Search results for: skills gained through learning

Authors: Sarita Agarwal, Deepika Delsa Dean

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Like the task of transferring photo images to artistic images, image-to-image translation aims to translate the data to the imitated data which belongs to the target domain. Neural Style Transfer and CycleGAN are two well-known deep learning architectures used for photo image-to-art image transfer. However, studies involving these two models concentrate on one-to-one domain translation, not one-to-multi domains translation. Our study tries to investigate deep learning architectures, which can be controlled to yield multiple artistic style translation only by adding a conditional vector. We have expanded CycleGAN and constructed Conditional CycleGAN for 5 kinds of categories translation. Our study found that the architecture inserting conditional vector into the middle layer of the Generator could output multiple artistic images.

Keywords: genetic counseling, FMR1 gene, fragile x-associated primary ovarian insufficiency, premutation

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Authors: Rima Al-Awadhi, Abdul Jaleel Tharayil

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On a regular basis, KOC engages into various types of Projects. However, due to very nature and complexity involved, each project experience generates a lot of ‘learnings’ that need to be factored into while drafting a new contract and thus avoid repeating the same mistakes. But, many a time these learnings are localized and remain as tacit leading to scope re-work, larger cycle time, schedule overrun, adjustment orders and claims. Also, these experiences are not readily available to new employees leading to steep learning curve and longer time to competency. This is to share our experience in designing and implementing a process driven architecture for the ‘lessons learnt’ knowledge sharing framework in KOC. It high-lights the ‘lessons learnt’ sharing process adopted, integration with the organizational processes, governance framework, the challenges faced and learning from our experience in implementing a ‘lessons learnt’ framework.

Keywords: lessons learnt, knowledge transfer, knowledge sharing, successful practices, Lessons Learnt Workshop, governance framework

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Authors: Nazia Shehzad

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Language and art can supplement and correlate each other. Through the ages art has been a means of visual expression used to convey a wide series of incarnated ideas. Art can take the perceiver into different times and into different worlds. It can also be used to introduce different levels of vocabulary to the learners of a second language. Learning a second language for most students is a very difficult and strenuous experience. They are not only trying to accommodate to a new language but are also trying to adjust to themselves and a new environment. They are anxious about almost everything, but they are especially self-conscious about their performance in the classroom. By relocating the focus from the student to an object, everyone participates, thus waiving a certain degree of self-consciousness. The experience, a student has with art in the classroom has to be gratifying for both the student and the teacher. If the atmosphere in the classroom is too grave it will not serve any useful purpose. Art is an excellent way to teach English and encourage collaboration and interaction between students of all ages. As making art involves many different processes, it is wonderful for classification and following/giving instructions. It is also an effective way to achieve and implement language of characterization and comparison and vocabulary acquirement for the elements of design (shape, size, color, texture, tone etc.) is so much more entertaining if done in a practical and hands-on way. Expressing ideas and feelings through art is also of immeasurable value where students are at the beginning stages of English language acquisition and for many of my Saudi students it was a form of therapy. It is also a way to respect, search, examine and share the cultural traditions of different cultures, and of the students themselves. Art not only provides a field for ideas to keep aimless, meandering minds of students' busy but is also a productive tool to analyze English language in a new order. As an ESL teacher, using art is a highly compelling way to bridge the gap between student and teacher. It’s difficult to keep students concentrated, especially when they speak a different language. To get students to actually learn and explore something in your foreign language lesson, artwork is your best friend. Many teachers feel that through amalgamation of the arts into their academic lessons students are able to learn more profoundly because they use diverse ways of thinking and problem solving. Teachers observe that drawing often retains students who might otherwise be dispassionate and can help students move ahead simple recall when they are asked to make connections and come up with an exclusive interpretation through an artwork or drawing. Students use observation skills when they are drawing, and this can help to persuade students who might otherwise remain silent or need more time to process information.

