Search results for: learning management systems

Authors: Vandana N. Purav

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The Dynamical systems concept is a mathematical formalization for any fixed rule that describes the time dependence of a points position in its ambient space. e.g. pendulum of a clock, the number of fish each spring in a lake, the number of rabbits spring in an enclosure, etc. The Dynamical system theory used to describe the complex nature that is dynamical systems with differential equations called continuous dynamical system or dynamical system with difference equations called discrete dynamical system. The concept of dynamical system has its origin in Newtonian mechanics.

Keywords: dynamical systems, Fibonacci numbers, Newtonian mechanics, discrete dynamical system

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Authors: Michael Oppong, Stephanie Owusu Ansah, Daniel Ofori

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The study investigated students’ post-covid-19 experiences with e-learning platforms among undergraduate students of public universities in the Ashanti region of Ghana. The study respectively drew 289 respondents from two public universities, i.e., Kwame Nkrumah University of Science and Technology (KNUST) Business School and the Kumasi Technical University (KsTU) Business School in Ghana. Given that the population from the two public universities was fairly high, sampling had to be done. The overall population of the study was 480 students randomly sampled from the two public universities using the sampling ratio given by Alreck and Settle (2004). The population constituted 360 students from the Kwame Nkrumah University of Science and Technology (KNUST) Business School and 120 from the Kumasi Technical University Business School (KsTU). The study employed questionnaires as a data collection tool. The data gathered were 289 responses out of 480 questionnaires administered, representing 60.2%. The data was analyzed using pie charts, bar charts, percentages, and line graphs. Findings revealed that the e-learning platforms were still useful. However, the students used it on a weekly basis post-COVID-19, unlike in the COVID-19 era, where it was used daily. All other academic activities, with the exception of examinations, are still undertaken on the e-learning platforms; however, it is underutilized in the post-COVID-19 experience. The study recommends that universities should invest in infrastructure development to enable all academic activities, most especially examinations, to be undertaken using the e-learning platforms to curtail future challenges.

Keywords: e-learning platform, undergraduate students, post-COVID-19 experience, public universities

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Authors: Peaceman Sopazi, Mabila Mathebula, John Smallwood

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Recent health and safety (H&S) concerns and their resultant impact on railway operations, namely, the severe acute respiratory syndrome (SARS) or collectively known as SARS-CoV-2 (Covid-19) pandemic and the Fourth Industrial Revolution (4IR), which have dominated public discourse, brought into question as to whether, or not, some aspects of how we have so far managed safety oversight as railway regulatory bodies and operators will remain relevant in a changing railway environment. Railway practitioners have generally found themselves between a proverbial rock and a hard place by being confronted by emerging challenges which have brought along great opportunities for sustainability. As witnesses and participants to the progressively introduced railway safety management, and transformation regimes, this paper attempts to share gathered field experience on adaptable regulatory oversight and safety awareness. The discourse is approached from a South African context but also with an informed perspective of what seems to work and what usually does not. The authors share their own multi and transdisciplinary experience coupled with insights they have gained as researchers of global trends in general safety management and specific aspects of railway safety management, for sustainability. In addition to sharing a largely experience-based methodology for survival, suggestions are offered for consideration as a way of keeping the railway safety management discourse alive as practitioners navigate a new path which is shrouded in a cloud of untold uncertainty. The authors further believe that the right timing for the implementation of the proposed suggestions in this paper will produce beneficial outcomes. Finally, the paper will identify areas that are still open for further investigation for and by researchers and practitioners alike.

Keywords: health & safety management, safety awareness, railway safety management, railway systems sustainability

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Authors: Anshu Radha Aggarwal

