Search results for: teaching and learning empathy

Authors: Rana Zeina

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Cognitive and behavioral symptoms may, in fact, overlap and be related to the level of the general cognitive function. We measured the behavioral aspects of autism and its correlation to the cognitive ability in 30 children with ASD. We used a neuropsychological battery CANTAB eclipse to evaluate the ASD children's cognitive ability. Individuals with ASDs and challenging behaviors showed significant correlation between some cognitive abilities and motor behavior aspects. Based on these findings we can conclude that the motor behavioral problems in autism affect specific cognitive abilities in ASDs such as comprehension, learning, reversal, acquisition, attention set shifting, and speed of reaction to one stimulus. Future research should also focus on the relationship between motor stereotypes and other subtypes of repetitive behaviors, such as verbal stereotypes, and ritual and routine adherence and use different types of CANTAB tests.

Keywords: cognitive ability, CANTAB test, behaviour motor aspects, autism spectrum disorders

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Authors: Obe Olumide Olayinka, Victor Balanica, Eugen Neagoe

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The effects of hypertension are often lethal thus its early detection and prevention is very important for everybody. In this paper, a neural network (NN) model was developed and trained based on a dataset of hypertension causative parameters in order to forecast the likelihood of occurrence of hypertension in patients. Our research goal was to analyze the potential of the presented NN to predict, for a period of time, the risk of hypertension or the risk of developing this disease for patients that are or not currently hypertensive. The results of the analysis for a given patient can support doctors in taking pro-active measures for averting the occurrence of hypertension such as recommendations regarding the patient behavior in order to lower his hypertension risk. Moreover, the paper envisages a set of three example scenarios in order to determine the age when the patient becomes hypertensive, i.e. determine the threshold for hypertensive age, to analyze what happens if the threshold hypertensive age is set to a certain age and the weight of the patient if being varied, and, to set the ideal weight for the patient and analyze what happens with the threshold of hypertensive age.

Keywords: neural network, hypertension, data set, training set, supervised learning

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Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: bidirectional encoder representations from transformers, BERT, chatbot, cryptocurrency, deep learning

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Authors: Rabia Bashir, Sajjad Akbar

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There is an inevitable demand of web mining due to rapid increase of huge information on the Internet, but the striking variety of web structures has made required content retrieval a difficult task. To counter this issue, Web Content Mining (WCM) emerges as a potential candidate which extracts and integrates suitable resources of data to users. In past few years, research has been done on several extraction techniques for WCM i.e. agent-based, template-based, assumption-based, statistic-based, wrapper-based and machine learning. However, it is still unclear that either these approaches are efficiently tackling the significant challenges of WCM or not. To answer this question, this paper identifies these challenges such as language independency, structure flexibility, performance, automation, dynamicity, redundancy handling, intelligence, relevant content retrieval, and privacy. Further, mapping of these challenges is done with existing extraction mechanisms which helps to adopt the most suitable WCM approach, given some conditions and characteristics at hand.

Keywords: content mining challenges, web content mining, web content extraction approaches, web information retrieval

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Authors: Mohammed Alkahtani, Ali Ahmad, Saber Darmoul, Shatha Samman, Ayoub Al-zabidi, Khaled Ba Matraf

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Education systems are complex and involve interactions between humans (teachers and students); media based technologies, lectures, classrooms, etc. to provide educational services. The education system performance is characterized by how well students learn, which is measured using student grades on exams and quizzes, achievements on standardized tests, among others. Advances in portable communications technologies, such as mobile phones, tablets, and laptops, created a different type of classroom, where students seem to engage in more than just the intended learning activities. The performance of more than one task in parallel or in rapid transition is commonly known as multitasking. Several operations in educational systems are performed simultaneously, resulting in a multitasking education environment. This paper surveys existing research on multitasking in educational settings, summarizes literature findings, provides a synthesis of the impact of multitasking on performance, and identifies directions of future research.