Keywords: amalgamation of arts, expressing ideas and feelings through arts, effective way to achieve and implement language, language and art can supplement and correlate each other

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Authors: Anna Sanczyk

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Teacher agency plays a crucial role in effective teaching, supporting diverse students, and providing an enriching learning environment; therefore, it is significant to gain a deeper understanding of language teachers’ sense of agency in teaching linguistically and culturally diverse students. This paper presents an overview of qualitative research on how language teachers exercise their agency in diverse classrooms. The analysis of the literature reveals that language teachers strive for addressing students’ needs and challenging educational inequalities, but experience educational constraints in enacting their agency. The examination of the research on language teacher agency identifies four major areas where language teachers experience challenges in enacting their agency: (1) implementing curriculum; (2) adopting school reforms and policies; (3) engaging in professional learning; (4) and negotiating various identities as professionals. The practical contribution of this literature review is that it provides a much-needed compilation of the studies on how language teachers exercise agency amid educational constraints. The discussion of the overview points to the importance of teacher identity, learner advocacy, and continuous professional learning and the critical need of promoting empowerment, activism, and transformation in language teacher education. The findings of the overview indicate that language teacher education programs should prepare teachers to be active advocates for English language learners and guide teachers to become more conscious of complexities of teaching in constrained educational settings so that they can become agentic professionals. This literature overview illustrates agency work in English language teaching contexts and contributes to understanding of the important link between experiencing educational constraints and development of teacher agency.

Keywords: advocacy, educational constraints, language teacher agency, language teacher education

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Authors: Abhigyan Hedau, Priya Shelke, Riddhi Mirajkar, Shreyash Chaple, Mrunali Gadekar, Himanshu Akula

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The heart is the coordinating centre of the major endocrine glandular structure of the body, which produces hormones that profoundly affect the operations of the body, and diagnosing cardiovascular disease is a difficult but critical task. By extracting knowledge and information about the disease from patient data, data mining is a more practical technique to help doctors detect disorders. We use a variety of machine learning methods here, including logistic regression and support vector classifiers (SVC), K-nearest neighbours Classifiers (KNN), Decision Tree Classifiers, Random Forest classifiers and Gradient Boosting classifiers. These algorithms are applied to patient data containing 13 different factors to build a system that predicts heart disease in less time with more accuracy.

Keywords: logistic regression, support vector classifier, k-nearest neighbour, decision tree, random forest and gradient boosting

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Authors: Lancer Scott

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Purpose: High quality clinical disaster medicine requires providers working collaboratively to care for multiple patients in chaotic environments; however, many providers lack adequate training. To address this deficit, we created a competency-based, 5-hour Emergency Preparedness Training (EPT) curriculum using didactics, small-group discussion, and kinetic learning. The goal was to evaluate the effect of a short course on improving provider knowledge, confidence and skills in disaster scenarios. Methods: Diverse groups of medical university students, health care professionals, and community members were enrolled between 2011 and 2014. The course consisted of didactic lectures, small group exercises, and two live, multi-patient mass casualty incident (MCI) scenarios. The outcome measures were based on core competencies and performance objectives developed by a curriculum task force and assessed via trained facilitator observation, pre- and post-testing, and a course evaluation. Results: 708 participants completed were trained between November 2011 and August 2014, including 49.9% physicians, 31.9% medical students, 7.2% nurses, and 11% various other healthcare professions. 100% of participants completed the pre-test and 71.9% completed the post-test, with average correct answers increasing from 39% to 60%. Following didactics, trainees met 73% and 96% of performance objectives for the two small group exercises and 68.5% and 61.1% of performance objectives for the two MCI scenarios. Average trainee self-assessment of both overall knowledge and skill with clinical disasters improved from 33/100 to 74/100 (overall knowledge) and 33/100 to 77/100 (overall skill). The course assessment was completed by 34.3% participants, of whom 91.5% highly recommended the course. Conclusion: A relatively short, intensive EPT course can improve the ability of a diverse group of disaster care providers to respond effectively to mass casualty scenarios.

Keywords: clinical disaster medicine, training, hospital preparedness, surge capacity, education, curriculum, research, performance, training, student, physicians, nurses, health care providers, health care

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Authors: Harun Bozna

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MOOC (massive open online course) is a groundbreaking education platform and a current buzzword in higher education. Although MOOCs offer many appreciated learning experiences to learners from various universities and institutions, they have considerably higher dropout rates than traditional education. Only about 10% of the learners who enroll in MOOCs actually complete the course. In this case, perceptions of participants and a comprehensive analysis of MOOCs have become an essential part of the research in this area. This study aims to explore the MOOCs in detail for better understanding its content, purpose and primarily drop out issues. The researcher conducted an online questionnaire to get perceptions of graduate students on their learning experiences in MOOCs and arranged a semi- structured oral interview with some participants. The participants are Turkish graduate level students doing their MA and Ph.D. in various programs. The findings show that participants are more likely to drop out courses due to lack of time and lack of pressure.

