Search results for: learning networks

Authors: Mehdi Damaliamiri, Firouzeh Akbari

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Teaching literature to children at an early age is of great importance, and there have been different methods to facilitate learning literature. Based on the law, all children going to school in Iran should learn the Persian language and literature. This has been concomitant with two different levels of learning related to urban or rural bilingualism. For bilingual children living in the villages, learning literature and a new language (Persian) turns into a big challenge as it is done based on the translation the teacher does while in the city, it is easier as the confrontation of children with the Persian language is more. Over recent years, to change the trend of learning Persian by children speaking another language, the TV and radio programs have been considered to be effective, but the scores of the students in Persian language national exams show that these programs have not been so effective for the bilingual students living in the villages. To identify the determinants of weak learning of Persian by bilingual children, two different regions were chosen, Turkish-speaking and Kurdish-speaking communities, to compare their learning of Persian at the first and second levels of elementary school. The criteria of learning was based on the syllabification of Persian words, word order in the sentence, and compound sentences. Students were taught in Persian how to recognize syllabification without letting them translate the words in their own languages and were asked to produce simple sentences in Persian in response to situational questions. Teaching methods, language relatedness with Persian, and exposure to social media programs, especially TV and radio, were the factors that were considered to affect the potential of children in learning Persian.

Keywords: bilingualism, persian, education, Literature

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Authors: Noga Bregman

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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

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Authors: H. Kiani, S. Moradi, B. Soltani Soulgani, S. Mousavian

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Desalting/dehydration plants (DDP) are often installed in crude oil production units in order to remove water-soluble salts from an oil stream. In order to optimize this process, desalting unit should be modeled. In this research, artificial neural network is used to model efficiency of desalting unit as a function of input parameter. The result of this research shows that the mentioned model has good agreement with experimental data.

Keywords: desalting unit, crude oil, neural networks, simulation, recovery, separation

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Authors: Mei-Ying Liao, Lee-Ching Wei, Jung-Hsiang Tseng

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The main purpose of this study was to explore the process of planning and execution of the music learning center in preschool. This study was conducted through a collaborative action research method. The research members included a university music professor, a teaching guide, a preschool director, and a preschool teacher, leading a class of 5-6-year-old children to participate in this study. Five teaching cycles were performed with a subject of bird. In the whole process that lasted three months, the research members would maintain the conversation, reflection, and revision repeatedly. A triangular validated method was used to collect data, including archives, interviews, seminars, observations, journals, and learning evaluations to improve research on the validity and reliability. It was found that a successful music learning center required comprehensive planning and execution. It is also important to develop good listening, singing, respect, and homing habits at the beginning of running the music learning center. By timely providing diverse musical instruments, learning materials, and activities according to the teaching goals, children’s desire to learning was highly stimulated. Besides, peer interactions improved their ensemble and problem-solving abilities. The collaborative action research enhanced the preschool teacher’s confidence and promoted professional growth of the research members.

Keywords: collaborative action research, case study, music learning center, music development

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Authors: Pia Kastl

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Potentials of blended learning are the flexibility of learning and the possibility to get in touch with lecturers and fellow students on site. By combining face-to-face sessions with digital self-learning units, the learning process can be optimized, and learning success increased. To examine wether blended learning outperforms online and face-to-face teaching, a theory-based questionnaire survey was conducted. The results show that the interaction and cooperation among students is poorly provided in blended learning, and face-to-face teaching performs better in this respect. The aim of this article is to identify concrete suggestions students have for improving cooperation and interaction in blended learning courses. For this purpose, interviews were conducted with students from various academic disciplines in face-to-face, online, or blended learning courses (N= 60). The questions referred to opinions and suggestions for improvement regarding the course design of the respective learning environment. The analysis was carried out by qualitative content analysis. The results show that students perceive the interaction as beneficial to their learning. They verbalize their knowledge and are exposed to different perspectives. In addition, emotional support is particularly important in exam phases. Interaction and cooperation were primarily enabled in the face-to-face component of the courses studied, while there was very limited contact with fellow students in the asynchronous component. Forums offered were hardly used or not used at all because the barrier to asking a question publicly is too high, and students prefer private channels for communication. This is accompanied by the disadvantage that the interaction occurs only among people who already know each other. Creating contacts is not fostered in the blended learning courses. Students consider optimization possibilities as a task of the lecturers in the face-to-face sessions: Here, interaction and cooperation should be encouraged through get-to-know-you rounds or group work. It is important here to group the participants randomly to establish contact with new people. In addition, sufficient time for interaction is desired in the lecture, e.g., in the context of discussions or partner work. In the digital component, students prefer synchronous exchange at a fixed time, for example, in breakout rooms or an MS Teams channel. The results provide an overview of how interaction and cooperation can be implemented in blended learning courses. Positive design possibilities are partly dependent on subject area and course. Future studies could tie in here with a course-specific analysis.