Keywords: multitasking, education, education environment, impact

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Authors: Divi Sharma

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The emergence of positive behaviour support (PBS) is directly linked to applied behaviour analysis that incorporates evidence-based approaches to addressing ethical challenges and improving autonomy, participation, and the overall quality of life of people living and learning in complex social environments. Its features include lifestyle improvement, collaboration with general caregivers, tracking progress with sound steps, comprehensive performance-based interventions, striving for contextual equality, and ensuring entry and implementation. This document aims to summarize its features with the support of case examples such as involving caregivers to play an active role in behavioural interventions, creating effective interventions within natural practices. Additionally, dealing with lifestyle changes, as well as a wide variety of behavioural changes, develop strong strategies which reduce professional dependence.

Keywords: positive behaviour support, quality of life, performance-based interventions, behavioural changes, participation

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Authors: Lisa Listiana

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ASEAN leader agreed to accelerate ASEAN Economic Community (AEC) implementation by 2015. The AEC Blueprint has set up obligations for its members to follow which include the establishment of (a) free trade in goods, according to ASEAN Free Trade Area: AFTA, (b) free trade in services, according to ASEAN Framework Agreement on Services: AFAS, (c) free trade in investment, according to ASEAN Comprehensive Investment Agreement: ACIA, (d) free capital flow, and (e) free flow of skilled labors. Consequently, these obligations bring both challenges and opportunities for its members. As accountant is included in the coverage of 8 skilled labors, the readiness of accounting profession to embrace AEC 2015 is pivotal. If Indonesian accountants do not accelerate their learning effort, the knowledge gap between Indonesian accountants and their international colleagues will only be worsened. This paper aims to analyze the current progress of AEC preparation and its challenges and opportunities for Indonesian accountants, and also to propose recommendation as necessary.

Keywords: AEC, ASEAN, readiness, Indonesian accountants

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Authors: Sandra Arango-Caro, Kristine Callis-Duehl

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The Education Research and Outreach Lab at the Donald Danforth Plant Science Center established the Plant and Agriculture Augmented and Virtual Reality Learning Laboratory (PAVRLL) to promote science education through professional development, school programs, internships, and outreach events. Professional development is offered to high school and college science and agriculture educators on the use and applications of zSpace and Oculus platforms. Educators learn to use, edit, or create lesson plans in the zSpace platform that are aligned with the Next Generation Science Standards. They also learn to use virtual reality experiences created by the PAVRLL available in Oculus (e.g. The Soybean Saga). Using a cost-free loan rotation system, educators can bring the AVR units to the classroom and offer AVR activities to their students. Each activity has user guides and activity protocols for both teachers and students. The PAVRLL also offers activities for 3D plant modeling. High school students work in teams of art-, science-, and technology-oriented students to design and create 3D models of plant species that are under research at the Danforth Center and present their projects at scientific events. Those 3D models are open access through the zSpace platform and are used by PAVRLL for professional development and the creation of VR activities. Both teachers and students acquire knowledge of plant and agriculture content and real-world problems, gain skills in AVR technology, 3D modeling, and science communication, and become more aware and interested in plant science. Students that participate in the PAVRLL activities complete pre- and post-surveys and reflection questions that evaluate interests in STEM and STEM careers, students’ perceptions of three design features of biology lab courses (collaboration, discovery/relevance, and iteration/productive failure), plant awareness, and engagement and learning in AVR environments. The PAVRLL was established in the fall of 2019, and since then, it has trained 15 educators, three of which will implement the AVR programs in the fall of 2021. Seven students have worked in the 3D plant modeling activity through a virtual internship. Due to the COVID-19 pandemic, the number of teachers trained, and classroom implementations have been very limited. It is expected that in the fall of 2021, students will come back to the schools in person, and by the spring of 2022, the PAVRLL activities will be fully implemented. This will allow the collection of enough data on student assessments that will provide insights on benefits and best practices for the use of AVR technologies in the classrooms. The PAVRLL uses cutting-edge educational technologies to promote science education and assess their benefits and will continue its expansion. Currently, the PAVRLL is applying for grants to create its own virtual labs where students can experience authentic research experiences using real Danforth research data based on programs the Education Lab already used in classrooms.

