Search results for: Deep learning based segmentation

Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

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Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

Procedia PDF Downloads 354

Authors: Naeem Ullah, Menglan Duan, Mac Darlington Uche Onuoha

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The lowering of subsea equipment into the deep waters is a challenging job due to the harsh offshore environment. Many researchers have introduced various installation systems to deploy the payload safely into the deep oceans. In general practice, dual floating vessels are not employed owing to the prevalent safety risks and hazards caused by ever-increasing dynamical effects sourced by mutual interaction between the bodies. However, while keeping in the view of the optimal grounds, such as economical one, the Y-method, the two conventional tugboats supporting the equipment by the two independent strands connected to a tri-plate above the equipment, has been employed to study multibody dynamics of the dual barge lifting operations. In this study, the two tugboats and the suspended payload (Y-method) are deployed for the lowering of subsea equipment into the deep waters as a multibody dynamic system. The two-wire ropes are used for the lifting and installation operation by this Y-method installation system. 6-dof (degree of freedom) for each body are considered to establish coupled 18-dof multibody model by embedding technique or velocity transformation technique. The fundamental and prompt advantage of this technique is that the constraint forces can be eliminated directly, and no extra computational effort is required for the elimination of the constraint forces. The inertial frame of reference is taken at the surface of the water as the time-independent frame of reference, and the floating frames of reference are introduced in each body as the time-dependent frames of reference in order to formulate the velocity transformation matrix. The local transformation of the generalized coordinates to the inertial frame of reference is executed by applying the Euler Angle approach. The spherical joints are articulated amongst the multibody as the kinematic joints. The hydrodynamic force, the two-strand forces, the hydrostatic force, and the mooring forces are taken into consideration as the external forces. The radiation force of the hydrodynamic force is obtained by employing the Cummins equation. The wave exciting part of the hydrodynamic force is obtained by using force response amplitude operators (RAOs) that are obtained by the commercial solver ‘OpenFOAM’. The strand force is obtained by considering the wire rope as an elastic spring. The nonlinear hydrostatic force is obtained by the pressure integration technique at each time step of the wave movement. The mooring forces are evaluated by using Faltinsen analytical approach. ‘The Runge Kutta Method’ of Fourth-Order is employed to evaluate the coupled equations of motion obtained for 18-dof multibody model. The results are correlated with the simulated Orcaflex Model. Moreover, the results from Orcaflex Model are compared with the MOSES Model from previous studies. The MBDS of single barge lifting operation from the former studies are compared with the MBDS of the established dual barge lifting operation. The dynamics of the dual barge lifting operation are found larger in magnitude as compared to the single barge lifting operation. It is noticed that the traction at the top connection point of the cable decreases with the increase in the length, and it becomes almost constant after passing through the splash zone.

Keywords: dual barge lifting operation, Y-method, multibody dynamics, shipbuilding, installation of subsea equipment, shipbuilding

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Authors: Irdawati Bay Nalls

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This study looked at Bilingual First Language Acquisition (BFLA) Spanish-English Mexican Americans across an elementary public school in the United States and the possibility of maintaining harmonious bilingualism. Adopting a phenomenological approach, with a focus on the status of bilingualism in education within a marginalized community, classroom observations, and small group and one-on-one interviews were conducted. This study explored the struggles of these bilinguals as they acculturated in America through their attempt to blend heritage and societal languages and cultural practices. Results revealed that bilinguals as young as 5 years old expressed their need to retain Spanish as a heritage language while learning English. 12 years old foresee that Spanish will not be taught to them in schools and highlighted the need to learn Spanish outside the school environments. Their voices revealed counter-narratives on identity and the need to maintain harmonious bilingualism as these students strived to give equal importance to the learning of English and Spanish as first languages despite the setbacks faced.

