Search results for: student learning

Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

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Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek

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Discrete Choice Experiments (DCE) are used to investigate how product attributes affect decision-makers’ choices. In DCEs, choice situations consisting of several alternatives are presented from which choice-makers select the preferred alternative. Standard multinomial logit models based on random utility theory can be used to estimate the utilities for the attributes. The overarching principle in these models is that respondents understand and use all the attributes when making choices. However, studies suggest that respondents sometimes ignore some attributes (commonly referred to as Attribute Non-Attendance/ANA). The choice modeling literature presents ANA as a static process, i.e., respondents’ ANA behavior does not change throughout the experiment. However, respondents may ignore attributes due to changing factors like availability of information on attributes, learning/fatigue in experiments, etc. We develop a dynamic mixture latent Markov model to model changes in ANA when information on attributes is provided. The model is illustrated on e-consumers’ webshop choices. The results indicate that the dynamic ANA model describes the behavioral changes better than modeling the impact of information using changes in parameters. Further, we find that providing information on attributes leads to an increase in the attendance probabilities for the investigated attributes.

Keywords: choice models, discrete choice experiments, dynamic models, e-commerce, statistical modeling

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Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

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An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

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Authors: Flaviu Mihai Frigura-Lliasa, Andreea Anamaria Anghel, Attila Simo

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Due to the beauty, usefulness, science, constantly changing, constantly evolving features, and most of the time, mystery it involves, nature-based art is seen as a both modern and timeless direction that has been extensively used in design. The goal of the team's activities was to experiment with ways of fusing the two most common contemporary ways of referring to green installations, that is, either in a pure artistic or in an ecological manner, and creating a living, dynamic, interactive installation capable of both receiving and interpreting external factors, such as natural and human stimuli, that would not only determine some of the mechanism's presets. By consequent, a complex experiment made up of various research and project stages was elaborated in order to transform an idea into an actual interactive green installation within months thanks to the interaction, teamwork, and design processes undertaken throughout the academic years by both university lecturers and some of our students. The outcomes would lead to the development of a dynamic artwork called "Modgrew" as well as the introduction of experiment-based learning at the Timisoara Faculty of Architecture and Urban Planning, as well as at the Faculty of Electrical and Power Engineering, for the green wall automation issues.

Keywords: green design, living walls, modular structure, interactive proof of concept

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Authors: Valdênia Carvalho e Almeida

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The goal of the present study is to investigate the semantic preference of the most frequent adjectives in research articles through a corpus-based analysis of texts published in journals in Applied Linguistics (AL). The corpus used in this study contains texts published in the period from 2014 to 2018 in the three journals: Language Learning and Technology; English for Academic Purposes, and TESOL Quaterly, totaling more than one million words. A corpus-based analysis was carried out on the corpus to identify the most frequent adjectives that co-occurred in the three journals. By observing the concordance lines of the adjectives and analyzing the words they associated with, the semantic preferences of each adjective were determined. Later, the AL corpus analysis was compared to the investigation of the same adjectives in a corpus of Chemistry. This second part of the study aimed to identify possible differences and similarities between the two corpora in relation to the use of the adjectives in research articles from both areas. The results show that there are some preferences which seem to be closely related not only to the academic genre of the texts but also to the specific domain of the discipline and, to a lesser extent, to the context of research in each journal. This research illustrates a possible contribution of Corpus Linguistics to explore the concept of semantic preference in more detail, considering the complex nature of the phenomenon.

Keywords: applied linguistics, corpus linguistics, chemistry, research article, semantic preference

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Authors: Anant Sharma, Ashwin Rajan

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Customer experience is measured today based on defining a set of metrics and KPIs, setting up thresholds and defining triggers across those thresholds. While this is an effective way of measuring against a Key Performance Indicator ( referred to as KPI in the rest of the paper ), this approach cannot capture the various nuances that make up the overall customer experience. Customers consume a product or service at various levels, which is not reflected in metrics like Customer Satisfaction or Net Promoter Score, but also across other measurements like recurring revenue, frequency of service usage, e-learning and depth of usage. Here we explore an alternative method of measuring customer experience by flipping the traditional views. Rather than rolling customers up to a metric, we roll up metrics to hierarchies and then measure customer experience. This method allows any team to quantify customer experience across multiple touchpoints in a customer’s journey. We make use of various data sources which contain information for metrics like CXSAT, NPS, Renewals, and depths of service usage collected across a customer lifecycle. This data can be mined systematically to get linkages between different data points like geographies, business groups, products and time. Additional views can be generated by blending synthetic contexts into the data to show trends and top/bottom types of reports. We have created a framework that allows us to measure customer experience using the above logic.