Keywords: blended learning, higher education, hybrid teaching, qualitative research, student learning

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Authors: Ahmed Amin Mousa, Huda Mazeed, Eman Saad

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The study aims to identify the extent of the effectiveness of the artistic formation program using some types of pastes to reduce the hyperactivity of the kindergarten child. The researcher has discussed the effectiveness of the artistic program using some types of pastes in reducing the hyperactivity of the kindergarten child. The research sample included 120 children of ages between 5 to 6 years old from the five schools for special needs section learning disability, Cairo Province. The study used the empirical like curriculum which depends on designing one group using the before and after application measurement for the group to validate the fidelity of both the hypothesis and the effectiveness of the program. The variables of the study were specified as follows; artistic formation program using paper Mache as an independent variable and its effect on skills of kindergarten child with learning disabilities as a subsequent variable. The researchers depended on applying a group of artistic formation program using pulp melding skills for kindergarten children with learning disabilities. The tools of the study, designed by the researcher, included: recording card used for recording the Effective program using pulp molding skills for kindergarten children with learning disabilities during practicing the artistic formation activity. In additional, there was a program using pulp molding skills for kindergarten children with learning disabilities. The results proved the effectiveness of the program using pulp molding skills for kindergarten children with learning disabilities.

Keywords: artistic program, developing skills, kindergarten, children, learning disabilities

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Authors: Ibraheem Alzahrani

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The Saudi Arabia ministry of higher education has established 24 universities across various cities in the kingdom. The universities have the mandate of sustaining technological progress in both teaching and learning. The present study explores the statues of teaching in Saudi universities, focusing on biology, a critical curriculum. The paper explores biology teachers’ points of view is several Saudi higher education institutions through questionnaires disseminated via emails. According to the findings, the current teaching methods are traditional and the teachers believe that it is critical to change it. This study also, reviews how biology has been taught in the kingdom over the past, as well as how it is undertaken presently. In addition, some aspects of biology teaching are considered, including the biology curriculum and learning objectives in higher education biology.

Keywords: higher education, teaching style, traditional learning, electronic learning, web 2.0 applications, blended learning

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Authors: Qusay Alghazali, Tibor Cinkler, Abdulhalim Fayad

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In modern optical networks, the flex grid spectrum usage is most widespread, where higher bit rate streams get larger spectrum slices while lower bit rate traffic streams get smaller spectrum slices. To our practice, under the ITU-T recommendation, G.694.1, spectrum slices of 50, 75, and 100 GHz are being used with central frequency at 193.1 THz. However, when these spectrum slices are not sufficient, multiple spectrum slices can use either one next to another or anywhere in the optical wavelength. In this paper, we propose the analysis of the wavelength assignment problem. We compare different algorithms for this spectrum assignment with and without protection. As a reference for comparisons, we concluded that the Integer Linear Programming (ILP) provides the global optimum for all cases. The most scalable algorithm is the greedy one, which yields results in subsequent ranges even for more significant network instances. The algorithms’ benchmark implemented using the LEMON C++ optimization library and simulation runs based on a minimum number of spectrum slices assigned to lightpaths and their execution time.

