial self-confidence to gain a deeper understanding of UIC dynamics from an industry standpoint. It explored factors influencing problem-based learning, alignment of students' learning styles and preferences with the experiential learning approach, specific activities and strategies, and the role of mentorship from industry professionals in fostering entrepreneurial self-confidence. The second section focused on various interactions within UICs, including communication, knowledge exchange, and collaboration. It identified key elements, patterns, and dynamics of interaction, highlighting challenges and limitations. Additionally, the section emphasized success stories and notable outcomes related to UICs' positive impact on students' entrepreneurial journeys. Overall, this research contributes valuable insights into the dynamics of UICs and their role in fostering students' entrepreneurial skills. UICs face challenges in communication and establishing a common language. Transparency, adaptability, and regular communication are vital for successful collaboration. Realistic expectation management and clearly defined frameworks are crucial. Responsible data handling requires data assurance and confidentiality agreements, emphasizing the importance of trust-based relationships when dealing with data sharing and handling issues. The identified key factors and challenges provide a foundation for universities and industrial partners to develop more effective UIC strategies for enhancing students' entrepreneurial capabilities and preparing them for success in today's digital age labor market. The study underscores the significance of collaborative learning and transparent communication in UICs for entrepreneurial development in CDD.

Keywords: collaborative learning, curriculum co-design and co-delivery, entrepreneurial skills, problem-based learning, university-industry collaborations

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Authors: Peter Akayuure, Michael Johnson Nabie

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Similar to many colonized nations in the world, one indelible mark left by colonial masters after Ghana’s independence in 1957 has been the fact that many contexts used to teach statistics and probability concepts are often alien and do not resonate with the social domain of our indigenous Ghanaian child. This has seriously limited the understanding, discoveries, and applications of mathematics for national developments. With the recent curriculum demands of making the Ghanaian child mathematically literate, this qualitative study involved video recordings and mathematical analysis of play sessions of an indigenous girl game called Ampe with the aim to demystify the concepts in probability theorem, which is applied in mathematics related fields of study. The mathematical analysis shows that the game of Ampe, which is widely played by school girls in Ghana, is suitable for learning concepts of the probability theorems. It was also revealed that as a girl game, the use of Ampe provides good lessons to educators, textbook writers, and teachers to rethink about the selection of mathematics tasks and learning contexts that are sensitive to gender. As we undertake to transform teacher education and student learning, the use of indigenous games should be critically revisited.

Keywords: Ampe, mathematical analysis, probability theorem, Ghanaian girl game

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Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

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Authors: Han Chih Feng, Yi-Cheng Hou, Jing-Huei Wu

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Diabetes is a chronic disease. Nutrition knowledge and skills enable individuals with type 2 diabetes to optimize metabolic self-management and quality of life. This research studies the effect of nutritional education on diabetes inpatients in terms of their cognition, behavior, and attitude. The participants are inpatients diagnosed with diabetes at Taipei Tzu Chi Hospital. A total of 103 participants, 58 male, and 45 females, enrolled in the research between January 2018 and July 2018. The research evaluates cognition, behavior, and attitude level before and after nutritional education conducted by dietitians. The result shows significant improvement in actual consumption (2.5 ± 1.4 vs 3.8 ± 0.7; p<.001), diet control motivation (2.7 ± 0.8 vs 3.4 ± 0.6; p<.001), correct nutrition concept (1.2± 0.4 vs 2.4 ± 0.5; p<.001), learning willingness (2.7± 0.9 vs 3.4 ± 0.6; p<.001), cognitive behaviors (1.4 ± 0.5 vs 2.9 ± 0.7; p<.001). AC sugar (278.5 ± 321.5 vs 152.2 ± 49.1; p<.001) and HbA1C (10.3 ± 2.6 vs 8.6 ± 1.9; p<.001) are significant improvement after nutritional education. After nutritional education, participants oral hypoglycemic agents increased from 16 (9.2%) to 33 (19.0%), insulin decreased from 75 (43.1%) to 68 (39.1%), and hypoglycemic drugs combined with insulin decreased from 83 (47.7%) to 73 (42.0%).Further analysis shows that female inpatients have significant improvement in diet control motivation (3.91 ± 0.85 vs 4.44 ± 0.59; p<0.000), correct nutrition concept (3.24± 0.48 vs 4.47± 0.51; p<0.000), learning willingness (3.89 ± 0.86 vs 4.44 ± 0.59; p<0.000) and cognitive behaviors (2.42 ± 0.58 vs 4.02 ± 0.69; p<0.000); male inpatients have significant improvement in actual food intake (4.41± 0.92 vs 3.97 ± 0.42; p<0.000), diet control motivation (3.62 ± 0.86 vs 4.29 ± 0.62; p<0.000), correct nutrition concept (3.26 ± 0.44 vs 4.36 ± 0.49; p<0.000), learning willingness (3.72± 0.93 vs 4.33± 0.63; p<0.000) and cognitive behaviors (2.45± 0.54 vs 4.03± 0.77; p<0.000). In conclusion, nutritional education proves effective, regardless of gender, in improving an inpatient’s cognition, behavior, and attitude toward diabetes self-management.