Keywords: analytics, customers experience, BI, business operations, KPIs, metrics

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Authors: Edward Shizha, Edward Makwarimba

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Newcomer and refugee youth feel excluded in the education system in Canada, and the formal education environment does not fully cater for their learning needs. The objective of this study was to build knowledge and understanding of the educational needs and experiences of these youth in Canada and how available afterschool programs can most effectively support their learning needs and academic outcomes. The Employment and Social Development Canada (ESDC), which funded this research, enables and empowers students to advance their educational experience through targeted investments in services that are delivered by youth-serving organizations outside the formal education system through afterschool initiatives. A literature review and a provincial/territorial internet scan were conducted to determine the availability of services and programs that serve the educational needs and academic outcomes of newcomer youth in 10 provinces and 3 territories in Canada. The goal was to identify intersectional factors (e.g., gender, sexuality, culture, social class, race, etc.) that influence educational outcomes of newcomer/refugee students and to recommend ways the ESDC could complement settlement services to enhance students’ educational success. First, data was collected through a literature search of various databases, including PubMed, Web of Science, Scopus, Google docs, ACADEMIA, and grey literature, including government documents, to inform our analysis. Second, a provincial/territorial internet scan was conducted using a template that was created by ESDC staff with the input of the researchers. The objective of the web-search scan was to identify afterschool programs, projects, and initiatives offered to newcomer/refugee youth by service provider organizations. The method for the scan included both qualitative and quantitative data gathering. Both the literature review and the provincial/territorial scan revealed that there are gender disparities in educational outcomes of newcomer and refugee youth. High school completion rates by gender show that boys are at higher risk of not graduating than girls and that girls are more likely than boys to have at least a high school diploma and more likely to proceed to postsecondary education. Findings from literature reveal that afterschool programs are required for refugee youth who experience mental health challenges and miss out on significant periods of schooling, which affect attendance, participation, and graduation from high school. However, some refugee youth use their resilience and ambition to succeed in their educational outcomes. Another finding showed that some immigrant/refugee students, through ethnic organizations and familial affiliation, maintain aspects of their cultural values, parental expectations and ambitious expectations for their own careers to succeed in both high school and postsecondary education. The study found a significant combination of afterschool programs that include academic support, scholarships, bursaries, homework support, career readiness, internships, mentorship, tutoring, non-clinical counselling, mental health and social well-being support, language skills, volunteering opportunities, community connections, peer networking, culturally relevant services etc. These programs assist newcomer youth to develop self-confidence and prepare for academic success and future career development. The study concluded that advantages of afterschool programs are greatest for youth at risk for poor educational outcomes, such as Latino and Black youth, including 2SLGBTQI+ immigrant youth.

Keywords: afterschool programs, educational outcomes, newcomer youth, refugee youth, youth-serving organizations

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Authors: Ayeni Margaret Foluso, K. A. Omotayo

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This study investigated the impact of selected environmental variables as determinants of students’ achievements in biology in secondary schools. The selected environmental variables are class size and laboratory adequacy. The purpose was to find out whether these environmental variables can bring about improvement in the learning of biology by Senior Secondary School Students. The study design used was descriptive research of the survey type. Two instruments were used that is, Biology Achievement Test and School Environment Questionnaire .The population of the study consisted of all Biology students in both public and private Senior Secondary Schools class III (SSIII) in all the three selected states in South West Nigeria. A sample of 900 Biology students and 45 Biology Teachers from both public and private Senior Secondary Schools Class III were used. Two research hypotheses were generated for the study. The data collected were subjected to both descriptive statistics of mean and standard deviation; and the inferential statistics of regression Analyses was employed to test the hypotheses formulated. From the results, it was revealed that the selected environmental variables had influence on the students’ achievement in biology.

