Search results for: translator training

Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

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In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange

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Authors: Abdul Salim Amin

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This paper focuses on how judiciaries in post-conflict society gain legitimacy through reformation. Legitimacy plays a pivotal role in shaping peoples’ behavior to submit to the law and verifies the rightfulness of an organ for taking binding decisions. Among various dynamics, judicial independence, access to justice and behavioral changes of the judicial officials broadly contribute in legitimation of judiciary in general, and the court in particular. Increasing the independence of judiciary through reform limits the interference of governmental branches in judicial issues and protects basic rights of the citizens. Judicial independence does not only matter in institutional terms, individual independence also influences the impartiality and integrity of judges, which can be increased through education and better administration of justice. Finally, access to justice as an intertwined concept both at the legal and moral spectrum of judicial reform avails justice to the citizen and increases the level of public trust and confidence. Efficient legal decisions on fostering such elements through holistic reform create a rule of law atmosphere. Citizens do not accept illegitimate judiciary and do not trust its decisions. Lack of such tolerance and confidence deters the rule of law and, thus, undermines the democratic development of a society.

Keywords: legitimacy, judicial reform, judicial independence, access to justice, legal training, informal justice, rule of law

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Authors: Cornellia Ayu, Putrianti Herni, Saptoto Robertus

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In the context of global tourism and creative economies, digital maturity has become a crucial factor for the sustainable development of small and medium enterprises (SMEs). This paper explores the journey toward digital maturity among SMEs in Sleman, Yogyakarta, Indonesia, focusing on their empowerment to foster sustainable tourism and creative economy growth. The study adopts a mixed-methods approach, integrating qualitative interviews with SME owners and quantitative surveys to assess their digital capabilities and readiness. Data were collected from a diverse sample of SMEs engaged in various sectors, including crafts and culinary services. Findings reveal significant gaps in digital literacy and infrastructure, impeding the full realization of digital benefits. However, targeted interventions, such as digital training programs and the provision of affordable technology, have shown promise in bridging these gaps. The study concludes that enhancing digital maturity among SMEs is vital for their competitiveness and sustainability in the modern economy. The insights gained can inform policymakers and stakeholders aiming to bolster the digital transformation of SMEs in similar contexts.

Keywords: digital maturity, small medium enterprises, digital literacy, sustainable tourism, creative economy

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Authors: S. Damapong, C. Kingkeow, W. Kongnoo, P. Pattapokin, S. Pruenglamphu

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As the presence of Thai children double burden malnutrition, we conducted a project to promote holistic age-appropriate nutrition for Thai children. Researchers developed P1-P7 computer software for managing and analyzing diverse types of collected data. The study objectives were: i) to use software to manage and analyze the collected data, ii) to evaluate the children nutritional status and their caretakers’ nutrition practice to create regulations for improving nutrition. Data were collected by means of questionnaires, called P1-P7. P1, P2 and P5 were for children and caretakers, and others were for institutions. The children nutritional status, height-for-age, weight-for-age, and weight-for-height standards were calculated using Thai child z-score references. Institution evaluations consisted of various standard regulations including the use of our software. The results showed that the software was used in 44 out of 118 communities (37.3%), 57 out of 240 child development centers and nurseries (23.8%), and 105 out of 152 schools (69.1%). No major problems have been reported with the software, although user efficiency can be increased further through additional training. As the result, the P1-P7 software was used to manage and analyze nutritional status, nutrition behavior, and environmental conditions, in order to conduct Thai Child Evaluation (TCE). The software was most widely used in schools. Some aspects of P1-P7’s questionnaires could be modified to increase ease of use and efficiency.

Keywords: P1-P7 software, Thai child evaluation, nutritional status, malnutrition

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Authors: Madhusudan Purohit, Stephen Philip, Bharathkumar Inturi

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In this paper we report the quantitative structure activity relationship of novel bis-triazole derivatives for predicting the activity profile. The full model encompassed a dataset of 46 Bis- triazoles. Tripos Sybyl X 2.0 program was used to conduct CoMSIA QSAR modeling. The Partial Least-Squares (PLS) analysis method was used to conduct statistical analysis and to derive a QSAR model based on the field values of CoMSIA descriptor. The compounds were divided into test and training set. The compounds were evaluated by various CoMSIA parameters to predict the best QSAR model. An optimum numbers of components were first determined separately by cross-validation regression for CoMSIA model, which were then applied in the final analysis. A series of parameters were used for the study and the best fit model was obtained using donor, partition coefficient and steric parameters. The CoMSIA models demonstrated good statistical results with regression coefficient (r2) and the cross-validated coefficient (q2) of 0.575 and 0.830 respectively. The standard error for the predicted model was 0.16322. In the CoMSIA model, the steric descriptors make a marginally larger contribution than the electrostatic descriptors. The finding that the steric descriptor is the largest contributor for the CoMSIA QSAR models is consistent with the observation that more than half of the binding site area is occupied by steric regions.

