Search results for: accelerated online learning

Authors: Samson T. Obafemi, Seraphin D. Eyono-Obono

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Information and Communication Technologies (ICTs) are pervasive nowadays, including in education where they are expected to improve the performance of learners. However, the hope placed in ICTs to find viable solutions to the problem of poor academic performance in schools in the developing world has not yet yielded the expected benefits. This problem serves as a motivation to this study whose aim is to examine the perceptions of educators on the advantages and disadvantages of e-learning. This aim will be subdivided into two types of research objectives. Objectives on the identification and design of theories and models will be achieved using content analysis and literature review. However, the objective on the empirical testing of such theories and models will be achieved through the survey of educators from different schools in the Pinetown District of the South African Kwazulu-Natal province. SPSS is used to quantitatively analyse the data collected by the questionnaire of this survey using descriptive statistics and Pearson correlations after assessing the validity and the reliability of the data. The main hypothesis driving this study is that there is a relationship between the demographics of educators’ and their adherence to learning theories on one side, and their perceptions on the advantages and disadvantages of e-learning on the other side, as argued by existing research; but this research views these learning theories under three perspectives: educators’ adherence to self-regulated learning, to constructivism, and to progressivism. This hypothesis was fully confirmed by the empirical study except for the demographic factor where teachers’ level of education was found to be the only demographic factor affecting the perceptions of educators on the advantages and disadvantages of e-learning.

Keywords: academic performance, e-learning, learning theories, teaching and learning

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Authors: Diego Roberto Goncalves De Pontes, Sergio Donizetti Zorzo

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Studies show that most users do not read privacy policies from the online services they use. Some authors claim that one of the main causes of this is that policies are long and usually hard to understand, which make users lose interest in reading them. In this scenario, users may agree with terms without knowing what kind of data is being collected and why. Given that, we aimed to develop a model that would present the privacy policies contents in an easy and graphical way for the user to understand. We call it the Privacy Label. Using information recovery techniques, we propose an architecture that is able to extract information about what kind of data is being collected and to what end in the policies and show it to the user in an automated way. To assess our model, we calculated the precision, recall and f-measure metrics on the information extracted by our technique. The results for each metric were 68.53%, 85.61% e 76,13%, respectively, making it possible for the final user to understand which data was being collected without reading the whole policy. Also, our proposal can facilitate the notice-and-choice by presenting privacy policy information in an alternative way for online users.

Keywords: privacy, policies, user behavior, computer human interaction

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Authors: Kai Yip Michael Tsang

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Science writing has played a crucial part in science assessments. This paper reports a study in an area that has received little research attention – how Language across the Curriculum (LAC, i.e. science language and literacy) learning activities in science lessons can increase the science knowledge development of English as a foreign language (EFL) students in Hong Kong. The data comes from a school-based interventional study in chemistry classrooms, with written data from questionnaires, assessments and teachers’ logs and verbal data from interviews and classroom observations. The effectiveness of the LAC teaching and learning activities in various chemistry classrooms were compared and evaluated, with discussion of some implications. Students in the treatment group with lower achieving students received LAC learning and teaching activities while students in the control group with higher achieving students received conventional learning and teaching activities. After the study, they performed better in control group in formative assessments. Moreover, they had a better attitude to learning chemistry content with a richer language support. The paper concludes that LAC teaching and learning activities yielded positive learning outcomes among chemistry learners with low English ability.

Keywords: science learning and teaching, content and language integrated learning, language across the curriculum, English as a foreign language

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Authors: Delowar Hossain, Genci Capi

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This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: deep learning, genetic algorithm, object recognition, robot grasping

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Authors: Sadia Idrees, Gianpaolo Vignali, Simeon Gill

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The study aims to establish the virtual size and fit technology features to enhance fashion online retailing platforms, utilising digital human measurements to provide customised style and function to consumers. A few firms in the UK have launched advanced interactive fashion shopping domains for personalised shopping globally, aided by the latest internet technology. Virtual size and fit interfaces have a great potential to provide a personalised better-fitted garment to promote mass customisation globally. Made-to-measure clothing, consuming unstitched fabric is a common practice offered by fashion brands in Pakistan. This product is regarded as economical and sustainable to be utilised by consumers in Pakistan. Although the manual sizing system is practiced to sell garments online, virtual size and fit visualisation and recommendation technologies are uncommon in Pakistani fashion interfaces. A comparative assessment of Pakistani fashion brand websites and UK technology-driven fashion interfaces was conducted to highlight the vast potential of the virtual size and fit technology. The results indicated that web 2.0 technology adopted by Pakistani apparel brands has limited features, whereas companies practicing web 3.0 technology provide interactive online real-store shopping experience leading to enhanced customer satisfaction and globalisation of brands.