Keywords: environmental variables, determinants, students’ achievement, school science

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Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

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This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

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Authors: Guangyuan Zhao, Nan Huang, Xuesong Han, Xu Huang

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In order to solve the problem of sample dilution in the traditional particle filter algorithm and achieve accurate state estimation in a nonlinear system, a particle filter method based on an improved artificial bee colony (ABC) algorithm was proposed. The algorithm simulated the process of bee foraging and optimization and made the high likelihood region of the backward probability of particles moving to improve the rationality of particle distribution. The opposition-based learning (OBL) strategy is introduced to optimize the initial population of the artificial bee colony algorithm. The convergence factor is introduced into the neighborhood search strategy to limit the search range and improve the convergence speed. Finally, the crossover and mutation operations of the genetic algorithm are introduced into the search mechanism of the following bee, which makes the algorithm jump out of the local extreme value quickly and continue to search the global extreme value to improve its optimization ability. The simulation results show that the improved method can improve the estimation accuracy of particle filters, ensure the diversity of particles, and improve the rationality of particle distribution.

Keywords: particle filter, impoverishment, state estimation, artificial bee colony algorithm

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Authors: Sulaiman Al Amro

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There are currently considerable challenges concerning data security and privacy, particularly in relation to modern technologies. This includes the virtual world known as the Metaverse, which consists of a virtual space that integrates various technologies and is therefore susceptible to cyber threats such as malware, phishing, and identity theft. This has led recent studies to propose the development of Metaverse forensic frameworks and the integration of advanced technologies, including machine learning for intrusion detection and security. In this context, the application of first-order logic offers a formal and systematic approach to defining the conditions of cyberattacks, thereby contributing to the development of effective detection mechanisms. In addition, formalizing the rules and patterns of cyber threats has the potential to enhance the overall security posture of the Metaverse and, thus, the integrity and safety of this virtual environment. The current paper focuses on the primary actions employed by avatars for potential attacks, including Interval Temporal Logic (ITL) and behavior-based detection to detect an avatar’s abnormal activities within the Metaverse. The research established that the proposed framework attained an accuracy of 92.307%, resulting in the experimental results demonstrating the efficacy of ITL, including its superior performance in addressing the threats posed by avatars within the Metaverse domain.

Keywords: security, privacy, metaverse, cyberattacks, detection, first-order logic

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Authors: Chisakan Papapankiad

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The purposes of this research were 1) to study the competency of condominium managers, 2) to create the training curriculum via electronic media for condominium managers, and 3) to evaluate the training curriculum for condominium managers. The research methods included document analysis, interview, questionnaire, and a try-out. A total of 20 experts were selected to collect data by using Delphi technique. The designed curriculum was tried out with 30 condominium managers. The important steps of conducting this research included analyzing and synthesizing, creating interview questions, conducting factor analysis and developing the training curriculum, editing by experts, and trying out with sample groups. The findings revealed that there were five core competencies: leadership, human resources management, management, communication, and self-development. The training curriculum was designed and all the learning materials were put into a CD. The evaluation of the training curriculum was performed by five experts and the training curriculum was found to be cohesive and suitable for use in the real world. Moreover, the findings also revealed three important issues: 1) the competencies of the respondents after the experiment were higher than before the experiment and this had a level of significance of 0.01, 2) the competencies remained with the respondents at least 12 weeks and this also had a level of significance of 0.01, and 3) the overall level of satisfaction from the respondents were 'the highest level'.