Keywords: BFLA, Mexican-American, bilingual, harmonious bilingualism

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Authors: Lawrence Meda, Christopher Dumas, Moses Moyo, Zayd Waghid

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As a result of some schools embracing technology to enhance students’ learning experiences in the digital era, the Faculty of Education at a University of Technology in South Africa has mandated lecturers to scale up their utilisation of technology in their teaching. Lecturers have been challenged to utilise the institution’s Learning Management System - Blackboard among other technologies - to adequately prepare trainee teachers to be able to teach competently in schools. The purpose of this study is to investigate the extent to which lecturers are utilising Blackboard to enhance their teaching. The study will be conducted using a quantitative approach, and its paradigmatic position will be positivist. The study will be done as a case study of the university’s Faculty of Education. Data will be extracted from all 100 lecturers’ Blackboard sites according to their respective modules, and it will be analysed using the four pillars of Blackboard as a conceptual framework. It is presumed that there is an imbalance on the lecturers’ utilisation of the four pillars of Blackboard as the majority use it as a content dumping site.

Keywords: blackboard, digital, education, technology

Procedia PDF Downloads 146

Authors: Rosilah Hassan, Karam Dhafer Mayoof, Norngainy Mohd Tawil, Shamshubaridah Ramlee

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Application of adaptive online quiz system and a design are performed in this paper. The purpose of adaptive quiz system is to establish different questions automatically for each student and measure their competence on a definite area of discipline. This model determines students competencies in cases like distant-learning which experience challenges frequently. Questions are specialized to allow clear deductions about student gains; they are able to identify student competencies more effectively. Also, negative effects of questions requiring higher knowledge than competency over student’s morale and self-confidence are dismissed. The advantage of the system in the quiz management requires less total time for measuring and is more flexible. Self sufficiency of the system in terms of repeating, planning and assessment of the measurement process allows itself to be used in the individual education sets. Adaptive quiz technique prevents students from distraction and motivation loss, which is led by the questions with quite lower hardness level than student’s competency.

Keywords: e-learning, adaptive system, security, quiz database

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Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

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Authors: Mariana Volpini, Volker Bartenbach, Marcos Pinotti, Robert Riener

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Restoration of gait ability is an important task in the rehabilitation of people with neurological disorders presenting a great impact in the quality of life of an individual. Based on the motor learning concept, robotic assisted treadmill training has been introduced and found to be a feasible and promising therapeutic option in neurological rehabilitation but unfortunately it is not available for most patients in developing countries due to the high cost. This paper presents the concept of a low cost rehabilitation robot to help consolidate the robotic-assisted gait training as a reality in clinical practice in most countries. This work indicates that it is possible to build a simpler rehabilitation device respecting the physiological trajectory of the ankle.

Keywords: bioengineering, gait therapy, low cost rehabilitation robot, rehabilitation robotics

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Authors: Kaoru Tomita

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This study explores how visual information helps us to learn foreign language pronunciation. Visual assistance and its effect for learning foreign language have been discussed widely. For example, simplified illustrations in textbooks are used for telling learners which part of the articulation organs are used for pronouncing sounds. Vowels are put into a chart that depicts a vowel space. Consonants are put into a table that contains two axes of place and manner of articulation. When comparing a still picture and a moving picture for visualizing learners’ pronunciation, it becomes clear that the former works better than the latter. The visualization of vowels was applied to class activities in which native and non-native speakers’ English was compared and the learners’ feedback was collected: the positions of six vowels did not scatter as much as they were expected to do. Specifically, two vowels were not discriminated and were arranged very close in the vowel space. It was surprising for the author to find that learners liked analyzing their own pronunciation by linking formant ones and twos on a sheet of paper with a pencil. Even a simple method works well if it leads learners to think about their pronunciation analytically.

Keywords: feedback, pronunciation, visualization, vowel

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Authors: Faiza Babur Khan, Sohail Asghar

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With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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Authors: Juha Kettunen

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This study presents a project that tests and adjusts active European learning and teaching methods in Indonesian universities to increase their external impact on enterprises and other organizations; it also assesses the implementation of the Erasmus+ projects funded by the European Union. The project is based on the approach of innovation pedagogy that responds to regional development needs and integrates applied research and development projects into education to create capabilities for students to participate in development work after graduation. The assessment of the Erasmus+ project resulted in many improvements that can be made to achieve higher quality and innovativeness. The results of this study are useful for those who want to improve the applied research and development projects of higher education institutions.