Keywords: e-commerce, mass customization, virtual size and fit, web 3.0 technology

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Authors: Shivangi Agrawal, Hsiu-I Ting

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Entrepreneurship is an essential source of economic growth and a prominent factor influencing socio-economic development. Entrepreneurship education educates and enhances entrepreneurial activity. This study aims to understand current trends in entrepreneurship education and evaluate the effectiveness of diverse entrepreneurship education programs. An increasing number of universities offer entrepreneurship education courses to create and successfully continue entrepreneurial ventures. Despite the prevalence of entrepreneurship education, research studies lack inconsistency about the effectiveness of entrepreneurship education to promote and develop entrepreneurship. Strategies to develop entrepreneurial attitudes and intentions among individuals are hindered by a lack of understanding of entrepreneurs' educational purposes, components, methodology, and resources required. Lack of adequate entrepreneurship education has been linked with low self-efficacy and lack of entrepreneurial intent. Moreover, in the age of digitisation and during the COVID-19 pandemic, digital learning platforms (e.g., online entrepreneurship education courses and programs) and other digital tools (e.g., digital game-based entrepreneurship education) have become more relevant to entrepreneurship education. This paper contributes to the continuation of academic literature in entrepreneurship education by evaluating and assessing current trends in entrepreneurship education programs, leading to better understanding to reduce gaps between entrepreneurial development requirements and higher education institutions.

Keywords: entrepreneurship education, digital technologies, academic entrepreneurship, COVID-19

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Authors: Amrah Maryam

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The emergence of online social networks (OSNs) has transformed the way we pursue and share information. On the one hand, OSNs provide great ease for the spreading of positive information while, on the other hand, they may also become a channel for the spreading of malicious rumors and misinformation throughout the social network. Thus, to assure the trustworthiness of OSNs to its users, it is of vital importance to detect the misinformation propagation in the network by placing network monitors. In this paper, we aim to place monitors near the suspected nodes with the intent to limit the diffusion of misinformation in the social network, and then we also detect the most significant nodes in the network for propagating true information in order to minimize the effect of already diffused misinformation. Thus, we initiate two heuristic monitor placement using articulation points and truth propagation using eigenvector centrality. Furthermore, to provide real-time workings of the system, we integrate both the monitor placement and truth propagation entities as well. To signify the effectiveness of the approaches, we have carried out the experiment and evaluation of Stanford datasets of online social networks.

Keywords: online social networks, monitor placement, independent cascade model, spread of misinformation

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Yasser F. Hassan

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Social networking involves use of an online platform or website that enables people to communicate, usually for a social purpose, through a variety of services, most of which are web-based and offer opportunities for people to interact over the internet, e.g. via e-mail and ‘instant messaging’, by analyzing the voting behavior and ratings of judges in a popular comments in social networks. While most of the party literature omits the electorate, this paper presents a model where elites and parties are emergent consequences of the behavior and preferences of voters. The research in artificial intelligence and psychology has provided powerful illustrations of the way in which the emergence of intelligent behavior depends on the development of representational structure. As opposed to the classical voting system (one person – one decision – one vote) a new voting system is designed where agents with opposed preferences are endowed with a given number of votes to freely distribute them among some issues. The paper uses ideas from machine learning, artificial intelligence and soft computing to provide a model of the development of voting system response in a simulated agent. The modeled development process involves (simulated) processes of evolution, learning and representation development. The main value of the model is that it provides an illustration of how simple learning processes may lead to the formation of structure. We employ agent-based computer simulation to demonstrate the formation and interaction of coalitions that arise from individual voter preferences. We are interested in coordinating the local behavior of individual agents to provide an appropriate system-level behavior.