Keywords: competency training curriculum, condominium managers, electronic media

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Authors: Glenn Koonce

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There is a need to address the improvement of university educational leadership preparation programs through the processes of accreditation and continuous improvement. The program faculty in a university in the eastern part of the United States has incorporated an employer satisfaction focus group to address their national accreditation standard so that employers are satisfied with completers' preparation for the position of principal or assistant principal. Using the Council for the Accreditation of Educator Preparation (CAEP) required proficiencies, the following research questions are investigated: 1) what proficiencies do completers perform the strongest? 2) what proficiencies need to be strengthened? 3) what other strengths beyond the required proficiencies do completers demonstrate? 4) what other areas of responsibility beyond the required proficiencies do completers demonstrate? and 5) how can the program improve in preparing candidates for their positions? This study focuses on employers of one public school district that has a large number of educational leadership completers employed as principals and assistant principals. Central office directors who evaluate principals and principals who evaluate assistant principals are focus group participants. Construction of the focus group questions is a result of recommendations from an accreditation regulatory specialist, reviewed by an expert panel, and piloted by an experienced focus group leader. The focus group session was audio recorded, transcribed, and analyzed using the NVivo Version 14 software. After constructing folders in NVivo, the focus group transcript was loaded and skimmed by diagnosing significant statements and assessing core ideas for developing primary themes. These themes were aligned to address the research questions. From the transcript, codes were assigned to the themes and NVivo provided a coding hierarchy chart or graphical illustration for framing the coding. A final report of the coding process was designed using the primary themes and pertinent codes that were supported in excerpts from the transcript. The outcome of this study is to identify themes that can provide evidence that the educational leadership program is meeting its mission to improve PreK-12 student achievement through well-prepared completers who have achieved the position of principal or assistant principal. The considerations will be used to derive a composite profile of employers' satisfaction with program completers with the capacity to serve, influence, and thrive as educational leaders. Analysis of the idealized themes will result in identifying issues that may challenge university educational leadership programs to improve. Results, conclusions, and recommendations are used for continuous improvement, which is another national accreditation standard required for the program.

Keywords: educational leadership preparation, CAEP accreditation, principal & assistant principal evaluations, continuous improvement

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Authors: Sukhdev Singh, Baljinder Singh Bal, Amandeep Singh, Kanchan Thappa

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A nation's future almost certainly rests on the future of its children, and a nation's wellbeing can be greatly improved by providing for the right upbringing of its children. Participating in physical education and sports programmes is crucial for reaching one's full potential. As we are all aware, sports have recently become incredibly popular on a global scale. Sports are continually becoming more and more popular, and this positive trend is probably going to last for some time to come. Motor abilities will provide more accurate information on the developmental process of children. Motor fitness is a component of physical fitness that includes strength, speed, flexibility, and agility, and is related to enhanced performance and the development of motor skills. In recent years, there has been increased interest in the differences in child growth between urban and rural environments. Differences in student growth, body dimensions, body composition, and fitness levels due to urban and rural environmental disparities have come into focus in recent years. The main aim of this study is to know the differentials of motor fitness components among the school children of rural and urban areas of the Jammu region. Material and Methods: In total, sixty male subjects (mean ± SD; age, 16.475 ± 1.0124 yrs.; height, 172.8 ± 2.0153 cm; Weight, 59.75 ± 3.628 kg) from the Jammu region took part in the study. A minimum sample size of 40 subjects was obtained and was derived from Rural (N1=20) and Urban (N2=20) school-going children. Statistical Applications: The Statistical Package for the Social Sciences (SPSS) version 14.0 was used for all analyses. The differences in the mean of each group for the selected variable were tested for the significance of difference by an independent samples t-test. For testing the hypotheses, the level of significance was set at 0.05. Results: Results revealed that there were significant differences of leg explosive strength (p=0.0040*), dynamic balance (p=0.0056*), and Agility (p=0.0176*) among the School Children of the rural and urban areas of the Jammu region. However, Results further revealed that there were not significant differences of cardio respiratory endurance (p=0.8612), speed (p=0.2231), Low Back/Hamstring Flexibility (p=0.6478), and Two Hand Coordination. (p= 0.0953) among the School Children of the rural and urban areas of the Jammu region. Conclusion: The results of study showed that there is significance difference between Rural and Urban School children of the Jammu region with regards to a variable," leg explosive strength, dynamic balance, Agility” and the there is no significance difference between Rural and Urban School children of the Jammu region with regards variable “cardio-respiratory endurance, speed, Low Back/Hamstring Flexibility, Two Hand Coordination”.