Keywords: assessment, augmented reality, education, plant science, virtual reality

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Authors: Elvin Karaaslan Klose

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Museums are important sites of informal, often semi-structured and self-paced learning. Challenged by digital alternatives and increased expectations from their visitors, museums have to adapt to the digital age by enriching their collection and educational content with additional options for interactivity. One such option lies in the concept of the electronic book, which can be used either on dedicated devices or downloaded by visitors before entering the exhibition area. These electronic books serve as an alternative or supplement to the classic audio guide and provide visitors with information about artifacts as well as background stories and factoids about the subjects of the exhibition. Bringing such interactive elements into the museum experience has been shown to increase information retention and enjoyment among young aged visitors and adults. This article aims to bring together both theoretical frameworks and practical examples of how interactive media in the form of electronic books can be used to enhance the experience of the museum visitor.

Keywords: electronic books, interactive media, arts education, museum education

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Authors: Yu-Mi Song, Sung-Ah Kim, Dongyoun Shin

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Cities are complex systems of diverse and inter-tangled activities. These activities and their complex interrelationships create diverse urban phenomena. And such urban phenomena have considerable influences on the lives of citizens. This research aimed to develop a method to reveal the causes and effects among diverse urban elements in order to enable better understanding of urban activities and, therefrom, to make better urban planning strategies. Specifically, this study was conducted to solve a data-recommendation problem found on a Korean public data homepage. First, a correlation analysis was conducted to find the correlations among random urban data. Then, based on the results of that correlation analysis, the weighted data network of each urban data was provided to people. It is expected that the weights of urban data thereby obtained will provide us with insights into cities and show us how diverse urban activities influence each other and induce feedback.

Keywords: big data, machine learning, ontology model, urban data model

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: one-class classification, outlier detection, generative adversary networks, semi-supervised learning

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Authors: Tanya Greathosue, Adrianna Taylor, Lori Darnel, Eileen Starr, Susie Ryder, Julie Clockston, Dawn Matera Bassett, Jess Retrum

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The United States has an identified need to improve the social work mental and behavioral health workforce shortage with a focus on culturally diverse and responsive mental and behavioral health practitioners to adequately serve its rapidly growing multicultural communities. The U.S. is experiencing rapid demographic changes. Ensuring that mental and behavioral health services are effective and accessible for diverse communities is essential for improving overall health outcomes. In response to this need, we developed a training program focused on interdisciplinary collaboration, evidence-based practices, and culturally responsive services. The success of the training program, funded by the Health Resource Service Administration (HRSA) Behavioral Health Workforce Education and Training (BHWET), has provided the foundation for stage two of our programming. In addition to HRSA/BHWET, we are receiving funding from Colorado Access, a state workforce development initiative, and Kaiser Permanente, a healthcare provider network in the United States. We have moved beyond improved learner outcomes to increasing recruitment of historically excluded, disproportionately mistreated learners, mentorship of students to improve retention, and successful, culturally responsive, diverse workforce development. These authors will utilize a pretest-posttest comparison group design and trend analysis to evaluate the success of the training program. Comparison groups will be matched based on age, gender identification, race, income, as well as prior experience in the field, and time in the degree program. This article describes our culturally responsive training program. Our goals are to increase the recruitment and retention of historically excluded, disproportionately mistreated learners. We achieve this by integrating cultural humility and sensitivity training into educational curricula for our scholars who participate in cohort classroom and seminar learning. Additionally, we provide our community partners who serve as internship sites with ongoing continuing education on how to promote and develop inclusive and supportive work environments for our learners. This work will be of value to mental and behavioral health care practitioners who serve historically excluded and mistreated populations. Participants will learn about culturally informed best practices to increase recruitment and retention of culturally diverse learners. Additionally, participants will hear how to create a culturally responsive training program that encourages an inclusive community for their learners through cohort learning, mentoring, community networking, and critical accountability.