Keywords: diabetes, nutrition education, actual consumption, diet control motivation, nutrition concept, learning willingness, cognitive behaviors

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Authors: Parvin Goli, Amirhosein Kefayat, Rezvan Goli

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Background: It is well established that parents can influence their offspring's neurodevelopment. It is shown that paternal environment and lifestyle is beneficial for the progeny's fitness and might affect their metabolic mechanisms; however, the effects of paternal exercise on the brain in the offspring have not been explored in detail. Objective: This study aims to review the impact of paternal physical exercise on memory and learning, neuroplasticity, as well as DNA methylation levels in the off-spring's hippocampus. Study design: In this systematic review and meta-analysis, an electronic literature search was conducted in databases including PubMed, Scopus, and Web of Science. Eligible studies were those with an experimental design, including an exercise intervention arm, with the assessment of any type of memory function, learning ability, or any type of brain plasticity as the outcome measures. Standardized mean difference (SMD) and 95% confidence intervals (CI) were computed as effect size. Results: The systematic review revealed the important role of environmental enrichment in the behavioral development of the next generation. Also, offspring of exercised fathers displayed higher levels of memory ability and lower level of brain-derived neurotrophic factor. A significant effect of paternal exercise on the hippocampal volume was also reported in the few available studies. Conclusion: These results suggest an intergenerational effect of paternal physical activity on cognitive benefit, which may be associated with hippocampal epigenetic programming in offspring. However, the biological mechanisms of this modulation remain to be determined.

Keywords: hippocampal plasticity, learning ability, memory, parental exercise

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Authors: Swapna Bhargavi Gantasala

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If teamwork is the key to organizational learning, productivity, and growth, then, why do some teams succeed in achieving these, while others falter at different stages? Building teams in higher education institutions has been a challenge and an open-ended constructivist approach was considered on an experimental basis for this study to address this challenge. For this research, teams of students from the MBA program were chosen to study the effect of teamwork in learning, the motivation levels among student team members, and the effect of collaboration in achieving team goals. The teams were built on shared vision and goals, cohesion was ensured, positive induction in the form of faculty mentoring was provided for each participating team and the results have been presented with conclusions and suggestions.

Keywords: teamwork, leadership, motivation and reinforcement, collaboration

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Authors: Y. Salfati, D. Sharef Bussel, J. Zamir

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In this paper, we present an Evaluation Case Study implementing the eight principles of Collaborative Approaches to Evaluation (CAE) as designed by Brad Cousins in the past decade. The focus of this paper is sharing a rich experience in which we achieved two main goals. The first was the development of a valuable and meaningful new teacher training program, and the second was a successful implementation of the CAE principles. The innovative teacher training program is based on the idea of including physical movement during the process of teaching and learning academic themes. The program is called Learning through Movement. This program is a response to a call from the Ministry of Education, claiming that today children sit in front of screens and do not exercise any physical activity. In order to contribute to children’s health, physical, and cognitive development, the Ministry of Education promotes learning through physical activities. Research supports the idea that sports and physical exercise improve academic achievements. The Learning through Movement program is operated by Kaye Academic College. Students in the Elementary School Training Program, together with students in the Physical Education Training Program, implement the program in collaboration with two mentors from the College. The program combines academic learning with physical activity. The evaluation began at the beginning of the program. During the evaluation process, data was collected by means of qualitative tools, including interviews with mentors, observations during the students’ collaborative planning, class observations at school and focus groups with students, as well as the collection of documentation related to the teamwork and to the program itself. The data was analyzed using content analysis and triangulation. The preliminary results show outcomes relating to the Teacher Training Programs, the student teachers, the pupils in class, the role of Physical Education teachers, and the evaluation. The Teacher Training Programs developed a collaborative approach to lesson planning. The students' teachers demonstrated a change in their basic attitudes towards the idea of integrating physical activities during the lessons. The pupils indicated higher motivation through full participation in classes. These three outcomes are indicators of the success of the program. An additional significant outcome of the program relates to the status and role of the physical education teachers, changing their role from marginal to central in the school. Concerning evaluation, a deep sense of trust and confidence was achieved, between the evaluator and the whole team. The paper includes the perspectives and challenges of the heads and mentors of the two programs as well as the evaluator’s conclusions. The evaluation unveils challenges in conducting a CAE evaluation in such a complex setting.