Keywords: spectrum assignment, integer linear programming, greedy algorithm, international telecommunication union, library for efficient modeling and optimization in networks

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Authors: Deonie Botha

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Digital transformation and the digitization of occupational health and safety training have grown exponentially due to a variety of contributing factors. The literature suggests that digitalization has numerous benefits but also has associated challenges. The aim of the paper is to develop an understanding of both the perceived benefits and challenges of digitalization in an occupational health and safety context in an effort to design and develop e-learning interventions that will optimize the benefits of digitalization and address the associated challenges. The paper proposes, deliberate and tests the design principles of an e-learning intervention to ensure alignment with the requirements of a digitally transformed environment. The results of the research are based on a literature review regarding the requirements and effect of the Fourth Industrial Revolution on learning and e-learning in particular. The findings of the literature review are enhanced with empirical research in the form of a case study conducted in an organization that designs and develops e-learning content in the occupational health and safety industry. The primary findings of the research indicated that: (i) The requirements of learners and organizations in respect of e-learning are different than previously (i.e., a pre-Fourth Industrial Revolution related work setting). (ii) The design principles of an e-learning intervention need to be aligned with the entire value chain of the organization. (iii) Digital twins support and enhance the design and development of e-learning. (iv)Learning should incorporate a multitude of sensory experiences and should not only be based on visual stimulation. (v) Data that are generated as a result of e-learning interventions should be incorporated into big data streams to be analyzed and to become actionable. It is therefore concluded that there is general consensus on the requirements that e-learning interventions need to adhere to in a digitally transformed occupational health and safety work environment. The challenge remains for organizations to incorporate data generated as a result of e-learning interventions into the digital ecosystem of the organization.

Keywords: digitalization, training, fourth industrial revolution, big data

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Authors: Takwa Jahan

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Music can be used in ESL classroom to create a learning environment. As literature abounds with positive statements, music can be used as a vehicle for second language acquisition. Music can be applied as an instrument to help second language learners to acquire vocabulary, grammar, spelling and other four skills and to expand cultural knowledge. Vocabulary learning is perceived boring by learners. As listening to music and singing songs are enjoyable to students, it can be used effectively to acquire vocabulary in second language. This paper reports a study to find out how music exhilarates vocabulary acquisition as the learners stay relaxed and thus learning becomes more enjoyable. For conducting my research two groups of fifty students- music and non-music group were formed. Data were collected through class observation, test, questionnaires, and interview. The finding shows that music group acquired much amount of vocabulary than the non-music group. They enjoyed vocabulary learning activities based on listening songs.

Keywords: effective instrument, ESL classroom, music, relax environment, vocabulary learning

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Authors: Felicitas Pielsticker, Christoph Pielsticker, Ingo Witzke

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Many people know ‘Mathematics needs practice!’ statement or similar ones from their mathematics lessons. It seems important to practice when learning mathematics. At the same time, it also seems important to practice how to learn mathematics. This paper places neuroscientific-radiological findings on “practicing” while learning mathematics in a context of mathematics education. To accomplish this, we use a literature-based discussion of our case study on practice. We want to describe neuroscientific-radiological findings in the context of mathematics education and point out stimulating connections between both perspectives. From a connective perspective we expect incentives that lead discussions in future research in the field of mathematics education.

Keywords: functional magnetic resonance imaging, fMRI, education, mathematics learning, practicing

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Authors: James Kaweesa

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The Internet of Things (IoT) has become a critical component of modern technology, enabling the connection of numerous devices to the internet. The interconnected nature of IoT devices, along with their heterogeneous and resource-constrained nature, makes them vulnerable to various types of attacks, such as malware, denial-of-service attacks, and network scanning. Intrusion Detection Systems (IDSs) are a key mechanism for protecting IoT networks and from attacks by identifying and alerting administrators to suspicious activities. In this review, the paper will discuss the different types of IDSs available for IoT systems and evaluate their effectiveness in detecting and preventing attacks. Also, examine the various evaluation methods used to assess the performance of IDSs and the challenges associated with evaluating them in IoT environments. The review will highlight the need for effective and efficient IDSs that can cope with the unique characteristics of IoT networks, including their heterogeneity, dynamic topology, and resource constraints. The paper will conclude by indicating where further research is needed to develop IDSs that can address these challenges and effectively protect IoT systems from cyber threats.