Keywords: culturally diverse mental health practitioners, recruitment, mentorship, workforce development, underserved clinics, professional development

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Authors: Kelechi E. Ezeji

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The inclusion of relevant content in curricula of architecture schools is vital for attainment of Computer Aided Design (CAD) proficiency by graduates. Implementing this content involves, among other variables, the presence of competent tutors. Consequently, this study sought to investigate the importance of personnel recruitment for inclusion of content vital to the implementation of CAD in the curriculum for architecture education. This was with a view to developing a framework for appropriate implementation of CAD curriculum. It was focused on departments of architecture in universities in south-east Nigeria which have been accredited by National Universities Commission. Survey research design was employed. Data were obtained from sources within the study area using questionnaires, personal interviews, physical observation/enumeration and examination of institutional documents. A multi-stage stratified random sampling method was adopted. The first stage of stratification involved random sampling by balloting of the departments. The second stage involved obtaining respondents’ population from the number of staff and students of sample population. Chi Square analysis tool for nominal variables and Pearson’s product moment correlation test for interval variables were used for data analysis. With ρ < 0.5, the study found significant correlation between the number of CAD literate academic staff and use of CAD in design studio/assignments; that increase in the overall number of teaching staff significantly affected total CAD credit units in the curriculum of the department. The implications of these findings were that for successful implementation leading to attainment of CAD proficiency to occur, CAD-literacy should be a factor in the recruitment of staff and a policy of in-house training should be pursued.

Keywords: computer-aided design, education, personnel recruitment, curriculum

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Authors: S. Maddi Muhammed, Paul Davis, John Geraghty, Mabruk Derbesh

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This study discusses the probability of using electronic management in higher education institutions in Libya. This could be as sampled by creating an electronic gate at the faculties of Engineering and Computing "Information Technology" at Zaytuna University or any other university in Libya. As we all know, the competitive advantage amongst universities is based on their ability to use information technology efficiently and broadly. Universities today value information technology as part of the quality control and assurance and a ranking criterion for a range of services including e-learning and e-Registration. This could be done by developing email systems, electronic or virtual libraries, electronic cards, and other services provided to all students, faculty or staff. This paper discusses a range of important topics that explain how to apply the gate "E" with the faculties at Zaytuna University, Bani Walid colleges in Libya.

Keywords: e-management, educational institutions (EI), Libya, Zaytuna, information technology

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Authors: Avatharam Ganivada, Krishna Shah

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The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

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Authors: Moumita Chanda, Md. Fazlul Karim Patwary

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Smoking is one of the most popular recreational drug use behaviors, and it contributes to birth defects, COPD, heart attacks, and erectile dysfunction. To completely eradicate this disease, it is imperative that it be identified and treated. Numerous smoking cessation programs have been created, and they demonstrate how beneficial it may be to help someone stop smoking at the ideal time. A tomography meter is an effective smoking detector. Other wearables, such as RF-based proximity sensors worn on the collar and wrist to detect when the hand is close to the mouth, have been proposed in the past, but they are not impervious to deceptive variables. In this study, we create a machine that can discriminate between smokers and non-smokers in real-time with high sensitivity and specificity by watching and collecting the human lung and analyzing the X-ray data using machine learning. If it has the highest accuracy, this machine could be utilized in a hospital, in the selection of candidates for the army or police, or in university entrance.

Keywords: CNN, smoker detection, non-smoker detection, OpenCV, artificial Intelligence, X-ray Image detection

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Authors: Cigdem Fidan

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Deaf students in Turkey generally do not have access to foreign language classes. However, the knowledge of foreign languages, especially English, is important for them to access knowledge and other opportunities in the globalizing world. In addition, learning any language including foreign languages is a basic linguistic human right. This study applies critical discourse analysis to examine language ideologies, perceptions of deafness and current language and education policies used for deaf education in Turkey. The findings show that representation of deafness as a disability in policy documents, ignorance the role of sign languages in education and lack of policies that support foreign language education for the deaf may result in inaccessibility of foreign language education for deaf students in Turkey. The paper concludes with recommendations for policymakers, practitioners, and advocates for the deaf.

