Search results for: hybrid project-based learning

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: Mikheil Kalmakhelidze

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Record linkage (RL) problem has become more and more important in recent years due to the growing interest towards big data analysis. The problem can be formulated in a very simple way: Given two entries a and b of a database, decide whether they represent the same object or not. There are two classical deterministic and probabilistic ways of solving the RL problem. Using simple Bayes classifier in many cases produces useful results but sometimes they show to be poor. In recent years several successful approaches have been made towards solving specific RL problems by neural network algorithms including single layer perception, multilayer back propagation network etc. In our work, we model the RL problem for specific dataset of student applications in fuzzy description logic (FDL) where linkage of specific pair (a,b) depends on the truth value of corresponding formula A(a,b) in a canonical FDL model. As a main result, we build neural network for deciding truth value of FDL formulas in a canonical model and thus link RL problem to machine learning. We apply the approach to dataset with 10000 entries and also compare to classical RL solving approaches. The results show to be more accurate than standard probabilistic approach.

Keywords: description logic, fuzzy logic, neural networks, record linkage

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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: 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: Abraham Motlhabane

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This research analysed the written views of science education students regarding the teaching of laboratory work using the online mode. The research adopted the qualitative methodology. The qualitative research was aimed at investigating small and distinct groups normally regarded as a single-site study. Qualitative research was used to describe and analyze the phenomena from the student’s perspective. This means the research began with assumptions of the world view that use theoretical lenses of research problems inquiring into the meaning of individual students. The research was conducted with three groups of students studying for Postgraduate Certificate in Education, Bachelor of Education and honors Bachelor of Education respectively. In each of the study programmes, the science education module is compulsory. Five science education students from each study programme were purposively selected to participate in this research. Therefore, 15 students participated in the research. In order to analysis the data, the data were first printed and hard copies were used in the analysis. The data was read several times and key concepts and ideas were highlighted. Themes and patterns were identified to describe the data. Coding as a process of organising and sorting data was used. The findings of the study are very diverse; some students are in favour of online laboratory whereas other students argue that science can only be learnt through hands-on experimentation.

Keywords: online learning, laboratory work, views, perceptions

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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: Gabriela Wyszogrodzka, Przemyslaw Dorozynski, Barbara Gil, Maciej Strzempek, Bartosz Marszalek, Piotr Kulinowski, Wladyslaw Piotr Weglarz, Elzbieta Menaszek

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MOFs (Metal-Organic Frameworks) belong to a new group of porous materials with a hybrid organic-inorganic construction. Their structure is a network consisting of metal cations or clusters (acting as metallic centers, nodes) and the organic linkers between nodes. The interest in MOFs is primarily associated with the use of their well-developed surface and large porous. Possibility to build MOFs of biocompatible components let to use them as potential drug carriers. Furthermore, forming MOFs structure from cations possessing paramagnetic properties (e.g. iron cations) allows to use them as MRI (Magnetic Resonance Imaging) contrast agents. The concept of formation of particles that combine the ability to transfer active substance with imaging properties has been called theranostic (from words combination therapy and diagnostics). By building MOF structure from iron cations it is possible to use them as theranostic agents and monitoring the distribution of the active substance after administration in real time. In the study iron-MOF: Fe-MIL-101-NH2 was chosen, consisting of iron cluster in nodes of the structure and amino-terephthalic acid as a linker. The aim of the study was to investigate the possibility of applying Fe-MIL-101-NH2 as inhalable theranostic particulate system for the first-line anti-tuberculosis antibiotic – isoniazid. The drug content incorporated into Fe-MIL-101-NH2 was evaluated by dissolution study using spectrophotometric method. Results showed isoniazid encapsulation efficiency – ca. 12.5% wt. Possibility of Fe-MIL-101-NH2 application as the MRI contrast agent was demonstrated by magnetic resonance tomography. FeMIL-101-NH2 effectively shortening T1 and T2 relaxation times (increasing R1 and R2 relaxation rates) linearly with the concentrations of suspended material. Images obtained using multi-echo magnetic resonance imaging sequence revealed possibility to use FeMIL-101-NH2 as positive and negative contrasts depending on applied repetition time. MOFs micronization via ultrasound was evaluated by XRD, nitrogen adsorption, FTIR, SEM imaging and did not influence their crystal shape and size. Ultrasonication let to break the aggregates and achieve very homogeneously looking SEM images. MOFs cytotoxicity was evaluated in in vitro test with a highly sensitive resazurin based reagent PrestoBlue™ on L929 fibroblast cell line. After 24h no inhibition of cell proliferation was observed. All results proved potential possibility of application of ironMOFs as an isoniazid carrier and as MRI contrast agent in inhalatory treatment of tuberculosis. Acknowledgments: Authors gratefully acknowledge the National Science Center Poland for providing financial support, grant no 2014/15/B/ST5/04498.

