Search results for: learning disability

Authors: Matthew Bamidele Ojuawo

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To some parents, task avoidance implies the time when argument ensues between parents and their children in order to get certain things done correctly without being forced. However, some children avoid certain task because of the fears that it is too hard or cannot be done without parental help. Laziness plays a role in task avoidance when children do not want to do something because they do not feel like it is easy enough or if they just want their parent help them get it over with more quickly. Children with attention deficit disorder more often have difficulties with social skills, such as social interaction and forming and maintaining friendships. The focus of this study is how task avoidance and attention deficit have effect on the mathematics performance of pupils in the lower basic classroom. Mathematics performance of pupils with learning disabilities has been seriously low due to avoidance of task and attention deficit posed as carried out in the previous researches, but the research has not been carried out in the lower basic classroom in Oyo, Oyo state, Nigeria.

Keywords: task avoidance, parents, children with attention deficit, mathematics

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Authors: Yacoub Aljaffery

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Many English writing instructors try to avoid creative writing in their classrooms thinking they need to teach essay rules and organization skills. They seem to forget that creative writing has do’s and don’ts as well. While academic writing is different from fiction writing in some important ways (although perhaps the boundaries are fruitfully blurring), there is much that can be writerly selves. The differences between creative writing and academic writing are that creative writing is written mainly to entertain with the creativity of the mind and academic writing is written mainly to inform in a formal manner or to incite the reader to make an action such as purchase the writer’s product. In this research paper, we are going to find out how could Arabic speaking students, who are learning academic writing in universities, benefit from creative writing such as literature, theatrical scripts, music, and poems. Since Arabic language is known as poetic language, students from this culture tend to like writing with creativity. We will investigate the positive influence of creative writing rules on academic essays and paragraphs in universities, and We will prove the importance of using creative writing activities in any academic writing classroom.

Keywords: ESL teaching, motivation, teaching methods, academic writing , creative writing

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Authors: Mariam Wagih Nagib Eskandar

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The engineering design process is the activities formulation, to help an engineer raising a plan with a specified goal and performance. The engineering design process is a multi-stage course of action including the conceptualization, research, feasibility studies, establishment of design parameters, preliminary and finally the detailed design. It is a progression from the abstract to the concrete; starting with probably abstract ideas about need, and thereafter elaborating detailed specifications of the object that would satisfy the needs, identified. Engineering design issues, problems, and solutions are discussed in this paper using qualitative approach from an information structure perspective. The objective is to identify the problems, to analyze them and propose solutions by integrating; innovation, practical experience, time and resource management, communications skills, isolating the problem in coordination with all stakeholders. Consequently, this would be beneficial for the engineering community to improve the Engineering design practices.

Keywords: education, engineering, math, performanceengineering design, architectural engineering, team-based learning, construction safetyrequirement engineering, models, practices, organizations

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Authors: Aliya Moreira, Blake Duffy, Sam Kosinski, Kate Heckman, Erika Steensma