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As per the Right to Education Act (RTE), 2009, every child in the age group of 6-14 years shall be admitted in a neighborhood school. All the Out of School Children identified have to be enrolled / mainstreamed in to age appropriate class and there-after be provided special training. This paper addresses issues emerging from provisions in the RTE Act that specifically refer to the enrolment of out-of school children into age appropriate classes and the requirement to provide special trainings that will enable this to take place. In the context of RTE Act, the Out-of-School Children are first enrolled in the formal school and then they are provided with Special Training through NRSTCs (Long Term / Short term basis). These centers are functioning in formal school campus itself. This paper specifies the role of special training centers (STC). It presents a re-envisioning of assessment that recognizes two principal functions of assessment, assessment for learning and assessment of learning, instead of the more familiar categories of formative, diagnostic, summative, and evaluative assessment. The use of these two functions of assessment highlights and emphasizes the role of special training centers (STC) to assess their level for giving them appropriate special training and to evaluate their improvement in learning level. Challenge of problem faced by teachers to do diagnostic assessment, including its place in the sequence of assessment procedures appropriate in identifying and addressing individual children’s learning difficulties are solved by special training centers (STC). It is important that assessment is used to identify children with learning difficulties at the earliest possible stage so that appropriate support and intervention can be put in place. So appropriate challenges with tools are presented here for their assessment at entry level and at completion level of primary children by special training centers (STC).

Keywords: right to education, assessment, challenges, out of school children

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Authors: Sanjivrao Katakam, Thanumoorthi I., Antony Gerald, Ratan Kulkarni, Shaju Nair

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With increasing energy costs and its impact on the business, sustainability today has evolved from a social expectation to an economic imperative. Therefore, finding methods to reduce cost has become a critical directive for Industry leaders. Effective energy management is the only way to cut costs. However, Energy Management has been a challenge because it requires a change in old habits and legacy systems followed for decades. Today exorbitant levels of energy and operational data is being captured and stored by Industries, but they are unable to convert these structured and unstructured data sets into meaningful business intelligence. It must be noted that for quick decisions, organizations must learn to cope with large volumes of operational data in different formats. Energy analytics not only helps in extracting inferences from these data sets, but also is instrumental in transformation from old approaches of energy management to new. This in turn assists in effective decision making for implementation. It is the requirement of organizations to have an established corporate strategy for reducing operational costs through visibility and optimization of energy usage. Energy analytics play a key role in optimization of operations. The paper describes how today energy data analytics is extensively used in different scenarios like reducing operational costs, predicting energy demands, optimizing network efficiency, asset maintenance, improving customer insights and device data insights. The paper also highlights how analytics helps transform insights obtained from energy data into sustainable solutions. The paper utilizes data from an array of segments such as retail, transportation, and water sectors.

Keywords: energy analytics, energy management, operational data, business intelligence, optimization

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Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi

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This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.

Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control

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Authors: M. M. Essa, S. Subash, M. Akbar, S. Al-Adawi, A. Al-Asmi, G. J. Guillemein

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Transgenic (tg) mice which contain an amyloid precursor protein (APP) gene mutation, develop extracellular amyloid beta (Aβ) deposition in the brain, and severe memory and behavioral deficits with age. These mice serve as an important animal model for testing the efficacy of novel drug candidates for the treatment and management of symptoms of Alzheimer's disease (AD). Several reports have suggested that oxidative stress is the underlying cause of Aβ neurotoxicity in AD. Date palm fruits contain very high levels of antioxidants and several medicinal properties that may be useful for improving the quality of life in AD patients. In this study, we investigated the effect of dietary supplementation of Omani date palm fruits on the memory, anxiety and learning skills along with inflammation in an AD mouse model containing the double Swedish APP mutation (APPsw/Tg2576). The experimental groups of APP-transgenic mice from the age of 4 months were fed custom-mix diets (pellets) containing 2% and 4% Date palm fruits. We assessed spatial memory and learning ability, psychomotor coordination, and anxiety-related behavior in Tg and wild-type mice at the age of 4-5 months and 18-19 months using the Morris water maze test, rota rod test, elevated plus maze test, and open field test. Further, inflammatory parameters also analyzed. APPsw/Tg2576 mice that were fed a standard chow diet without dates showed significant memory deficits, increased anxiety-related behavior, and severe impairment in spatial learning ability, position discrimination learning ability and motor coordination along with increased inflammation compared to the wild type mice on the same diet, at the age of 18-19 months In contrast, PPsw/Tg2576 mice that were fed a diet containing 2% and 4% dates showed a significant improvements in memory, learning, locomotor function, and anxiety with reduced inflammatory markers compared to APPsw/Tg2576 mice fed the standard chow diet. Our results suggest that dietary supplementation with dates may slow the progression of cognitive and behavioral impairments in AD. The exact mechanism is still unclear and further extensive research needed.