Keywords: higher education, innovations, social network, project management

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Authors: Vajhollah Ghorbanizadeh, Seyed Mohsen Asadi, Mirali Seyednaghavi, Davoud Hoseynpour

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In the current era, all organizations need knowledge to be able to manage the diverse human resources. Creative, dynamic and knowledge-based Human resources are important competitive advantage and the scarcest resource in today's knowledge-based economy. In addition managers with skills of knowledge management must be aware of human resource management science. It is now generally accepted that successful implementation of knowledge management requires dynamic interaction between knowledge management and human resource management. This is emphasized at systematic approach to knowledge management as well. However human resource management can be complementary of knowledge management because human resources management with the aim of empowering human resources as the key resource organizations in the 21st century, the use of other resources, creating and growing and developing today. Thus, knowledge is the major capital of every organization which is introduced through the process of knowledge management. In this context, knowledge management is systematic approach to create, receive, organize, access, and use of knowledge and learning in the organization. This article aims to define and explain the concepts of knowledge management and human resource management and the importance of these processes and concepts. Literature related to knowledge management and human resource management as well as related topics were studied, then to design, illustrate and provide a theoretical model to explain the factors affecting the relationship between knowledge management and human resource management and knowledge management system approach, for schematic design and are drawn.

Keywords: systemic approach, human resources, knowledge, human resources management, knowledge management

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Authors: Christopher Meyer, Laima Gerlitz

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European ports are facing high political pressure through the implementation of initiatives such as the European Green Deal or IMO's 2030 targets (Fit for 55). However, small and medium-sized ports face even higher challenges compared to bigger ones due to lower capacities in various fields such as investments, infra-structure, Human Resources, and funding opportunities. Small and Medium-Sized Ports (SMPs) roles in economic systems are various depending on their specific functionality in maritime ecosystems. Depending on their different situations, being an actor in multiport gateways, aligned to core ports, regional nodes in peripheries for the hinterland, specialized cluster members, or logistical nodes, different strategic business models may be applied to increase SMPs' competitiveness among other bigger ports. Additionally, SMPs are facing more challenges for future development in terms of digital and green transition of their operations. Thus, it is necessary to evaluate the own strategical position and apply management strategies alongside the regional growth and innovation strategies for diversification or specialisation of own port businesses. The research uses inductive perspectives to set up a transferable framework based on case studies to be analysed. In line with particular research and document analysis, qualitative approaches were considered. The research is based on a deep literature review on SMPs as well as theories on diversification and specialisation. Existing theories from different fields are evaluated on their application for the port sector and these specific maritime actors, paying respect to enabling innovation incorporation to enhance digital and environmental transition with fu-ture perspectives for SMPs. The paper aims to provide a decision-making matrix for the strategic positioning of SMPs in Europe, including opportunities to get access to particular EU funds for future development alongside the Regional In-novation Strategies on Smart Specialisation.

Keywords: strategic planning, sustainability transition, competitiveness portfolio, EU green deal

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Authors: Mamadou Dione, Eric Matzner-lober, Philippe Alexandre

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The Energy Transition Act defined by the French State has precise implications on Renewable Energies, in particular on its remuneration mechanism. Until then, a purchase obligation contract permitted the sale of wind-generated electricity at a fixed rate. Tomorrow, it will be necessary to sell this electricity on the Market (at variable rates) before obtaining additional compensation intended to reduce the risk. This sale on the market requires to announce in advance (about 48 hours before) the production that will be delivered on the network, so to be able to predict (in the short term) this production. The fundamental problem remains the variability of the Wind accentuated by the geographical situation. The objective of the project is to provide, every day, short-term forecasts (48-hour horizon) of wind production using weather data. The predictions of the GFS model and those of the ECMWF model are used as explanatory variables. The variable to be predicted is the production of a wind farm. We do two approaches: a direct approach that predicts wind generation directly from weather data, and an integrated approach that estimâtes wind from weather data and converts it into wind power by power curves. We used machine learning techniques to predict this production. The models tested are random forests, CART + Bagging, CART + Boosting, SVM (Support Vector Machine). The application is made on a wind farm of 22MW (11 wind turbines) of the Compagnie du Vent (that became Engie Green France). Our results are very conclusive compared to the literature.