Keywords: distance education, MOOCs, drop out, perception of graduate students

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Authors: Goldie Lynn Diaz, Ma. Teresa Tricia G. Bautista, Elisabeth Engeljakob, Mary Glaze Rosal

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Introduction: Residents are expected to convey unfavorable news, discuss prognoses, and relieve suffering, and address do-not-resuscitate orders, yet some report a lack of competence in providing this type of care. Recognizing this need, Family Medicine residency programs are incorporating end-of-life care from symptom and pain control, counseling, and humanistic qualities as core proficiencies in training. Objective: This study determined the competency of Family Medicine Residents from various institutions in Metro Manila on rendering care for the dying. Materials and Methods: Trainees completed a Palliative Care Evaluation tool to assess their degree of confidence in patient and family interactions, patient management, and attitudes towards hospice care. Results: Remarkably, only a small fraction of participants were confident in performing independent management of terminal delirium and dyspnea. Fewer than 30% of residents can do the following without supervision: discuss medication effects and patient wishes after death, coping with pain, vomiting and constipation, and reacting to limited patient decision-making capacity. Half of the respondents had confidence in supporting the patient or family member when they become upset. Majority expressed confidence in many end-of-life care skills if supervision, coaching and consultation will be provided. Most trainees believed that pain medication should be given as needed to terminally ill patients. There was also uncertainty as to the most appropriate person to make end-of-life decisions. These attitudes may be influenced by personal beliefs rooted in cultural upbringing as well as by personal experiences with death in the family, which may also affect their participation and confidence in caring for the dying. Conclusion: Enhancing the quality and quantity of end-of-life care experiences during residency with sufficient supervision and role modeling may lead to knowledge and skill improvement to ensure quality of care. Fostering bedside learning opportunities during residency is an appropriate venue for teaching interventions in end-of-life care education.

Keywords: end of life care, geriatrics, palliative care, residency training skill

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Authors: Min Chen, Rubi Gupta

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Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

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Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Paul Nadasdy

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In 2020, oral communication classes at many universities in Japan switched to online and hybrid lessons because of the coronavirus pandemic. Teachers had to adapt their practices immediately and deal with the challenges of the online environment. Even for experienced teachers, this still presented a problem as many had not conducted online classes before. Simultaneously, for many students, this type of learning was completely alien to them, and they had to adapt to the challenges faced by communicating in English online. This study collected data from 418 first grade students in the first semester of English communication classes at a technical university in Tokyo, Japan. Zoom software was used throughout the learning period. Though there were many challenges in the setting up and implementation of Zoom classes at the university, the results indicated that the students enjoyed the format and made the most of the circumstances. This proved the robustness of the course that was taught in regular lessons and the adaptability of teachers and students to challenges in a very short timeframe.

Keywords: zoom, hybrid lessons, communicative english, online teaching

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Authors: Mohammed Alharbi, Clare Wood, Vasileios Samaras

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Sustainability leadership is a controversial topic, particularly in the engineering context. The theoretical and practical technical focus of the engineering profession impacts our lives. Technologically, engineers significantly contribute to our modern civilization. Industrial revolutions are among the top engineering accomplishments that have contributed to the flourishing of our life. However, engineers have not always received the credit they deserve; instead, they have been blamed for the advent of various global issues, among them the global warming phenomena that are believed to be a result of the industrial revolutions. Global challenges demand engineers demonstrate more than their technical skills for effective contribution to a sustainable future. As a result, engineering leadership has emerged as a new research field. Sustainable manufacturing is a cornerstone for sustainable development. Investigating the change to more sustainable manufacturing practices is a significant issue for all, and even more in the field of engineering leadership. Engineers dominate the manufacturing industry; however, one of the main criticism of engineers is the lack of leadership skills. The literature on engineering leadership has not highlighted enough the engineers' leadership ability in leading sustainable manufacturing. Since we are at the cusp of a new industrial revolution -Industry 4.0, it is vital to investigate the ability of engineers to lead the industry towards a sustainable future. The primary purpose of this paper is to evaluate engineers' sustainability leadership competencies utilizing The Cambridge University Behavioral Competency Model. However, the practical application of the Cambridge model is limited due to the absence of a reliable measurement tool. Therefore, this study developed a valid and reliable survey instrument tool compatible with the Cambridge model as a secondary objective. More than 300 Saudi engineers from the manufacturing industry responded to an online questionnaire collected through the Qualtrics platform and analyzed using SPSS software. The findings provide a contemporary understanding of engineers' mindset related to sustainability leadership. The output of this research study could be valuable in designing effective engineering leadership programs in academia or industry, particularly for enhancing a sustainable manufacturing environment.