Keywords: Alzheimer's disease, date palm fruits, Oman, cognitive decline, memory loss, anxiety, inflammation

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Authors: Paul Ihuoma Oluikpe

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The purpose of this paper is to explore and highlight the process of creating value for strategy management by embedding knowledge management in the business process. Knowledge management can be seen from a three-dimensional perspective of content, connections and competencies. These dimensions can be embedded in the knowledge processes (create, capture, share, and apply) and operationalized within a business process to effectively create a scenario where knowledge can be focused on enabling a process and the process in turn generates outcomes. The application of knowledge management on business processes of organizations is rare and underreported. Few researches have explored this paradigm although researches have tended to reinforce the notion that competitive advantage sits within the internal aspects of the firm. Given this notion, it is surprising that knowledge management research and practice have not focused sufficiently on the business process which is the basic unit of organizational decision implementation. This research serves to generate understanding on applying KM in business process using a large multinational in Sub-Saharan Africa.

Keywords: knowledge management, business process, strategy, multinational

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Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

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Automatic text classification applies mostly natural language processing (NLP) and other AI-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: machine learning, text classification, NLP techniques, semantic representation

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Authors: Grienggrai Rajchakit

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This paper is concerned with the exponential stability of switched linear systems with interval time-varying delays. The time delay is any continuous function belonging to a given interval, in which the lower bound of delay is not restricted to zero. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton's formula, a switching rule for the exponential stability of switched linear systems with interval time-varying delays and new delay-dependent sufficient conditions for the exponential stability of the systems are first established in terms of LMIs. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: exponential stability, hybrid systems, time-varying delays, lyapunov-krasovskii functional, leibniz-newton's formula

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Authors: Yasith Mindula Saipath Wickramasinghe

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Augmented reality applications require a high processing power to load, render and live stream high-definition AR models and virtual scenes; it also requires device sensors to work excessively to coordinate with internal hardware, OS and give the expected outcome in advance features like object detection, real time tracking, as well as voice and text recognition. Excessive thermal generation due to these advanced functionalities has become a major research problem as it is unbearable for smaller mobile devices to manage such heat increment and battery drainage as it causes physical harm to the devices in the long term. Therefore, effective thermal management is one of the major requirements in Augmented Reality application development. As this paper discusses major causes for this issue, it also provides possible solutions in the means of operating system adaptations as well as further research on best coding practises to optimize the application performance that reduces thermal excessive thermal generation.

Keywords: augmented reality, device thermal management, GPU, operating systems, device I/O, overheating

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Authors: Huang Dennis, Aurelio Aziel, Burra Venkata Durga Kumar

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Nowadays, smartphones and mobile operating systems have been popularly widespread in our daily lives. As people use smartphones, they tend to store more private and essential data on their devices, because of this it is very important to develop more secure mobile operating systems and cloud storage to secure the data. However, several factors can cause security risks in mobile operating systems such as malware, malicious app, phishing attacks, ransomware, and more, all of which can cause a big problem for users as they can access the user's private data. Those problems can cause data loss, financial loss, identity theft, and other serious consequences. Other than that, during the pandemic, people will use their mobile devices more and do all sorts of transactions online, which may lead to more victims of online scams and inexperienced users being the target. With the increase in attacks, researchers have been actively working to develop several countermeasures to enhance the security of operating systems. This study aims to provide an overview of the security and privacy issues in mobile operating systems, identifying the potential risk of operating systems, and the possible solutions. By examining these issues, we want to provide an easy understanding to users and researchers to improve knowledge and develop more secure mobile operating systems.

Keywords: mobile operating system, security, privacy, Malware

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Authors: Marcelo Dias Carvalho, Leticia Ishikawa

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Supply Chain Risk Management refers to a set of strategies used by companies to avoid supply chain disruption caused by damage at production facilities, natural disasters, capacity issues, inventory problems, incorrect forecasts, and delays. Many companies use the techniques of the Toyota Production System, which in a way goes against a better management of supply chain risks. This paper studies key events in some multinationals to analyze the trade-off between the best supply chain risk management techniques and management policies designed to create lean enterprises. The result of a good balance of these actions is the reduction of losses, increased customer trust in the company and better preparedness to face the general risks of a supply chain.