Keywords: cyber-threats, iot, intrusion detection system, networks

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Authors: Kunihiro Kamataki

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In this study, active learning based on simple science experiments was developed in a university class of the freshman, in order to improve their scientific literacy. Through the active learning based on simple experiments of generation of cloud in a plastic bottle, students increased the interest in the global atmospheric problem and were able to discuss and find solutions about this problem positively from various viewpoints of the science technology, the politics, the economy, the diplomacy and the relations among nations. The results of their questionnaires and free descriptions of this class indicate that they improve the scientific literacy and motivations of other classroom lectures to acquire knowledge. It is thus suggested that the science experiment is strong tool to improve their intellectual curiosity rapidly and the connections that link the impression of science experiment and their interest of the social problem is very important to enhance their learning effect in this education.

Keywords: active learning, scientific literacy, simple scientific experiment, university education

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Authors: Noha Hamie Haidar

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The purpose of this case study was to explore faculty attitudes toward online learning in a Lebanese Higher Education Institution (HEI). The research problem addressed the disinterest among faculty at the Arts, Sciences, and Technology University of Lebanon (AUL) in enhancing learning using online technology. The research questions for the study examined the attitudes of the faculty toward applying online learning and the extent of the faculty readiness to adopt this technological change. A qualitative case study design was used that employed multiple sources of information including semi-structured interviews and existing literature. The target population was AUL faculty including full-time instructors and administration (n=25). Data analysis was guided by the lens of Kanter’s theoretical approach, which focused on faculty’s awareness, desire, knowledge, ability, and reinforcement model (ADKAR) for adopting change. Key findings indicated negative impressions concerning online learning such as authority (ministry of education, culture, and rules); and change (increased enrollment and different teaching styles). Yet, within AUL’s academic environment, the opportunity for the adoption of online learning was identified; faculty showed positive elements, such as the competitive advantage to first enter the Lebanese Market, and higher student enrollment. These results may encourage AUL’s faculty to adopt online learning and to achieve a positive social change by expanding the ability of students in HEIs to compete globally.

Keywords: faculty, higher education, technology, online learning

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Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: Huey-Wen Chou, Shuo-Heng Liang

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This study focuses on studying college students’ multitasking with cellphones/laptops during lectures. In-class multitasking behavior is defined as the activities students engaged that are irrelevant to learning. This study aims to understand if students' learning engagement affects students' multitasking as well as to investigate the causes or motivations that contribute to the occurrence of multitasking behavior. Survey data were collected and analyzed by PLS method and multiple regression to test the research model and hypothesis. Major results include: 1. Students' multitasking motivation positively predicts students’ in-class multitasking. 2. Factors affecting multitasking in class, including efficiency, entertainment and social needs, significantly impact on multitasking. 3. Polychronic personality traits will positively predict students’ multitasking. 4. Students' classroom learning engagement negatively predicts multitasking. 5. Course attributes negatively predict student learning engagement and positively predict student multitasking.

Keywords: engagement, monochronic personality, multitasking, learning, personality traits

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Authors: Ali Mohammad Mobaser Azad, Alireza Akhlaghinia

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Blockchain is changing our world and launching a new generation of decentralized networks. Meanwhile, Blockchain-based networks like Ethereum have been created and they will facilitate these processes using tools like smart contracts. The Ethereum has fundamental structures, each of which affects the activity of the nodes. Our purpose in this paper is to review similar research and examine various components to demonstrate the performance of the Ethereum network and to do this, and we used the data published by the Ethereum Foundation in different time spots to examine the number of changes that determine the status of network performance. This will help other researchers understand better Ethereum in different situations.

Keywords: blockchain, ethereum, smart contract, decentralization consensus algorithm

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Authors: Roopali Kulkarni, Yuliya Khrypko

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A major problem in educational digital game design is that game developers are often focused on maintaining the fun and playability of an educational game, whereas educators are more concerned with the learning aspect of the game rather than its entertaining characteristics. There is a clear need to understand what key aspects of digital learning games make them an effective learning medium in tertiary education. Through a systematic literature review and content analysis, this paper identifies, evaluates, and summarizes twenty-three key attributes of digital games used in tertiary education and presents a summary digital game-based learning (DGBL) model for designing and evaluating an educational digital game of any genre that promotes effective learning in tertiary education. The proposed solution overcomes limitations of previously designed models for digital game evaluation, such as a small number of game attributes considered or applicability to a specific genre of digital games. The proposed DGBL model can be used to assist game designers and educators with creating effective and engaging educational digital games for the tertiary education curriculum.