Keywords: imaging agents, metal-organic frameworks, theranostics, tuberculosis

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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: Yuying Liu

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Despite the increasing popularity of Chinese and the recognition of the growing commodifying ideology of Chinese language in many contexts (Liu and Gao, 2020; Guo, Shin and Shen 2020), the ideological orientations of the Chinese diaspora community towards the Chinese language remain under-researched. This research contributes seeks to bridge this gap by investigating the micro-level language ideologies embedded in the Chinese complementary schools in the Republic of Ireland. Informed by Ruíz’s (1984) metaphorical representations of language, 11 Chinese complementary schools’ websites were analysed as discursive texts that signal the language policy and ideology to prospective learners and parents were analysed. The results of the analysis suggest that a move from a portrayal of Chinese as linked to student heritage identity, to the commodification of linguistic and cultural diversity, is evident. It denotes the growing commodifying ideology among the Chinese complementary schools in the Republic of Ireland. The changing profile of the complementary school, from serving an ethnical community to teaching Chinese as a foreign language for the wider community, indicates the possibility of creating the a positive synergy between the Complementary school and the mainstream education. This study contributes to the wider discussions of language ideology and language planning, with regards to modern language learning and heritage language maintenance.

Keywords: the Chinese language;, Chinese as heritage language, Chinese as foreign language, Chinese community schools

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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: Susana Barreto

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This paper explores a pedagogical exercise that employs family photos as catalysts for teaching visual analysis and inspiring academic writing among MA students. The study aimed to achieve two primary objectives: to impart students with the skills of analyzing images or artifacts and to ignite their writing for research purposes. Conducted at Viana Polytechnic in Portugal, the exercise involved two classes on Arts Management and Art Education Master course comprising approximately twenty students from diverse academic backgrounds, including Economics, Design, Fine Arts, and Sociology, among others. The exploratory exercise involved selecting an old family photo, analyzing its content and context, and deconstructing the chosen images in an intuitive and systematic manner. Students were encouraged to engage in photo elicitation, seeking insights from family/friends to gain multigenerational perspectives on the images. The feedback received from this exercise was consistently positive, largely due to the personal connection students felt with the objects of analysis. Family photos, with their emotional significance, fostered deeper engagement and motivation in the learning process. Furthermore, visual analysing family photos stimulated critical thinking as students interpreted the composition, subject matter, and potential meanings embedded in the images. This practice enhanced their ability to comprehend complex visual representations and construct compelling visual narratives, thereby facilitating the writing process. The exercise also facilitated the identification of patterns, similarities, and differences by comparing different family photos, leading to a more comprehensive analysis of visual elements and themes. Throughout the exercise, students found analyzing their own photographs both enjoyable and insightful. They progressed through preliminary analysis, explored content and context, and artfully interwove these components. Additionally, students experimented with various techniques such as converting photos to black and white, altering framing angles, and adjusting sizes to unveil hidden meanings.The methodology employed included observation, documental analysis of written reports, and student interviews. By including students from diverse academic backgrounds, the study enhanced its external validity, enabling a broader range of perspectives and insights during the exercise. Furthermore, encouraging students to seek multigenerational perspectives from family and friends added depth to the analysis, enriching the learning experience and broadening the understanding of the cultural and historical context associated with the family photos Highlighting the emotional significance of these family photos and the personal connection students felt with the objects of analysis fosters a deeper connection to the subject matter. Moreover, the emphasis on stimulating critical thinking through the analysis of composition, subject matter, and potential meanings in family photos suggests a targeted approach to developing analytical skills. This improvement focuses specifically on critical thinking and visual analysis, enhancing the overall quality of the exercise. Additionally, the inclusion of a step where students compare different family photos to identify patterns, similarities, and differences further enhances the depth of the analysis. This comparative approach adds a layer of complexity to the exercise, ultimately leading to a more comprehensive understanding of visual elements and themes. The expected results of this study will culminate in a set of practical recommendations for implementing this exercise in academic settings.