Keywords: voting system, rough sets, multi-agent, social networks, emergence, power indices

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Authors: Seree Chadcham, Niphon Sukvilai

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This study is the research and development which is intended to: 1) design of the Intelligent Scaffolding Learning Management System (ISLMS) for vocational education, 2) assess the suitability of the Design of Intelligent Scaffolding Learning Management System for Vocational Education. Its methods are divided into 2 phases. Phase 1 is the design of the ISLMS for Vocational Education and phase 2 is the assessment of the suitability of the design. The samples used in this study are work done by 15 professionals in the field of Intelligent Scaffolding, Learning Management System, Vocational Education, and Information and Communication Technology in education selected using the purposive sampling method. Data analyzed by arithmetic mean and standard deviation. The results showed that the ISLMS for vocational education consists of 2 main components which are: 1) the Intelligent Learning Management System for Vocational Education, 2) the Intelligent Scaffolding Management System. The result of the system suitability assessment from the professionals is in the highest range.

Keywords: intelligent, scaffolding, learning management system, vocational education

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Authors: Maryam Savari, Mohamad Nizam Ayub, Ainuddin Wahid Abdul Wahab

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Game-based Learning (GBL) is an alternative that provides learners with an opportunity to experience a volatile environment in a safe and secure place. A volatile environment requires a different technique to facilitate learning and prevent injury and other hazards. Subjects involving elasticity are always considered hazardous and can cause injuries,for instance a bouncing ball. Elasticity is a topic that necessitates hands-on practicality for learners to experience the effects of elastic objects. In this paper the scope is to investigate the natural interaction between learners and elastic objects in a safe environment using GBL. During interaction, the potentials of natural contact in the process of learning were explored and gestures exhibited during the learning process were identified. GBL was developed using Kinect technology to teach elasticity to primary school children aged 7 to 12. The system detects body gestures and defines the meanings of motions exhibited during the learning process. The qualitative approach was deployed to constantly monitor the interaction between the student and the system. Based on the results, it was found that Natural Interaction GBL (Ni-GBL) is engaging for students to learn, making their learning experience more active and joyful.

Keywords: elasticity, Game-Based Learning (GBL), kinect technology, natural interaction

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Authors: R. M. Bashir, Sabo Elizabeth

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Electronic learning is an increasingly popular learning approach in higher educational institutions due to vast growth of internet technology. An investigation on the assessment of e-learning facilities and information need by open and distance learning students in Jalingo, Nigeria was conducted. Structured questionnaires were administered to 70 students of the university. Information sourced from the respondents covered demographic, economic and institutional variables. Data collected for demographic variables were computed as frequency count and percentages. Information on assessment of e-learning facilities and information need among open and distance learning students was computed on a three or four point Likert Rating Scale. Findings indicated that there are more men compared to women, a large proportion of the respondents are married and there are more matured students. A high proportion of the students obtained qualifications higher than the secondary school certificate. The proportion of computer literate students was higher compared with those students that owned a computer. Inadequate e-books and reference materials, internet gadgets and inadequate books (hard copies) and reference material are factors that limit utilization of e-learning facilities. Inadequate computer facilities caused delay in examination schedule at the study center. Open and distance learning students required to a high extent information on university timetable and schedule of activities, books (hard and e-books) and reference materials and contact with course coordinators via internet for better learning and academic performance.

Keywords: open and distance learning, information required, electronic books, internet gadgets, Likert scale test

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Authors: D. Jayalakshmi, S. S. Bhosale

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This paper, in its first part, presents the state-of-the-art literature of design approaches for geosynthetic reinforced unpaved roads. The literature starting since 1970 and the critical appraisal of flexible pavement design by Giroud and Han (2004) and Jonathan Fannin (2006) is presented. The design example is illustrated for Indian conditions. The example emphasizes the results computed by Giroud and Han's (2004) design method with the Indian road congress guidelines by IRC SP 72 -2015. The input data considered are related to the subgrade soil condition of Maharashtra State in India. The unified soil classification of the subgrade soil is inorganic clay with high plasticity (CH), which is expansive with a California bearing ratio (CBR) of 2% to 3%. The example exhibits the unreinforced case and geotextile as reinforcement by varying the rut depth from 25 mm to 100 mm. The present result reveals the base thickness for the unreinforced case from the IRC design catalogs is in good agreement with Giroud and Han (2004) approach for a range of 75 mm to 100 mm rut depth. Since Giroud and Han (2004) method is applicable for both reinforced and unreinforced cases, for the same data with appropriate Nc factor, for the same rut depth, the base thickness for the reinforced case has arrived for the Indian condition. From this trial, for the CBR of 2%, the base thickness reduction due to geotextile inclusion is 35%. For the CBR range of 2% to 5% with different stiffness in geosynthetics, the reduction in base course thickness will be evaluated, and the validation will be executed by the full-scale accelerated pavement testing set up at the College of Engineering Pune (COE), India.