Keywords: DGBL model, digital games, educational games, game-based learning, tertiary education

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Authors: Hassan Sharafuddin, Chekra Allani

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Academicians at the Arab Open University have always voiced their concern about the efficacy of the blended learning process. Based on 75% independent study and 25% face-to-face tutorial, it poses the challenge of the predisposition to adjustment. Being used to the psychology of traditional educational systems, AOU students cannot be easily weaned from being spoon-fed. Hence they lack the motivation to plunge into self-study. For better involvement of AOU students into the learning practices, it is imperative to diagnose the factors that impede or increase their motivation. This is conducted through an empirical study grounded upon observations and tested hypothesis and aimed at monitoring and optimizing the students’ learning outcome. Recommendations of the research will follow the findings.

Keywords: academic performance, blended learning, educational psychology, independent study, pedagogy

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

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The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

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Authors: F. Allag, S. Bouharati, M. Belmahdi, R. Zegadi

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The rapid expansion of deserts in recent decades as a result of human actions combined with climatic changes has highlighted the necessity to understand biological processes in arid environments. Whereas physical processes and the biology of flora and fauna have been relatively well studied in marginally used arid areas, knowledge of desert soil micro-organisms remains fragmentary. The objective of this study is to conduct a diversity analysis of bacterial communities in unvegetated arid soils. Several biological phenomena in hot deserts related to microbial populations and the potential use of micro-organisms for restoring hot desert environments. Dry land ecosystems have a highly heterogeneous distribution of resources, with greater nutrient concentrations and microbial densities occurring in vegetated than in bare soils. In this work, we found it useful to use techniques of artificial intelligence in their treatment especially artificial neural networks (ANN). The use of the ANN model, demonstrate his capability for addressing the complex problems of uncertainty data.

Keywords: desert soil, climatic changes, bacteria, vegetation, artificial neural networks

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Authors: Jamie David Hopkin

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This study aims to contribute uniquely to help colleges and community learning and development institutes to help aid progression within ESOL learning. The study investigates the barriers that migrant and displaced learners face accessing further education in Scotland. The study also includes a set of recommendations both for colleges and CLD institutes to help ESOL learners in their journey to further education. The research found that integration into Scottish society is one of the biggest motivators for ESOL students to learn English. It also found that the place of gender and “gender roles” contribute to the barriers that learners face in terms of progression and learning. The study also reviews all literature related to ESOL learning in Scotland and found that there are only two main policies that support ESOL learning, and both are slightly outdated in terms of supporting progression. This study aims to help bridge the gap in knowledge around the progression from informal learning to formal education. The recommendations that are made in this study are aimed to help institutes and learners on their journey to a positive destination. The main beneficiaries of this research are current and future ESOL learners in Scotland, ESOL institutes, and TESOL professionals.

Keywords: community learning and development, English for speakers of other languages, further education, higher education TESOL, teaching English as a second language

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: Mohamed Lotfy, Ghada Soliman

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Recognizing Arabic dot-matrix digits is a challenging problem due to the unique characteristics of dot-matrix fonts, such as irregular dot spacing and varying dot sizes. This paper presents an approach for recognizing Arabic digits printed in dot matrix format. The proposed model is based on Convolutional Neural Networks (CNN) that take the dot matrix as input and generate embeddings that are rounded to generate binary representations of the digits. The binary embeddings are then used to perform Optical Character Recognition (OCR) on the digit images. To overcome the challenge of the limited availability of dotted Arabic expiration date images, we developed a True Type Font (TTF) for generating synthetic images of Arabic dot-matrix characters. The model was trained on a synthetic dataset of 3287 images and 658 synthetic images for testing, representing realistic expiration dates from 2019 to 2027 in the format of yyyy/mm/dd. Our model achieved an accuracy of 98.94% on the expiry date recognition with Arabic dot matrix format using fewer parameters and less computational resources than traditional CNN-based models. By investigating and presenting our findings comprehensively, we aim to contribute substantially to the field of OCR and pave the way for advancements in Arabic dot-matrix character recognition. Our proposed approach is not limited to Arabic dot matrix digit recognition but can also be extended to text recognition tasks, such as text classification and sentiment analysis.