Keywords: forecast aggregation, machine learning, spatio-temporal dynamics modeling, wind power forcast

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Authors: Bichi Muktar Sani

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The philosophy of Physical and Health Education is to develop academic and professional competency which will enable individuals earn a living and render unique services to the society and also provide good basis of knowledge and experience that characterize an educated and fully developed person through physical activities. With the increase of sedentary activities such as watching television, playing videogames, increased computer technology, automation and reduction of high school Physical and Health Education schedules, young people are most likely to become overweight, and less fit. Physical Education is a systematic instruction in sports, training, practice, gymnastics, exercises, and hygiene given as part of a school or college program. Physical and Health Education is the study, practice, and appreciation of the art and science of human movement. Physical and Health Education is course in the curricula that utilizes the learning in the cognitive, affective, and psychomotor domains in a lay or movement exploration setting. The paper made some recommendations on the way forward.

Keywords: issues, challenges, physical education, school

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Authors: Sang-Woo Kim, Young-Seon Lee

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An important concern in metal forming, even at elevated temperatures, is whether a desired deformation can be accomplished without any failure of the material. A detailed understanding of the critical condition for crack initiation provides not only the workability limit of a material but also a guide-line for process design. This paper describes the utilization of ductile fracture criteria in conjunction with the finite element method (FEM) for predicting the onset of fracture in warm metal working processes of magnesium alloy sheets. Critical damage values for various ductile fracture criteria were determined from uniaxial tensile tests and were expressed as the function of strain rate and temperature. In order to find the best criterion for failure prediction, Erichsen cupping tests under isothermal conditions and FE simulations combined with ductile fracture criteria were carried out. Based on the plastic deformation histories obtained from the FE analyses of the Erichsen cupping tests and the critical damage value curves, the initiation time and location of fracture were predicted under a bi-axial tensile condition. The results were compared with experimental results and the best criterion was recommended. In addition, the proposed methodology was used to predict the onset of fracture in non-isothermal deep drawing processes using an irregular shaped blank, and the results were verified experimentally.

Keywords: magnesium, AZ31 alloy, ductile fracture, FEM, sheet forming, Erichsen cupping test

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Authors: Bharath R., Tharun Sai N., Bhuvan G.

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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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Authors: Folasade R. Sulaiman

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Pupils’ health and nutrition are basically important to their schooling. The preponderance of avoidable deaths among children in Africa (WHO, 2000) may not be unconnected with the nutritional and health education status of families and communities that have their children as school clients. This study adopted a descriptive survey design focusing on the assessment of the level of nutritional and health education of families and community members in the rural riverine areas of Ogun State. Two research questions were raised. The Nutritional and Health Education of Families and Communities Inventory (NHEFCI) was used to collect data from 250 rural child-bearing aged women, and 0.73 test-retest reliability coefficient was established to determine the strength of the instrument. Data collected were analysed using descriptive statistics of frequency counts, percentages and mean in accordance with research questions raised in the study. The findings revealed amongst others: that 65% of the respondents had low level of nutritional and health education among the families and community members; while 72% had low level of awareness of the possible influence of nutritional and health education on the learning outcomes of the children. Based on the findings, it was recommended among others that government should intensify efforts on sensitization, mass literacy campaign etc.; also improve upon the already existing School Feeding Programme in Nigerian primary schools to provide at least one balanced diet for children while in school; community health workers, social workers, Non-Governmental Organizations (NGO) should collaborate with international Organizations like UNICEF, UNESCO, WHO etc. to organize sensitization programmes for members of the rural riverine communities on the importance of meeting the health and nutritional needs of their children in order to attain their educational potentials.