Keywords: 3D QSAR, CoMSIA, triazoles, novel heterocycles

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Authors: Hussain Darraj

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Background: Healthcare workers, especially nurses, are subjected to a great risk of psychological stress, mostly moral distress. Therefore, it is crucial to address moral distress in nurses. Objectives: The aim of this study is to study the extent of moral distress among hospital nurses in Jazan. Methods: This study used a cross-sectional study design, which included 419 nurses from Jazan hospitals. A questionnaire was used to measure moral distress and its related factors. Results: The average total score for moral distress among the study participants is 134.14, with a standard deviation of 53.94. Moreover, the current study findings indicate that those over the age of 35 years who work as nurse managers, working in critical departments, have the intention to leave a position, have received ethical training or workshops, have provided care for COVID-19 cases, or work in a department with staff shortages are associated with the experience of higher-level moral stress. Conclusion: Nurses are recommended to be provided with ongoing education and resources in order to reduce moral distress and create a positive work atmosphere for nurses. Moreover, the current study sheds light on the importance of organizational support to provide enough resources and staffing in order to reduce moral distress among nurses. Further research is needed to focus on other health professionals and moral distress. Moreover, future studies are also required to explore the strategies to reduce moral distress levels among nurses.

Keywords: moral distress, Jazan, nurses, hospital

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Authors: Samuel Nii Tackie, Oyebade K. Oyedotun, Ebenezer O. Olaniyi, Adnan Khashman

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Artificial neural networks have been used in different fields of artificial intelligence, and more specifically in machine learning. Although, other machine learning options are feasible in most situations, but the ease with which neural networks lend themselves to different problems which include pattern recognition, image compression, classification, computer vision, regression etc. has earned it a remarkable place in the machine learning field. This research exploits neural networks as a data mining tool in predicting the number of times a student repeats a course, considering some attributes relating to the course itself, the teacher, and the particular student. Neural networks were used in this work to map the relationship between some attributes related to students’ course assessment and the number of times a student will possibly repeat a course before he passes. It is the hope that the possibility to predict students’ performance from such complex relationships can help facilitate the fine-tuning of academic systems and policies implemented in learning environments. To validate the power of neural networks in data mining, Turkish students’ performance database has been used; feedforward and radial basis function networks were trained for this task; and the performances obtained from these networks evaluated in consideration of achieved recognition rates and training time.

Keywords: artificial neural network, data mining, classification, students’ evaluation

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Authors: Binod Duwadi

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This article examines the language and literacy practices of English Code-mixing in Nepalese Classroom. Situating the study within an ecological framework, a systematic functional linguistic (SFL) approach was used to analyze students writing in two Neplease schools. Data collection included interviews with teachers, classroom observations, instructional materials, and focal students’ writing samples. Data analyses revealed vastly different language ecologies between the schools owing to sharp socioeconomic stratification, the structural organization of schools, and the pervasiveness of standard language ideology, with stigmatizes English code mixing (ECM) and privileges Standard English in schools. Functional analysis of students’ writing showed that the nature of the writing tasks at the schools created different affordances for exploiting lexicogrammatically choices for meaning making-enhancing them in the case of one school but severely restricting them in the case of another- perpetuating the academic disadvantage for code mixing speakers. Recommendations for structural and attitudinal changes through teacher training and implementation of approaches that engage students’ bidialectal competence for learning are made as important first steps towards addressing educational inequities in Nepalese schools.