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Introduction: The One Health initiative promotes recognition of the interrelatedness between people, animals, plants, and their shared environment. The field of comparative medicine studies the similarities and differences between humans and animals for the purpose of advancing medical sciences. Currently, medical school education is narrowly focused on human anatomy and physiology, but as the COVID-19 pandemic has demonstrated, a holistic understanding of health requires comprehension of the interconnection between health and the lived environment. To prepare future physicians for unique challenges from emerging zoonoses to climate change, medical students can benefit from exposure to and experience with One Health and Comparative Medicine content. Methods: In January 2020, an elective course for medical students on One Health and Comparative Medicine was created to provide medical students with the background knowledge necessary to understand the applicability of animal and environmental health in medical research and practice. The 2-week course was continued in January 2021, with didactic and experiential activities taking place virtually due to the COVID-19 pandemic. In response to student feedback, lectures were added to expand instructional content on zoonotic and wildlife diseases for the second iteration of the course. Other didactic sessions included interprofessional lectures from 20 physicians, veterinarians, public health professionals, and basic science researchers. The first two cohorts of students were surveyed regarding One Health and Comparative Medicine concepts at the beginning and conclusion of the course. Results: 16 medical students have completed the comparative medicine course thus far, with 87.5% (n=14) completing pre-and post-course evaluations. 100% of student respondents indicated little to no exposure to comparative medicine or One Health concepts during medical school. Following the course, 100% of students felt familiar or very familiar with comparative medicine and One Health concepts. To assess course efficacy, questions were evaluated on a five-point Likert scale. 100% agreed or strongly agreed that learning Comparative Medicine and One Health topics augmented their medical education. 100% agreed or strongly agreed that a course covering this content should be regularly offered to medical students. Conclusions: Data from the student evaluation surveys demonstrate that the Comparative Medicine course was successful in increasing medical student knowledge of Comparative Medicine and One Health. Results also suggest that interprofessional training in One Health and Comparative Medicine is applicable and useful for medical trainees. Future iterations of this course could capitalize on the inherently interdisciplinary nature of these topics by enrolling students from veterinary and public health schools into a longitudinal course. Such recruitment may increase the course’s value by offering multidisciplinary student teams the opportunity to conduct research projects, thereby strengthening both the individual learning experience as well as sparking future interprofessional research ventures. Overall, these efforts to educate medical students in One Health topics should be reproducible at other institutions, preparing more future physicians for the diverse challenges they will encounter in practice.

Keywords: medical education, interprofessional instruction, one health, comparative medicine

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Gulshad Azatova, Aleksandr Kapitonov, Natig Aminov

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Multiagent systems have gained significant attention in various fields, such as robotics, autonomous vehicles, and distributed computing, where multiple agents cooperate and communicate to achieve complex tasks. Efficient communication among agents is a crucial aspect of these systems, as it directly impacts their overall performance and scalability. This scholarly work provides an exploration of essential communication elements and conducts a comparative assessment of diverse protocols utilized in multiagent systems. The emphasis lies in scrutinizing the strengths, weaknesses, and applicability of these protocols across various scenarios. The research also sheds light on emerging trends within communication protocols for multiagent systems, including the incorporation of machine learning methods and the adoption of blockchain-based solutions to ensure secure communication. These trends provide valuable insights into the evolving landscape of multiagent systems and their communication protocols.

Keywords: communication, multi-agent systems, protocols, consensus

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Authors: Arlene Villarama, Micol Grace Guanzon, Zenaida Ramos

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This paper provides insights into teaching English as a Foreign Language in the Philippines. The authors reviewed relevant theories and literature, and provide an analysis of the issues in teaching English in the Philippine setting in the light of these theories. The authors made an investigation in Bagong Barrio National High School (BBNHS) - a public school in Caloocan City. The institution has a population of nearly 3,000 students. The performances of randomly chosen 365 respondents were scrutinised. The study regarding the success of teaching English as a foreign language to Filipino children were highlighted. This includes the respondents’ family background, surroundings, way of living, and their behavior and understanding regarding education. The results show that there is a significant relationship between demonstrative, communal, and logical areas that touch the efficacy of introducing English as a foreign Dialectal. Filipino children, by nature, are adventurous and naturally joyful even for little things. They are born with natural skills and capabilities to discover new things. They highly consider activities and work that ignite their curiosity. They love to be recognised and are inspired the most when given the assurance of acceptance and belongingness. Fun is the appealing influence to ignite and motivate learning. The magic word is excitement. The study reveals the many facets of the accumulation and transmission of erudition, in introduction and administration of English as a foreign phonological; it runs and passes through different channels of diffusion. Along the way, there are particles that act as obstructions in protocols where knowledge are to be gathered. Data gained from the respondents conceals a reality that is beyond one’s imagination. One significant factor that touches the inefficacy of understanding and using English as a foreign language is an erroneous outset gained from an old belief handed down from generation to generation. This accepted perception about the power and influence of the use of language, gives the novices either a negative or a positive notion. The investigation shows that a higher number of dislikes in the use of English can be tracked down from the belief of the story on how the English language came into existence. The belief that only the great and the influential have the right to use English as a means of communication kills the joy of acceptance. A significant notation has to be examined so as to provide a solution or if not eradicate the misconceptions that lie behind the substance of the matter. The result of the authors’ research depicts a substantial correlation between the emotional (demonstrative), social (communal), and intellectual (logical). The focus of this paper is to bring out the right notation and disclose the misconceptions with regards to teaching English as a foreign language. This will concentrate on the emotional, social, and intellectual areas of the Filipino learners and how these areas affect the transmittance and accumulation of learning. The authors’ aim is to formulate logical ways and techniques that would open up new beginnings in understanding and acceptance of the subject matter.