Keywords: engineer, leadership, manufacturing, sustainability

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Authors: Bernard Morais Joosa

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Kerala, the southern state of India, is known for its accomplishments in universal education and enrollments. Through this mission, the Government proposes comprehensive educational reforms including 1000 Government schools into international standards during the first phase. The idea is not only to improve the infrastructural facilities but also to reform the teaching and learning process to the present day needs by introducing ICT enabled learning and providing smart classrooms. There will be focus on creating educational programmes which are useful for differently abled students. It is also meant to reinforce the teaching–learning process by providing ample opportunities to each student to construct their own knowledge using modern technology tools. The mission will redefine the existing classroom learning process, coordinate resource mobilization efforts and develop ‘Janakeeya Vidyabhyasa Mathruka.' Special packages to support schools which are in existence for over 100 years will also be attempted. The implementation will enlist full involvement and partnership of the Parent Teacher Association. Kerala was the first state in the country to attain 100 percent literacy more than two and a half decades ago. Since then the State has not rested on its laurels. It has moved forward in leaps and bounds conquering targets that no other State could achieve. Now the government of Kerala is taking off towards new goal of comprehensive educational reforms. And it focuses on Betterment of educational surroundings, use of technology in education, renewal of learning method and 1000 schools will be uplifted as Smart Schools. Need to upgrade 1000 schools into international standards and turning classrooms from standard 9 to 12 in high schools and higher secondary into high-tech classrooms and a special unique package for the renovation of schools, which have completed 50 and 100 years. The government intends to focus on developing standards first to eighth standards in tune with the times by engaging the teachers, parents, and alumni to recapture the relevance of public schools. English learning will be encouraged in schools. The idea is not only to improve the infrastructure facilities but also reform the curriculum to the present day needs. Keeping in view the differently-abled friendly approach of the government, there will be focus on creating educational program which is useful for differently abled students. The idea is to address the infrastructural deficiencies being faced by such schools. There will be special emphasis on ensuring internet connectivity to promote IT-friendly existence. A task-force and a full-time chief executive will be in charge of managing the day to day affairs of the mission. Secretary of the Public Education Department will serve as the Mission Secretary and the Chairperson of Task Force. As the Task Force will stress on teacher training and the use of information technology, experts in the field, as well as Directors of SCERT, IT School, SSA, and RMSA, will also be a part of it.

Keywords: educational standards, methodology, pedagogy, technology

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Authors: Payam Najafi, Behnam Ebrahimi, Hamid Montazerolghaem, Safoura Akbari-Alavijeh, Rasoul Tarkesh Esfahani

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The combination of work and study has been recently gained lots of attention due to the crucial demand of industries to skillfully trained youth. Nevertheless, the distance between university and industry makes this combination challenging. According to the OECD (2012), in most countries, there is a limited link between students’ field of study and their area of work while studying. On the other hand, high unemployment rates among the specialized workforce, which is common in developing countries, highlights the need to strengthen this relationship. Innovative Center of Isfahan Chamber of Commerce has defined a project called 'POUYESH', which helps students to find related work opportunities to their field of study as well as supporting industries to supply their needed workforce. The present research is sought to explore the effect of the running project as a model of combining work and study on the university-industry linkage.