Keywords: code-mixing, ecological perspective, systematic functional approach, language and identity

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Authors: Vhuhwavho Gadisi, Rebecca Alowo, German Nkhonjera

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It has been noted that technical programming for handling groundwater resources is not accessible. The lack of these systems hinders groundwater management processes necessary for decision-making through monitoring and evaluation regarding the Jukskei River of the Crocodile River (West) Basin in Johannesburg, South Africa. Several challenges have been identified in South Africa's Jukskei Catchment concerning groundwater management. Some of those challenges will include the following: Gaps in data records; there is a need for training and equipping of monitoring staff; formal accreditation of monitoring capacities and equipment; there is no access to regulation terms (e.g., meters). Taking into consideration necessities and human requirements as per typical densities in various regions of South Africa, there is a need to construct several groundwater level monitoring stations in a particular segment; the available raw data on groundwater level should be converted into consumable products for example, short reports on delicate areas (e.g., Dolomite compartments, wetlands, aquifers, and sole source) and considering the increasing civil unrest there has been vandalism and theft of groundwater monitoring infrastructure. GIS was employed at the catchment level to plot the relationship between those identified groundwater parameters in the catchment area and the identified borehole. GIS-based maps were designed for groundwater monitoring to be pretested on one borehole in the Jukskei catchment. This data will be used to establish changes in the borehole compared to changes in the catchment area according to identified parameters.

Keywords: GIS, monitoring, Jukskei, catchment

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Authors: Fatemeh Nejati, Farah Habib, Sayeh Goudarzi

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Architecture and structure have always been closely interrelated so that they should be integrated into a unified, coherent and beautiful universe, while in the contemporary era, both structures and architecture proceed separately. The purpose of architecture is the art of creating form and space and order for human service, and the goal of the structural engineer is the transfer of loads to the structure, too. This research seeks to achieve the goal by looking at the relationship between the form of architecture and structure from its inception to the present day to the Global Identification and Management Plan. Finally, by identifying the main components of the design of the structure in interaction with the architectural form, an effective step is conducted in the Professional training direction and solutions to professionals. Therefore, after reviewing the evolution of structural and architectural coordination in various historical periods as well as how to reach the form of the structure in different times and places, components are required to test the components and present the final theory that one hundred to be tested in this regard. Finally, this research indicates the fact that the form of architecture and structure has an aesthetic link, which is influenced by a number of components that could be edited and has a regular order throughout history that could be regular. The research methodology is analytic, and it is comparative using analytical and matrix diagrams and diagrams and tools for conducting library research and interviewing.

Keywords: architecture, structural form, structural and architectural coordination, effective components, aesthetics

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Authors: Aleksandra Majewska

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The article analyses the impact of Western sanctions on Russian rhythmic gymnastics since the outbreak of war in Ukraine. The chronological presentation of events shows how international political tensions and economic sanctions have affected the organisation of competitions, training and the careers of athletes. The article outlines the key moments and decisions that have changed the landscape of Russian sport, including the decision to change the citizenship made by some gymnasts in order to continue competing in international competitions. Russia strongly opposes participation in competitions without its flag and anthem while maintaining the view that Russian gymnasts are crucial to the prestige of rhythmic gymnastics in the world. In response to the sanctions, Russia created its own rules for rhythmic gymnastics, according to which they now compete domestically. Furthermore, this sport in Russia is strongly linked to politics, which further emphasises its importance in the national and international context. The information collected derives from numerous interviews with Russian athletes, coaches and other people, which are available only in the Russian language. The findings highlight the significant difficulties Russian athletes have faced due to their isolation in the international arena and the adaptive strategies adopted by Russia in the face of these challenges. The article makes an important contribution to understanding the consequences of global politics on the world of sport and the fate of individual athletes.

Keywords: sport, gymnastics, war in Ukraine, sanctions

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Authors: Marco F. Benaglia, Mei H. Chen, Kune M. Tsai, Chia H. Hung