Keywords: accumulation, behaviour, facets, misconceptions, transmittance

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Authors: Anam Alam, Rahim Jamaluddin Kanji

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With the rapid growth of event in everywhere, event extraction has now become an important matter to retrieve the information from the unstructured data. One of the challenging problems is to extract the event from it. An event is an observable occurrence of interaction among entities. The paper investigates the effectiveness of event extraction capabilities of three software tools that are Wandora, Nitro and SPSS. We performed standard text mining techniques of these tools on the data sets of (i) Afghan War Diaries (AWD collection), (ii) MUC4 and (iii) WebKB. Information retrieval measures such as precision and recall which are computed under extensive set of experiments for Event Extraction. The experimental study analyzes the difference between events extracted by the software and human. This approach helps to construct an algorithm that will be applied for different machine learning methods.

Keywords: event extraction, Wandora, nitro, SPSS, event analysis, extraction method, AFG, Afghan War Diaries, MUC4, 4 universities, dataset, algorithm, precision, recall, evaluation

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Authors: Shao-Hsun Keng, Hwang-Ruey Song

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This paper examines the causal effect of the tenure track system on instructors’ grading practices and teaching effectiveness by taking advantage of a natural experiment in Taiwan. The results show that assistant professors subject to the tenure track policy are more likely to grade leniently and fail fewer students. The course grade is 5% higher in classes taught by assistant professors subject to the tenure system. However, the tendency to grade leniently is reversed after assistant professors subject to the tenure system are promoted to a higher rank. Our findings are consistent with the exchange theory. We also show that teaching and student efforts are adversely affected by the tenure policy, which could reduce student learning and the quality of the workforce in the long run.

Keywords: tenure track system, grading leniency, study time, grade inflation

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Authors: Ali Kazemi

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Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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Authors: Houxiang Zhu, Chun Liang

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The CRISPR-Cpf1 system has been successfully applied in genome editing. However, target efficiency of the CRISPR-Cpf1 system varies among different gRNA sequences. The published CRISPR-Cpf1 gRNA data was reanalyzed. Many sequences and structural features of gRNAs (e.g., the position-specific nucleotide composition, position-nonspecific nucleotide composition, GC content, minimum free energy, and melting temperature) correlated with target efficiency were found. Using machine learning technology, a support vector machine (SVM) model was created to predict target efficiency for any given gRNAs. The first web service application, CRISPR-DT (CRISPR DNA Targeting), has been developed to help users design optimal gRNAs for the CRISPR-Cpf1 system by considering both target efficiency and specificity. CRISPR-DT will empower researchers in genome editing.

Keywords: CRISPR-Cpf1, genome editing, target efficiency, target specificity

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Authors: Nidhi Kaushal, Sanjit Mishra

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Narrative writings in literature are ample source of knowledge and easily understandable. In every old tradition, we found that people learn ethics from oral tales. They had their leaders and lessons of leadership in their stories. In India, we have sufficient amount of stories of leaders. Whether the story is of an ordinary person or a corporate leader of large firm, it always has a unique message of motivation. The objective of this paper is to elaborate the story lines in literature and get the leadership lessons from them, so that we can set up a new concept of leadership based on scholarship of literature. This is our hypothesis that leadership lessons can be learned from the study of literary writings and it can also act an innovative way of learning the management skills through literature. The role of the leader can be familiarly communicated in the form of the tales. Describing a positive psychological narrative from the text is the best way to manifesting an idea into the minds of people. We accomplished this paper that leadership as an attribute can be learned from the folk psychological literary writings.

