Search results for: 70% ethanol effectiveness

Authors: Eman Ayman, Gehan Nagy

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The learning environment has four main parameters that affect its efficiency which they are: pedagogy, user, technology, and space. According to Morrone, enhancing these parameters to be adaptable for future developments is essential. The educational organization will be in need of developing its learning spaces. Flexibility of design an immersive technology could be used as tools for this development. when flexible design concepts are used, learning spaces that can accommodate a variety of teaching and learning activities are created. To accommodate the various needs and interests of students, these learning spaces are easily reconfigurable and customizable. The immersive learning opportunities offered by technologies like virtual reality, augmented reality, and interactive displays, on the other hand, transcend beyond the confines of the traditional classroom. These technological advancements could improve learning. This thesis highlights the problem of the lack of innovative, flexible learning spaces in educational institutions. It aims to develop guidelines for enhancing the learning environment by the integration of flexible design and immersive technology. This research uses a mixed method approach, both qualitative and quantitative: the qualitative section is related to the literature review theories and case studies analysis. On the other hand, the quantitative section will be identified by the results of the applied studies of the effectiveness of redesigning a learning space from its traditional current state to a flexible technological contemporary space that will be adaptable to many changes and educational needs. Research findings determine the importance of flexibility in learning spaces' internal design as it enhances the space optimization and capability to accommodate the changes and record the significant contribution of immersive technology that assists the process of designing. It will be summarized by the questionnaire results and comparative analysis, which will be the last step of finalizing the guidelines.

Keywords: flexibility, learning space, immersive technology, learning environment, interior design

Procedia PDF Downloads 93

Authors: Alba Prats-Bisbe, Jaume López-Carballo, David Leno-Colorado, Alberto García Molina, Alicia Romero Marquez, Elena Hernández Pena, Eloy Opisso Salleras, Raimon Jané Campos

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Neurological disorders are a leading cause of disability and premature mortality worldwide. Neurorehabilitation (NRHB) is a clinical process aimed at reducing functional impairment, promoting societal participation, and improving the quality of life for affected individuals. Virtual reality (VR) technology is emerging as a promising NRHB support tool. Its immersive nature fosters a strong sense of agency and embodiment, motivating patients to engage in meaningful tasks and increasing adherence to therapy. However, the clinical benefits of VR interventions are challenging to determine due to the high heterogeneity among health applications. This study explores a stepwise development approach for creating VR-based tools to assist individuals with neurological disorders in medical practice, aiming to enhance reproducibility, facilitate comparison, and promote the generalization of findings. Building on previous research, the step-by-step methodology encompasses: Needs Identification– conducting cross-disciplinary meetings to brainstorm problems, solutions, and address barriers. Intervention Definition– target population, set goals, and conceptualize the VR system (equipment and environments). Material Selection and Placement– choose appropriate hardware and software, place the device within the hospital setting, and test equipment. Co-design– collaboratively create VR environments, user interfaces, and data management strategies. Prototyping– develop VR prototypes, conduct user testing, and make iterative redesigns. Usability and Feasibility Assessment– design protocols and conduct trials with stakeholders in the hospital setting. Efficacy Assessment– conduct clinical trials to evaluate outcomes and long-term effects. Cost-Effectiveness Validation– assess reproducibility, sustainability, and balance between costs and benefits. NRHB is complex due to the multifaceted needs of patients and the interdisciplinary healthcare architecture. VR has the potential to support various applications, such as motor skill training, cognitive tasks, pain management, unilateral spatial neglect (diagnosis and treatment), mirror therapy, and ecologically valid activities of daily living. Following this methodology was crucial for launching a VR-based system in a real hospital environment. Collaboration with neuropsychologists lead to develop A) a VR-based tool for cognitive rehabilitation in patients with acquired brain injury (ABI). The system comprises a head-mounted display (HTC Vive Pro Eye) and 7 tasks targeting attention, memory, and executive functions. A desktop application facilitates session configuration, while database records in-game variables. The VR tool's usability and feasibility were demonstrated in proof-of-concept trials with 20 patients, and effectiveness is being tested through a clinical protocol with 12 patients completing 24-session treatment. Another case involved collaboration with nurses and paediatric physiatrists to create B) a VR-based distraction tool during invasive techniques. The goal is to alleviate pain and anxiety associated with botulinum toxin (BTX) injections, blood tests, or intravenous placements. An all-in-one headset (HTC Vive Focus 3) deploys 360º videos to improve the experience for paediatric patients and their families. This study presents a framework for developing clinically relevant and technologically feasible VR-based support tools for hospital settings. Despite differences in patient type, intervention purpose, and VR system, the methodology demonstrates usability, viability, reproducibility and preliminary clinical benefits. It highlights the importance approach centred on clinician and patient needs for any aspect of NRHB within a real hospital setting.