Keywords: visual analysis, academic writing, pedagogical exercise, family photos

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Authors: Brad Curabba

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Utilising active, process-based learning methods to improve critical thinking and writing skills of second language (L2) writers brings unique challenges. To comprehensively satisfy different learners' needs, when commenting on student work, instructors can embed multiple feedback methods so that the capstone of their abilities as writers can be achieved. This research project assesses faculty and student perceptions regarding the effectiveness of various feedback practices used in process-based writing classrooms with L2 students at the American University of Sharjah (AUS). In addition, the research explores the challenges encountered by faculty during the provision of feedback practices. The quantitative research findings are based on two concurrent electronically distributed anonymous surveys; one aimed at students who have just completed a process-based writing course, and the other at instructors who delivered these courses. The student sample is drawn from multiple sections of Academic Writing I and II, and the faculty survey was distributed among the Department of Writing Studies (DWS) faculty. Our findings strongly suggest that all methods of feedback are deemed equally important by both students and faculty. Students, in particular, find process writing and its feedback practices to have greatly contributed to their writing proficiency.

Keywords: process writing, feedback, formative feedback, composition, reflection

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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: Malin Isaksson

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Teaching French as a foreign language usually implies teaching French literature, especially in higher education. Training university students in literary reading in a foreign language requires addressing several aspects at the same time: the (foreign) language, the poetic language, the aesthetic aspects of the studied works, and various interpretations of them. A pilot study sought to test a teaching model that would support students in learning to perform competent readings and short analyses of French literary works, in a rather independent manner. This shared practice paper describes the use of a flipped classroom method in two French literature courses, a campus course and an online course, and suggests that the teaching model may provide efficient tools for teaching literary reading and analysis in a foreign language. The teaching model builds on a high level of student activity and focuses on attentive reading, meta-perspectives such as theoretical concepts, individual analyses by students where said concepts are applied, and group discussions of the studied texts and of possible interpretations.

Keywords: attentive reading, flipped classroom, literature in foreign language studies, teaching literature analysis

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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

Abstract:

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

Abstract:

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

Abstract:

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

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Authors: Rakesh Choudhary, Ajay Kumar, Deepak Sharma

Abstract:

The main goal of this paper is to investigate the challenges and benefits of IoT integration in biogas production. This overview explains how the inclusion of IoT can enhance biogas production efficiency. Therefore, such collected data can be explored by advanced analytics, including Artificial intelligence (AI) and Machine Learning (ML) algorithms, consequently improving bio-energy processes. To boost biogas generation efficiency, this report examines the use of IoT devices for real-time data collection on key parameters, e.g., pH, temperature, gas composition, and microbial growth. Real-time monitoring through big data has made it possible to detect diverse, complex trends in the process of producing biogas. The Informed by advanced analytics can also help in improving bio-energy production as well as optimizing operational conditions. Moreover, IoT allows remote observation, control and management, which decreases manual intervention needed whilst increasing process effectiveness. Such a paradigm shift in the incorporation of IoT technologies into biogas production systems helps to achieve higher productivity levels as well as more practical biomass quality biomethane through real-time monitoring-based proactive decision-making, thus driving continuous performance improvement.

Keywords: internet of things, biogas, renewable energy, sustainability, anaerobic digestion, real-time monitoring, optimization

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Authors: Hatib Shabbir

Abstract:

Student support services play an important role in providing technical and motivational support to distance learner. ICT based systems have improved the efficiency and effectiveness of support services. In distance education, students being at distant require quick responses from their institution. In the manual system, it is practically hard to give prompt response to each and every student, so as a result student has to suffer a lot. The best way to minimize inefficiencies is to use automated systems. This project involves the development of centralized automated software that would not only replace the manual degree issuance system of 1.3 million students studying at AIOU but also provide online tracking to all the students applying for Degrees. DTS is also the first step towards the paperless culture which is adopted by the major organizations of the world. DTS would not only save university cost but also save students cost and time too by conveying all the information/objection through email and SMS. Moreover, DTS also monitors the performance of each and every individual working in the exam department AIOU and generates daily, monthly and yearly reports of every individual which helps a lot in continuous performance monitoring of the employees.

Keywords: aiou dts, dts aiou, dts, degree tracking aiou

Procedia PDF Downloads 218