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As societal and family structures, consumer dietary habits, and awareness about food safety and quality continue to evolve in most developed countries, the demand for refrigerated and frozen foods has been growing, and the issues related to their preservation have gained increasing attention. A well-established cold chain logistics system is essential to avoid any temperature abuse; therefore, assessing potential disruptions in the operational processes of cold chain logistics centers becomes pivotal. This study preliminarily employs HACCP to find disruption factors in cold chain logistics centers that may cause temperature abuse. Then, concept mapping is applied: selected experts engage in brainstorming sessions to identify any further factors. The panel consists of ten experts, including four from logistics and home delivery, two from retail distribution, one from the food industry, two from low-temperature logistics centers, and one from the freight industry. Disruptions include equipment-related aspects, human factors, management aspects, and process-related considerations. The areas of observation encompass freezer rooms, refrigerated storage areas, loading docks, sorting areas, and vehicle parking zones. The experts also categorize the disruption factors based on perceived similarities and build a similarity matrix. Each factor is evaluated for its impact, frequency, and investment importance. Next, multiple scale analysis, cluster analysis, and other methods are used to analyze these factors. Simultaneously, key disruption factors are identified based on their impact and frequency, and, subsequently, the factors that companies prioritize and are willing to invest in are determined by assessing investors’ risk aversion behavior. Finally, Cumulative Prospect Theory (CPT) is applied to verify the risk patterns. 66 disruption factors are found and categorized into six clusters: (1) "Inappropriate Use and Maintenance of Hardware and Software Facilities", (2) "Inadequate Management and Operational Negligence", (3) "Product Characteristics Affecting Quality and Inappropriate Packaging", (4) "Poor Control of Operation Timing and Missing Distribution Processing", (5) "Inadequate Planning for Peak Periods and Poor Process Planning", and (6) "Insufficient Cold Chain Awareness and Inadequate Training of Personnel". This study also identifies five critical factors in the operational processes of cold chain logistics centers: "Lack of Personnel’s Awareness Regarding Cold Chain Quality", "Personnel Not Following Standard Operating Procedures", "Personnel’s Operational Negligence", "Management’s Inadequacy", and "Lack of Personnel’s Knowledge About Cold Chain". The findings show that cold chain operators prioritize prevention and improvement efforts in the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster, particularly focusing on the factors of "Temperature Setting Errors" and "Management’s Inadequacy". However, through the application of CPT theory, this study reveals that companies are not usually willing to invest in the improvement of factors related to the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster due to its low occurrence likelihood, but they acknowledge the severity of the consequences if it does occur. Hence, the main implication is that the key disruption factors in cold chain logistics centers’ processes are associated with personnel issues; therefore, comprehensive training, periodic audits, and the establishment of reasonable incentives and penalties for both new employees and managers may significantly reduce disruption issues.

Keywords: concept mapping, cold chain, HACCP, cumulative prospect theory

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Authors: Sihem Benmimoune, Abdelbaki Lemgharbi, Ahmed Ait Yahia, Abdelkrim Kameli

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Our study is based on chemical and phytochemical characterization of Artemisia absinthium L and in vitro tests to demonstrate the biological activities of essential oil and natural extract. A qualitative and quantitative comparison of the essential oil extracted by two extraction procedures was performed by analysis of CG/SM and the yield calculation. The method of hydrodistillation has a chemical composition and provides oil content than the best training water vapor. These oils are composed mainly of thujone followed chamazulene and ρ-cymene. The antimicrobial activity of wormwood oil was tested in vitro by two methods (agar diffusion and microdilution) on four plant pathogenic fungi (Aspergillus sp, Botrytis cinerea, Fusarium culmorum and Helminthosporium sp). The study of the antifungal effect showed that this oil has an inhibitory effect counterpart the microorganisms tested in particular the strain Botrytis cinerea. Otherwise, this activity depends on the nature of the oil and the germ itself. The antioxidant activity in vitro was studied with the DPPH method. The activity test shows that the oil and extract of Artemisia absinthium have a very low antioxidant capacity compared to the antioxidants used as a reference. The extract has a potentially high antiradical power not from its oil. The quantitative determinations of phenolic compounds by the Folin-Ciocalteu revealed that absinthe is low in total polyphenols and tannins.

Keywords: artemisia absinthium, biological activities, essential oil, extraction processes

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Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

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Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

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Authors: Ruchika Malhotra, Megha Khanna

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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

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Authors: Nizar Ahmad

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Peace without community participation will remain a vision, so, this study presents the contribution and efforts made by community base organization in views of local conflict affect population in Pakhtun society. A four conflict affected villages of Malakad Division were selected and a sample size of 278 household respondents were determined through online survey system software out of total 982 households. A Chi-square test was applied to ascertain association between various communication base organizations factors with state of peace in the area. It was found that provision of humanitarian aid, rehabilitation of displaced population, rebuilding of trust in government and peace festivals by communication organization had significant association with state of peace in the area. In contrast provision of training, peace education monitoring and reporting of human rights violation in war zone by local organization was non-significantly related to the state of peace in the area. Community base organization play an active role in building peace in the area but lack capacity, linkages with external actors and outside support. National and international organization actors working in the area of peace and conflict resolution need to focus on the capacity, networking and peace initiatives of local organizations working in fragile context.