Keywords: motor fitness, rural areas, school children, urban areas

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Authors: Kayode E. Oyetade, Seraphin D. Eyono Obono

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Age ratings are very helpful in providing parents with relevant information for the purchase and use of digital technologies by the children; this is why the non-definition of age ratings for the use of ICT's by children in schools is a major concern; and this problem serves as a motivation for this study whose aim is to examine the factors affecting the perceptions of educators on the learners’ youngest age for the introduction of ICT's in schools. This aim is achieved through two types of research objectives: the identification and design of theories and models on age ratings, and the empirical testing of such theories and models in a survey of educators from the Camperdown district of the South African KwaZulu-Natal province. A questionnaire is used for the collection of the data of this survey whose validity and reliability is checked in SPSS prior to its descriptive and correlative quantitative analysis. The main hypothesis supporting this research is the association between the demographics of educators, their personality, and their perceptions on the learners’ youngest age for the introduction of ICT's in schools; as claimed by existing research; except that the present study looks at personality from three dimensions: self-actualized personalities, fully functioning personalities, and healthy personalities. This hypothesis was fully confirmed by the empirical study conducted by this research except for the demographic factor where only the educators’ grade or class was found to be associated with the personality of educators.

Keywords: age ratings, educators, e-learning, personality theories

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Authors: Anes Enakoa, Yawei Liang

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Question Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP). In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer selection is one of the main components of the QA, which is concerned with selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging especially in Arabic due to its particularities. To address this challenge, an approach is proposed to answer questions with multiple answer choices for Arabic QA systems based on Textual Entailment (TE) recognition. The developed approach employs a Support Vector Machine that considers lexical, semantic and syntactic features in order to recognize the entailment between the generated hypotheses (H) and the text (T). A set of experiments has been conducted for performance evaluation and the overall performance of the proposed method reached an accuracy of 67.5% with C@1 score of 80.46%. The obtained results are promising and demonstrate that the proposed method is effective for TE recognition task.

Keywords: information retrieval, machine learning, natural language processing, question answering, textual entailment

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Authors: Guebli Abdelkader, Reguieg Madani, Belkadi Adel, Sbaa Bouabdellah

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The identification of mechanical variables in the motor performance trajectory has a prominent role in improving skill performance, error-exceeding, it contributes seriously to solving some problems of learning and training. The study aims to highlight the indicators of motor performance for Paralympic athletes during the practicing sports between modelling and between excellence in motor performance, this by taking into account the distinction of athlete practicing with special behavioral skills for the Paralympic athletes. In the study, we relied on the analysis of some previous research of biomechanical performance indicators during some of the events sports (shooting activities in the Paralympic athletics, shooting skill in the wheelchair basketball). The results of the study highlight the distinction of disabled practitioners of sporting events identified in motor performance during practice, by overcoming some physics indicators in human movement, as a lower center of body weight, increase in offset distance, such resistance which requires them to redouble their efforts. However, the results of the study highlighted the strength of the correlation between biomechanical variables of motor performance and the digital level achievement similar to the other practitioners normal.

Keywords: sports, the disabled, motor performance, Paralympic

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Authors: Sinan Serkan Çağlı

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This study explores the effectiveness of incorporating storytelling tasks into language acquisition programs for young learners. The research investigates how storytelling, as a pedagogical tool, can contribute to the enhancement of language acquisition skills in children. Drawing upon relevant literature and empirical data, this article examines the impact of storytelling on vocabulary development, comprehension, and overall language proficiency in early childhood education in Turkey. The study adopts a qualitative approach, including classroom observations and interviews with teachers and students. Findings suggest that storytelling tasks not only foster linguistic competence but also stimulate cognitive and socio-emotional development in young learners. Additionally, the article explores various storytelling techniques and strategies suitable for different age groups. It is evident that integrating storytelling tasks into language learning environments can create engaging and effective opportunities for young learners to acquire language skills in a natural and enjoyable way. This research contributes valuable insights into the pedagogical practices that promote language acquisition in early childhood, emphasizing the significance of storytelling as a powerful educational tool, especially in Turkey for EFL students.