Keywords: deaf learners, English as a foreign language, language policy, linguistic human rights

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Authors: Edwin Foo, Woei Wen, Lui, Meijun Zhao, Shigeru Kuchii, Chin Sai Wong, Chung Sern Goh, Yi Hao He

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This presentation presents an elderly care and assistive social robot development work. We named this robot JOS and he is restricted to table top operation. JOS is designed to have a maximum volume of 3600 cm3 with its base restricted to 250 mm and his mission is to provide companion, assist and help the elderly. In order for JOS to accomplish his mission, he will be equipped with perception, reaction and cognition capability. His appearance will be not human like but more towards cute and approachable type. JOS will also be designed to be neutral gender. However, the robot will still have eyes, eyelid and a mouth. For his eyes and eyelids, they will be built entirely with Robotis Dynamixel AX18 motor. To realize this complex task, JOS will be also be equipped with micro-phone array, vision camera and Intel i5 NUC computer and a powered by a 12 V lithium battery that will be self-charging. His face is constructed using 1 motor each for the eyelid, 2 motors for the eyeballs, 3 motors for the neck mechanism and 1 motor for the lips movement. The vision senor will be house on JOS forehead and the microphone array will be somewhere below the mouth. For the vision system, Omron latest OKAO vision sensor is used. It is a compact and versatile sensor that is only 60mm by 40mm in size and operates with only 5V supply. In addition, OKAO vision sensor is capable of identifying the user and recognizing the expression of the user. With these functions, JOS is able to track and identify the user. If he cannot recognize the user, JOS will ask the user if he would want him to remember the user. If yes, JOS will store the user information together with the capture face image into a database. This will allow JOS to recognize the user the next time the user is with JOS. In addition, JOS is also able to interpret the mood of the user through the facial expression of the user. This will allow the robot to understand the user mood and behavior and react according. Machine learning will be later incorporated to learn the behavior of the user so as to understand the mood of the user and requirement better. For the speech system, Microsoft speech and grammar engine is used for the speech recognition. In order to use the speech engine, we need to build up a speech grammar database that captures the commonly used words by the elderly. This database is built from research journals and literature on elderly speech and also interviewing elderly what do they want to robot to assist them with. Using the result from the interview and research from journal, we are able to derive a set of common words the elderly frequently used to request for the help. It is from this set that we build up our grammar database. In situation where there is more than one person near JOS, he is able to identify the person who is talking to him through an in-house developed microphone array structure. In order to make the robot more interacting, we have also included the capability for the robot to express his emotion to the user through the facial expressions by changing the position and movement of the eyelids and mouth. All robot emotions will be in response to the user mood and request. Lastly, we are expecting to complete this phase of project and test it with elderly and also delirium patient by Feb 2015.

Keywords: social robot, vision, elderly care, machine learning

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Authors: Ridzuan Hussin, Mohd Zaihidee Arshad

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The creativity of earlier artists and sculptors in designing geometric is extraordinary provided with only a compass. Indeed, geometric in Islamic art and design are unique and have their own aesthetic values. In order to further understand geometric, self-learning with the approach of hands on would be appropriate. For this study, Islamic themed geometric designed and created, concerning only; i. The Square Repetition Unit and √2, ii. The Hexagonal Repetition Unit and √3 and iii. Double Hexagon. The aim of this research is to evaluate the creativity of Islamic geometric pattern artworks, through Fundamental Arts and Gestalt theory. Data was collected using specific tasks, and this research intends to identify the difference of Islamic geometric between 21 untitled selected geometric artworks (conventional design method), and 25 digital untitled geometric pattern artworks method. The evaluation of creativity, colors, layout, pattern and unity is known to be of utmost importance, although there are differences in the conventional or the digital approach.

Keywords: Islamic geometric design, Gestalt, fundamentals of art, patterns

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Authors: Sara Fayez Fawzy Mikhael

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Inclusive education services for students with Autism remains in its early developmental stages in Thailand. Despite many more children with autism are attending schools since the Thai government introduced the Education Provision for People with Disabilities Act in 2008, the services students with autism and their families receive are generally lacking. This quantitative study used Attitude and Preparedness to Teach Students with Autism Scale (APTSAS) to investigate 110 primary school teachers’ attitude and preparedness to teach students with autism in the general education classroom. Descriptive statistical analysis of the data found that student behavior was the most significant factor in building teachers’ negative attitudes students with autism. The majority of teachers also indicated that their pre-service education did not prepare them to meet the learning needs of children with autism in particular, those who are non-verbal. The study is significant and provides direction for enhancing teacher education for inclusivity in Thailand.