Keywords: leadership, literature, management, psychology

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Authors: Chunfang Zhou

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The growing issues of sustainability have increased the discussions on how to foster “green engineers” from diverse perspectives in both contexts of education and organizations. As creativity has been considered as the first stage of innovation process that can also be regarded as a path to sustainability, this paper will particularly propose creativity as a scientific literacy meaning a collection of awareness, ability, and skills about sustainability. From this sense, creativity should be an element in IT engineering education and organizational learning programmes, since IT engineers are one group of key actors in designing, researching and developing social media products that are most important channels of improving public awareness of sustainability. This further leads this paper to discuss by which pedagogical strategies and by which training methods in organizations, creativity and sustainability can be integrated into IT engineering education and IT enterprise innovation process in order to meeting the needs of ‘creative engineers’ in the society changes towards sustainability. Accordingly, this paper contributes to future work on the links between creativity, innovation, sustainability, and IT engineering development both theoretically and practically.

Keywords: creativity, innovation, IT engineers, sustainability

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Authors: Julia Kapr, Andrea Rossi, Haribaskar Ramachandran, Marius Pollet, Ilka Egger, Selina Dangeleit, Katharina Koch, Jean Krutmann, Ellen Fritsche

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It is widely acknowledged that animal models do not always represent human disease. Especially human brain development is difficult to model in animals due to a variety of structural and functional species-specificities. This causes significant discrepancies between predicted and apparent drug efficacies in clinical trials and their subsequent failure. Emerging alternatives based on 3D in vitro approaches, such as human brain spheres or organoids, may in the future reduce and ultimately replace animal models. Here, we present a human induced pluripotent stem cell (hiPSC)-based 3D neural in a vitro disease model for the Cockayne Syndrome B (CSB). CSB is a rare hereditary disease and is accompanied by severe neurologic defects, such as microcephaly, ataxia and intellectual disability, with currently no treatment options. Therefore, the aim of this study is to investigate the molecular and cellular defects found in neural hiPSC-derived CSB models. Understanding the underlying pathology of CSB enables the development of treatment options. The two CSB models used in this study comprise a patient-derived hiPSC line and its isogenic control as well as a CSB-deficient cell line based on a healthy hiPSC line (IMR90-4) background thereby excluding genetic background-related effects. Neurally induced and differentiated brain sphere cultures were characterized via RNA Sequencing, western blot (WB), immunocytochemistry (ICC) and multielectrode arrays (MEAs). CSB-deficiency leads to an altered gene expression of markers for autophagy, focal adhesion and neural network formation. Cell migration was significantly reduced and electrical activity was significantly increased in the disease cell lines. These data hint that the cellular pathologies is possibly underlying CSB. By induction of autophagy, the migration phenotype could be partially rescued, suggesting a crucial role of disturbed autophagy in defective neural migration of the disease lines. Altered autophagy may also lead to inefficient mitophagy. Accordingly, disease cell lines were shown to have a lower mitochondrial base activity and a higher susceptibility to mitochondrial stress induced by rotenone. Since mitochondria play an important role in neurotransmitter cycling, we suggest that defective mitochondria may lead to altered electrical activity in the disease cell lines. Failure to clear the defective mitochondria by mitophagy and thus missing initiation cues for new mitochondrial production could potentiate this problem. With our data, we aim at establishing a disease adverse outcome pathway (AOP), thereby adding to the in-depth understanding of this multi-faced disorder and subsequently contributing to alternative drug development.

Keywords: autophagy, disease modeling, in vitro, pluripotent stem cells

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Authors: Chad Brown

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This paper establishes general conditions for the convergence rates of nonparametric sieve estimators with dependent data. We present two key results: one for nonstationary data and another for stationary mixing data. Previous theoretical results often lack practical applicability to deep neural networks (DNNs). Using these conditions, we derive convergence rates for DNN sieve estimators in nonparametric regression settings with both nonstationary and stationary mixing data. The DNN architectures considered adhere to current industry standards, featuring fully connected feedforward networks with rectified linear unit activation functions, unbounded weights, and a width and depth that grows with sample size.