Keywords: storytelling, language acquisition, young learners, early childhood education, pedagogy, language proficiency

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Authors: Stefano Scippo, Damiana Luzzi, Stefano Cuomo, Maria Ranieri

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Background: In response to the rise in natural disasters linked to climate change, numerous studies on Disaster Risk Reduction Education (DRRE) have emerged since the '90s, mainly using a didactic transmission-based approach. Effective DRRE should align with an interactive, experiential, and participatory educational model, which can be costly and risky. A potential solution is using simulations facilitated by eXtended Reality (XR). Research Question: This study aims to conduct a scoping review to explore educational methodologies that use XR to enhance knowledge among teachers, students, and citizens about environmental risks, natural disasters (including climate-related ones), and their management. Method: A search string of 66 keywords was formulated, spanning three domains: 1) education and target audience, 2) environment and natural hazards, and 3) technologies. On June 21st, 2023, the search string was used across five databases: EBSCOhost, IEEE Xplore, PubMed, Scopus, and Web of Science. After deduplication and removing papers without abstracts, 2,152 abstracts (published between 2013 and 2023) were analyzed and 2,062 papers were excluded, followed by the exclusion of 56 papers after full-text scrutiny. Excluded studies focused on unrelated technologies, non-environmental risks, and lacked educational outcomes or accessible texts. Main Results: The 34 reviewed papers were analyzed for context, risk type, research methodology, learning objectives, XR technology use, outcomes, and educational affordances of XR. Notably, since 2016, there has been a rise in scientific publications, focusing mainly on seismic events (12 studies) and floods (9), with a significant contribution from Asia (18 publications), particularly Japan (7 studies). Methodologically, the studies were categorized into empirical (26) and non-empirical (8). Empirical studies involved user or expert validation of XR tools, while non-empirical studies included systematic reviews and theoretical proposals without experimental validation. Empirical studies were further classified into quantitative, qualitative, or mixed-method approaches. Six qualitative studies involved small groups of users or experts, while 20 quantitative or mixed-method studies used seven different research designs, with most (17) employing a quasi-experimental, one-group post-test design, focusing on XR technology usability over educational effectiveness. Non-experimental studies had methodological limitations, making their results hypothetical and in need of further empirical validation. Educationally, the learning objectives centered on knowledge and skills for surviving natural disaster emergencies. All studies recommended XR technologies for simulations or serious games but did not develop comprehensive educational frameworks around these tools. XR-based tools showed potential superiority over traditional methods in teaching risk and emergency management skills. However, conclusions were more valid in studies with experimental designs; otherwise, they remained hypothetical without empirical evidence. The educational affordances of XR, mainly user engagement, were confirmed by the studies. Authors’ Conclusions: The analyzed literature lacks specific educational frameworks for XR in DRRE, focusing mainly on survival knowledge and skills. There is a need to expand educational approaches to include uncertainty education, developing competencies that encompass knowledge, skills, and attitudes like risk perception.

Keywords: disaster risk reduction education, educational technologies, scoping review, XR technologies

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Authors: Raied Khayou

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The Hawza Al-'Ilmiyya is a network of religious seminaries in the Shia branch of Islam. This research mainly focuses on the oldest school located in Najaf, Iraq, because its core curriculum and main characteristics have been unchanged since the fourth century of Islam. Relying on a thorough literature review of Arabic and English publications, and interviews with current and previous students of the seminary, the current research outlines the factors proving how this seminary was crucial in keeping the Shia religious identity intact despite sometimes gruesome attempts of interference and persecution. There are several factors that helped the seminary to preserve its central importance. First, rooted in their theology, Shia Muslims believe that the Hawza Al-’Ilmiyya and its graduates carry a sacred authority. Secondly, the financial independence of the Seminary helped to keep it intact from any governmental or political meddling. Third, its unique teaching method, its matchless openness for new students, and its flexible curriculum made it attractive for many students who were interested in learning more about Shia theology and jurisprudence. The Hawza Al-‘Ilmiyya has the exclusive right to train clerics who hold the religious authority of Shia Islamic jurisprudence, and the seminary’s success in staying independent throughout history kept Shia Islamic theology independent, as well.