Keywords: just in time, lean manufacturing, supply chain disruptions, supply chain management

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Authors: Tirtha Raj Dhakal, Brian Davidson, Bob Farquharson

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Institutional design is an important aspect in efficient water resource management. In Nepal, the water supply in both farmers’- and agency-managed irrigation systems has become sub-standard because of the weak institutional framework. This study characterizes both forms of the schemes and links existing institution and governance of the schemes with its performance with reference to cost recovery, maintenance of the schemes and water distribution throughout the schemes. For this, two types of surveys were conducted. A management survey of ten farmers’-managed and five agency-managed schemes of Chitwan valley and its periphery was done. Also, a farm survey comprising 25 farmers from each of head, middle and tail regions of both schemes; Narayani Lift Irrigation Project (agency-managed) and Khageri Irrigation System (farmers’-managed) of Chitwan Valley as a case study was conducted. The results showed that cost recovery of agency-managed schemes in 2015 was less than two percent whereas service fee collection rate in farmers’-managed schemes was nearly 2/3rd that triggered poor maintenance of the schemes and unequal distribution of water throughout the schemes. Also, the institution on practice is unable to create any incentives for farmers for economical use of water as well as willingness to pay for its use. This, thus, compels the need of refined institutional framework which has been suggested in this paper aiming to improve the cost recovery and better water distribution throughout the irrigation schemes.

Keywords: cost recovery, governance, institution, schemes' performance

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Authors: Pinkey Yaqub

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The aim of this study was to investigate secondary (grades IX and X) students’ attitudes towards learning the English language based on the medium of instruction of the school, the gender of the students and the grade level in which they studied. A further aim was to determine students’ proficiency in the English language according to their gender, the grade level and the medium of instruction of the school. A survey was used to investigate the attitudes of secondary students towards English language learning. Simple random sampling was employed to obtain a representative sample of the target population for the research study as a comprehensive list of established English medium schools, and newly established English medium schools were available. A questionnaire ‘Attitude towards English Language Learning’ (AtELL) was adapted from a research study on Libyan secondary school students’ attitudes towards learning English language. AtELL was reviewed by experts (n=6) and later piloted on a representative sample of secondary students (n= 160). Subsequently, the questionnaire was modified - based on the reviewers’ feedback and lessons learnt during the piloting phase - and directly administered to students of grades 9 and 10 to gather information regarding their attitudes towards learning the English language. Data collection spanned a month and a half. As the data were not normally distributed, the researcher used Mann-Whitney tests to test the hypotheses formulated to investigate students’ attitudes towards learning English as well as proficiency in the language across the medium of instruction of the school, the gender of the students and the grade level of the respondents. Statistical analyses of the data showed that the students of established English medium schools exhibited a positive outlook towards English language learning in terms of the behavioural, cognitive and emotional aspects of attitude. A significant difference was observed in the attitudes of male and female students towards learning English where females showed a more positive attitude in terms of behavioural, cognitive and emotional aspects as compared to their male counterparts. Moreover, grade 10 students had a more positive attitude towards learning English language in terms of behavioural, cognitive and emotional aspects as compared to grade 9 students. Nonetheless, students of newly established English medium schools were more proficient in English as gauged by their examination scores in this subject as compared to their counterparts studying in established English medium schools. Moreover, female students were more proficient in English while students studying in grade 9 were less proficient in English than their seniors studying in grade 10. The findings of this research provide empirical evidence to future researchers wishing to explore the relationship between attitudes towards learning language and variables such as the medium of instruction of the school, gender and the grade level of the students. Furthermore, policymakers might revisit the English curriculum to formulate specific guidelines that promote a positive and gender-balanced outlook towards learning English for male and female students.