Keywords: base thickness, design approach, equation, full scale accelerated pavement set up, Indian condition

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Authors: Sathapath Kilaso

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Attendance checking in the classroom for student is object to record the student’s attendance in order to support the learning activities in the classroom. Despite the teaching trend in the 21st century is the student-center learning and the lecturer duty is to mentor and give an advice, the classroom learning is still important in order to let the student interact with the classmate and the lecturer or for a specific subject which the in-class learning is needed. The development of the system prototype by applied the microcontroller technology and embedded system with the “internet of thing” trend and the web socket technique will allow the lecturer to be alerted immediately whenever the data is updated.

Keywords: arduino, embedded system, classroom, raspberry PI

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Authors: Shu-Chen Wu

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This paper will present a study by the author which investigates Chinese teachers’ perspectives on learning at play and their teaching activities in the designed play activities. It asks the question of how Chinese teachers understand learning at play and how they design play activities in the classroom. Six kindergarten teachers in Hong Kong were invited to select and record exemplary play episodes which contain the largest amount of learning elements in their own classrooms. Applying video-stimulated interview, eight teachers in two focus groups were interviewed to elicit their perspectives on designing play activity and their teaching activities. The findings reveal that Chinese teachers have a very structured representation of learning at play, and the phenomenon of uniformity of teachers’ act was found. The contributions of which are important and useful for professional practices and curricular policies.

Keywords: learning at play, teacher involvement, video-stimulated interview, uniformity

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Authors: Vasanthi Muniasamy, Intisar Magboul Ejalani, M.Anandhavalli, K. Gauthaman

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Social Media (SM) are websites increasingly popular and built to allow people to express themselves and to interact socially with others. Most SMT are dominated by youth particularly college students. The proliferation of popular social media tools, which can accessed from any communication devices has become pervasive in the lives of today’s student life. Connecting traditional education to social media tools are a relatively new era and any collaborative tool could be used for learning activities. This study focuses (i) how the social media tools are useful for the learning activities of the students of faculty of medicine in King Khalid University (ii) whether the social media affects the collaborative learning with interaction among students, among course instructor, their engagement, perceived ease of use and perceived ease of usefulness (TAM) (iii) overall, the students satisfy with this collaborative learning through Social media.

Keywords: social media, Web 2.0, perceived ease of use, perceived usefulness, collaborative Learning

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Authors: Abdullah Abu-Tineh, Carol Murphy, Nigel Calder, Nasser Mansour

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This paper reports on an aspect of e-learning in developing inquiry-based learning (IBL). We present data on the views of teachers and students in Qatar following a professional development programme intended to help teachers implement IBL in their science and mathematics classrooms. Key to this programme was the use of WebQuests. Views of the teachers and students suggested that WebQuests helped students to develop technical skills, work collaboratively and become independent in their learning. The use of WebQuests also enabled a combination of digital and non-digital tools that helped students connect ideas and enhance their understanding of topics.

Keywords: digital technology, inquiry-based learning, mathematics and science education, professional development

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Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf, Kamal Kharrazi

