Search results for: training

Authors: Manirath Wongsim, Ekkachai Naenudorn, Nipotepat Muangkote

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Information Technology (IT), play an important role in business management strategies and can provide assistance in all phases of decision making. Thus, many organizations need to be seen as adopting IT, which is critical for a company to organize, manage and operate its processes. In order to implement IT successfully, it is important to understand the underlying factors that influence agricultural system's adoption success. Therefore, this research intends to study this perspective of factors that influence and impact successful IT adoption and related agricultural performance. Case study and survey methodology were adopted for this research. Case studies in two Thai- organizations were carried out. The results of the two main case studies suggested 21 factors that may have an impact on IT adoption in agriculture in Thailand, which led to the development of the preliminary framework. Next, a survey instrument was developed based on the findings from case studies. Survey questionnaires were gathered from 217 respondents from two large-scale surveys were sent to selected members of Thailand farmer, and Thailand computer to test the research framework. The results indicate that the top five critical factors for ensuring IT adoption in agricultural were: 1) network and communication facilities; 2) software; 3) hardware; 4) farmer’s IT knowledge, and; 5) training and education. Therefore, it is now clear which factors are influencing IT adoption and which of those factors are critical success factors for ensuring IT adoption in agricultural organization.

Keywords: agricultural systems adoption, factors influencing IT adoption, factors affecting in agricultural adoption

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Authors: Rashid Javed, Hardy Lehmkuehler, Franz Josef-Behr

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Web Processing Services (WPS) have up growing concern in geoinformation research. However, teaching about them is difficult because of the generally complex circumstances of their use. They limit the possibilities for hands- on- exercises on Web Processing Services. To support understanding however a Training Tools Collection was brought on the way at University of Applied Sciences Stuttgart (HFT). It is limited to the scope of Geostatistical Interpolation of sample point data where different algorithms can be used like IDW, Nearest Neighbor etc. The Tools Collection aims to support understanding of the scope, definition and deployment of Web Processing Services. For example it is necessary to characterize the input of Interpolation by the data set, the parameters for the algorithm and the interpolation results (here a grid of interpolated values is assumed). This paper reports on first experiences using a pilot installation. This was intended to find suitable software interfaces for later full implementations and conclude on potential user interface characteristics. Experiences were made with Deegree software, one of several Services Suites (Collections). Being strictly programmed in Java, Deegree offers several OGC compliant Service Implementations that also promise to be of benefit for the project. The mentioned parameters for a WPS were formalized following the paradigm that any meaningful component will be defined in terms of suitable standards. E.g. the data output can be defined as a GML file. But, the choice of meaningful information pieces and user interactions is not free but partially determined by the selected WPS Processing Suite.

Keywords: deegree, interpolation, IDW, web processing service (WPS)

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Authors: Athena Pedro, Gina Stockingt

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This study aimed to explore current management strategies used by Grade 1 educators working with learners presenting with Attention Deficit Hyperactivity Disorder (ADHD) symptoms in mainstream schools in the Western Cape. A sample of grade 1 educators were selected for the study. The sample comprised of twelve grades 1 educators from four local schools in the Western Cape. All twelve educators were individually interviewed and discussed the management strategies used in the classroom when working with learner presenting with ADHD symptoms. The data was analysed qualitatively with a focus in identifying, sorting and analyse meaning according to the subjective perception, understanding and behaviour of the grade 1 educators within their context. Furthermore, the social, cultural, political and physical environment of the participants were taken into consideration to explore and interpret the link between these elements. The findings were as follows: many educators felt that they did not receive enough training on Attention Deficit Hyperactivity Disorder, therefore lacking knowledge on how to apply management strategies to address this. Managing a diverse range of learners, lack of resources, lack of parental involvement, lack of assistance in the classroom, as well as distracted and disorganised children posed as challenges for educators working with learners presenting with Attention Deficit Hyperactivity Disorder symptoms.

Keywords: ADHD, Grade 1 educators, Learners, Management strategies

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Authors: Anthony Proschka, Deepak Mishra, Merlyn Ramanan, Zurab Baratashvili

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Small and medium-sized businesses receive over 160 billion invoices every year. Since these documents exhibit many subtle differences in layout and text, extracting structured fields such as sender name, amount, and VAT rate from them automatically is an open research question. In this paper, existing work in template-based document extraction is extended, and a system is devised that is able to reliably extract all required fields for up to 70% of all documents in the data set, more than any other previously reported method. The approaches are described for 1) detecting through visual features which template a given document belongs to, 2) automatically generating extraction rules for a given new template by composing regular expressions from multiple components, and 3) computing confidence scores that indicate the accuracy of the automatic extractions. The system can generate templates with as little as one training sample and only requires the ground truth field values instead of detailed annotations such as bounding boxes that are hard to obtain. The system is deployed and used inside a commercial accounting software.