Keywords: attitude, behavioral aspect of attitude, cognitive aspect of attitude, emotional aspect of attitude

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Authors: Catherine Vasnetsov, Victor Vasnetsov

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Context: Thermo-responsive polymers are materials that undergo significant changes in their physical properties in response to temperature changes. These polymers have gained significant attention in research due to their potential applications in various industries and medicine. However, the molecular mechanisms underlying their behavior are not well understood, particularly in relation to cosolvency, which is crucial for practical applications. Research Aim: This study aimed to theoretically investigate the phenomenon of cosolvency in long-chain polymers using the Flory-Huggins statistical-mechanical framework. The main objective was to understand the interactions between the polymer, solvent, and cosolvent under different conditions. Methodology: The research employed a combination of Monte Carlo computer simulations and advanced machine-learning methods. The Flory-Huggins mean field theory was used as the basis for the simulations. Spinodal graphs and ternary plots were utilized to develop an initial computer model for predicting polymer behavior. Molecular dynamic simulations were conducted to mimic real-life polymer systems. Machine learning techniques were incorporated to enhance the accuracy and reliability of the simulations. Findings: The simulations revealed that the addition of very low or very high volumes of cosolvent molecules resulted in smaller radii of gyration for the polymer, indicating poor miscibility. However, intermediate volume fractions of cosolvent led to higher radii of gyration, suggesting improved miscibility. These findings provide a possible microscopic explanation for the cosolvency phenomenon in polymer systems. Theoretical Importance: This research contributes to a better understanding of the behavior of thermo-responsive polymers and the role of cosolvency. The findings provide insights into the molecular mechanisms underlying cosolvency and offer specific predictions for future experimental investigations. The study also presents a more rigorous analysis of the Flory-Huggins free energy theory in the context of polymer systems. Data Collection and Analysis Procedures: The data for this study was collected through Monte Carlo computer simulations and molecular dynamic simulations. The interactions between the polymer, solvent, and cosolvent were analyzed using the Flory-Huggins mean field theory. Machine learning techniques were employed to enhance the accuracy of the simulations. The collected data was then analyzed to determine the impact of cosolvent volume fractions on the radii of gyration of the polymer. Question Addressed: The research addressed the question of how cosolvency affects the behavior of long-chain polymers. Specifically, the study aimed to investigate the interactions between the polymer, solvent, and cosolvent under different volume fractions and understand the resulting changes in the radii of gyration. Conclusion: In conclusion, this study utilized theoretical modeling and computer simulations to investigate the phenomenon of cosolvency in long-chain polymers. The findings suggest that moderate cosolvent volume fractions can lead to improved miscibility, as indicated by higher radii of gyration. These insights contribute to a better understanding of the molecular mechanisms underlying cosolvency in polymer systems and provide predictions for future experimental studies. The research also enhances the theoretical analysis of the Flory-Huggins free energy theory.

Keywords: molecular modelling, flory-huggins, cosolvency, stimuli-responsive polymers

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Authors: Ayman M. Mansour, Bilal Hawashin, Mohammed A. Mansour

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In this paper, we propose a cooperative learning mechanism in a multi-agent intelligent system. The basic idea is that intelligent agents are capable of collaborating with one another by sharing their knowledge. The agents will start collaboration by providing their knowledge rules to the other agents. This will allow the most important and insightful detection rules produced by the most experienced agent to bubble up for the benefit of the entire agent community. The updated rules will lead to improving the agents’ decision performance. To evaluate our approach, we designed a five–agent system and implemented it using JADE and FuzzyJess software packages. The agents will work with each other to make a decision about a suspicious medical case. This system provides quick response rate and the decision is faster than the manual methods. This will save patients life.

Keywords: intelligent, multi-agent system, cooperative, fuzzy, learning

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Authors: C. W. Kan, H. F. Cheung, Y. S. Lee

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This study examines the results of colour fading of cotton fabric by plasma-induced ozone treatment, with an aim to provide learning materials for fashion designers when designing colour fading effects in fashion products. Cotton knitted fabrics were dyed with red reactive dye with a colour depth of 1.5% and were subjected to ozone generated by a commercially available plasma machine for colour fading. The plasma-induced ozone treatment was conducted with different parameters: (i) air concentration = 10%, 30%, 50% and 70%; (ii) water content in fabric = 35% and 45%, and (iii) treatment time = 10 minutes, 20 minutes and 30 minutes. Finally, the colour properties of the plasma–induced ozone treated fabric were measured by spectrophotometer under illuminant D₆₅ to obtain the CIE L*, CIE a* and CIE b* values.