Keywords: work and study, university-industry linkage, POUYESH project, field of study

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Authors: Wang Jiankun

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This paper analyses how different educational backgrounds affect the mathematics performance of middle and high school students in terms of three dimensions: parental involvement, school teaching ability, and demographic variables and personal attributes of the student. Based on the analysis of Beijing High School Mathematics Competition in 2022, it was found that students from high level schools won significantly more awards than those from low level schools. In addition, a significant positive correlation (p<0.05) was identified between school level and students' mathematics performance. This study also confirms that parents' education level and family environment show a significant impact on the next generation’s mathematics learning performance. The findings suggest that interest and student’s habits, the family environment and the quality of teaching and learning at school are the main factors affecting the mathematics performance of middle and high school students.

Keywords: educational background, academic performance, middle and high school education, teenager

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Authors: Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath

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Where human beings can easily learn and adopt pronunciation variations, machines need training before put into use. Also humans keep minimum vocabulary and their pronunciation variations are stored in front-end of their memory for ready reference, while machines keep the entire pronunciation dictionary for ready reference. Supervised methods are used for preparation of pronunciation dictionaries which take large amounts of manual effort, cost, time and are not suitable for real time use. This paper presents an unsupervised adaptation model for building agile and dynamic pronunciation dictionaries online. These methods mimic human approach in learning the new pronunciations in real time. A new algorithm for measuring sound distances called Dynamic Phone Warping is presented and tested. Performance of the system is measured using an adaptation model and the precision metrics is found to be better than 86 percent.

Keywords: pronunciation variations, dynamic programming, machine learning, natural language processing

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Authors: Ahmad Rouhani, Masood Jabbari, Sima Honarmand

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This paper introduces a method to optimal design of a hybrid Wind/Photovoltaic/Fuel cell generation system for a typical domestic load that is not located near the electricity grid. In this configuration the combination of a battery, an electrolyser, and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. The Matlab/Simulink is applied for choosing the appropriate structure and the optimization of system sizing. A teaching learning based optimization is used to optimize the cost function. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results have been analyzed in terms of technics and economics. The simulation results indicate that the proposed hybrid system would be a feasible solution for stand-alone applications at remote locations.

Keywords: hybrid energy system, optimum sizing, power management, TLBO

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Authors: Amrita Anil Agashe, Sumant Tapas, Ajay Verma Yogesh Sonavane, Sourabh Yeravar

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Due to advancement in MEMS technology today wireless sensors network has gained a lot of importance. The wide range of its applications includes environmental and habitat monitoring, object localization, target tracking, security surveillance etc. Wireless sensor networks consist of tiny sensor devices called as motes. The constrained computation power, battery power, storage capacity and communication bandwidth of the tiny motes pose challenging problems in the design and deployment of such systems. In this paper, we propose a ubiquitous framework for Real-Time Tracking, Sensing and Management System using IITH motes. Also, we explain the algorithm that we have developed for location management in wireless sensor networks with the aspect of mobility. Our developed framework and algorithm can be used to detect emergency events and safety threats and provides warning signals to handle the emergency.

Keywords: mobility management, motes, multihop, wireless sensor networks

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Authors: George Kurian, Hongmei Chi

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Digital evidence plays a critical role in most legal investigations. In many cases, thumbnail databases show important information in that investigation. The probability of having digital evidence retrieved from a computer or smart device has increased, even though the previous user removed data and deleted apps on those devices. Due to the increase in digital forensics, the ability to store residual information from various thumbnail applications has improved. This paper will focus on investigating thumbnail information from Windows 10. Thumbnail images of interest in forensic investigations may be intact even when the original pictures have been deleted. It is our research goal to recover useful information from thumbnails. In this research project, we use various forensics tools to collect left thumbnail information from deleted videos or pictures. We examine and describe the various thumbnail sources in Windows and propose a methodology for thumbnail collection and analysis from laptops or desktops. A machine learning algorithm is adopted to help speed up content from thumbnail pictures.

Keywords: digital forensic, forensic tools, soundness, thumbnail, machine learning, OCR

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Authors: Arun Prasad Jaganathan

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In today's dynamic industrial world, traditional task allocation methods often fall short in adapting to evolving operational conditions. This paper introduces an AI-enabled task assistance and management system designed to overcome the limitations of conventional approaches. By using artificial intelligence (AI) and machine learning (ML), the system intelligently interprets user instructions, analyzes tasks, and allocates resources based on real-time data and environmental factors. Additionally, geolocation tracking enables proactive identification of potential delays, ensuring timely interventions. With its transparent reporting mechanisms, the system provides stakeholders with clear insights into task progress, fostering accountability and informed decision-making. The paper presents a comprehensive overview of the system architecture, algorithm, and implementation, highlighting its potential to revolutionize task management across diverse industries.