Keywords: data mining, information retrieval, business, feature extraction, layout, business data processing, document handling, end-user trained information extraction, document archiving, scanned business documents, automated document processing, F1-measure, commercial accounting software

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Authors: Olayinka M. Ayannuga

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This study explored the effect of cognitive reframe in reducing depression among Senior Secondary School Adolescents. It adopted a pre-test, post-test, control quasi-experimental research design with a 2x2 factorial matrix. Participants included 120 depressed adolescents randomly drawn from public Senior Secondary School Two (SSS.II) students in Lagos State, Nigeria. Sixty participants were randomly selected and assigned to the treatment and control groups. Participants in the Cognitive Reframe (CR) group were trained for 8 weeks, while those in the Control group were given a placebo. Two instruments were used for data collection namely: Self – Esteem Scale (SES: Rosenberg 1965: α = 0.85), and The Self Rating Depression Scale (SDS: Zung, 1972; α 0 = 0.87) were administered at pretest level. However, only the Self-Rating Depression Scale (SDS) was re-administered at post-test to measure the effect of the intervention. The results revealed that there was a significant effect of cognitive reframe training programmes on secondary school adolescents’ depression, also there were significant effects of self-esteem on secondary school adolescents’ depression. The study showed that the technique is capable of reducing depression among adolescents. It was recommended, amongst others, that Counselling psychologists, Curriculum planners and Teachers could explore incorporating the contents of cognitive reframe into the secondary school curriculum for students’ capacity building to reduce depression tendencies.

Keywords: adolescents, cognitive reframe, depression, self – esteem

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Authors: Tiina Brandt, Isaac Wanasika

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Culturally diverse global companies need to understand cultural differences between leaders and employees from different backgrounds. Communication is culturally contingent and has a significant impact on effective execution of leadership goals. The awareness of cultural variations related to communication and interactions will help leaders modify their own behavior, and consequently improve the execution of goals and avoid unnecessary faux pas. Our focus is on young adults that have experienced cultural integration, culturally diverse surroundings in schools and universities, and cultural travels. Our central research problem is to understand the impact of different national cultures on communication. We focus on four countries with distinct national cultures and spatial distribution. The countries are Finland, Indonesia, Russia and USA. Our sample is based on business students (n = 225) from various backgrounds in the four countries. Their responses of communication and leadership styles were analyzed using ANOVA and post-hoc test. Results indicate that culture impacts on communication behavior. Even young culturally-exposed adults with cultural awareness and experience demonstrate cultural differences in their behavior. Apparently, culture is a deeply seated trait that cannot be completely neutralized by environmental variables. Our study offers valuable input for leadership training programs and for expatriates when recognizing specific differences on leaders’ behavior due to culture.

Keywords: communication, culture, interaction, leadership

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

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Authors: Abduselam Faris, Rijalu Negash, Zera Kedir

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This study was initiated to identify constraints and opportunities of the wood production value chain in Southwest Ethiopia. About 385 wood trees growing farmers were randomly interviewed. Similarly, about 30 small-scale wood processors, 30 retailers, 15 local collectors and 5 wholesalers were purposively included in the study. The results of the study indicated that 98.96 % of the smallholder farmers that engaged in the production of wood trees which is used for wood were male-headed, with an average age of 46.88 years. The main activity that the household engaged was agriculture (crop and livestock) which accounts for about 61.56% of the sample respondents. Through value chain mapping of actors, the major value chain participant and supporting actors were identified. On average, the tree-growing farmers generated gross income of 9385.926 Ethiopian birr during the survey year. Among the critical constraints identified along the wood production value chain was limited supply of credit, poor market information dissemination, high interference of brokers, and shortage of machines, inadequate working area and electricity. The availability of forest resources is the leading opportunity in the wood production value chain. Reinforcing the linkage among wood production value chain actors, providing skill training for small-scale processors, and developing suitable policy for wood tree wise use is key recommendations forward.