Keywords: computer vision, pattern recognition, optical character recognition, deep learning

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Authors: Jong Boonpracha

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This paper studied the application of the design of local wisdom learning for providing creative activity for juveniles with exhibit media. The Suan-oui Youth Center has the objectives to design and develop exhibit media that encourage participation and learning of youths on local wisdom of Ratanakosin Island. The research was conducted in three stages: 1) to study the principle of local wisdom learning of cultural heritage at Ratanakosin Island 2) to study exhibit media that encouraged participation and creative activities of youth on local wisdom learning, and 3) to design a youth center that provide media exhibition for local wisdom learning. The research revealed the following: 34.6 percent of respondents wanted to apply local living wisdom in their career and for hobby. At least two kinds of exhibit media effectively provided creative activities for youths. A multi-purpose area, for example, with still pictures, visual symbols, and simulations would increase the level of youths’ interaction and participation.

Keywords: exhibit media, local wisdom, youth center, design

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Authors: Zahra Alqahtani

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The use of e-learning technologies is gaining momentum in all educational institutions of the world, including Saudi universities. In the e-learning context, there is a growing need and concern among Saudi universities to improve and enhance quality assurance for e-learning systems. Practicing quality assurance activities and applying quality standards in e-learning in Saudi universities is thought to reduce the negative viewpoints of some stakeholders and ensure stakeholders’ satisfaction and needs. As a contribution to improving the quality of e-learning method in Saudi universities, the main purpose of this study is to explore and investigate strategies for the development of quality assurance in e-learning in one university in Saudi Arabia, which is considered a good reference university using the best and ongoing practices in e-learning systems among Saudi universities. In order to ensure the quality of its e-learning methods, Saudi university has adopted Quality Matters Standards as a controlling guide for the quality of its blended and full e-course electronic courses. Furthermore, quality assurance can be further improved if a variety of perspectives are taken into consideration from the comprehensive viewpoints of faculty members, administrative staff, and students.This qualitative research involved the use of different types of interviews, as well as documents that contain data related to e-learning methods in the Saudi university environment. This exploratory case study was undertaken, from the perspectives of various participants, to understand the phenomenon of quality assurance using an inductive technique.The results revealed six main supportive factors that assist in ensuring the quality of e-learning in the Saudi university environment. Essentially, these factors are institutional support, faculty member support, evaluation of faculty, quality of e-course design, technology support, and student support, which together have a remarkable positive effect on quality, forming intrinsic columns connected by bricks leading to quality e-learning. Quality Matters standards are considered to have a strong impact on improving faculty members' skills and on the development of high-quality blended and full e-courses.

Keywords: E-learning, quality assurance, quality matters standards, KKU-supportive factors

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Authors: Paul Shize Li, Frank Alber

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A fundamental task of clinical genomics is to unravel the functions of genes and their associations with disorders. Although experimental biology has made efforts to discover and elucidate the molecular mechanisms of individual genes in the past decades, still about 40% of human genes have unknown functions, not to mention the diseases they may be related to. For those biologists who are interested in a particular gene with unknown functions, a powerful computational method tailored for inferring the functions and disease relevance of uncharacterized genes is strongly needed. Studies have shown that genes strongly linked to each other in multiple biological networks are more likely to have similar functions. This indicates that the densely connected subgraphs in multiple biological networks are useful in the functional and phenotypic annotation of uncharacterized genes. Therefore, in this work, we have developed an integrative network approach to identify the frequent local clusters, which are defined as those densely connected subgraphs that frequently occur in multiple biological networks and consist of the query gene that has few or no disease or function annotations. This is a local clustering algorithm that models multiple biological networks sharing the same gene set as a three-dimensional matrix, the so-called tensor, and employs the tensor-based optimization method to efficiently find the frequent local clusters. Specifically, massive public gene expression data sets that comprehensively cover dynamic, physiological, and environmental conditions are used to generate hundreds of gene co-expression networks. By integrating these gene co-expression networks, for a given uncharacterized gene that is of biologist’s interest, the proposed method can be applied to identify the frequent local clusters that consist of this uncharacterized gene. Finally, those frequent local clusters are used for function and disease annotation of this uncharacterized gene. This local tensor clustering algorithm outperformed the competing tensor-based algorithm in both module discovery and running time. We also demonstrated the use of the proposed method on real data of hundreds of gene co-expression data and showed that it can comprehensively characterize the query gene. Therefore, this study provides a new tool for annotating the uncharacterized genes and has great potential to assist clinical genomic diagnostics.