Keywords: community base peacebuilding, conflict resolution, terrorism, violence

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Authors: S. Bagur, S. Verger, B. Mut

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Early childhood intervention (ECI) is understood as the set of interventions aimed at the child population with developmental disorders or disabilities from 0 to 6 years of age, the family, and the environment. Under the principles of family-centred practices, the members of the family nucleus are direct agents of intervention. Thus, the multidisciplinary team of professionals should work to improve family empowerment and the level of parenting skills. The aim of the present study is to analyse descriptively and differentially the level of parenting skills and family empowerment of parents using ECI services during the foster care phase. There were 135 families participating in the study. Three questionnaires were completed. The results show that the employment situation, the age of the child receiving an intervention, and the number of children in the family nucleus or the professional carrying out the intervention are variables that have a differential impact on different items of empowerment and parenting skills. The results are discussed and future lines of research are proposed, with the understanding that the initial analysis of the variables of empowerment and parenting skills may be predictors for the improvement of child development and family well-being. In addition, it is proposed to identify and analyse professional training in order to be able to adapt early care practices without depending on the discipline of the professional of reference.

Keywords: developmental disabilities, early childhood intervention, family empowerment, parenting skills

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Authors: Liu Yi Hui, Lin Yu Fang, Chiu Fan Yun

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In preparation for the coming super-aged society in Taiwan, the Ministry of Labor announced the Middle-aged and Elderly Employment Promotion Act in 2019, dedicating a chapter to expressly prohibiting age discrimination. This study aimed to enhance understanding of workplace ageism by collecting data through in-depth interviews. The findings can be summarized as follows: 1. Elderly employment in Taiwan and its three underlying motivations: Mainly in economic, social, and psychological needs. Economically, elders opt to continue working beyond the traditional retirement age because of financial shocks, a lack of financial planning, and being the breadwinner of the family. Socially and psychologically, they continue working to have a more diversified retirement life and find a new purpose in life. 2. Ageism on the re-employment of elders: On the ground, senior workers may face the age-based stereotype that their work performance is inferior and a broader social environment that is ostensibly friendly but essentially hostile. 3. Possible ways to facilitate elderly employment in terms of empowerment: By developing and empowering seniors with new skills or abilities for re-employment and strengthening their problem-solving skills in the face of new things through training programs, we can not only build the confidence and substantial abilities of senior workers in the workplace but also flip the social stereotype about age.

Keywords: senior-friendly workplaces, elderly employment, empowerment, ageism

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Authors: Hagar Elsayed

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This case study examines the framing of the diverse populations of Arab, Muslim and South Asian immigrants and their descendants in local communities by both federal and local law enforcement agencies. It explores how urban spaces and policing are constructed as necessary components of national security in the context of the war on terror by focusing on practices employed in local spaces such as Dearborn, Michigan and training methods adopted on a national level. The proliferation of American Arabs as ‘terrorist’ works to legitimize not only increasing state surveillance, but also military strategies which infringe on ‘inside’ spaces. Sustaining these progressively militarized civil policing operations, which demand intense mobilization of state power, requires that whole neighborhoods and districts are reimagined to portray these geographies in a certain light. This case study is central in understanding how Arab, South Asian, and Muslim civilians’ transformation into a “national security” issue have created militarized police enforcement agencies that employ military tactics to map the terrain of Otherness. This study looks at how race factors into key recent incidents, and asks whether this militarization builds from past forms of racist policing, and whether these specific incidents are reflective of larger patterns or whether they are just isolated incidents.

Keywords: American-Muslims, Arabs, militarization, policing

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Authors: Tso-Yen Mao, De-Yen Liu, Chun-Feng Huang