Keywords: value chain analysis, wood production, southwest Ethiopia, constraints and opportunities

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Authors: Anastassis Kozanitis

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The first year of college or university can be particularly challenging for students from minority groups, who often face unique obstacles related to their cultural background, socioeconomic status, or underrepresented identities. Recognizing the importance of fostering inclusivity and supporting the success of these students, educational institutions in Quebec, Canada, have implemented a range of initiatives tailored to address their specific needs. This presentation provides an overview of four key first-year experience measures for minority groups, focusing on mentorship programs, student-lead cultural centers, walk-in support offices, and diversity training, all aimed at promoting inclusion and enhancing the academic journey and overall well-being of these students. Semi-structured individual interviews were conducted with individuals working in connection with the measures of interest. A qualitative content analysis allowed for the characterization of facilitating factors of the support measures identified. Hence, all four measures have proven to be instrumental in supporting the transition and success of first-year students from minority groups. These initiatives provide safe spaces where students can connect with their cultural heritage, engage in dialogue, and celebrate diversity. In conclusion, first-year experience initiatives for minority groups in college and university play a pivotal role in fostering inclusivity and supporting the success of students from underrepresented backgrounds.

Keywords: diversity, first year, minority groups, inclusion, support measures, higher education

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Authors: Yingkun Huang, Li Guo, Zekang Lan, Kai Tian

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Hard disk drives (HDD) failure of the exascale supercomputing system may lead to service interruption and invalidate previous calculations, and it will cause permanent data loss. Therefore, initiating corrective actions before hard drive failures materialize is critical to the continued operation of jobs. In this paper, a highly accurate analysis model based on CNN-LSTM and oversampling technique was proposed, which can correctly predict the necessity of a disk replacement even ten days in advance. Generally, the learning-based method performs poorly on a training dataset with long-tail distribution, especially fault prediction is a very classic situation as the scarcity of failure data. To overcome the puzzle, a new oversampling was employed to augment the data, and then, an improved CNN-LSTM with the shortcut was built to learn more effective features. The shortcut transmits the results of the previous layer of CNN and is used as the input of the LSTM model after weighted fusion with the output of the next layer. Finally, a detailed, empirical comparison of 6 prediction methods is presented and discussed on a public dataset for evaluation. The experiments indicate that the proposed method predicts disk failure with 0.91 Precision, 0.91 Recall, 0.91 F-measure, and 0.90 MCC for 10 days prediction horizon. Thus, the proposed algorithm is an efficient algorithm for predicting HDD failure in supercomputing.

Keywords: HDD replacement, failure, CNN-LSTM, oversampling, prediction

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Authors: Amenaghawon Clement Osemwinyen

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The Activity, Student-centred, Experiment, Improvisation - Plan, Do, See, Improve (ASEI-PDSI) method championed by the Strengthening Mathematics And Science Education (SMASE) - Nigeria Project is an attempt to improve the quality of mathematics, which has consistently declined over the years in both public primary and secondary schools across the country. The study thus assessed the ASEI-PDSI method on students’ attitudes and achievement in junior secondary schools (JSS) mathematics in FCT-Abuja. A survey research design was adopted, and 100 mathematics teachers using a stratified random sampling method were used for the study. The data were collected using structured questionnaires and analyzed using descriptive statistics. The findings showed that the ASEI-PDSI method had significantly improved the attitudes of students toward mathematics. The study also revealed that the ASEI-PDSI method significantly influenced junior secondary school (JSS) students’ mathematics achievement. Amongst the recommendations were that teachers should be encouraged to adopt the ASEI-PDSI method in teaching and learning mathematics in order to create a mathematically stimulating classroom environment which could advertently influence junior secondary school (JSS) students’ attitude and academic performance in mathematics. Also, regular in-service training programs should be organized by stakeholders (government and other interest groups) so as to improve the teaching strategies of teachers, mostly as they affect the ASEI-PDSI method.