Keywords: collaborative evaluation, training teachers, learning through movement

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Authors: Victor Arokia Doss, Kuberapandian Dharaniyambigai, K. Julia Rose Mary

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Advanced Glycation End (AGE) products are the end products due to the reaction between excess reducing sugar present in diabetes and free amino group in protein lipids and nucleic acids. Thus, non-enzymic glycation of molecules such as hemoglobin, collagen, and other structurally and functionally important proteins add to the pathogenic complications such as diabetic retinopathy, neuropathy, nephropathy, vascular changes, atherosclerosis, Alzheimer's disease, rheumatoid arthritis, and chronic heart failure. The most common non-cross linking AGE, carboxymethyl lysine (CML) is formed by the oxidative breakdown of fructosyllysine, which is a product of glucose and lysine. CML is formed in a wide variety of tissues and is an index to assess the extent of glycoxidative damage. Thus we have constructed a mathematical and computational model that predicts the effect of temperature differences in vivo, on the formation of CML, which is now being considered as an important intracellular milieu. This hybrid model that had been tested for its parameter fitting and its sensitivity with available experimental data paves the way for designing novel laboratory experiments that would throw more light on the pathological formation of AGE adducts and in the pathophysiology of diabetic complications.

Keywords: advanced glycation end-products, CML, mathematical model, computational model

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Geoffrey A. Wright

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In an attempt to address shortcomings revealed in international assessments and lamented in legislation, many schools are reducing or eliminating elective courses, applying the rationale that replacing "non-essential" subjects with core subjects, such as mathematics and language arts, will better position students in the global market. However, there is evidence that systematically pairing a core subject with another complementary subject may lead to greater overall learning in both subjects. In this paper, we outline the methods and preliminary findings from a study we conducted analyzing the influence learning programming has on student mathematical comprehension and ability. The purpose of this research is to demonstrate in what ways two subjects might complement each other, and to better understand the principles and conditions that encourage what we call lateral transfer, the synergistic effect that occurs when a learner studies two complementary subjects.

Keywords: programming, engineering, technology, complementary subjects

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Authors: Theo Ndereyimana, Yann Dufresne, Micael Boulet, Stephane Moreau

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The DEM (Discrete Element Method) is used a lot in the industry to simulate large-scale flows of particles; for instance, in a fluidized bed, it allows to predict of the trajectory of every particle. One of the main limits of the DEM is the computational time. The CGM (Coarse-Graining Method) has been developed to tackle this issue. The goal is to increase the size of the particle and, by this means, decrease the number of particles. The method leads to a reduction of the collision frequency due to the reduction of the number of particles. Multiple characteristics of the particle movement and the fluid flow - when there is a coupling between DEM and CFD (Computational Fluid Dynamics). The main characteristic that is impacted is the energy dissipation of the system, to regain the dissipation, an ADM (Additional Dissipative Mechanism) can be added to the model. The objective of this current work is to observe the influence of the choice of the ADM and the factor of coarse-graining on the numerical results. These results will be compared with experimental results of a fluidized bed and with a numerical model of the same fluidized bed without using the CGM. The numerical model is one of a 3D cylindrical fluidized bed with 9.6M Geldart B-type particles in a bubbling regime.

Keywords: additive dissipative mechanism, coarse-graining, discrete element method, fluidized bed

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Authors: Diego De Castro Rodrigues, Marcelo B. Nery, Sergio Adorno

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The project aims to develop a framework for social data analysis, particularly by mobilizing criminal records and applying descriptive computational techniques, such as associative algorithms and extraction of tree decision rules, among others. The methods and instruments discussed in this work will enable the discovery of patterns, providing a guided means to identify similarities between recurring situations in the social sphere using descriptive techniques and data visualization. The study area has been defined as the city of São Paulo, with the structuring of social data as the central idea, with a particular focus on the quality of the information. Given this, a set of tools will be validated, including the use of a database and tools for visualizing the results. Among the main deliverables related to products and the development of articles are the discoveries made during the research phase. The effectiveness and utility of the results will depend on studies involving real data, validated both by domain experts and by identifying and comparing the patterns found in this study with other phenomena described in the literature. The intention is to contribute to evidence-based understanding and decision-making in the social field.

Keywords: social data analysis, criminal records, computational techniques, data mining, big data

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Authors: Xiaohua Zou, Yongxin Su

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The reasonable operation of heating, ventilation, and air conditioning (HVAC) is of great significance in improving the security, stability, and economy of power system operation. However, the uncertainty of the operating environment, thermal comfort varies by users and rapid decision-making pose challenges for HVAC demand response optimization. In this regard, this paper proposes a reinforcement learning-based method for HVAC demand response optimization considering few-shot personalized thermal comfort (PTC). First, an HVAC DR optimization framework based on few-shot PTC model and DRL is designed, in which the output of few-shot PTC model is regarded as the input of DRL. Then, a few-shot PTC model that distinguishes between awake and asleep states is established, which has excellent engineering usability. Next, based on soft actor criticism, an HVAC DR optimization algorithm considering the user’s PTC is designed to deal with uncertainty and make decisions rapidly. Experiment results show that the proposed method can efficiently obtain use’s PTC temperature, reduce energy cost while ensuring user’s PTC, and achieve rapid decision-making under uncertainty.