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Purpose: This research intends to investigate the reliability and validity of ventilatory threshold (VT) and respiratory compensation point (RCP) determined by skeletal muscle hemodynamic status. Methods: One hundred healthy male (age: 22±3 yrs; height: 173.1±6.0 cm; weight: 67.1±10.5 kg) performed graded cycling exercise test which ventilatory and skeletal muscle hemodynamic data were collected simultaneously. VT and RCP were determined by combined V-slope (VE vs. VCO2) and ventilatory efficiency (VE/VO2 vs. VE/VCO2) methods. Pearson correlation, paired t-test, and Bland-Altman plots were used to analyze reliability, validity, and similarities. Statistical significance was set at α =. 05. Results: There are high test-retest correlations of VT and RCP in ventilatory or near-infrared spectroscopy (NIRS) methods (VT vs. VTNIRS: 0.95 vs. 0.94; RCP vs. RCPNIRS: 0.93 vs. 0.93, p<. 05). There are high coefficient of determination at the first timing point of O2Hb decreased (R2 = 0.88, p<. 05) with VT, and high coefficient of determination at the second timing point of O2Hb declined (R2 = 0.89, p< .05) with RCP. VO2 of VT and RCP are not significantly different between ventilatory and NIRS methods (p>. 05). Conclusion: Using NIRS method to determine VT and RCP is reliable and valid in male individuals during graded exercise. Non-invasive skeletal muscle hemodynamics monitor also can be used for controlling training intensity in the future.

Keywords: anaerobic threshold, exercise intensity, hemodynamic, NIRS

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Authors: Farnaz Farzin, Julie C. Thomson, Rob Dekkers, Geoff Whittam

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Research has shown that techno-entrepreneurship is economically significant. Therefore, it is suggested that teaching techno-entrepreneurship may be important because such programmes would prepare current and future generations of learners to recognize and act on high-technology opportunities. Education in techno-entrepreneurship may increase the knowledge of how to start one’s own enterprise and recognize the technological opportunities for commercialisation to improve decision-making about starting a new venture; also it influence decisions about capturing the business opportunities and turning them into successful ventures. Universities can play a main role in connecting and networking techno-entrepreneurship students towards a cooperative attitude with real business practice and industry knowledge. To investigate and answer whether education for techno-entrepreneurs really helps, this paper chooses a comparison of literature reviews as its method of research. Then, 6 different studies were selected. These particular papers were selected based on a keywords search and as their aim, objectives, and gaps were close to the current research. In addition, they were all based on the influence of techno-entrepreneurship education in self-employment and intention of students to start new ventures. The findings showed that teaching techno-entrepreneurship education may have an influence on students’ intention and their future self-employment, but which courses should be covered and the duration of programmes needs further investigation.

Keywords: techno entrepreneurship education, training, higher education, intention, self-employment

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Authors: Farah Nameni, Hamidreza Poursadra, Maasumeh Nurani Pilehrud

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Exercise training induced Inflammation and stress. Antioxidant, for example L- Carnitine has beneficial effects in immune system and increased antioxidant enzymes activity. L- Carnitine protects the tissue against the oxidative side effect and helps the body to protect against stress during and after acute exercise. The aim of this study was to determine the effect of L-Carnitine on the blood enzymes: GPX SOD, CAT and GR response. In this study, 20 basketball players girls participated. Subjects were randomly assigned into two groups; placebo and supplementation. Antioxidadision enzymes (Superoxide Dismutase, Catalase, Glutathione Reductase, Glutathione Peroxidase) evaluated. L-Carnitine supplement group orally daily received 3000 mg powder for 14 dys. Then all participates trained basketball exercise acute. Blood samples were drawn vein before and immediately after exercise. Superoxide Dismutase, Catalase, Glutathione Reductase, Glutathione Peroxidase were measured, and data was analyzed using repeated measure ANOVA, Bonferroni and t-test. Our results showed: SOD, GPX and GPX (P < 0.05) have a significant increase. These results suggest L-Carnitine supplementation may increase GPX SOD, CAT, and basal anti oxidative capacity. L-Carnitine can modulate the alterations of exercise oxidative damage in girl basketball players.

Keywords: l-carnitine, GPX, SOD, CAT, exercise, GR, anti-oxidant

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Authors: Khalida Douibi, Rodrigo Balp, Solène Le Bars

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In the medical field, applications related to human experiments are frequently linked to reduced samples size, which makes the training of machine learning models quite sensitive and therefore not very robust nor generalizable. This is notably the case in Brain-Computer Interface (BCI) studies, where the sample size rarely exceeds 20 subjects or a few number of trials. To address this problem, several resampling approaches are often used during the data preparation phase, which is an overly critical step in a data science analysis process. One of the naive approaches that is usually applied by data scientists consists in the transformation of the entire database before the resampling phase. However, this can cause model’ s performance to be incorrectly estimated when making predictions on unseen data. In this paper, we explored the effect of data leakage observed during our BCI experiments for device control through the real-time classification of SSVEPs (Steady State Visually Evoked Potentials). We also studied potential ways to ensure optimal validation of the classifiers during the calibration phase to avoid overfitting. The results show that the scaling step is crucial for some algorithms, and it should be applied after the resampling phase to avoid data leackage and improve results.