Keywords: local tensor clustering, query gene, gene co-expression network, gene annotation

Procedia PDF Downloads 165

Authors: Aung Aung Kyi, Khin Khin Aye

Abstract:

The mode of teaching and learning has been changed dramatically due to the Covid-19 pandemic that made schools close and students may have been away from the campus. However, many schools all over the countries are helping students to facilitate e-learning through online teaching and learning platform. Regarding this, Sarasas bilingual school in Bangkok conducted the high school students’ satisfaction survey since it is important for every school to improve its quality of education that must meet the students' need. For the good of the school's reputation, the purpose of the study is to examine the level of satisfaction that enhances the best services in the future. This study applied random sampling techniques and the data were collected using a self-administered survey. Descriptive analysis and independent sample t-tests were used to measure the importance of satisfaction components. The results showed G-11 (A) students were extremely satisfied with “Accessibility of course resources and materials through online platform” and “Ontime homework submission” while G-11 (B) students were extremely satisfied with “Teacher assisted with guiding my learning activities” and “Course teacher for this online course interacted with me in a timely fashion”. Additionally, they were also satisfied with a clear understanding of the teacher’s introduction during online learning. A significant difference in the satisfaction was observed between G-11 (A) and G-11 (B) students in terms of “A clear understanding on introduction was given by the teacher at the beginning of this online course”(P=0.03), “Teacher assisted with guiding my learning activities” (P=0.003), and “Comfortable surrounding during online learning” (P=0.02). With regard to gender, it has been seen that female high school students were extremely satisfied with the amount of course interaction with their teacher and her guidance with learning activities during online learning. By understanding the survey assessment, schools can improve their quality of education through the best digital educational platform that helps satisfy their students in the future.

Keywords: Bangkok high school students., covid-19 pandemic, online learning platform, satisfaction

Procedia PDF Downloads 212

Authors: Nidhi Gopal

Abstract:

Routing is the process of moving a packet of data from source to destination and enables messages to pass from one computer to another and eventually reach the target machine. A router is a networking device that forwards data packets between computer networks. It is connected to two or more data lines from different networks (as opposed to a network switch, which connects data lines from one single network). This paper mainly emphasizes upon the study of router device, its top level architecture, and how various sub-modules of router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top module.

Keywords: data packets, networking, router, routing

Procedia PDF Downloads 811

Authors: Andre Bechuke

Abstract:

The quality of every learning programme in Higher Education (HE) is dependent on the planning, design, and development of the curriculum decisions. These curriculum development decisions are highly influenced by the knowledge of the end-user, who are not always just the students. When curriculum experts plan, design and develop learning programmes, they always have the end-users in mind throughout the process. Without proper knowledge of the end-user(s), the design and development of a learning programme might be flawed. Curriculum experts often struggle to determine who the real end-user is. As such, it is even more challenging to establish what needs to be known about the end user that should inform the plan, design, and development of a learning programme. This research sought suggest approaches to guide curriculum experts to identify the end-user(s), taking into consideration the pressure and influence other agencies and structures or stakeholders (industry, students, government, universities context, lecturers, international communities, professional regulatory bodies) have on the design of a learning programme and the graduates of the programmes. Considering the influence of these stakeholders, which is also very important, the task of deciding who the real end-user of the learning programme becomes very challenging. This study makes use of criteria 1 and 18 of the Council on Higher Education criteria for programme accreditation to guide the process of identifying the end-users when developing a learning programme. Criterion 1 suggests that designers must ensure that the programme is consonant with the institution’s mission, forms part of institutional planning and resource allocation, meets national requirements and the needs of students and other stakeholders, and is intellectually credible. According to criterion 18, in designing a learning programme, steps must be taken to enhance the employability of students and alleviate shortages of expertise in relevant fields. In conclusion, there is hardly ever one group of end-users to be considered for developing a learning programme, and the notion that students are the end-users is not true, especially when the graduates are unable to use the qualification for employment.

Keywords: council on higher education, curriculum design and development, higher education, learning programme

Procedia PDF Downloads 79