Keywords: sieve extremum estimates, nonparametric estimation, deep learning, neural networks, rectified linear unit, nonstationary processes

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Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

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In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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Authors: Mikko Salminen, Simo Järvelä, Niklas Ravaja

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One of the central models of emotional intelligence (EI) is that of Mayer and Salovey’s, which includes ability to monitor own feelings and emotions and those of others, ability to discriminate different emotions, and to use this information to guide thinking and actions. There is vast amount of previous research where positive links between EI and, for example, leadership successfulness, work outcomes, work wellbeing and organizational climate have been reported. EI has also a role in the effectiveness of work teams, and the effects of EI are especially prominent in jobs requiring emotional labor. Thus, also the organizational context must be taken into account when considering the effects of EI on work outcomes. Based on previous research, it is suggested that EI can also protect managers from the negative consequences of stress. Stress may have many detrimental effects on the manager’s performance in essential work tasks. Previous studies have highlighted the effects of stress on, not only health, but also, for example, on cognitive tasks such as decision-making, which is important in managerial work. The motivation for the current study came from the notion that, unfortunately, many stressed individuals may not be aware of the circumstance; periods of stress-induced physiological arousal may be prolonged if there is not enough time for recovery. To tackle this problem, physiological stress levels of managers were collected using recording of heart rate variability (HRV). The goal was to use this data to provide the managers with feedback on their stress levels. The managers could access this feedback using a www-based learning environment. In the learning environment, in addition to the feedback on stress level and other collected data, also developmental tasks were provided. For example, those with high stress levels were sent instructions for mindfulness exercises. The current study focuses on the relation between the measured physiological stress levels and EI of the managers. In a pilot study, 33 managers from various fields wore the Firstbeat Bodyguard HRV measurement devices for three consecutive days and nights. From the collected HRV data periods (minutes) of stress and recovery were detected using dedicated software. The effects of EI on HRV-calculated stress indexes were studied using Linear Mixed Models procedure in SPSS. There was a statistically significant effect of total EI, defined as an average score of Schutte’s emotional intelligence test, on the percentage of stress minutes during the whole measurement period (p=.025). More stress minutes were detected on those managers who had lower emotional intelligence. It is suggested, that high EI provided managers with better tools to cope with stress. Managing of own emotions helps the manager in controlling possible negative emotions evoked by, e.g., critical feedback or increasing workload. High EI managers may also be more competent in detecting emotions of others, which would lead to smoother interactions and less conflicts. Given the recent trend to different quantified-self applications, it is suggested that monitoring of bio-signals would prove to be a fruitful direction to further develop new tools for managerial and leadership coaching.

Keywords: emotional intelligence, leadership, heart rate variability, personality, stress

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Authors: Ma'amun Muhammed

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The ability of smartphones in enhancing communication, providing access to business and serving as a pool for information retrieval has a far reaching and potentially beneficial impacts on enhancing teaching in higher institutions in the developing countries like Nigeria. Nigeria as one of the fast growing economies in Africa, whose citizens patronize smartphones can utilize this opportunity by inculcating the culture of using smartphones not only for communication, business transaction, banking etc. but also for enhancing teaching in the higher institutions. Smartphones have become part and parcel of our lives, particularly among young people. The primary objective of this paper is to ascertain the use of smartphones in enhancing teaching in Nigeria’s higher institutions, to achieve this, content analysis was used thoroughly. This paper examines the opportunities offered by smartphones to the students of higher institutions of learning, the challenges being faced by lecturers of these institutions in classrooms. Lastly, it offers solution on how some of these critical challenges will be overcame, so as to utilize the technology of these devices.

Keywords: communication, information retrieval, mobile phone, smartphones teaching

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Authors: S. S. Kenny Lee, C. C. Kong, S. K. Ting

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Teaching engineering lab provides opportunity for students to practice theories learned through physical experiment in the laboratory. However, building laboratories to accommodate increased number of students are expensive, making it impossible for an educational institution to afford the high expenses. In this paper, we develop a low cost and remote platform to aid teaching undergraduate students. The platform is constructed where the real experiment setting up in laboratory can be reconfigure and accessed remotely, the aim is to increase student’s desire to learn at which they can interact with the physical experiment using network enabled devices at anywhere in the campus. The platform is constructed with Raspberry Pi as a main control board that provides communication between computer interfaces to the actual experiment preset in the laboratory. The interface allows real-time remote viewing and triggering the physical experiment in the laboratory and also provides instructions and learning guide about the experimental.