Keywords: achievement, ASEI-PDSI method, attitude, mathematics, SMASE

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Authors: Nkosingiphile M. Mbhele, Jean Steyn

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A focus group discussion was implemented, which comprised of senior South African Police Service managers and police academics in South Africa. The measurement of solidarity, isolation, and cynicism among functional South African Police Service officials and a thirty-item questionnaire came about by reviewing the literature. This research uses a survey format to assess the police culture theme of solidarity, isolation, and cynicism among South African Police Service officers in 9 South African provinces. Although a survey format is used in research, it engages in a quasi-experimental pre-test/post-test repeated measures research (longitudinal) design. Although there are differences among South African Police Service police (SAPS) officers, overall, there are signs of solidarity, isolation, and cynicism among SAPS members. Attitudes of solidarity, isolation, and cynicism are present among most police officials and have been presented from the start of training and held, maintained, or strengthened for the next years of their SAPS careers. This issue is problematic to society with regard to community-orientated policing since they have to interact with the members of the community. To author’s best knowledge, longitudinal studies of police culture are rare to find; not much has been researched on this topic. However, this paper offers to bridge that gap by providing answers to longitudinal police attitudes towards the public within the police culture themes of isolation and cynicism attitudes.

Keywords: South African police service, police culture, solidarity, isolation, cynicism, public

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Authors: Qisheng Hu, Jianglei Han, Yue Yang, My Hoa Ha

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When a company is considering purchasing software for commercial use, contract risk assessment is critical to identify risks to mitigate the potential adverse business impact, e.g., security, financial and regulatory risks. Contract risk assessment requires reviewers with specialized knowledge and time to evaluate the legal documents manually. Specifically, validating contracts for a software vendor requires the following steps: manual screening, interpreting legal documents, and extracting risk-prone segments. To automate the process, we proposed a framework to assist legal contract document risk identification, leveraging pre-trained deep learning models and natural language processing techniques. Given a set of pre-defined risk evaluation problems, our framework utilizes the pre-trained transformer-based models for question-answering to identify risk-prone sections in a contract. Furthermore, the question-answering model encodes the concatenated question-contract text and predicts the start and end position for clause extraction. Due to the limited labelled dataset for training, we leveraged transfer learning by fine-tuning the models with the CUAD dataset to enhance the model. On a dataset comprising 287 contract documents and 2000 labelled samples, our best model achieved an F1 score of 0.687.

Keywords: contract risk assessment, NLP, transfer learning, question answering

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Yaser Kazemzadeh, Keyvan Molanoruzy, Mojtaba Izady

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The balance is the key component of motor skills to maintain postural control and the execution of complex skills. The present study was designed to evaluate the impact of soft knee pads on static and dynamic balance of male athletes. For this aim, thirty young athletes in different sport fields with 3 years professional sport training background and thirty healthy young men nonathletic (age: 24.5 ± 2.9, 24.3 ± 2.4, weight: 77.2 ± 4.3 and 80/9 ± 6/3 and height: 175 ± 2/84, 172 ± 5/44 respectively) as subjects selected. Then, subjects in two manner (without knee and with soft knee pads made of neoprene) execute standard error test (BESS) to assess static balance and star test to assess dynamic balance. For analyze of data, t-tests and one-way ANOVA were significant 05/0 ≥ α statistical analysis. The results showed that the use of soft knee significantly reduced error rate in static balance test (p ≥ 0/05). Also, use a soft knee pads decreased score of athlete group and increased score of nonathletic group in star test (p ≥ 0/05). These findings, indicates that use of knees affects static and dynamic balance in athletes and nonathletic in different manner and may increased athletic performance in sports that rely on static balance and decreased performance in sports that rely on dynamic balance.

Keywords: static balance, dynamic balance, soft knee, athletic men, non athletic men

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Authors: Njeim Pressila, Hajj-Boutros Guy, Antony D. Karelis

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Background: Acute resistance exercise is associated with an elevated inflammation response, which could lead to delayed onset muscle soreness (DOMS). There is evidence that suggests that ingesting foods that have anti-inflammation properties may help reduce DOMS. A vegan diet has also been shown to be an anti-inflammatory diet which could, in turn, decrease DOMS. Objective and hypothesis: The purpose of the present study will be to compare markers of DOMS between vegans and omnivores after acute resistance exercise in young females. We hypothesize that vegans will have a better recovery of DOMS markers after a resistance exercise session compared to omnivores. Methods: Population: We will recruit30 vegans and 30 omnivores to participate in this study. Allvolunteers will follow either a vegan or an omnivore diet for at least 2 years. Anthropometric measurements, body composition, musclestrength (leg and chest press), markers of DOMS (swelling, pain, and stiffness), and dietary factors, as well as a wellness and anxiety questionnaire will be measured. All participants will also perform an acute resistance exercise session in order to induce DOMS. Pertinence: This project will give us a better understanding on the recovery process of vegans after a resistance training session and, as such, provide useful information to health professionals and athletes/coaches (kinesiologists and nutritionists)