Keywords: data leackage, data science, machine learning, SSVEP, BCI, overfitting

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Authors: Hirreche Baghdad Mohamed

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Our research is linked to cultural policies because the initiation to taste and beauty is a matter for all cultural and educational institutions. It's done by a downstream process (programs, actions, lessons, etc.) that begins at a young age in order to inscribe aesthetic values in memories, imaginations, and practices. Preparing future art lovers probably takes a lot of time. Upstream, continuity is ensured by the "cultural industries" which make cultural products available to actors in the "art market" through professional training, production, dissemination, and sales processes. It turns out that the cultural industries borrow from the "classical" industries the same processes and logic: product, production, marketing, diffusion, profit and profits, supply and demand, the market, the creation of wealth, the entrepreneurship. Today, culture has become a product almost like the others. In the cultural industries system, we protect the rights of authors (owners) and the rights of intermediaries (entrepreneurs of culture), and we provide consumers with an accessible product that meets their needs and expectations. We aim to present an inventory and to reveal, through the speeches of the actors themselves, the processes and modes of operation and deployment of the plastic arts market by showing how it is perceived, imagined, and lived in the city of 'Oran from the 2000s to the present day. However, it is possible to clarify this field of research by looking at previous periods; and even to make comparisons with other regions in Algeria in order to give meaning to practices in various contexts.

Keywords: Oran, Algeria, fine art, art market

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Authors: Michael Ayodeji Boyede

Abstract:

Studies have shown that workers’ job performance is very low in Nigeria, especially in the food and beverage industry. This trend had been partially attributed to low workers’ self-efficacy, poor self-knowledge, lack of empathy and poor psychological well-being. The descriptive survey design was adopted. Four factories were purposively selected from three states in Southwestern, Nigeria (Lagos, Ogun and Oyo States). Proportionate random sampling techniques were used in selecting 1,820 junior and supervisory cadre workers in Nestle Plc (369), Coca-Cola Plc (392), Cadbury Plc (443) and Nigeria Breweries (616). The five research instruments used were: Workers’ self-efficacy (r=0.81), Workers’ self-knowledge (r=0.78), Workers’ empathy (r=0.74), Workers’ psychological well-being (r=0.70) and Workers’ performance rating (r=0.72) scales. Quantitative data were analysed using Pearson product moment correlation, Multiple regression at 0.05 level of significance. Findings show that there were significant relationships between Workers’ job performance and self-efficacy (r=.56), self-knowledge (r=.54), Empathy (r=.55) and Psychological Well-being (r=.69) respectively. Self-efficacy, self-knowledge, empathy and psychological well-being jointly predict workers’ job performance (F (4,1815) = 491.05) accounting for 52.0% of its variance. Psychological well-being (B=.52). Self-efficacy (B=.10), self-knowledge (B=.11), empathy (B=. 09) had predictive relative weights on workers’ job performance. Inadequate knowledge and training of the supervisors led to a mismatch of workers thereby reducing workers’ job performance. High self-efficacy, empathy, psychological well-being and good self-knowledge influence workers job performance in the food and beverage industry. Based on the finding employers of labour should provide work environment that would enhance and promote the development of these factors among the workers.

Keywords: self-efficacy, self-knowledge, empathy, psychological well-being, job performance

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Authors: Zabeehullah, Fahim Arif, Yawar Abbas

Abstract:

Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

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Authors: Sultan Aldaihani, Eiman Al-Fadhli

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Internet of Things (IoTs) expected to change the future of academic libraries operations. It enables academic libraries to be smart libraries through, for example, the connection of the physical objects with the Internet. The implementation of IoTs will improve library resources and services. Therefore, this research aims to investigate the applications of Internet of Things (IoTs) for information resources and services. Understanding perceptions of academic librarians toward IoTs before adopting of such applications will assist decision-makers in academic libraries in their strategic planning. An online questionnaire was administered to academic librarians at Kuwait University. The findings of this study showed that academic librarians have awareness for the IoTs. They have strongly believed that the IoTs contributes to the development of information resources, services, and understanding of the user's information behavior. Identifying new applications of the IoTs in libraries was the highest possible reason for future adoption. Academic librarians indicated that lack of privacy and data penetration were the greatest problem in their future adoption of IoTs. Academic libraries need to implement the IoTs for enhancing their information resources and services. One important step in the success of future adoption is to conduct awareness and training programs for academic librarians. They also need to maintain higher security and privacy measurements in their implementation for the IoTs. This study will assist academic libraries in accommodating this technology.