Keywords: attitude, autism, teachers, thailandsports activates, movement skills, motor skills

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Authors: Abdulla D. Alblooshi

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The stock market is a representation of human behavior and psychology, such as fear, greed, and discipline. Those are manifested in the form of price movements during the trading sessions. Therefore, predicting the stock movement and prices is a challenging effort. However, those trading sessions produce a large amount of data that can be utilized to train an AI agent for the purpose of predicting the stock movement. Predicting the stock market price action will be advantageous. In this paper, the stock movement data of three DFM listed stocks are studied using historical price movements and technical indicators value and used to train an agent using KNN and SVM methods to predict the future price movement. MATLAB Toolbox and a simple script is written to process and classify the information and output the prediction. It will also compare the different learning methods and parameters s using metrics like RMSE, MAE, and R².

Keywords: KNN, ANN, style, SVM, stocks, technical indicators, RSI, MACD, moving averages, RMSE, MAE

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Authors: Samwail Fahmi Francis Yacoub

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Inclusive education services for students with Autism remains in its early developmental stages in Thailand. Despite many more children with autism are attending schools since the Thai government introduced the Education Provision for People with Disabilities Act in 2008, the services students with autism and their families receive are generally lacking. This quantitative study used Attitude and Preparedness to Teach Students with Autism Scale (APTSAS) to investigate 110 primary school teachers’ attitude and preparedness to teach students with autism in the general education classroom. Descriptive statistical analysis of the data found that student behavior was the most significant factor in building teachers’ negative attitudes students with autism. The majority of teachers also indicated that their pre-service education did not prepare them to meet the learning needs of children with autism in particular, those who are non-verbal. The study is significant and provides direction for enhancing teacher education for inclusivity in Thailand.

Keywords: attitude, autism, teachers, movement skills, motor skills, children, behavior.

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Authors: K. O. Ogbedeh, C. P. Ekwe, G. O. Ihejirika, S. A. Dialoke, O. P. Onyewuchi, C. P. Anyanwu, I. E. Kalu

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As one of the major pests of field crops, termites attack groundnut at all stages of its development, especially during prolonged dry spell. Effect of palm bunch ash and neem(Azardirachta indica A. Juss) leaf powder on termite infestation in groundnut field in Owerri, Nigeria was investigated in this study. The field trial was carried out in 2016 at the Teaching and Research Farm of the Federal University of Technology, Owerri, Nigeria. The experiment was laid out in a 3x3 Factorial fitted into a Randomized Complete Block Design (RCBD) with three replications. The treatments include three rates of palm bunch ash at 0.0 (control), 1.0 and 2.0tons/ha and three rates of neem leaf powder at 0.0(control), 1.0, 2.0 tons/ha respectively. Data were collected on percentage emergence, termite incidence and termite severity. These were subjected to analysis of variance (ANOVA), and means were separated using least significant difference at 5% level of probability. The result shows that there were no significant (P= 0.05) differences in percentage emergence amongst treatment means due to palm bunch ash and neem leaf powder applications. Contrarily, palm bunch ash at 2.0 tons/ha recorded the least termite incidence especially at twelve weeks after planting (12WAP) with a value of 22.20% while control plot maintained highest values at 6WAP (48.70%) and 12WAP (48.30%) respectively. Also palm bunch ash at 2.0tons/ha depressed termite severity more than other treatments especially at 2 and 4 WAP (0.56) respectively. Control plots on the other hand consistently maintained highest termite severity throughout the trial with the highest value at 2 and 12WAP (1.56). Conclusively, palm bunch ash exhibited highest depressive action against termite on groundnut especially at higher application value (2.0tons/ha).

Keywords: groundnut, incidence, neem, palm, severity, termites

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Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha

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This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

Keywords: TDNN, neural networks, noise, speech recognition

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Authors: Ahmed R. Althobaiti, Malcolm Munro

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Communication and effective information exchange within technology has become a crucial part of delivering knowledge to students during the learning process. It enables better understanding, builds trust, respect and increase the knowledge between students. This paper examines the communication between undergraduate students and their lecturers during the Traditional lecture and in using the Interactive Electronic Lecture System (IELS). The IELS is an application that offers a set of components, which support the effective communication between students, themselves and their lecturers. Moreover, this paper highlights the communication skills such as sender, receiver, channel and feedback. It will show how the IELS creates a rich communication environment between its users and how they communicate effectively. To examine and check the effectiveness of communication an experiment has been conducted for groups of users; students and lecturers. The first group communicated during the Traditional lecture while the second group communicated by the IELS application. The result showed that there was an effective communication between the second group more than the first group.