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When we teach, we have two critical elements at our disposal to help students: learning styles as well as testing styles. There are many different ways in which educators can effectively teach their students; verbal learning and experience-based learning. Lecture as a form of verbal learning style is a traditional arrangement in which teachers are more active and share information verbally with students. In experienced-based learning as the process of through, students learn actively through hands-on learning materials and observing teachers or others. Meanwhile, standard testing or assessment is the way to determine progress toward proficiency. Teachers and instructors mainly use essay (requires written responses), multiple choice questions (includes the correct answer and several incorrect answers as distractors), or open-ended questions (respondents answers it with own words). The current study focused on exploring an effective teaching style and testing methods as the function of age over school ages. In the present study, totally 410 participants were selected randomly from four grades (2ⁿᵈ, 4ᵗʰ, 6ᵗʰ, and 8ᵗʰ). Each subject was tested individually in one session lasting around 50 minutes. In learning tasks, the participants were presented three different instructions for learning materials (learning by doing, learning by observing, and learning by listening). Then, they were tested via different standard assessments as free recall, cued recall, and recognition tasks. The results revealed that generally students remember more of what they do and what they observe than what they hear. The age effect was more pronounced in learning by doing than in learning by observing, and learning by listening, becoming progressively stronger in the free-recall, cued-recall, and recognition tasks. The findings of this study indicated that learning by doing and free recall task is more age sensitive, suggesting that both of them are more strategic and more affected by developmental differences. Pedagogically, these results denoted that learning by modeling and engagement in program activities have the special role for learning. Moreover, the findings indicated that the multiple-choice questions can produce the best performance for school-aged children but is less age-sensitive. By contrast, the essay as essay can produce the lowest performance but is more age-sensitive. It will be very helpful for educators to know that what types of learning styles and test methods are most effective for students in each school grade.

Keywords: experience-based learning, learning style, school-aged children, testing methods, verbal learning

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Prachya Kamonphet

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The purposes of this research were to study the learning motivation factors for Pre-cadets in Armed Forces Academies Preparatory School, Ministry of Defense. The subjects were 320 Pre-cadets (from all 3-year classes of Pre-cadets, the academic year 2015). The research instruments were questionnaires. The collected data were analyzed by means of Descriptive Statistic and One-Way Analysis of Variance. The results of this study were as follows: The relation between the Pre-cadets’ average grade and the motivation in studying was significance.In the aspect of the environment related to Pre-cadets’ families and the motivation in studying.In the aspect of the environment related to Pre-cadets’ studying, it was found that teaching method, learning place, educational media, relationship between teachers and Pre-cadets, relationship between Pre-cadets and their friends, and relationship between Pre-cadets and the commanders were significant.

Keywords: learning motivation factors, learning motivation, armed forces academies preparatory school, learning

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Due to increasing cost pressure in global markets, artificial intelligence is becoming a technology that is decisive for competition. Predictive quality enables machinery and plant manufacturers to ensure product quality by using data-driven forecasts via machine learning models as a decision-making basis for test results. The use of cross-process Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: predictive quality, hydraulics, machine learning, classification, supervised learning

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Authors: John Lloyd Angolluan, Jennile Caday, Crystal Mae Estrella, Reike Alliyah Taladua, Zion Michael Ysulat

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One of the requirements of having the ability to communicate in English is by having adequate vocabulary. Nowadays, people are more engaged in watching movie streams on which they can watch movies in a very portable way, such as Netflix. Wherein Netflix became global demand for online media has taken off in recent years. This research aims to know whether the use of bimodal subtitles on Netflix English movies can enhance vocabulary. This study is quantitative and utilizes a descriptive method, and this study aims to explore the use of bimodal subtitles on Netflix English movies to enhance the vocabulary of students. The respondents of the study were the selected Second-year English majors of Rizal Technological University Pasig and Boni Campus using the purposive sampling technique. The researcher conducted a survey questionnaire through the use of Google Forms. In this study, the weighted mean was used to evaluate the student's responses to the statement of the problems of the study of the use of bimodal subtitles on Netflix English movies. The findings of this study revealed that the bimodal subtitle on Netflix English movies enhanced students’ vocabulary learning acquisition by providing learners with access to large amounts of real and comprehensible language input, whether accidentally or intentionally, and it turns out that bimodal subtitles on Netflix English movies help students recognize vocabulary, which has a positive impact on their vocabulary building. Therefore, the researchers advocate that watching English Netflix movies enhances students' vocabulary by using bimodal subtitled movie material during their language learning process, which may increase their motivation and the usage of bimodal subtitles in learning new vocabulary. Bimodal subtitles need to be incorporated into educational film activities to provide students with a vast amount of input to expand their vocabulary.