Keywords: learning materials, colour fading, colour properties, fashion products

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Authors: S. Anastasiou, C. Nathanailides, S. Logothetis, G. Kanlis

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The Greek aquaculture industry is second most important economic sector for the growth of the Greek Economy. The purpose of the present work is to present some data for the management challenges that the Aquaculture industry in Greece is currently facing. Currently the Greek aquaculture industry is going through a series of mergers and restructure. The financial status of the different aquaculture companies, the working conditions and management practices may vary according to lending exposure, market mix, company size, and technological parameters of the different fish farm units and rearing systems. Frequently, the aquaculture personnel are exposed to harsh environmental conditions and to occupational risk. Furthermore, there is pressure on the personnel of fish farms to constantly improve their production efficiency and to enhance their work skills to the new methods and practices which are adopted by the aquaculture industry. There is some data to suggest the existence of gender inequality in the workforce of Greek fish farms. Women are paid less, frequently absent higher managerial positions and most of the male workmates consider the job to harsh for women. Nevertheless, high level of job satisfaction was observed in both men and women. This high level of job satisfaction of the aquaculture personnel can be attributed, at least partially, to the nature of the work which has a very distinct working environment but most of the staff has very positive experiences with the interaction with their workmates and the satisfaction of being in a business which always exceeds its production target. Indeed, there is some evidence to suggest that the Greek aquaculture industry is always exceeding its production targets, while it is rapidly adopting and improving new technology, constantly improving of human resources management practices, which include constant training of the staff, very good communication channels between management and the personnel and reducing the risk of occupational hazard to the aquaculture personnel. All these parameters of management may have a determining role for the volume and quality of the production and future of this sector in Greece.

Keywords: aquaculture, fish quality, management, production targets

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Authors: Bilal Ahmed, Muhammad Rafiq, Choongjae Im

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The tech-savvy Gen Z's transfer towards interactive concept learning is hammering the demand for online collaborative learning environments, renovating conventional education approaches. The authors propose a novel approach to enhance learning outcomes to improve retention in 3D interactive education by connecting virtual reality (VR) and non-VR devices in the classroom and distance learning. The study evaluates students' experiences with VR interconnectivity devices in human anatomy lectures using real-time 3D interactive data visualization. Utilizing the renowned "Guo & Pooles Inventory" and the "Flow for Presence Questionnaires," it used an experimental research design with a control and experimental group to assess this novel connecting strategy's effectiveness and significant potential for in-person and online educational settings during the sessions. The experimental group's interactions, engagement levels, and usability experiences were assessed using the "Guo & Pooles Inventory" and "Flow for Presence Questionnaires," which measure their sense of presence, engagement, and immersion throughout the learning process using a 5-point Likert scale. At the end of the sessions, we used the "Perceived Usability Scale" to find our proposed system's overall efficiency, effectiveness, and satisfaction. By comparing both groups, the students in the experimental group used the integrated VR environment and VR to non-VR devices, and their sense of presence and attentiveness was significantly improved, allowing for increased engagement by giving students diverse technological access. Furthermore, learners' flow states demonstrated increased absorption and focus levels, improving information retention and Perceived Usability. The findings of this study can help educational institutions optimize their technology-enhanced teaching methods for traditional classroom settings as well as distance-based learning, where building a sense of connection among remote learners is critical. This study will give significant insights into educational technology and its ongoing progress by analyzing engagement, interactivity, usability, satisfaction, and presence.

Keywords: interactive learning environments, human-computer interaction, virtual reality, computer- supported collaborative learning

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Authors: Weichen Chang

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To create a guided teaching method for AI generative drawing design, this paper develops a set of teaching models for AI generative drawing (DCAI), which combines learning modes such as problem-solving, thematic inquiry, phenomenon-based, task-oriented, and DFC . Through the information security AI picture book learning guided programs and content, the application of participatory action research (PAR) and interview methods to explore the dual knowledge of Context and ChatGPT (DCAI) for AI to guide the development of students' AI learning skills. In the interviews, the students highlighted five main learning outcomes (self-study, critical thinking, knowledge generation, cognitive development, and presentation of work) as well as the challenges of implementing the model. Through the use of DCAI, students will enhance their consensus awareness of generative mapping analysis and group cooperation, and they will have knowledge that can enhance AI capabilities in DCAI inquiry and future life. From this paper, it is found that the conclusions are (1) The good use of DCAI can assist students in exploring the value of their knowledge through the power of stories and finding the meaning of knowledge communication; (2) Analyze the transformation power of the integrity and coherence of the story through the context so as to achieve the tension of ‘starting and ending’; (3) Use ChatGPT to extract inspiration, arrange story compositions, and make prompts that can communicate with people and convey emotions. Therefore, new knowledge construction methods will be one of the effective methods for AI learning in the face of artificial intelligence, providing new thinking and new expressions for interdisciplinary design and design education practice.