Keywords: communication, effective information exchange, lecture, student

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Authors: Slim Chokri

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Load forecasting is one of the central functions in power systems operations. Electricity cannot be stored, which means that for electric utility, the estimate of the future demand is necessary in managing the production and purchasing in an economically reasonable way. A majority of the recently reported approaches are based on neural network. The attraction of the methods lies in the assumption that neural networks are able to learn properties of the load. However, the development of the methods is not finished, and the lack of comparative results on different model variations is a problem. This paper presents a new approach in order to predict the Tunisia daily peak load. The proposed method employs a computational intelligence scheme based on the Fuzzy neural network (FNN) and support vector regression (SVR). Experimental results obtained indicate that our proposed FNN-SVR technique gives significantly good prediction accuracy compared to some classical techniques.

Keywords: neural network, load forecasting, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression

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Authors: Shamini Dhana, G. Subrahmanya VRK Rao

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The fashion industry is advancing towards a mindset of zero waste, personalization, creativity, and circularity. The trend of upcycling clothing and materials into personalized fashion is being demanded by the next generation. There is a need for a digital tool to accelerate the process towards mass customization. Dhana’s D/Sphere fashion technology platform uses digital tools to accelerate upcycling. In essence, advanced fashion garments can be designed and developed via reuse, repurposing, recreating activities, and using existing fabric and circulating materials. The D/Sphere platform has the following objectives: to provide (1) An opportunity to develop modern fashion using existing, finished materials and clothing without chemicals or water consumption; (2) The potential for an everyday customer and designer to use the medium of fashion for creative expression; (3) A solution to address the global textile waste generated by pre- and post-consumer fashion; (4) A solution to reduce carbon emissions, water, and energy consumption with the participation of all stakeholders; (5) An opportunity for brands, manufacturers, retailers to work towards zero-waste designs and as an alternative revenue stream. Other benefits of this alternative approach include sustainability metrics, trend prediction, facilitation of disassembly and remanufacture deep learning, and hyperheuristics for high accuracy. A design tool for mass personalization and customization utilizing existing circulating materials and deadstock, targeted to fashion stakeholders will lower environmental costs, increase revenues through up to date upcycled apparel, produce less textile waste during the cut-sew-stitch process, and provide a real design solution for the end customer to be part of circular fashion. The broader impact of this technology will result in a different mindset to circular fashion, increase the value of the product through multiple life cycles, find alternatives towards zero waste, and reduce the textile waste that ends up in landfills. This technology platform will be of interest to brands and companies that have the responsibility to reduce their environmental impact and contribution to climate change as it pertains to the fashion and apparel industry. Today, over 70% of the $3 trillion fashion and apparel industry ends up in landfills. To this extent, the industry needs such alternative techniques to both address global textile waste as well as provide an opportunity to include all stakeholders and drive circular fashion with new personalized products. This type of modern systems thinking is currently being explored around the world by the private sector, organizations, research institutions, and governments. This technological innovation using digital tools has the potential to revolutionize the way we look at communication, capabilities, and collaborative opportunities amongst stakeholders in the development of new personalized and customized products, as well as its positive impacts on society, our environment, and global climate change.