Keywords: engineering lab, low cost, network, remote platform, reconfigure, real-time

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Authors: Mohamed Nabhan

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The research aims to build a measure of sensory preferences for (wrestling and boxing) players. The researchers used the descriptive approach and a sample of (8) consisting of (40) wrestling players, (40) boxing players with different scales, and they were chosen in a deliberate random way, and the most important results were that there were statistically significant differences between wrestlers and boxers in the sensory preferences of their senses. There is no indication in the sensory preferences for the senses of “sight and hearing” and that the significance is in favor of the wrestlers in the senses of “sight and touch,” and there is a convergence in the sense of hearing. Through the value of the averagesAfter collecting the data and statistical treatments and the results reached by the researcher, it was possible to reach: The following conclusions and recommendations: There are differences between wrestling and boxing players in their sensory preferences, the senses used in learning, due to several reasons, the most important of which may be as follows:- Scales for the player and for each sport separately. The nature of the game, the performance of skills, and dealing with the opponent or competitor.Tools used in performance and training.

Keywords: sensory preferences, sensory scale, wrestling players, boxing players

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Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

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Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation.

Keywords: extended Kalman filter, classification problem, radial basis function networks (RBFN), finite impulse response (FIR) filter

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Authors: Ya-Hui Lee, Ching-Yi Lu, Hui-Chuan Wei

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The purpose of this research was to explore the relation between proactive coping and well-being of middle-aged adults. We conducted survey research that with t-test, one way ANOVA, Pearson correlation and stepwise multiple regression to analyze. This research drew on a sample of 395 participants from the senior learning centers of Taiwan. The results provided the following findings: 1.The participants from different residence areas associated significant difference with proactive coping, but not with well-being. 2. The participants’ perceived of financial level associated significant difference with both proactive coping and well-being. 3. There was significant difference between participants’ income and well-being. 4. The proactive coping was positively correlated with well-being. 5. From stepwise multiple regression analysis showed that two dimensions of proactive coping had positive predictability. Finally, these results of this study can be provided as references for designing older adult educational programs in Taiwan.

Keywords: middle-age and older adults, learners, proactive coping, well-being

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Authors: Evisa Mitrou, Nicholas Tsitsianis, Supriya Shinde

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In the age of digitisation and globalisation, businesses have shifted online and are investing in big data analytics (BDA) to respond to changing market conditions and sustain their performance. Our study shifts the focus from the adoption of BDA to the impact of BDA on financial performance. We explore the financial performance of both BDA-vendors (business-to-business) and BDA-clients (business-to-customer). We distinguish between the five BDA-technologies (big-data-as-a-service (BDaaS), descriptive, diagnostic, predictive, and prescriptive analytics) and discuss them individually. Further, we use four perspectives (internal business process, learning and growth, customer, and finance) and discuss the significance of how each of the five BDA-technologies affects the performance measures of these four perspectives. We also present the analysis of employee engagement, average turnover, average net income, and average net assets for BDA-clients and BDA-vendors. Our study also explores the effect of the COVID-19 pandemic on business continuity for both BDA-vendors and BDA-clients.

Keywords: BDA-clients, BDA-vendors, big data analytics, financial performance

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Authors: Rahime Filiz Kiremit

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This study identifies six different articles to explain which strategies are most effective for kindergarten English Language Learners. The literature review project has information about six different research articles, purpose of the studies, and results of the studies. There are several strategies can be used for ELL students to help them to develop their English language skills. Some articles mention technology as a multimedia integrated into the curriculum, some of them mention writing as a method of learning English as a second language. However, they all have a common strategy that is shared reading. According to these six articles, shared reading has a big role of ELL students’ language developmental process. All in all, read-aloud with multimedia enhancement strategy is the best strategy to use in the classroom, because this strategy is based on shared reading and also integrated with technology.