Keywords: vgeans, omnivores, delayed onset muscle soreness, pain, stifness

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Authors: Dilara Usta, Fatos Korkmaz

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Background: Individuals who utilise health services maintain relationships with health professionals, insurers and institutions. The nature of these relationships requires service receivers to have trust in the service providers because maintaining health services without reciprocal trust is very difficult. Therefore, individual evaluations of trust within the scope of health services have become increasingly important. Objective: To investigate patients’ trust in the health-care system and their relevant socio-demographical characteristics. Methods: This research was conducted using a descriptive design which included 493 literate patients aged 18-65 years who were hospitalised for a minimum of two days at public university and training&research hospitals in Ankara, Turkey. Patients’ trust in health-care professionals, insurers, and institutions were investigated. Data were collected using a demographic questionnaire and the Multidimensional Trust in Health-Care Systems Scale between September 2015 and April 2016. Results: The participants’ mean age was 47.7±13.1; 70% had a moderate income and 69% had a prior hospitalisation and 63.5% of the patients were satisfied with the health-care services. The mean Multidimensional Trust in Health-Care Systems Scale score for the sample was 61.5±8.3; the provider subscale had a mean of 38.1±5, the insurers subscale had a mean of 12.9±3.7, and institutions subscale had a mean of 10.6±1.9. Conclusion: Patients’ level of trust in the health-care system was above average and the trust level of the patients with higher educational and socio-economic levels was lower compared to the other patients. Health-care professionals should raise awareness about the significance of trust in the health-care system.

Keywords: delivery of health care, health care system, nursing, patients, trust

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Authors: J. K. Adedeji, S. T. Ijatuyi

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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

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Authors: Antoine Vikkey Hinson, Ranty Jolianelle Dassi, Menonli Adjobimey, Rose Mikponhoue, Paul Ayelo

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Introduction: The psychological hardship of the teaching profession maintains a chronic stress that inevitably evolves into burnout (BO) in the absence of adequate preventive measures. The objective of this study is to study the prevalence and factors associated with burnout among secondary school teachers in the city of Cotonou in 2022. Methods: This was a descriptive cross-sectional study with an analytical aim and prospective data collection that took place over a period of 2 months, from July 19 to August 19 and from October 1 to October 31, 2022. Sampling was done using a three-stage probability sampling technique. Data analysis was performed using R 4.1.1 software. Bivariate logistic regression was used to identify associated factors. The significance level chosen was 5% (p < 0.05). Results: A total of 270 teachers were included in the study, of whom 208 (77.00%) were men. The mean age of the workers was 38.03 ± 8.30 years. According to the Maslach Burnout Inventory, 58.51% of the teachers had burnout, with 41.10% of teachers in emotional exhaustion, 27.40% in depersonalization and 21.90% in loss of personal accomplishment. The severity of the syndrome was low to moderate in almost all teachers. The occurrence of BO was associated with), not practicing sports (ORa= 2,38 [1,32; 4,28]), jobs training (ORa= 1,86 [1,04; 3,34]) and an imbalance of effort/reward (ORa= 5,98 [2,24;15,98]). Conclusion: The prevalence of BO is high among secondary school teachers in the city of Cotonou. A larger scale study, including research on its consequences on the teacher and the learner, is necessary in order to act quickly to implement a prevention program.

Keywords: burnout, teachers, Maslach burnout inventory, associated factors, Benin

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Authors: John G. Vongas, Raghid Al Hajj

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In recent years, there has been a surge in research on empathy across disciplines ranging from management and psychology to philosophy and neuroscience. In organizational behavior, in particular, scholars have become interested in leader empathy given the rise of workplace diversity and the growing perception of leaders as managers of group emotions. It would appear that the current zeitgeist in behavioral and philosophical science is that empathy is a cornerstone of morality and that our world would be better off if only more people – and by extension, more leaders – were empathic. In spite of these claims, however, researchers have used different terminologies to explore empathy, confusing it at times with other related constructs such as emotional intelligence and compassion. Second, extant research that specifies what empathic leaders do and how their behavior affects organizational stakeholders, including themselves, does not devolve from a unifying theoretical framework. These problems plague knowledge development in this important research domain. Therefore, to the authors' best knowledge, this paper provides the first comprehensive review and synthesis of the literature on leader empathy by drawing on disparate yet complementary fields of inquiry. It clarifies empathy from other constructs and presents a theoretical model that elucidates the mechanisms by which a leader’s empathy translates into behaviors that could be either beneficial or harmful to the leaders themselves, as well as to their followers and groups. And third, it specifies the boundary conditions under which a leader’s empathy will become manifest. Finally, it suggests ways in which training could be implemented to improve empathy in practice while also remaining skeptical of its conceptualization as a moral or even effective guide in human affairs.