Keywords: artificial intelligence, task-oriented, contextualization, design education

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Authors: Eva Štěpánková

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Environmental management implementation is presently one of the ways of organization success and value improvement. Increasing an organization motivation to environmental measures introduction is caused primarily by the rising pressure of the society that generates various incentives to endeavor for the environmental performance improvement. The aim of the paper is to identify and characterize the key incentives and expectations leading organizations to the environmental management implementation. The author focuses on five businesses of different size and field, operating in the Czech Republic. The qualitative approach and grounded theory procedure are used in research. The results point out that the significant incentives for environmental management implementation represent primarily demands of customers, the opportunity to declare the environmental commitment and image improvement. The researched enterprises less commonly expect the economical contribution, competitive advantage increase or export rate improvement. The results show that marketing contributions are primarily expected from the environmental management implementation.

Keywords: environmental management, environmental management system, ISO 14001, Czech Republic

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Authors: R. Bawazir, P. Jones

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Social Stories are widely used to teach social and communication skills or concepts to individuals on the autistic spectrum. This paper presents a theoretical framework for using Social Stories in conjunction with the creative arts. The paper argues that Bandura’s social learning theory can be used to explain the mechanisms behind Social Stories and the way they influence changes in response, while Gardner’s multiple intelligences theory can be used simultaneously to demonstrate the role of the creative arts in learning. By using Social Stories with the creative arts for individuals on the autistic spectrum, the aim is to meet individual needs and help individuals with autism to develop in different areas of learning and communication.

Keywords: individuals on the autistic spectrum, social stories, the creative arts, theoretical framework

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Authors: Jansirani Natarajan, Mickael Antoinne Joseph

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The COVID-19 pandemic has interrupted face-to-face education and forced universities into an emergency remote teaching curriculum over a short duration. This abrupt transition in the Spring 2020 semester left both faculty and students without proper preparation for continuing higher education in an online environment. Online learning took place in different formats, including fully synchronous, fully asynchronous, and blended in our university through the e-learning platform MOODLE. Studies have shown that students’ engagement, is a critical factor for optimal online teaching. Very few studies have assessed online engagement with ERT during the COVID-19 pandemic. Purpose: Therefore, this study, sought to understand how the sudden transition to emergency remote teaching impacted nursing students’ engagement with online courses in a Middle Eastern public university. Method: A cross-sectional descriptive research design was adopted in this study. Data were collected through a self-reported online survey using Dixon’s online students’ engagement questionnaire from a sample of 177 nursing students after the ERT learning semester. Results The maximum possible engagement score was 95, and the maximum scores in the domains of skills engagement, emotional engagement, participation engagement, and performance engagement were 30, 25, 30, and 10 respectively. Dixson (2010) noted that a mean item score of ≥3.5 (total score of ≥66.5) represents a highly engaged student. The majority of the participants were females (71.8%) and 84.2% were regular BSN students. Most of them (32.2%) were second-year students and 52% had a CGPA between 2 and 3. Most participants (56.5%) had low engagement scores with ERT learning during the COVID lockdown. Among the four engagement domains, 78% had low engagement scores for the participation domain. There was no significant association found between the engagement and the demographic characteristics of the participants. Conclusion The findings supported the importance of engaging students in all four categories skill, emotional, performance, and participation. Based on the results, training sessions were organized for faculty on various strategies for engaging nursing students in all domains by using the facilities available in the MOODLE (online e-learning platform). It added value as a dashboard of information regarding ERT for the administrators and nurse educators to introduce numerous active learning strategies to improve the quality of teaching and learning of nursing students in the University.