Keywords: HVAC, few-shot personalized thermal comfort, deep reinforcement learning, demand response

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Authors: Mei-Chun. Chang

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STEAM (Science, Technology, Engineering, Art, and Mathematics) represents a cross-disciplinary and learner-centered teaching model that cultivates students to link theory with the presentation of real situations, thereby improving their various abilities. This study explores students' learning performance after using the 6E model in STEAM teaching for a professional course in the digital media design department of technical colleges, as well as the difficulties and countermeasures faced by STEAM curriculum design and its implementation. In this study, through industry experts’ work experience, activity exchanges, course teaching, and experience, learners can think about the design and development value of virtual idol products that meet the needs of users and to employ AR/VR technology to innovate their product applications. Applying action research, the investigation has 35 junior students from the department of digital media design of the school where the researcher teaches as the research subjects. The teaching research was conducted over two stages spanning ten weeks and 30 sessions. This research collected the data and conducted quantitative and qualitative data sorting analyses through ‘design draft sheet’, ‘student interview record’, ‘STEAM Product Semantic Scale’, and ‘Creative Product Semantic Scale (CPSS)’. Research conclusions are presented, and relevant suggestions are proposed as a reference for teachers or follow-up researchers. The contribution of this study is to teach college students to develop original virtual idols and product designs, improve learning effectiveness through STEAM teaching activities, and effectively cultivate innovative and practical cross-disciplinary design talents.

Keywords: STEAM, 6E model, virtual idol, learning effectiveness, practical courses

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Authors: Richa Raje, Anumol Antony

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Playing is the foremost stepping stone for childhood development. Play is an essential aspect of a child’s development and learning because it creates meaningful enduring environmental connections and increases children’s performance. The children’s proficiencies are ever varying in their course of growth. There is innovation in the activities, as it kindles the senses, surges the love for exploration, overcomes linguistic barriers and physiological development, which in turn allows them to find their own caliber, spontaneity, curiosity, cognitive skills, and creativity while learning during play. This paper aims to comprehend the learning in play which is the most essential underpinning aspect of the outdoor play area. It also assesses the trend of playgrounds design that is merely hammered with equipment's. It attempts to derive a relation between the natural environment and children’s activities and the emotions/senses that can be evoked in the process. One of the major concerns with our outdoor play is that it is limited to an area with a similar kind of equipment, thus making the play highly regimented and monotonous. This problem is often lead by the strict timetables of our education system that hardly accommodates play. Due to these reasons, the play areas remain neglected both in terms of design that allows learning and wellbeing. Poorly designed spaces fail to inspire the physical, emotional, social and psychological development of the young ones. Currently, the play space has been condensed to an enclosed playground, driveway or backyard which confines the children’s capability to leap the boundaries set for him. The paper emphasizes on study related to kids ranging from 5 to 11 years where the behaviors during their interactions in a playground are mapped and analyzed. The theory of affordance is applied to various outdoor play areas, in order to study and understand the children’s environment and how variedly they perceive and use them. A higher degree of affordance shall form the basis for designing the activities suitable in play spaces. It was observed during their play that, they choose certain spaces of interest majority being natural over other artificial equipment. The activities like rolling on the ground, jumping from a height, molding earth, hiding behind tree, etc. suggest that despite equipment they have an affinity towards nature. Therefore, we as designers need to take a cue from their behavior and practices to be able to design meaningful spaces for them, so the child gets the freedom to test their precincts.

Keywords: children, landscape design, learning environment, nature and play, outdoor play

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Authors: Ann P. Daunic, Nancy Corbett