Keywords: compassion, empathy, leadership, group outcomes

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Authors: Trevor R. Higgins

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To speed/enhance recovery from sport, cold water immersion (CWI) and contrast water therapy (CWT) have become common practice within the high-level team sport. Initially, research into CWI and CWT protocols and recovery was sparse; athletes relied solely upon an anecdotal support. However, an increase into recovery research has occurred. A number of reviews have subsequently been conducted to clarify scientific evidence. However, as the nature of physiological stress and training status of participants will impact on results, an opportunity existed to narrow the focus to a more exacting review evaluating hydrotherapy for recovery in a team sport. A Boolean logic [AND] keyword search of databases was conducted: SPORTDiscus; AMED; CINAHL; MEDLINE. Data was extracted and the standardized mean differences were calculated with 95% CI. The analysis of pooled data was conducted using a random-effect model, with Heterogeneity assessed using I2. 23 peer reviewed papers (n=606) met the criteria. Meta-analyses results indicated CWI was likely beneficial for recovery at 24h (Countermovement Jump (CMJ): p= 0.05, CI -0.004 to 0.578; All-out sprint: p=0.02, -0.056 to 0.801; DOMS: p=0.08, CI -0.092 to 1.936) and at 72h (accumulated sprinting: p=0.07, CI -0.062 to 1.209; DOMS: p=0.09, CI -0.121 to 1.555) following team sport. Whereas CWT was likely beneficial for recovery at 1h (CMJ: p= 0.07, CI -0.004 to 0.863) and at 48h (fatigue: p=0.04, CI 0.013 to 0.942) following team sport. Athlete’s perceptions of muscle soreness and fatigue are enhanced with CWI and/or CWT, however even though CWI and CWT were beneficial in attenuating decrements in neuromuscular performance 24 hours following team sport, indications are those benefits were no longer Sydney evident 48 hours following team sport.

Keywords: cold water immersion, contrast water therapy, recovery, team sport

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Authors: Deshar Bashu Dev

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In this modern age, most people in developed and developing countries are affected by mental illness. There are many mental illnesses, and their differing symptoms impact peoples’ lives in different ways. These illnesses affect the way people think and feel, as well as how they behave with others. Mental illness results from compound interactions between the mind, body, and environment. New technologies and sciences make the world a better place. These technologies are becoming smarter and are being developed every day to help make daily life easier However, people suffer from mental illness in every part of the world. The philosophy propounded by the Buddha, Buddhism, teaches that all life is connected, from the microcosm to macrocosm. In the 2,500 years that elapsed since the death of the Buddha, his disciples have spread his teachings and developed sophisticated psycho-therapeutic methodologies. We can find many examples in Buddhist texts and in the modern age where Buddhist philosophy modern science could not solve. The Noble Eightfold Path, which is one of the main philosophies of Buddhism; it eradicates hatred and ill will and cultivates good deeds, kindness, and compassion. Buddhism, as a practice of dialectic conversation and mindfulness training, is full of rich therapeutic tools that the mental health community has adopted to help people. Similarly, Buddhist meditation is very necessary; it purifies thoughts and avoids unnecessary thinking. This research aims to study different causes of mental illness; analyzes the different approaches to eradicate mental illness problems and provides conclusions and recommendations present solutions through Buddhism in this modern age.