Keywords: nutritional and health education, learning capacities, school-age children, universal basic education, rural riverine areas

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Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

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Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

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Authors: Svetlana Polskaya

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The study deals with the issue of using the Content and Language Integrated Learning (CLIL) concept when teaching Master Program students majoring in neuromarketing and entrepreneurship. Present-day employers expect young graduates to conduct professional communication with their English-speaking peers and demonstrate proper knowledge of the industry’s terminology and jargon. The idea of applying CLIL was the result of the above-mentioned students possessing high proficiency in English, thus, not requiring any further knowledge of the English language in terms of traditional grammar or lexis. Due to this situation, a CLIL-type program was devised, allowing learners to acquire new knowledge of entrepreneurship and neuromarketing spheres combined with simultaneous honing their English language practical usage. The case study analyzes CLIL application within this particular program as well as the experience accumulated in the process.

Keywords: CLIL, entrepreneurship, neuromarketing, foreign language acquisition, proficiency level

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Authors: Natcha Wattanaprapa, Alongkorn Taengtong, Phachaya Chaiwchan

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This study investigates and promotes the distribution of community enterprise products of Samut Songkhram province by using e-commerce web technology to help distribute the products. This study also aims to develop the information system to be able to operate on multiple platforms and promote the easy usability on smartphones to increase the efficiency and promote the distribution of community enterprise products of Samut Songkhram province in three areas including Baan Saraphi learning center, the learning center of Bang Noi Floating market as well as Bang Nang Li learning center. The main structure consists of spreading the knowledge regarding the tourist attraction in the area of community enterprise, e-commerce system of community enterprise products, and Chatbot. The researcher developed the system into an application form using the software package to create and manage the content on the internet. Connect management system (CMS) word press was used for managing web pages. Add-on CMS word press was used for creating the system of Chatbot, and the database of PHP My Admin was used as the database management system. The evaluation by the experts and users in 5 aspects, including the system efficiency, the accuracy in the operation of the system, the convenience and ease of use of the system, the design, and the promotion of product distribution in Samut Songkhram province by using questionnaires revealed that the result of evaluation in the promotion of product distribution in Samut Songkhram province was the highest with the mean of 4.20. When evaluating the efficiency of the developed system, it was found that the result of system efficiency was the highest level with a mean of 4.10.

Keywords: community enterprise, digital commerce, promotion of product distribution, Samut Songkhram province

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Authors: Shih-Fang Lo, Tzu-Wei Guo, Chih-Hsuan Lee

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Tropical fisheries are vulnerable to the physical and biogeochemical oceanic changes associated with climate change. Warmer temperatures and extreme weather have beendamaging the abundance and growth patterns of aquatic organisms. In recent year, the shrinking of fish stock and labor shortage have increased the threat to global aquacultural production. Thus, building a climate-resilient and sustainable mechanism becomes an urgent, important task for global citizens. To tackle the problem, Taiwanese fishermen applies the artificial intelligence (AI) technology. In brief, the AI system (1) measures real-time water quality and chemical parameters infish ponds; (2) monitors fish stock through segmentation, detection, and classification; and (3) implements fishermen’sprevious experiences, perceptions, and real-life practices. Applying this system can stabilize the aquacultural production and potentially increase the labor force. Furthermore, this AI technology can build up a more resilient and sustainable system for the fishermen so that they can mitigate the influence of extreme weather while maintaining or even increasing their aquacultural production. In the future, when the AI system collected and analyzed more and more data, it can be applied to different regions of the world or even adapt to the future technological or societal changes, continuously providing the most relevant and useful information for fishermen in the world.