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Background and Significance: Researchers emphasize the role that motivation, self-esteem, and self-regulation play in children’s early adjustment to the school culture, including skills such as identifying their own feelings and understanding the feelings of others. As social-emotional growth, academic learning, and successful integration within culture and society are inextricably connected, the Social-Emotional Learning Foundations (SELF) curriculum was designed to integrate social-emotional learning (SEL) instruction within early literacy instruction (specifically, reading) for Kindergarten and first-grade students at risk for emotional and behavioral difficulties. Storybook reading is a typically occurring activity in the primary grades; thus SELF provides an intervention that is both theoretically and practically sound. Methodology: The researchers will report on findings from the first two years of a three-year study funded by the US Department of Education’s Institute of Education Sciences to evaluate the effects of the SELF curriculum versus “business as usual” (BAU). SELF promotes the development of self-regulation by incorporating instructional strategies that support children’s use of SEL related vocabulary, self-talk, and critical thinking. The curriculum consists of a carefully coordinated set of materials and pedagogy designed specifically for primary grade children at early risk for emotional and behavioral difficulties. SELF lessons (approximately 50 at each grade level) are organized around 17 SEL topics within five critical competencies. SELF combines whole-group (the first in each topic) and small-group lessons (the 2nd and 3rd in each topic) to maximize opportunities for teacher modeling and language interactions. The researchers hypothesize that SELF offers a feasible and substantial opportunity within the classroom setting to provide a small-group social-emotional learning intervention integrated with K-1 literacy-related instruction. Participating target students (N = 876) were identified by their teachers as potentially at risk for emotional or behavioral issues. These students were selected from 122 Kindergarten and 100 first grade classrooms across diverse school districts in a southern state in the US. To measure the effectiveness of the SELF intervention, the researchers asked teachers to complete assessments related to social-emotional learning and adjustment to the school culture. A social-emotional learning related vocabulary assessment was administered directly to target students receiving small-group instruction. Data were analyzed using a 3-level MANOVA model with full information maximum likelihood to estimate coefficients and test hypotheses. Major Findings: SELF had significant positive effects on vocabulary, knowledge, and skills associated with social-emotional competencies, as evidenced by results from the measures administered. Effect sizes ranged from 0.41 for group (SELF vs. BAU) differences in vocabulary development to 0.68 for group differences in SEL related knowledge. Conclusion: Findings from two years of data collection indicate that SELF improved outcomes related to social-emotional learning and adjustment to the school culture. This study thus supports the integration of SEL with literacy instruction as a feasible and effective strategy to improve outcomes for K-1 students at risk for emotional and behavioral difficulties.

Keywords: Socio-cultural context for learning, social-emotional learning, social skills, vocabulary development

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Authors: Ahmed Krobba, Meriem Touzene, Mohamed Debeyche

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The wireless communications system (5G) will provide more diverse applications and higher quality services for users compared to the long-term evolution 4G (LTE). 5G uses a higher carrier frequency, which suffers from information loss in 5G coverage. Most 5G users often cannot obtain high-quality communications due to transmission channel noise and channel complexity. Physical Uplink Control Channel (PUCCH-NR: Physical Uplink Control Channel New Radio) plays a crucial role in 5G NR telecommunication technology, which is mainly used to transmit link control information uplink (UCI: Uplink Control Information. This study based of evaluating the performance of channel physical uplink control PUCCH-NR under low Signal-to-Noise Ratios with various antenna numbers reception. We propose the artificial intelligence approach based on deep neural networks (Deep Learning) to estimate the PUCCH-NR channel in comparison with this approach with different conventional methods such as least-square (LS) and minimum-mean-square-error (MMSE). To evaluate the channel performance we use the block error rate (BLER) as an evaluation criterion of the communication system. The results show that the deep neural networks method gives best performance compared with MMSE and LS

Keywords: 5G network, uplink (Uplink), PUCCH channel, NR-PUCCH channel, deep learning

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Authors: Ida Zubaidah

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With the advancement of information and communication technologies, in many cases, geographical distance is no longer considered as a main barrier in distance education. Geographical distance, even from a continent to another, between students and their instructor or students and their campus can be connected by the Internet, telephone or any other means of communication technology. Managing distance learning in an archipelagic country like Indonesia, however, has some different stories. Comprising more than 17,000 islands and 6.000 of them inhabited, Indonesia is considered as one of the most archipelagic countries in the world. In some areas or islands that have adequate public transportation and communication facilities the courses can be delivered quite well. In other areas that geographically very remote and dispersed islander, Universitas Terbuka, an open university in Indonesia, has to have very different strategies in overcoming the specific and even emergency situations in learning delivery. This ongoing research paper aims to share experiences of how Universitas Terbuka makes serious and unique efforts in overcoming the barriers and obstacles in providing educational service in part of difficult areas, especially in eastern areas of Indonesia. The data collection methods are observation of sample areas and in-depth interview with the head of regional offices of Universitas Terbuka in eastern Indonesia, staff, and tutors. Conducting educational deliveries in in difficult areas with no regular and adequate transportation has made the regional office have specific strategies in making the learning process run as smooth as possible. Sending a tutor to an area to meet some students and conducting a series of tutorial, which are supposed to be weekly, in several days is one of the strategies. Recruiting local people to manage the students in the area is another strategy. The absence of regular transportation from island to island, high tides, hurricanes, are among the obstacles faced by the regional offices in doing their job. Non geographical barriers such as unavailability of qualified tutor, inadequate tutor payment, are problems as well. The learning process, however, has to be done in any way, otherwise the distance education mission to reach unreachable cannot be achieved.