Keywords: bimodal subtitles, Netflix, English movies, vocabulary, subtitle, language, media

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Authors: Mst. Tuhin Akter, Sharun Akter Khushbu, S. M. Shaqib

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A real-time system architecture is highly effective for monitoring and detecting various damaged products or fruits that may deteriorate over time or become infected with diseases. Deep learning models have proven to be effective in building such architectures. However, building a deep learning model from scratch is a time-consuming and costly process. A more efficient solution is to utilize deep neural network (DNN) based transfer learning models in the real-time monitoring architecture. This study focuses on using a novel strawberry dataset to develop effective transfer learning models for the proposed real-time monitoring system architecture, specifically for evaluating and detecting strawberry freshness. Several state-of-the-art transfer learning models were employed, and the best performing model was found to be Xception, demonstrating higher performance across evaluation metrics such as accuracy, recall, precision, and F1-score.

Keywords: strawberry freshness evaluation, deep neural network, transfer learning, image augmentation

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Authors: Sami Meddeb, M. L Giorgi, J. L. Courouau

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This work presents the progress of studies aiming to guarantee the lifetime of 316L(N) steel in a sodium-cooled fast reactor by determining the elementary corrosion mechanism, which is akin to an accelerated dissolution by dissolved oxygen. The mechanism involving iron, the main element of steel, is particularly studied in detail, from the viewpoint of the data available in the literature, the modeling of the various mechanisms hypothesized. Experiments performed in the CORRONa facility at controlled temperature and dissolved oxygen content are used to test both literature data and hypotheses. Current tests, performed at various temperatures and oxygen content, focus on specifying the chemical reaction at play, determining its free enthalpy, as well as kinetics rate constants. Specific test configuration allows measuring the reaction kinetics and the chemical equilibrium state in the same test. In the current state of progress of these tests, the dissolution of iron accelerated by dissolved oxygen appears as directly related to a chemical complexation reaction of mixed iron-sodium oxide (Na-Fe-O), a compound that is soluble in the liquid sodium solution. Results obtained demonstrate the presence in the solution of this corrosion product, whose kinetics is the limiting step under the conditions of the test. This compound, the object of hypotheses dating back more than 50 years, is predominant in solution compared to atomic iron, presumably even for the low oxygen concentration, and cannot be neglected for the long-term corrosion modeling of any heat transfer system.

Keywords: corrosion, sodium fast reactors, iron, oxygen

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Authors: Eskinder Desta Shumuye, Jun Zhao, Zike Wang

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This paper summarizes the results of experimental studies carried out at Zhengzhou University, School of Mechanics and Engineering Science, research laboratory, on the performance of concrete produced by combining Ordinary Portland Cement (OPC) with Ground-Granulated Blast Furnace Slag (GGBS). Concrete specimens cast with OPC and various percentage of GGBS (0%, 30%, 50%, and 70%) were subjected to high temperature exposure and extensive experimental test reproducing basic freeze-thaw cycle and a chloride-ion attack to determine their combined effects within the concrete samples. From the experimental studies, comparisons were made on the physical, mechanical, and microstructural properties in compassion with ordinary Portland cement concrete (OPC). Further, durability of GGBS cement concrete, such as exposure to accelerated carbonation, chloride ion attack, and freeze-thaw action in compassion with various percentage of GGBS and ordinary Portland cement concrete of similar mixture composition was analyzed. The microstructure, mineralogical composition, and pore size distribution of concrete specimens were determined via Scanning Electron Microscopy (SEM) analysis and X-Ray Diffraction (XRD). The result demonstrated that when the exposure temperature increases from 200 ºC to 400 ºC, the residual compressive strength was fluctuating for all concrete group, and compressive strength and chloride ion exposure of the concrete decreased with the increasing of slag content. The SEM and EDS results showed an increase in carbonation rate with increasing in slag content.

Keywords: accelerated carbonation, chloride-ion, concrete, ground-granulated blast furnace slag, GGBS, high-temperature

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Authors: Nasrin Badrkhani

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The increasing use of educational technologies has created a tremendous transformation in all fields and most importantly, in the field of education and learning. In recent decades, traditional learning approaches have undergone fundamental changes with the emergence of new learning technologies. Research shows that suitable educational tools play an effective role in the transmission, comprehension, and impact of educational concepts. These tools provide a tangible basis for thinking and constructing concepts, resulting in an increased interest in learning. They provide real and true experiences to students and convey educational meanings and concepts more quickly and clearly. It can be said that educational technology, as an active and modern teaching method, with capabilities such as engaging multiple senses in the educational process and involving the learner, makes the learning environment more flexible. It effectively impacts the skills of children with special needs by addressing their specific needs. Teachers are no longer the sole source of information, and students are not mere recipients of information. They are considered the main actors in the field of education and learning. Since education is one of the basic rights of every human being and children with special needs face unique challenges and obstacles in education, these challenges can negatively affect their abilities and learning. To combat these challenges, one of the ways is to use educational technologies for more diverse, effective learning. Also, the use of educational technology for students with special needs has increasingly proven effective in boosting their self-confidence and helping them overcome learning challenges, enhancing their learning outcomes.