Keywords: academic libraries, internet of things, information resources, information services

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Authors: S. Wietrzychowski

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The following review has identified specific programs, as well as the elements of these programs, that have been shown to be most effective in preventing suicide in schools. Suicide is an issue that affects many students each year. Although this is a prominent issue, there are few prevention programs used within schools. The primary objective of most prevention programs is to reduce risk factors such as depression and hopelessness, and increase protective factors like support systems and help-seeking behaviors. Most programs include a gatekeeper training model, education component, peer support group, and/or counseling/treatment. Research shows that some of these programs, like the Signs of Suicide and Youth Aware of Mental Health Programme, are effective in reducing suicide behaviors and increasing protective factors. These programs have been implemented in many countries across the world and have shown promising results. Since schools can provide easy access to adolescents, implement education programs, and train staff members and students how to identify and to report suicide behaviors, school-based programs seem to be the best way to prevent suicide among adolescents. Early intervention may be an effective way to prevent suicide. Although, since early intervention is not always an option, school-based programs in high schools have also been shown to decrease suicide attempts by up to 50%. As a result of this presentation, participants will be able to 1.) list at least 2 evidence-based suicide prevention programs, 2.) identify at least 3 factors which protect against suicide, and 3.) describe at least 3 risk factors for suicide.

Keywords: school, suicide, prevention, programs

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Authors: Zhanna Dedovets

Abstract:

Fostering a mathematical style of thinking is crucial for cultivating intellectual personalities capable of thriving in modern society. Intuitive thinking stands as a cornerstone among the components of mathematical cognition, playing a pivotal role in grasping mathematical truths across various disciplines. This article delves into the exploration of leveraging search activities rooted in students' intuitive thinking, particularly when tackling geometric problems. Emphasizing both student engagement with the task and their active involvement in the search process, the study underscores the importance of heuristic procedures and the freedom for students to chart their own problem-solving paths. Spanning several years (2019-2023) at the Physics and Mathematics Lyceum of Dushanbe, the research engaged 17 teachers and 78 high school students. After assessing the initial levels of intuitive thinking in both control and experimental groups, the experimental group underwent training following the authors' methodology. Subsequent analysis revealed a significant advancement in thinking levels among the experimental group students. The methodological approaches and teaching materials developed through this process offer valuable resources for mathematics educators seeking to enhance their students' learning experiences effectively.

Keywords: teaching of mathematics, intuitive thinking, heuristic procedures, geometric problem, students.

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Authors: Lee Bih Ni, Emily Doreen Lee, Wee Hui Yean

Abstract:

This paper was prepared to see the perceptions of online lectures regarding collaborative learning, in terms of how lecturers view online collaborative learning in the higher learning institution. The purpose of this study was conducted to determine the perceptions of online lectures about collaborative learning, especially how lecturers see online collaborative learning in the university. Adult learning education enhance collaborative learning culture with the target of involving learners in the learning process to make teaching and learning more effective and open at the university. This will finally make students learning that will assist each other. It is also to cut down the pressure of loneliness and isolation might felt among adult learners. Their ways in collaborative online was also determined. In this paper, researchers collect data using questionnaires instruments. The collected data were analyzed and interpreted. By analyzing the data, researchers report the results according the proof taken from the respondents. Results from the study, it is not only dependent on the lecturer but also a student to shape a good collaborative learning practice. Rational concepts and pattern to achieve these targets be clear right from the beginning and may be good seen by a number of proposals submitted and include how the higher learning institution has trained with ongoing lectures online. Advantages of online collaborative learning show that lecturers should be trained effectively. Studies have seen that the lecturer aware of online collaborative learning. This positive attitude will encourage the higher learning institution to continue to give the knowledge and skills required.

Keywords: collaborative online learning, lecturers’ training, learning, online

Procedia PDF Downloads 454