Keywords: distance education, Terbuka University, difficult area, geographical barrier, learning services

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Authors: Xiaoyan Dai, Hsieh Yisan

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Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

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Authors: James Q. Feng

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Pneumatic nebulizers (as variations based on the Collison nebulizer) have been widely used for producing fine aerosol droplets from a liquid material. As qualitatively described by many authors, the basic working principle of those nebulizers involves utilization of the negative pressure associated with an expanding gas jet to syphon liquid into the jet stream, then to blow and shear into liquid sheets, filaments, and eventually droplets. But detailed quantitative analysis based on fluid mechanics theory has been lacking in the literature. The purpose of present work is to investigate the nature of negative pressure distribution associated with compressible gas jet flow in the Collison nebulizer by a computational fluid dynamics (CFD) analysis, using an OpenFOAM® compressible flow solver. The value of the negative pressure associated with a gas jet flow is examined by varying geometric parameters of the jet expansion channel adjacent to the jet orifice outlet. Such an analysis can provide valuable insights into fundamental mechanisms in liquid aspiration process, helpful for effective design of the pneumatic atomizer in the Aerosol Jet® direct-write system for micro-feature, high-aspect-ratio material deposition in additive manufacturing.

Keywords: collison nebulizer, compressible gas jet flow, liquid aspiration, pneumatic atomization

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Authors: Sarra Haouala, Issam Doghri

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In this work, a multiscale computational strategy is proposed for the analysis of structures, which are described at a refined level both in space and in time. The proposal is applied to two-phase viscoelastic-viscoplastic (VE-VP) reinforced thermoplastics subjected to large numbers of cycles. The main aim is to predict the effective long time response while reducing the computational cost considerably. The proposed computational framework is a combination of the mean-field space homogenization based on the generalized incrementally affine formulation for VE-VP composites, and the asymptotic time homogenization approach for coupled isotropic VE-VP homogeneous solids under large numbers of cycles. The time homogenization method is based on the definition of micro and macro-chronological time scales, and on asymptotic expansions of the unknown variables. First, the original anisotropic VE-VP initial-boundary value problem of the composite material is decomposed into coupled micro-chronological (fast time scale) and macro-chronological (slow time-scale) problems. The former is purely VE, and solved once for each macro time step, whereas the latter problem is nonlinear and solved iteratively using fully implicit time integration. Second, mean-field space homogenization is used for both micro and macro-chronological problems to determine the micro and macro-chronological effective behavior of the composite material. The response of the matrix material is VE-VP with J2 flow theory assuming small strains. The formulation exploits the return-mapping algorithm for the J2 model, with its two steps: viscoelastic predictor and plastic corrections. The proposal is implemented for an extended Mori-Tanaka scheme, and verified against finite element simulations of representative volume elements, for a number of polymer composite materials subjected to large numbers of cycles.

Keywords: asymptotic expansions, cyclic loadings, inclusion-reinforced thermoplastics, mean-field homogenization, time homogenization

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Authors: Sajed A. Habib

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Problem-based learning (PBL) is a student-centered pedagogy that originated in the medical field and has also been used extensively in other knowledge disciplines with recognized advantages and limitations. PBL has been used in various undergraduate engineering programs with mixed outcomes. The current fourth industrial revolution (digital era or Industry 4.0) has made it essential for many science and engineering students to receive effective training in advanced courses such as industrial automation and robotics. This paper presents a case study at Assumption University of Thailand, where a PBL-like approach was used to teach some aspects of automation and robotics to selected groups of undergraduate engineering students. These students were given some basic level training in automation prior to participating in a subsequent training session in order to solve technical problems with increased complexity. The participating students’ evaluation of the training sessions in terms of learning effectiveness, skills enhancement, and incremental knowledge following the problem-solving session was captured through a follow-up survey consisting of 14 questions and a 5-point scoring system. From the most recent training event, an overall 70% of the respondents indicated that their skill levels were enhanced to a much greater level than they had had before the training, whereas 60.4% of the respondents from the same event indicated that their incremental knowledge following the session was much greater than what they had prior to the training. The instructor-facilitator involved in the training events suggested that this method of learning was more suitable for senior/advanced level students than those at the freshmen level as certain skills to effectively participate in such problem-solving sessions are acquired over a period of time, and not instantly.