Keywords: aquaculture, artificial intelligence (AI), real-time system, sustainable fishery

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Authors: Yang Song, Yifan Guo, Edward F. Gehringer

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Fifty years of research has found great potential for peer assessment as a pedagogical approach. With peer assessment, not only do students receive more copious assessments; they also learn to become assessors. In recent decades, more educational peer assessments have been facilitated by online systems. Those online systems are designed differently to suit different class settings and student groups, but they basically fall into two categories: rating-based and ranking-based. The rating-based systems ask assessors to rate the artifacts one by one following some review rubrics. The ranking-based systems allow assessors to review a set of artifacts and give a rank for each of them. Though there are different systems and a large number of users of each category, there is no comprehensive comparison on which design leads to higher reliability. In this paper, we designed algorithms to evaluate assessors' reliabilities based on their rating/ranking against the global ranks of the artifacts they have reviewed. These algorithms are suitable for data from both rating-based and ranking-based peer assessment systems. The experiments were done based on more than 15,000 peer assessments from multiple peer assessment systems. We found that the assessors in ranking-based peer assessments are at least 10% more reliable than the assessors in rating-based peer assessments. Further analysis also demonstrated that the assessors in ranking-based assessments tend to assess the more differentiable artifacts correctly, but there is no such pattern for rating-based assessors.

Keywords: peer assessment, peer rating, peer ranking, reliability

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Authors: Roslina Ibrahim, Azizah Jaafar, Khalili Khalil

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Educational games (EG) are regarded as a promising teaching and learning tool for the new generation. Growing number of studies and literatures can be found in EG studies. Both academic researchers and commercial developers come out with various educational games prototypes and titles. Despite that, acceptance of educational games still lacks among the students. It is important to understanding students’ perceptions of EG, since they are the main stakeholder of the technology. Thus, this study seeks to understand perceptions of undergraduates’ students using a framework originated from user acceptance theory. The framework consists of six constructs with twenty-eight items. Data collection was done on 180 undergraduate students of Universiti Teknologi Malaysia, Kuala Lumpur using self-developed online EG called ROBO-C. Data analysis was done using descriptive, factor analysis and correlations. Performance expectancy, effort expectancy, attitude, and enjoyment factors were found significantly correlated with the intention to use EG. This study provides more understanding towards the use of educational games among students.

Keywords: educational games, perceptions, acceptance, UTAUT

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Authors: Nareshkumar Harale, B. B. Meshram

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The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies.

Keywords: network intrusion detection, network intrusion prevention, association rule mining, system analysis and design

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Authors: Talar Agopian

Abstract:

Teaching English as a Second Language (ESL) is a common practice in many Lebanese schools. However, ESL teaching is done in traditional ways. Methods such as constructivism are seldom used, especially in villages. Here lies the significance of this research which joins constructivism and Piaget’s theory of cognitive development in ESL classes in Lebanese villages. The purpose of the present study is to explore the effects of applying constructivist student-centered strategies in teaching grammar, reading comprehension, and poetry on students in elementary ESL classes in two villages in Lebanon, Zefta in South Lebanon and Boqaata in Mount Lebanon. 20 English teachers participated in a training titled “Teaching English with Fun”, which focused on strategies that create a student-centered class where active learning takes place and there is increased learner engagement and autonomy. The training covered three main areas in teaching English: grammar, reading comprehension, and poetry. After participating in the training, the teachers applied the new strategies and methods in their ESL classes. The methodology comprised two phases: in phase one, practice-based research was conducted as the teachers attended the training and applied the constructivist strategies in their respective ESL classes. Phase two included the reflections of the teachers on the effects of the application of constructivist strategies. The results revealed the educational benefits of constructivist student-centered strategies; the students of teachers who applied these strategies showed improved engagement, positive attitudes towards poetry, increased motivation, and a better sense of autonomy. Future research is required in applying constructivist methods in the areas of writing, spelling, and vocabulary in ESL classrooms of Lebanese villages.

Keywords: active learning, constructivism, learner engagement, student-centered strategies

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Authors: Anika Chebrolu

Abstract:

Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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Authors: Phalaunnnaphat Siriwongs

Abstract:

The classroom of the 21st century is an ever changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology are not the cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pin point an exact number, it is clear that in this case more does not mean better. By looking into the success and pitfalls of classroom size the true advantages of smaller classes will become clear. Previously, one class was comprised of 50 students. Being seventeen and eighteen- year- old students, sometimes it was quite difficult for them to stay focused. To help them understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.