Keywords: mental illness, Buddhism, mindfulness, Buddhist practices

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Authors: Mohamed M. Elsherbiny

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Social Avoidance is one of the most important problems that face a good number of disabled students. It results from the negative attitudes of non-disabled students, teachers and others. Some of the past research has shown that non-disabled individuals hold negative attitudes toward persons with disabilities. The present study aims to alleviate Social Avoidance by applying the Cognitive Behavioral Intervention. 24 Blind students aged 19–24 (university students) were randomly chosen we compared an experimental group (consisted of 12 students) who went through the intervention program, with a control group (12 students also) who did not go through such intervention. We used the Social Avoidance and Distress Scale (SADS) to assess social anxiety and distress behavior. The author used many techniques of cognitive behavioral intervention such as modeling, cognitive restructuring, extension, contingency contracts, self-monitoring, assertiveness training, role play, encouragement and others. Statistically, T-test was employed to test the research hypothesis. Result showed that there is a significance difference between the experimental group and the control group after the intervention and also at the follow up stages of the Social Avoidance and Distress Scale. Also for the experimental group, there is a significance difference before the intervention and the follow up stages for the scale. Results showed that, there is a decrease in social avoidance. Accordingly, cognitive behavioral intervention program was successful in decreasing social avoidance for blind students.

Keywords: social avoidance, cognitive behavioral intervention, blind disability, disability

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Authors: Sushree Sangita Mohanty

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The pedagogic system, which is used to work with indigenous groups, who have equally different socio-economic, socio-cultural & multi-lingual conditions with differing cognitive capabilities, makes the education situation complex. As a result, educating the indigenous people became just the dissemination of facts and information, but advancement in knowledge and possibilities somewhere hides. This gap arises complexities due to the language barrier and the teachers from a conventional background of teaching practices are unable to understand or connect with the students in the schools. This paper presents the research work of the Mother Tongue Based Multilingual Education (MTB-MLE) project that has developed a creative pedagogic endeavor for the students of Kalinga Institute of Social Sciences (KISS) for facilitating Multilingual Education (MLE) teaching. KISS is a home for 25,000 indigenous children. The students enrolled here are from 62 different indigenous communities who speak around 24 different languages with geographical articulation. The book contents include concept, understanding languages, similitudes among languages, the need of mother tongue in teaching and learning, skill development (Listening-Speaking-Reading-Writing), teachers activities for teaching in multilingual schools, the process of teaching, training format of multilingual teaching and procedures for basic data collection regarding multilingual schools and classroom handle.

Keywords: indigenous, multi-lingual, pedagogic, teachers, teaching practices

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

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Authors: Dewi Juliah Ratnaningsih, Imas Sukaesih Sitanggang

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Classification is one of data mining techniques that aims to discover a model from training data that distinguishes records into the appropriate category or class. Data mining classification methods can be applied in education, for example, to determine the classification of non-active students in Indonesia Open University. This paper presents a comparison of three methods of classification: Naïve Bayes, Bagging, and C.45. The criteria used to evaluate the performance of three methods of classification are stratified cross-validation, confusion matrix, the value of the area under the ROC Curve (AUC), Recall, Precision, and F-measure. The data used for this paper are from the non-active Indonesia Open University students in registration period of 2004.1 to 2012.2. Target analysis requires that non-active students were divided into 3 groups: C1, C2, and C3. Data analyzed are as many as 4173 students. Results of the study show: (1) Bagging method gave a high degree of classification accuracy than Naïve Bayes and C.45, (2) the Bagging classification accuracy rate is 82.99 %, while the Naïve Bayes and C.45 are 80.04 % and 82.74 % respectively, (3) the result of Bagging classification tree method has a large number of nodes, so it is quite difficult in decision making, (4) classification of non-active Indonesia Open University student characteristics uses algorithms C.45, (5) based on the algorithm C.45, there are 5 interesting rules which can describe the characteristics of non-active Indonesia Open University students.

Keywords: comparative analysis, data mining, clasiffication, Bagging, Naïve Bayes, C.45, non-active students, Indonesia Open University

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Authors: Naomi Weiner-Levy

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The Mofet Institute of Research, established a School of Professional Development, the only one of its kind in Israel and throughout the world. It offers specialized programs for teacher educators, providing them with the professional knowledge and skills. The studies aim at updating teachers about rapidly changing knowledge and skills. Teacher educators are conceptualized as shifting from first order practitioners (school teachers) to second order practitioners. Those who train teachers are referred to as third order practitioners. The instructors in the School of Professional Development are third-order practitioners – teacher educators specializing in teaching their colleagues. Collegial guidance by teachers’ college staff members is no simple task: Tutors must be expert in their field of specialization, as well as in instruction. Moreover, although colleagues, they have to position themselves within the group as authoritative figures in terms of instruction and knowledge. To date, the role and professional identity of these third-order practitioners, has not been studied. To understand the nature and development of professional identity, a qualitative study was conducted in which 12 tutors of various subjects were interviewed. These were analyzed by categorical content analysis. The findings, assessed professional identity through a post-modern prism, while examining the interplay among events that tutors experienced, the knowledge they acquired and the structuring of their professional identity. The Tutors’ identity transformed through negotiating with ‘self’ and ‘other’ in the class, and constructed by their mutual experiences as tutors and learners. Understanding the function and identity of tutors facilitates comprehension of this unique training process for teacher educators.