Keywords: artificial intelligence, machine learning, task allocation, operational efficiency, resource optimization

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Authors: Saima Haq

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This paper presents the contribution of the Sunflowers Vocational Center, Karachi, Pakistan, by providing a platform for the students of special needs to work with recycled materials and express themselves in a more extravagant form. The concept was to create products that would generate enough income to sustain the program while keeping the students cognitively engaged through arts and crafts and tactile instructions due to their severe intellectual disabilities. Papier-mâché is an art form that is hands-on, repetitive, economical as well as beneficial for the environment. The process of tearing paper into long strips then covering them with paste and laying the strips atop the mold provides constant sensory input for our autistic students as well as the rest of our student population. Given the marginalized stance the society has on special needs, we have marketed the paper-mâché products on social media platforms and have set up booths in carnivals, festivities, open markets that are aimed towards a cause to sell. Our students in the vocational center have also made bins, baskets, and trays that are used in all classrooms. This has cut our costs on classroom materials considerably and has added a sense of accomplishment and furthered the teamwork skills in our sunflowers. The other achievement is our long clientele; orders have been placed from several persons for birthdays, parties, events, and the like. This exposure has raised awareness of the capabilities of persons of special needs and has started a conversation on the topic. And additional achievement is that we have made our teachers, their families, our students, and their families conscientious of the environment and incorporated reusing newspapers into classrooms. Situations where plastic would be bought, for example, bin, dustbins, containers, basket, trays, the paper-mâché products made by our students have been used instead. Due to the low cost of materials, this project is easily replicable and very easy to start. Piñatas are a very popular item for children’s parties everywhere and are gaining popularity through social media. This is also easily replicable in any environment and can have a great impact on the use of plastic in any work or home environment.

Keywords: vocational training, special needs, cognitive skills, teamwork

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Authors: Mohammed A. M. Ibrahim

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This paper investigate the utilization of wire and wireless networks to be platform for distributed educational monitoring system. Universities in developing countries suffer from a lot of shortages(staff, equipment, and finical budget) and optimal utilization of the wire and wireless network, so universities can mitigate some of the mentioned problems and avoid the problems that maybe humble the education processes in many universities by using our implementation of the examinations system as a test-bed to utilize the network as a solution to the shortages for academic staff in Taiz University. This paper selects a two areas first one quizzes activities is only a test bed application for wireless network learning environment system to be distributed among students. Second area is the features and the security of wireless, our tested application implemented in a promising area which is the use of WLAN in higher education for leering environment.

Keywords: networking wire and wireless technology, wireless network security, distributed computing, algorithm, encryption and decryption

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Peter Williams

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Mobile digital technology, in the form of smart phones, tablets, laptops and their accompanying functionality/apps etc., is becoming ever more used by people with Learning Disabilities (LD) - for entertainment, to communicate and socialize, and enjoy self-expression. Despite this, there has been very little research into the experiences of such technology by this cohort, it’s role in articulating personal identity and self-advocacy and the barriers encountered in negotiating technology in everyday life. The proposed talk describes research funded by the British Academy addressing these issues. It aims to explore: i) the experiences of people with LD in using mobile technology in their everyday lives – the benefits, in terms of entertainment, self-expression and socialising, and possible greater autonomy; and the barriers, such as accessibility or usability issues, privacy or vulnerability concerns etc. ii) how the technology, and in particular the software/apps and interfaces, can be improved to enable the greater access to entertainment, information, communication and other benefits it can offer. It is also hoped that results will inform parents, carers and other supporters regarding how they can use the technology with their charges. Rather than the project simply following the standard research procedure of gathering and analysing ‘data’ to which individual ‘research subjects’ have no access, people with Learning Disabilities (and their supporters) will help co-produce an accessible, annotated and hyperlinked living e-archive of their experiences. Involving people with LD as informants, contributors and, in effect, co-researchers will facilitate digital inclusion and empowerment. The project is working with approximately 80 adults of all ages who have ‘mild’ learning disabilities (people who are able to read basic texts and write simple sentences). A variety of methods is being used. Small groups of participants have engaged in simple discussions or storytelling about some aspect of technology (such as ‘when my phone saved me’ or ‘my digital photos’ etc.). Some individuals have been ‘interviewed’ at a PC, laptop or with a mobile device etc., and asked to demonstrate their usage and interests. Social media users have shown their Facebook pages, Pinterest uploads or other material – giving them an additional focus they have used to discuss their ‘digital’ lives. During these sessions, participants have recorded (or employed the researcher to record) their observations on to the e-archive. Parents, carers and other supporters are also being interviewed to explore their experiences of using mobile technology with the cohort, including any difficulties they have observed their charges having. The archive is supplemented with these observations. The presentation will outline the methods described above, highlighting some of the special considerations required when working inclusively with people with LD. It will describe some of the preliminary findings and demonstrate the e-archive with a commentary on the pages shown.