Keywords: communication technology, students with special needs, self-confidence, raising the expectations and progress

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Authors: Sanskar, Abhinav Pal, Aryush Gupta, Sushil Kumar Mishra

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One of the critical and tedious assignments in agricultural practices is the detection of diseases on vegetation. Agricultural production is very important in today’s economy because plant diseases are common, and early detection of plant diseases is important in agriculture. Automatic detection of such early diseases is useful because it reduces control efforts in large productive farms. Using digital image processing and machine learning algorithms, this paper presents a method for plant disease detection. Detection of the disease occurs on different leaves of the plant. The proposed system for plant disease detection is simple and computationally efficient, requiring less time than learning-based approaches. The accuracy of various plant and foliar diseases is calculated and presented in this paper.

Keywords: plant diseases, machine learning, image processing, deep learning

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Authors: Aofan Liu, Qianqian Tan, Burra Venkata Durga Kumar

Abstract:

Data security is of the utmost importance in the healthcare area, as sensitive patient information is constantly sent around and analyzed by many different parties. The use of federated learning, which enables data to be evaluated locally on devices rather than being transferred to a central server, has emerged as a potential solution for protecting the privacy of user information. To protect against data breaches and unauthorized access, federated learning alone might not be adequate. In this context, the application of blockchain technology could provide the system extra protection. This study proposes a distributed federated learning system that is built on blockchain technology in order to enhance security in healthcare. This makes it possible for a wide variety of healthcare providers to work together on data analysis without raising concerns about the confidentiality of the data. The technical aspects of the system, including as the design and implementation of distributed learning algorithms, consensus mechanisms, and smart contracts, are also investigated as part of this process. The technique that was offered is a workable alternative that addresses concerns about the safety of healthcare while also fostering collaborative research and the interchange of data.

Keywords: data privacy, distributed system, federated learning, machine learning

Procedia PDF Downloads 133

Authors: Firas A. Al Laban, Mohamed Chabi, Sammani Danwawu Abdullahi

Abstract:

There are a real needs to integrate types of Open Educational Resources (OER) with an intelligent system to extract information and knowledge in the semantic searching level. Those needs raised because most of current learning standard adopted web based learning and the e-learning systems does not always serve all educational goals. Semantic Web systems provide educators, students, and researchers with intelligent queries based on a semantic knowledge management learning system. An ontology-based learning system is an advanced system, where ontology plays the core of the semantic web in a smart learning environment. The objective of this paper is to discuss the potentials of ontologies and mapping different kinds of ontologies; heterogeneous or homogenous to manage and control different types of Open Educational Resources. The important contribution of this research is to approach a methodology uses logical rules and conceptual relations to map between ontologies of different educational resources. We expect from this methodology to establish for an intelligent educational system supporting student tutoring, self and lifelong learning system.

Keywords: knowledge management systems, ontologies, semantic web, open educational resources

Procedia PDF Downloads 498

Authors: Dur-E- Shahwar

Abstract:

Much attention has been given to ‘bridging the gap’ between neuroscience and educational practice. In order to gain a better understanding of the nature of this gap and of possibilities to enable the linking process, we have taken a boundary perspective on these two fields and the brain-based learning approach, focusing on boundary-spanning actors, boundary objects, and boundary work. In 26 semi-structured interviews, neuroscientists and education professionals were asked about their perceptions in regard to the gap between science and practice and the role they play in creating, managing, and disrupting this boundary. Neuroscientists and education professionals often hold conflicting views and expectations of both brain-based learning and of each other. This leads us to argue that there are increased prospects for a neuro-scientifically informed learning practice if science and practice work together as equal stakeholders in developing and implementing neuroscience research.

Keywords: language learning, explore, educational practices, mentalist, practice

Procedia PDF Downloads 337