Keywords: multiple intelligences, role play, performance assessment, formative assessment

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Authors: Alhanouf Alharbi, Wafa Alotaibi

Abstract:

This study aims to analyse students’ and teachers’ perceptions of using Plickers as a formative assessment tool in EFL classrooms. The study implements a mixed methods approach. First, a questionnaire was administered to 64 students from two schools in Almadinah, a Saudi city. Then, in structured interviews, two English teachers provided their opinions on the advantages and disadvantages of integrating Plickers into their classrooms. The findings reveal that both teachers and students believe that using Plickers positively impacts students’ learning. Moreover, the findings encourage teachers to integrate technology-based formative assessments in EFL classrooms. However, there are some drawbacks to using Plickers, such as technological issues. Finally, English teachers are recommended to engage all their students in a daily formative assessment by implementing Plickers in their classes.

Keywords: plickers, formative assessment, technology, students, EFL classroom

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

Abstract:

Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfill requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: single classifier, ensemble learning, multi-target tracking, multiple classifiers

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Authors: Vijayalaxmi Khopade

Abstract:

The Prima facie caste system is intrinsic to Indian society. It is an ancient system of intense social stratification based upon birth and enjoying religious sanction. The uppermost strata and privileges are ascribed and enjoyed by brahmins (priestly class), while the lowest strata are occupied by Dalits who are not ascribed with any privileges. The caste system is inherently hierarchical, patriarchal, and systematic and thrives solely on exploitation justified through means of the Brahminical system of hegemony based singularly on birth. The caste system has extended its tentacles to other religions like Christianity, Buddhism, Jainism, and Islam in South Asia. Term Dalit is colloquially used to categorize persons belonging to lower strata in the caste hierarchy. However, this category is heterogenous and highly stratified, following practices like untouchability and exclusion amongst themselves. The modern Indian legal system acknowledges the existence of Caste and its perils. Therefore, by virtue of the Indian Constitution, provisions for affirmative action for the protection and development of Dalits are made. Courts in India have liberally interpreted laws to benefit Dalits. However, the modern system of governance is not immune from Caste based biases. These biases are reflected in the implementation of governance, including the dispensation of justice. The economic reforms of the 1990s gave a huge boost to the Indian diaspora. Persons of Indian origin are now seen making great strides in almost every sector and enjoying positions of power globally. As one peels off the layer of ethnic Indian origin, a deep seated layer of Caste and Caste based patriarchy is clearly visible. Indian diaspora enjoying positions of power essentially belongs to upper castes and carry Caste based biases with them. These castes have long enjoyed the benefits of education; therefore, they were the first ones to benefit from LPG (Liberalization, Privatization, Globalization) model adopted in the 1990s. Dalits, however, had little formal education until recently. The western legal system, to the best of our knowledge, does not recognize Caste and, therefore, cannot afford protection for Dalits, wherein discrimination and exploitation take place solely on the basis of Caste. Therefore, Dalits are left with no legal remedy outside domestic jurisdiction. Countries like the UK have made an attempt to include Caste in their Equality Bill 2010. This has met with tough resistance from Upper caste Hindus who shy away from recognizing their caste privileges and, therefore, the existence of Caste. In this paper, an attempt for comparative analysis is made between various legal protections accorded to Dalits in India vis-à-vis international human rights as protected by the United Nations under its declaration of Universal Human rights. An attempt has been made to mark a distinction between race and Caste and to establish a position of women in Caste based hierarchy. The paper also makes an argument for the inclusion of atrocities committed against Dalits as a violation of international human rights, their protection by the United Nations, and the trial of their violations by International Courts. The paper puts into perspective the need for an external agency like the United Nations and International courts to interfere in rights guaranteed by the Indian Constitution, even with the existence of a modern legal system in a sovereign democratic country.

Keywords: atrocity, caste, diaspora, legal framework

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