Keywords: automation, industry 4.0, model-based design training, problem-based learning

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Authors: Mitra Mesgar

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Online learning environment is becoming more popular among learners because of their multiple information representations. Despite the growing importance of online reading strategies among adult learners, little attention has been carried out to postgraduate EFL learners. This study is quantitative research designed and aimed to investigate metacognitive reading strategies employed by Iranian postgraduate learners to read online academic texts. This study is conducted by over 50 Iranian postgraduate students studying in different Malaysian universities. This study used two different survey questionnaires, namely, 1) background questionnaire and 2) OSORS questionnaire. The collected data were analyzed using SPSS. The findings of the study emphasized metacognitive reading strategies used by different aged adult learners. The results of the survey questionnaires revealed that adult learners use global reading strategies as well as problem-solving strategies and support reading strategies. Also, through one-way analysis of variance toward age factor revealed that it has no meaningful changes on metacognitive reading strategy usage. This means that metacognitive reading strategies used by adult learners are independent of age variable. Drawing from findings, adult learners have learning goals, and since they have more exposure to online academic texts, they are able to use different metacognitive online reading strategies that affect their understanding of academic texts.

Keywords: online reading strategies, metacognitive strategies, online learning, independent students, locus of control

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Authors: Rajendra Roul

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The main objective of the project is to bring attention towards the performance of an aerofoil when exposed to the fluid medium inside the wind tunnel. This project aims at involvement of civil as well as mechanical engineering thereby making itself as a multidisciplinary project. The airfoil of desired size is taken into consideration for the project to carry out effectively. An aerofoil is the shape of the wing or blade of propeller, rotor or turbine. Lot of experiment have been carried out through wind-tunnel keeping aerofoil as a reference object to make a future forecast regarding the design of turbine blade, car and aircraft. Lift and drag now become the major identification factor for any design industry which shows that wind tunnel testing along with software analysis (ANSYS) becomes the mandatory task for any researchers to forecast an aerodynamics design. This project is an initiative towards the mitigation of drag, better lift and analysis of wake surface profile by investigating the surface pressure distribution. The readings has been taken on airfoil model in Wind Tunnel Testing Machine (WTTM) at different air velocity 20m/sec, 25m/sec, 30m/sec and different angle of attack 00,50,100,150,200. Air velocity and pressures are measured in several ways in wind tunnel testing machine by use to measuring instruments like Anemometer and Multi tube manometer. Moreover to make the analysis more accurate Ansys fluent contribution become substantial and subsequently the CFD simulation results. Analysis on an Aerofoil have a wide spectrum of application other than aerodynamics including wind loads in the design of buildings and bridges for structural engineers.

Keywords: wind-tunnel, aerofoil, Ansys, multitube manometer

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Authors: Sobhy Fathy A. Hashesh

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This study aimed at investigating the effect of Andalus Knowledge Phases and Times (ANPT) model of learning and the effect of 'Intel Education Contribution in ANPT' on the development of students’ academic performance and emotional quotient. The society of the study composed of Andalus Private Schools, elementary school students (N=700), while the sample of the study composed of four randomly assigned groups (N=80) with one experimental group and one control group to study "ANPT" effect and the "Intel Contribution in ANPT" effect respectively. The study followed the quantitative and qualitative approaches in collecting and analyzing data to answer the study questions. Results of the study revealed that there were significant statistical differences between students’ academic performances and emotional quotients for the favor of the experimental groups. The study recommended applying this model on different educational variables and on other age groups to generate more data leading to more educational results for the favor of students’ learning outcomes.

Keywords: Al Andalus, emotional quotient, students, academic performance development

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Authors: Rosy Makeresemese Qhosola

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South Africa has maintained the effort to uphold its guiding principles in terms of its constitution. The constitution upholds principles such as equity, social justice, peace, freedom and hope, to mention but a few. So, such principles are made to form the basis for any legislation and policies that are in place to guide all fields/departments of government. Education is one of those departments or fields and is expected to abide by such principles as outlined in their policies. Therefore, as expected education policies and legislation outline their intentions to ensure the development of students’ clear critical thinking capacity as well as their creative capacities by creating learning contexts and opportunities that accommodate the effective teaching and learning strategies, that are learner centered and are compatible with the prescripts of a democratic constitution of the country. The paper aims at exploring and analyzing the progress of conventional accounting in terms of its adherence to the effective use of principles of good teaching, as per policy expectations in South Africa. The progress is traced by comparing conventional accounting to Critical Accounting Research (CAR), where the history of accounting as intended in the curriculum of SA and CAR are highlighted. Critical Accounting Research framework is used as a lens and mode of teaching in this paper, since it can create a space for the learning of accounting that is optimal marked by the use of more learner-centred methods of teaching. The Curriculum of South Africa also emphasises the use of more learner-centred methods of teaching that encourage an active and critical approach to learning, rather than rote and uncritical learning of given truths. The study seeks to maintain that conventional accounting is in contrast with principles of good teaching as per South African policy expectations. The paper further maintains that, the possible move beyond it and the adherence to the effective use of good teaching, could be when CAR forms the basis of teaching. Data is generated through Participatory Action Research where the meetings, dialogues and discussions with the focused groups are conducted, which consists of lecturers, students, subject heads, coordinators and NGO’s as well as departmental officials. The results are analysed through Critical Discourse Analysis since it allows for the use of text by participants. The study concludes that any teacher who aspires to achieve in the teaching and learning of accounting should first meet the minimum requirements as stated in the NQF level 4, which forms the basic principles of good teaching and are in line with Critical Accounting Research.