Keywords: circular fashion, deep learning, digital technology platform, personalization

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Authors: Michael Amale Kirko, Abebe Gebretsadik

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In the 21st century, developing students’ critical thinking skills has become a prime concern in higher education institutions. Cognizant of this fact, the Ethiopian higher education policy document used critical thinking as one of the guiding principles. The study aims to explore how English as a foreign language (EFL) teachers perceive and practice critical thinking skills (CTS) in teaching reading to improve reading comprehension at Wolaita Sodo University, Ethiopia. A descriptive survey study used an exploratory mixed-methods approach. The study involved 20 EFL instructors and 40 2nd-year English majoring students. The numerical data were collected using teacher and student surveys and classroom observations; the qualitative data were obtained through content analysis and interviews. Teacher survey results indicated that teachers' perceptions are above average (mean = 3.41). And the result of classroom observations showed the practice CTS in class was below average (mean=2.61). The content analysis result revealed instructors utilized fewer higher-order thinking questions during class activities, quizzes, midterm, and final exams. The teachers perceived that teacher, student, and material-related challenges were hindering the practice of CT to improve students’ reading comprehension. Finally, spearman’s rho output showed r=0.97 and p<0.05. Therefore, the results showed that the EFL teachers’ practices of CTS to improve students’ reading comprehension were less frequent; there was a strong, positive, and statistically significant relationship between the teachers’ perceptions and practices of CTS in reading class.

Keywords: perceptions, critical thinking skills, practices, infusing thinking skills, reading comprehension

Procedia PDF Downloads 77

Authors: Csilla Paksi-Petró

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The Hungarian national public administration training system providing continuous, lifelong further training to some ten thousand executives in public administration was launched in 2014, adding skills and competency development to the previous training solutions, which had a mainly legal and professional approach. The executive training system is being continuously developed since tackling the existing qualitative, and quantitative challenges calls for the introduction of novel, innovative solutions. With a gap-filling character, this study presents, in brief, the last eight years of system of executive training in public administration, supported by the outcomes of the author's empirical research, makes suggestions for the possible directions of its further development. Through this article, the reader may obtain an overview of the current Hungarian civil service further training system, its institution system, the method of its application, its target groups, its results, and its development prospects. By reading the article, the reader will get acquainted with the good practices of the Hungarian civil service further training system.

Keywords: coaching, e-learning, executive development, further-training

Procedia PDF Downloads 123

Authors: Bibire Abdulkareem Hussein

Abstract:

Job satisfaction and motivation are considered as major tools in sustaining institutional development, they are also the machinery used to achieve an institutional goals and objectives. However, it has been observed that some institutions failed in motivating and stimulating their workers; in contrast, workers may be motivated but not satisfied with the job and failed to perform efficiently and effectively. It is hoped that the study of this nature would be of significance value to all stakeholders in education specifically, lecturers in higher institutions in Nigeria. Also it significances will enhance lecturers’ effectiveness and performance in discharging their duties. It is against this backdrop that, this study investigated whether job satisfaction and motivation predict lecturers’ effectiveness in Nigeria Police Academy, Wudil, KanoState. The correlational research method was adopted for the study while purposive sampling technique was used to choose the institution and the sampled lectures (70). Simple random sampling technique was used to select one hundred cadets across the academy. Two instruments were used to elicit information from both lecturers and cadets. These were job satisfaction and motivation; and lecturers’ effectiveness Questionnaires. The instruments were subjected to pilot testing and found to have reliability coefficient of 0.69 and 0.71 respectively. The results of the study revealed that there was a significance relationship among job satisfaction, motivation and lecturers effectiveness in Nigeria Police Academy, Job satisfaction had a Beta weight (β) of .125, t = 3.253, p<0.05, Job motivation had a Beta weight (β) of .185, t = 3.849, p<0.05. There was a significance relationship between job satisfaction and lecturers’ effectiveness in Nigeria Police Academy the cal r is 0.21 while the crt r is 0.19. at p<0.05 and; there was a significance relationship between job motivation and lecturers effectiveness in Nigeria Police Academy the cal r is 0.20 while the crt r is 0.19 at p<0.05This study therefore concluded that there was a significance relationship among job satisfaction, motivation and lecturers effectiveness in Nigeria Police Academy s,In view of the findings of this study, the paper recommends that lecturers should be more pro-active and more effective in their primary assignment (teaching) in order to make meaningful impacts and inputs in the life of cadets and boost the standard of the academy. In the same vein, it is recommended that management should intensify efforts to improve lecturers’ welfares by providing more motivational techniques to enhance more productivity.

Keywords: academy, lecturers effectiveness, motivation, satisfaction

Procedia PDF Downloads 472