Keywords: Hawza Al'Ilmiyya, religious seminary, Shia Muslim education, Islamic jurisprudence

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Authors: Eteri Kharaishvili, Marina Chavleishvili, Manana Lobzhanidze, Nino Grigolia

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The article analyzes Georgia's involvement in global migration processes, assessing migration research and policy regulatory documents. The socio-economic situation of young people has been studied in the paper, their employment and unemployment levels are analyzed, reasons for migration of youth are revealed, the impact of migration on the socio-economic development of the country is substantiated. Youth demand on education is also assessed, problems in the education sector are identified, educational migration indicators are analyzed according to the internationalization process of this sector. Based on the analysis of the motivations of young people in Georgia, orientation of values and the aspects conditioning life strategies the factors affecting educational migration are determined and the results of the positive and negative impact of educational migration on the socio-economic development of the country are substantiated. The importance of efficient management of educational migration for Georgia in getting closer to the EU and achieving inclusive economic grow this substantiated. Recommendations for efficient management of the process of Georgian citizens’ learning and acquiring experience, as well as the internationalization of education sector and educational migration, are drawn.

Keywords: educational migration, migration management, migration of youth, socio-economic results of educational migration, youth employment

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Authors: Sharif Muddsair, Eisels Martin, Giesbrecht Eugenie

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With development of society increase the demand for the movement of people also increases gradually. The various modes of the transport in different extent which expat impacts, which depends on mainly technical-operating conditions. The up-to-date telematics systems provide the transport industry a revolutionary. Appropriate use of these systems can help to substantially improve the efficiency. Vehicle monitoring and fleet tracking are among services used for improving efficiency and effectiveness of utility vehicle. There are many telematics systems which may contribute to eco-driving. Generally, they can be grouped according to their role in driving cycle. • Before driving - eco-route selection, • While driving – Advanced driver assistance, • After driving – remote analysis. Our point of interest is regulated in third point [after driving – remote analysis]. TS [Telematics-system] make it possible to record driving patterns in real time and analysis the data later on, So that driver- classification-specific hints [fast driver, slow driver, aggressive driver…)] are given to imitate eco-friendly driving style. Together with growing number of vehicle and development of information technology, telematics become an ‘active’ research subject in IT and the car industry. Telematics has gone a long way from providing navigation solution/assisting the driver to become an integral part of the vehicle. Today’s telematics ensure safety, comfort and become convenience of the driver.

Keywords: internet of things, iot, connected vehicle, cv, ts, telematics services, ml, machine learning

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Authors: Jiawen Wang, Qijun Chen

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The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

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Authors: Angela Obose Oriazowanlan

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Despite the introduction of Entrepreneurship education into the Nigerian University curriculum to prepare graduates for self-employment roles in order to abate employment challenges, their unemployment rate still soars high. The study, therefore, examined the relevance of the curriculum contents and its delivery mechanism to equip graduates with appropriate entrepreneurial skills prior to graduation. Four research questions and two hypotheses guided the study. The survey research design was adopted for the study. An infinite population of graduates of a period of five years with 200 sample representatives using the simple random sampling technique was adopted. A 45-item structured questionnaire was used for data gathering. The gathered data thereof was anlysed using the descriptive statistics of mean and standard deviation, while the formulated hypotheses were tested with Z-score at 0.5 level of significance. The findings revealed, among others, that graduates acquisition of appropriate entrepreneurial skills for self-employment generation is low due to curriculum deficiencies, insufficient time allotment, and the delivery mechanism. It was recommended, among others, that the curriculum should be reviewed to improve its relevancy and that sufficient time should be allotted to enable adequate teaching and learning process.

Keywords: evaluation of entrepreneurship education (EE) curriculum, self-employment generation, graduates of tertiary institutions, Edo state, Nigeria

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Authors: Muhammad Sollehhuddin A. Jalil, Mohd Ibrahim Shapiai, Rubiyah Yusof