Keywords: engagement, perception, emergency remote learning, COVID-19

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Authors: A. Alharbi, R. Boukhanouf, T. Habeebullah, H. Ibrahim

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This paper presents a detailed description of evaporative cooling systems used for space cooling in Mina Valley, Saudi Arabia. The thermal performance and environmental impact of the evaporative coolers were evaluated. It was found that the evaporative cooling systems used for space cooling in pilgrims’ accommodations and in the train stations could reduce energy consumption by as much as 75% and cut carbon dioxide emission by 78% compared to traditional vapour compression systems.

Keywords: evaporative cooling, vapor compression, electricity consumption, CO2 emission

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Authors: T. Wanyama, B. Far

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Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: community water usage, fuzzy logic, irrigation, multi-agent system

Procedia PDF Downloads 280

Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

Abstract:

Recent advances in cognitive neuroscience have allowed a step forward in perceiving the processes involved in learning from the point of view of the acquisition of new information or the modification of existing mental content. The evoked potentials technique reveals how basic brain processes interact to achieve adequate and flexible behaviours. The objective of this work, using evoked potentials, is to study if it is possible to distinguish if a patient suffers a specific type of learning disorder to decide the possible therapies to follow. The methodology used, is the analysis of the dynamics of different areas of the brain during a cognitive activity to find the relationships between the different areas analyzed in order to better understand the functioning of neural networks. Also, the latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of non-invasive, innocuous, low-cost and easy-access techniques such as, among others, the evoked potentials that can help to detect early possible neuro-developmental difficulties for their subsequent assessment and cure. From the study of the amplitudes and latencies of the evoked potentials, it is possible to detect brain alterations in the learning process specifically in dyscalculia, to achieve specific corrective measures for the application of personalized psycho pedagogical plans that allow obtaining an optimal integral development of the affected people.

Keywords: dyscalculia, neurodevelopment, evoked potentials, Learning disabilities, neural networks

Procedia PDF Downloads 115

Authors: Supunmali Ahangama, Danny Chiang Choon Poo

Abstract:

Health analytics (HA) is used in healthcare systems for effective decision-making, management, and planning of healthcare and related activities. However, user resistance, the unique position of medical data content, and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. The success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose an HA process model with features from the rational unified process (RUP) model and agile methodology.

Keywords: agile methodology, health analytics, unified process model, UML

Procedia PDF Downloads 486

Authors: Venkata Narayana Chejarla, Nafisa Parvez Shaik, Gopi Vara Prasad Marabathula, Deva Kumar Bejjam

Abstract:

Yoga is an advanced, well-recognized method with roots in Indian philosophy. Yoga benefits both the body and the psyche. Yoga is a regular exercise that helps people relax and sleep better while also enhancing their balance, endurance, and concentration. Yoga can be learned in a variety of settings, including at home with the aid of books and the internet as well as in yoga studios with the guidance of an instructor. Self-learning does not teach the proper yoga poses, and doing them without the right instruction could result in significant injuries. We developed "Online Yoga Asana Trainer using Deep Learning" so that people could practice yoga without a teacher. Our project is developed using Tensorflow, Movenet, and Keras models. The system makes use of data from Kaggle that includes 25 different yoga poses. The first part of the process involves applying the movement model for extracting the 17 key points of the body from the dataset, and the next part involves preprocessing, which includes building a pose classification model using neural networks. The system scores a 98.3% accuracy rate. The system is developed to work with live videos.

Keywords: yoga, deep learning, movenet, tensorflow, keras, CNN

Procedia PDF Downloads 217

Authors: Y. Kim, H. Lee, M. Park, B. Lee

Abstract:

Planning is understood as the determination of what has to be performed, how, in which sequence, when, what resources are needed, and their cost within the organization before execution. In most construction project, it is evident that the inherent nature of planning is dynamic, and initial planning is subject to be changed due to various uncertain conditions of construction project. Planners take a continuous revision process during the course of a project and until the very end of project. However, current practice lacks reliable, systematic tool for setting variance thresholds to determine when and what corrective actions to be taken. Rather it is heavily dependent on the level of experience and knowledge of the planner. Thus, this paper introduces a machine learning approach to evaluate project control threshold reliability incorporating project-specific data and presents a method to automate the process. The results have shown that the model improves the efficiency and accuracy of the monitoring process as an early warning.

Keywords: machine learning, project control, project progress monitoring, schedule

Procedia PDF Downloads 230