Keywords: professional development, professional identity, teacher education, tutoring

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Authors: Chien-Kuo Chang, Yu-Hsiang Lin, Yi-Yun Tang, Min-Chiu Wu

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With the trend of technological advancement, the harm caused by power outages is substantial, mostly due to problems in the power grid. This highlights the necessity for further improvement in the reliability of the power system. In the power system, gas-insulated switches (GIS) and power cables play a crucial role. Long-term operation under high voltage can cause insulation materials in the equipment to crack, potentially leading to partial discharges. If these partial discharges (PD) can be analyzed, preventative maintenance and replacement of equipment can be carried out, there by improving the reliability of the power grid. This research will diagnose defects by identifying three different defects in GIS and three different defects in straight cable joints, for a total of six types of defects. The partial discharge data measured will be converted through phase analysis diagrams and pulse sequence analysis. Discharge features will be extracted using convolutional image processing, and three different deep learning models, CNN, ResNet18, and MobileNet, will be used for training and evaluation. Class Activation Mapping will be utilized to interpret the black-box problem of deep learning models, with each model achieving an accuracy rate of over 95%. Lastly, the overall model performance will be enhanced through an ensemble learning voting method.

Keywords: partial discharge, gas-insulated switches, straight cable joint, defect identification, deep learning, ensemble learning

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Authors: Brahmi Brahim, Mohammad Habibur Rahman, Maarouf Saad, Cristóbal Ochoa Luna

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A repetitive training movement is an efficient method to improve the ability and movement performance of stroke survivors and help them to recover their lost motor function and acquire new skills. The ETS-MARSE is seven degrees of freedom (DOF) exoskeleton robot developed to be worn on the lateral side of the right upper-extremity to assist and rehabilitate the patients with upper-extremity dysfunction resulting from stroke. Practically, rehabilitation activities are repetitive tasks, which make the assistive/robotic systems to suffer from repetitive/periodic uncertainties and external perturbations induced by the high-order dynamic model (seven DOF) and interaction with human muscle which impact on the tracking performance and even on the stability of the exoskeleton. To ensure the robustness and the stability of the robot, a new nonlinear backstepping control was implemented with designed tests performed by healthy subjects. In order to limit and to reject the periodic/repetitive disturbances, an iterative estimator was integrated into the control of the system. The estimator does not need the precise dynamic model of the exoskeleton. Experimental results confirm the robustness and accuracy of the controller performance to deal with the external perturbation, and the effectiveness of the iterative estimator to reject the repetitive/periodic disturbances.

Keywords: backstepping control, iterative control, Rehabilitation, ETS-MARSE

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Authors: Smriti Mary Gupta

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This article intends to show how literature may be used in language classes to develop student’s knowledge of English. First, we examine the evolution of literature in the language classroom, then we give account of some reasons that justify its use in language classes, of the role of reading in language development, and of the way poetry is treated in the ESL classroom. This paper aims to emphasize the use of literature as a popular tool to teach language skills (i.e. reading, writing, listening and speaking), language areas (i.e. vocabulary, grammar and pronunciation) as well as moral teachings, which is the necessity in present time. Reason for using religious literary texts in foreign language classroom and main criteria for selecting suitable religious literary texts in foreign language classes are stressed so as to make the reader familiar with the underlying reasons and criteria for language teachers, using and selecting religious literary texts. Moreover, religious literature and teaching of language skills, benefits the different genres of religious literature (i.e. poetry, fiction and drama), and also gaining knowledge of a particular religion through language teaching but some problems had been observed by language teachers within the area of English through religious literature (i.e. lack of preparation in the area of literature teaching in TESL/TEFL programs, absence of clarity in objectives defining the role of literature in ESL/EFL), language teachers not having the background, training and appropriate knowledge in religious literature, lack of pedagogically-designed teaching material that can be used by language teachers in a classroom.

Keywords: religious literature, teaching literature, teaching of language skills, foreign language teaching, literary competence

Procedia PDF Downloads 501