Keywords: critical accounting research, critical discourse analysis, participatory action research, principles of good teaching

Procedia PDF Downloads 289

Authors: M. A. Riurean, S. Heijnen, C. A. Knott, J. Makinde, D. Gotti, J. VD. Kamp

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Objectives: The current study is done in preparation for a randomized controlled study investigating the effects of an implicit motor learning protocol implemented using an extension-supporting glove. It will explore different protocols to find out which is preferred when studying motor learn-ing in the chronic stroke population that struggles with hand spasticity. Design: This exploratory study will follow 24 individuals who have a chronic stroke (> 6 months) during their usual care journey. We will record the results of two 9-Hole Peg Tests (9HPT) done during their therapy ses-sions with a physiotherapist or in their home before and after 4 weeks of them wearing an exten-sion-supporting glove used to employ the to-be-studied protocols. The participants will wear the glove 3 times/week for one hour while performing their activities of daily living and record the times they wore it in a diary. Their experience will be monitored through telecommunication once every week. Subjects: Individuals that have had a stroke at least 6 months prior to participation, hand spasticity measured on the modified Ashworth Scale of maximum 3, and finger flexion motor control measured on the Motricity Index of at least 19/33. Exclusion criteria: extreme hemi-neglect. Methods: The participants will be randomly divided into 3 groups: one group using the glove in a pre-set way of decreasing support (implicit motor learning), one group using the glove in a self-controlled way of decreasing support (autonomous motor learning), and the third using the glove with constant support (as control). Before and after the 4-week period, there will be an intake session and a post-assessment session. Analysis: We will compare the results of the two 9HPTs to check whether the protocols were effective. Furthermore, we will compare the results between the three groups to find the preferred one. A qualitative analysis will be run of the experience of participants throughout the 4-week period. Expected results: We expect that the group using the implicit learning protocol will show superior results.

Keywords: implicit learning, hand spasticity, stroke, error minimization, motor task

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Authors: Tolga Aydin, M. Fatih Alaeddinoğlu

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People, throughout the history, have made estimates and inferences about the future by using their past experiences. Developing information technologies and the improvements in the database management systems make it possible to extract useful information from knowledge in hand for the strategic decisions. Therefore, different methods have been developed. Data mining by association rules learning is one of such methods. Apriori algorithm, one of the well-known association rules learning algorithms, is not commonly used in spatio-temporal data sets. However, it is possible to embed time and space features into the data sets and make Apriori algorithm a suitable data mining technique for learning spatio-temporal association rules. Lake Van, the largest lake of Turkey, is a closed basin. This feature causes the volume of the lake to increase or decrease as a result of change in water amount it holds. In this study, evaporation, humidity, lake altitude, amount of rainfall and temperature parameters recorded in Lake Van region throughout the years are used by the Apriori algorithm and a spatio-temporal data mining application is developed to identify overflows and newly-formed soil regions (underflows) occurring in the coastal parts of Lake Van. Identifying possible reasons of overflows and underflows may be used to alert the experts to take precautions and make the necessary investments.

Keywords: apriori algorithm, association rules, data mining, spatio-temporal data

Procedia PDF Downloads 358

Authors: Lorena Alemán de la Garza, Marcela Georgina Gómez-Zermeño

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This paper presents the SolarSPELL case study that aims to generate information on the use of indicators that help evaluate the pedagogical quality of a digital library resources. SolarSPELL is a solar-powered digital library with WiFi connectivity. It offers a variety of open educational resources selected for their potential for the digital transformation of educational practices and the achievement of the 2030 Agenda for Sustainable Development, adopted by all United Nations Member States. The case study employed a quantitative methodology and the research instrument was applied to 55 teachers, directors and librarians. The results indicate that it is possible to strengthen the pedagogical quality of open educational resources, through actions focused on improving temporal and technological parameters. They also reveal that users believe that SolarSPELL improves the teaching-learning processes and motivates the teacher to improve his or her development. This study provides valuable information on a tool that supports teaching-learning processes and facilitates connectivity with renewable energies that improves the teacher training in active methodologies for ecosystem learning.

Keywords: educational innovation, digital library, pedagogical quality, solar energy, teacher training, sustainable development

Procedia PDF Downloads 109