Keywords: inclusive research, learning disabilities, methods, technology

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Authors: John Lloyd Angolluan, Jennile Caday, Crystal Mae Estrella, Reike Alliyah Taladua, Zion Michael Ysulat

Abstract:

One of the requirements of having the ability to communicate in English is by having adequate vocabulary. Nowadays, people are more engaged in watching movie streams on which they can watch movies in a very portable way, such as Netflix. Wherein Netflix became global demand for online media has taken off in recent years. This research aims to know whether the use of bimodal subtitles on Netflix English movies can enhance vocabulary. This study is quantitative and utilizes a descriptive method, and this study aims to explore the use of bimodal subtitles on Netflix English movies to enhance the vocabulary of students. The respondents of the study were the selected Second-year English majors of Rizal Technological University Pasig and Boni Campus using the purposive sampling technique. The researcher conducted a survey questionnaire through the use of Google Forms. In this study, the weighted mean was used to evaluate the student's responses to the statement of the problems of the study of the use of bimodal subtitles on Netflix English movies. The findings of this study revealed that the bimodal subtitle on Netflix English movies enhanced students’ vocabulary learning acquisition by providing learners with access to large amounts of real and comprehensible language input, whether accidentally or intentionally, and it turns out that bimodal subtitles on Netflix English movies help students recognize vocabulary, which has a positive impact on their vocabulary building. Therefore, the researchers advocate that watching English Netflix movies enhances students' vocabulary by using bimodal subtitled movie material during their language learning process, which may increase their motivation and the usage of bimodal subtitles in learning new vocabulary. Bimodal subtitles need to be incorporated into educational film activities to provide students with a vast amount of input to expand their vocabulary.

Keywords: bimodal subtitles, Netflix, English movies, vocabulary, subtitle, language, media

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Authors: Nuri Balta, Ali Eryilmaz

Abstract:

High-quality teachers are the key to improve student learning. Without a professional development of the teachers, the improvement of student success is difficult and incomplete. This study offers an in-service training course model for professional development of teachers (PD) entitled "teachers teaching teachers" (TTT). The basic premise of the PD program, designed for this study, was primarily aimed to increase the subject matter knowledge of high school physics teachers. The TTT course (the three hour long workshops), organized for this study, lasted for seven weeks with seventeen teachers took part in the TTT program at different amounts. In this study, the effect of the TTT program on teachers’ knowledge improvement was searched through the modern physics unit (MPU). The participating teachers taught the unit to one of their grade ten classes earlier, and they taught another equivalent class two months later. They were observed in their classes both before and after TTT program. The teachers were divided into placebo and the treatment groups. The aim of Solomon four-group design is an attempt to eliminate the possible effect of pre-test. However, in this study the similar design was used to eliminate the effect of pre teaching. The placebo group teachers taught their both classes as regular and the treatment group teachers had TTT program between the two teachings. The class observation results showed that the TTT program increased teachers’ knowledge and skills in teaching MPU. Further, participating in the TTT program caused teachers to teach the MPU in accordance with the requirements of the curriculum. In order to see any change in participating teachers’ success, an achievement test was applied to them. A large effect size (dCohen=.93) was calculated for the effect of TTT program on treatment group teachers’ achievement. The results suggest that staff developers should consider including topics, attractive to teachers, in-service training programs (a) to help teachers’ practice teaching the new topics (b) to increase the participation rate. During the conduction of the TTT courses, it was observed that teachers could not end some discussions and explain some concepts. It is now clear that teachers need support, especially when discussing counterintuitive concepts such as modern physics concepts. For this reason it is recommended that content focused PD programs be conducted at the helm of a scholarly coach.