Keywords: bilingual education, effective strategies, english language learners, kindergarten

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: text mining, topic extraction, independent, incremental, independent component analysis

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Authors: F. Arıkan, Z. Karakus

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Cancer is a widespread disease in the world and is the third reason of deaths among the chronic diseases. Educating patients and caregivers has a vital role for empowering them in managing disease and treatment's symptoms. Informing of the patients about their disease and treatment process decreases patient's distress and decisional conflicts, improves wellbeing of them, increase success of the treatment and survival. In this era, technological education methods are used for patients that have different chronic disease. Many studies indicated that especially web based patient education such as chronic obstructive lung disease; heart failure is more effective than printed materials. Web based education provide easiness to patients while they are reaching health services. It also has more advantages because of it decreases health cost and requirement of staff. It is thought that web based education may be beneficial method for cancer patient's empowerment in coping with the disease's symptoms. The aim of the study is evaluate the effectiveness of web based education for cancer patients' clinical outcomes.

Keywords: cancer patients, e-learning, nursing, web based education

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Authors: Khalil Khan, Ikram Syed, Muhammad Ehsan Mazhar, Iran Uddin, Nasir Ahmad

Abstract:

Face parts labeling is the process of assigning class labels to each face part. A face parts labeling method (FPL) which divides a given image into its constitutes parts is proposed in this paper. A database FaceD consisting of 564 images is labeled with hand and make publically available. A supervised learning model is built through extraction of features from the training data. The testing phase is performed with two semantic segmentation methods, i.e., pixel and super-pixel based segmentation. In pixel-based segmentation class label is provided to each pixel individually. In super-pixel based method class label is assigned to super-pixel only – as a result, the same class label is given to all pixels inside a super-pixel. Pixel labeling accuracy reported with pixel and super-pixel based methods is 97.68 % and 93.45% respectively.

Keywords: face labeling, semantic segmentation, classification, face segmentation

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Authors: Khaled ElEbyary, Ramy Shabara

Abstract:

L2 research has generally acknowledged the role of noticing in language learning. The role of teacher feedback is to trigger learners’ noticing of errors and direct the writing process. Recently L2 learners are seemingly using computerized applications which provide corrective feedback (CF) at different stages of writing (i.e., during and after writing). This study aimed principally to answer the question, “Is noticing likely to be maximized when feedback on erroneous output is electronically provided either during or after the composing stage, or does teacher annotated feedback have a stronger effect?”. Seventy-five participants were randomly distributed into four groups representing four conditions. These include receiving automated feedback at the composing stage, automated feedback after writing, teacher feedback, and no feedback. Findings demonstrate the impact of CF on writing and the intensity of noticing certain language areas at different writing stages and from different feedback sources.

Keywords: written corrective feedback, error correction, noticing, automated written corrective feedback, L2 acquisition

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Authors: V. Nikkhah Rashidabad, M. Manteghian, M. Masoumi, S. Mousavian, D. Ashouri

Abstract:

In this research, the capability of neural networks in modeling and learning complicated and nonlinear relations has been used to develop a model for the prediction of changes in the diameter of bubbles in pool boiling distilled water. The input parameters used in the development of this network include element temperature, heat flux, and retention time of bubbles. The test data obtained from the experiment of the pool boiling of distilled water, and the measurement of the bubbles form on the cylindrical element. The model was developed based on training algorithm, which is typologically of back-propagation type. Considering the correlation coefficient obtained from this model is 0.9633. This shows that this model can be trusted for the simulation and modeling of the size of bubble and thermal transfer of boiling.

Keywords: bubble diameter, heat flux, neural network, training algorithm

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Authors: S. Thongchai

Abstract:

Result of the study on knowledge management systems in businesses was shown that the most of these businesses provide internet accessibility for their employees in order to study new knowledge via internet, corporate website, electronic mail, and electronic learning system. These business organizations use information technology application for knowledge management because of convenience, time saving, ease of use, accuracy of information and knowledge usefulness. The result indicated prominent improvements for corporate knowledge management systems as the following; 1) administrations must support corporate knowledge management system 2) the goal of corporate knowledge management must be clear 3) corporate culture should facilitate the exchange and sharing of knowledge within the organization 4) cooperation of personnel of all levels must be obtained 5) information technology infrastructure must be provided 6) they must develop the system regularly and constantly.

Keywords: business organizations, information technology application, knowledge management systems, prominent improvements

Procedia PDF Downloads 388