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Nowadays, ontology is common in many areas like artificial intelligence, bioinformatics, e-commerce, education and many more. Ontology is one of the focus areas in the field of Information Retrieval. The purpose of an ontology is to describe a conceptual representation of concepts and their relationships within a particular domain. In other words, ontology provides a common vocabulary for anyone who needs to share information in the domain. There are several ontology domains in various fields including engineering and non-engineering knowledge. However, there are only a few available ontology for engineering knowledge. Fuzzy logic as engineering knowledge is still not available as ontology domain. In general, fuzzy logic requires step-by-step guidelines and instructions of lab experiments. In this study, we presented domain ontology for Fuzzy Logic Control (FLC) knowledge. We give Table of Content (ToC) with middle strategy based on the Uschold and King method to develop FLC ontology. The proposed framework is developed using Protégé as the ontology tool. The Protégé’s ontology reasoner, known as the Pellet reasoner is then used to validate the presented framework. The presented framework offers better performance based on consistency and classification parameter index. In general, this ontology can provide a platform to anyone who needs to understand FLC knowledge.

Keywords: engineering knowledge, fuzzy logic control ontology, ontology development, table of content

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Authors: Nazym Alykpashova

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This article is based on the results of the action research at Nazarbayev Intellectual School in Pavlodar, Kazakhstan. The participants of this research were high school students who study Global Perspectives and Project Work course. Intellectual schools are designed to become an experimental site that develops, monitors, studies, analyzes, approves, implements modern models of educational programs. Subjects in NIS aimed to develop skills that will be useful for students in their life. Students learn how to do projects, research credible information, solve different issues. Many subjects cover complex topics, and most teachers feel that they often have to deliver a lot of information within one hour. Many educators recognize Conceptual Teaching, as well as Conceptual Learning, has a lot of benefits for students in terms of developing their perception of the subject topics. This qualitative paper presents findings of two research questions which explored high school students’ perception of conceptual teaching and its impact on their academic performance. Individual semi-structured interviews and observations were conducted with Global Perspectives teachers and students. The results of this action research assist teachers reflect on their professional practice.

Keywords: concept-based teaching, students’ research skills, teacher’s professional development, kazakhstan

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Authors: Asma Ameur, Dhafer Malouche

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Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

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Authors: Ming-Yen Chang, Sheng-Hung Ke

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This research focuses on the development of a speed bump identification system for real-time control of adjustable shock absorbers in vehicular suspension systems. The study initially involved the collection of images of various speed bumps, and rubber speed bump profiles found on roadways. These images were utilized for training and recognition purposes through the deep learning object detection algorithm YOLOv5. Subsequently, the trained speed bump identification program was integrated with an in-vehicle camera system for live image capture during driving. These images were instantly transmitted to a computer for processing. Using the principles of monocular vision ranging, the distance between the vehicle and an approaching speed bump was determined. The appropriate control distance was established through both practical vehicle measurements and theoretical calculations. Collaboratively, with the electronically adjustable shock absorbers equipped in the vehicle, a shock absorber control system was devised to dynamically adapt the damping force just prior to encountering a speed bump. This system effectively mitigates passenger discomfort and enhances ride quality.

Keywords: adjustable shock absorbers, image recognition, monocular vision ranging, ride

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Authors: Shimaa Holail, Tamer Saleh, Xiongwu Xiao

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Building change detection (BCD) from satellite imagery is an essential topic in urbanization monitoring, agricultural land management, and updating geospatial databases. Recently, methods for detecting changes based on deep learning have made significant progress and impressive results. However, it has the problem of being insensitive to changes in buildings with complex spectral differences, and the features being extracted are not discriminatory enough, resulting in incomplete buildings and irregular boundaries. To overcome these problems, we propose a dual Siamese network based on the Unet model with the addition of a deep supervision strategy (DS) in this paper. This network consists of a backbone (encoder) based on ImageNet pre-training, a fusion block, and feature pyramid networks (FPN) to enhance the step-by-step information of the changing regions and obtain a more accurate BCD map. To train the proposed method, we created a new dataset (EGY-BCD) of high-resolution and multi-temporal aerial images captured over New Cairo in Egypt to detect building changes for this purpose. The experimental results showed that the proposed method is effective and performs well with the EGY-BCD dataset regarding the overall accuracy, F1-score, and mIoU, which were 91.6 %, 80.1 %, and 73.5 %, respectively.

Keywords: building change detection, deep supervision, semantic segmentation, EGY-BCD dataset

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Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

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Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

Procedia PDF Downloads 378