Keywords: high school physics, in-service training course, modern physics unit, teacher professional development

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Authors: Qi Wang

Abstract:

In the classroom, teachers have been trained to complete the target task within the limited lecture time, meanwhile learners need to receive a lot of new knowledge, however, most of the time the learners come without the proper pre-class preparation to efficiently take in the contents taught in class. Under this circumstance, teachers do have no time to check whether the learners fully understand the content or not, how the learners communicate in the different contexts, until teachers see the results when the learners are tested. In the past decade, the teaching of Chinese has taken a trend. Teaching focuses less on the use of proper grammatical terms/punctuation and is now placing a heavier focus on the materials from real life contexts. As a result, it has become a greater challenge to teachers, as this requires teachers to fully understand/prepare what they teach and explain the content with simple and understandable words to learners. On the other hand, the same challenge also applies to the learners, who come from different countries. As they have to use what they learnt, based on their personal understanding of the material to effectively communicate with others in the classroom, even in the contexts of a day to day communication. To reach this win-win stage, Feynman’s Technique plays a very important role. This practical report presents you how the Feynman’s Technique is applied into Chinese courses, both writing & oral, to motivate the learners to practice more on writing, reading and speaking in the past few years. Part 1, analysis of different teaching styles and different types of learners, to find the most efficient way to both teachers and learners. Part 2, based on the theory of Feynman’s Technique, how to let learners build the knowledge from knowing the name of something to knowing something, via different designed target tasks. Part 3. The outcomes show that Feynman’s Technique is the interaction of learning style and teaching style, the double-edged sword of Teaching & Learning Chinese as a Second Language.

Keywords: Chinese, Feynman’s technique, learners, teachers

Procedia PDF Downloads 139

Authors: Bharatendra Rai

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Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

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Authors: Chonmapat Torasa

Abstract:

This paper presents the performance of electricity generation and consumption from solar generator installed at Rajabhat Suan Sunandha’s learning center in Samutsongkram. The result from the experiment showed that solar cell began to work and distribute the current into the system when the solar energy intensity was 340 w/m2, starting from 8:00 am to 4:00 pm (duration of 8 hours). The highest intensity read during the experiment was 1,051.64w/m2. The solar power was 38.74kWh/day. The electromotive force from solar cell averagely was 93.6V. However, when connecting solar cell with the battery charge controller system, the voltage was dropped to 69.07V. After evaluating the power distribution ability and electricity load of tested solar cell, the result showed that it could generate power to 11 units of 36-wattfluorescent lamp bulbs, which was altogether 396W. In the meantime, the AC to DC power converter generated 3.55A to the load, and gave 781VA.

Keywords: solar cell, solar-cell power generating system, computer, systems engineering

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Authors: K. G. Adeosun, K. Osunaiye, E. C. Chinaguh, M. A. Aliyu, C. A. Onifade

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This study examined the effects of incompetence in the use of the mother tongue on the spoken English of selected Primary School pupils in Abeokuta South Local Government, Ogun State, Nigeria. The study used a structured questionnaire and interview guide as data collection instruments. The target population was 110 respondents. The sample was obtained by the use of simple random and stratified sampling techniques. The study samples were pupils from Government Primary Schools in Abeokuta South Local Government. The result revealed that the majority of pupils exhibited mother tongue interference in their oral production stage and that the local indigenous languages interfered with the pronunciation of English words to a large extent such that they pronounced ‘people’ as ‘fitful.’ The findings also revealed that there is no significant difference between inadequate teaching materials, shortage of funds towards the promotion of the mother tongue (Yoruba) and spoken English of Primary school pupils in the study area. The study recommended, among other things, that government should provide the necessary support for schools in the areas of teaching and learning materials, funds and other related materials that can enhance the effective use of the mother tongue towards spoken English by Primary School pupils. Government should ensure that oral English is taught to the pupils and the examination at the end of Primary school education should be made compulsory for all pupils. More so, the Government should provide language laboratories and other equipment to facilitate good teaching and learning of oral English.

Keywords: education, effective, government, learning, teaching

Procedia PDF Downloads 71