Keywords: neurological disorders, neurorehabilitation, stepwise development approach, virtual reality

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Authors: Xi Vivien Wu, Emily Neo Kim Ang, Yi Jung Tung, Wenru Wang

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Background and Objective: The increase in life expectancy and emphasis on self-reliance for the older adults are global phenomena. As such, lifelong learning in the community is considered a viable means of promoting successful and active aging. This systematic review aims to examine various lifelong learning programs for community-dwelling older adults and to synthesize the contents and outcomes of these lifelong learning programs. Methods: A systematic search was conducted in July to December 2016. Two reviewers were engaged in the process to ensure creditability of the selection process. Narrative description and analysis were applied with the support of a tabulation of key data including study design, interventions, and outcomes. Results: Eleven articles, which consisted of five randomized controlled trials and six quasi-experimental studies, were included in this review. Interventions included e-health literacy programs with the aid of computers and the Internet (n=4), computer and Internet training (n=3), physical fitness programs (n=2), music program (n=1), and intergenerational program (n=1). All studies used objective measurement tools to evaluate the outcomes of the study. Conclusion: The systematic review indicated lifelong learning programs resulted in positive outcomes in terms of physical health, mental health, social behavior, social support, self-efficacy and confidence in computer usage, and increased e-health literacy efficacy. However, the lifelong learning programs face challenges such as funding shortages, program cuts, and increasing costs. A comprehensive lifelong learning program could be developed to enhance the well-being of the older adults at a more holistic level. Empirical research can be done to explore the effectiveness of this comprehensive lifelong learning program.

Keywords: community-dwelling older adults, e-health literacy program, lifelong learning program, the wellbeing of the older adults

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Authors: A. Pietro Rimoldi, B. Anilkumar Gopinath, C. Minimol Korulla

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Coastal engineering structure is conventionally designed for a shorter planning horizon usually 20 years. These structures are subjected to different offshore climatic externalities like waves, tides, tsunamis etc. during the design life period. The probability of occurrence of these different offshore climatic externalities varies. The impact frequently caused by these externalities on the structures is of concern because it has a significant bearing on the capital /operating cost of the project. There can also be repeated short time occurrence of these externalities in the assumed planning horizon which can cause heavy damage to the conventional coastal structure which are mainly made of rock. A replacement of the damaged portion to prevent complete collapse is time consuming and expensive when dealing with hard rock structures. But if coastal structures are made of Geo-synthetic containment systems such replacement is quickly possible in the time period between two successive occurrences. In order to have a better knowledge and to enhance the predictive capacity of these occurrences, this study estimates risk of encounter within the design life period of various externalities based on the concept of exponential distribution. This gives an idea of the frequency of occurrences which in turn gives an indication of whether replacement is necessary and if so at what time interval such replacements have to be effected. To validate this theoretical finding, a pilot project has been taken up in the field so that the impact of the externalities can be studied both for a hard rock and a Geosynthetic tube structure. The paper brings out the salient feature of a case study which pertains to a project in which Geosynthetic tubes have been used for reformation of a seawall adjacent to a conventional rock structure in Alappuzha coast, Kerala, India. The effectiveness of the Geosystem in combatting the impact of the short-term externalities has been brought out.

Keywords: climatic externalities, exponential distribution, geosystems, planning horizon

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Authors: Huang Ying

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The present study was to investigate factors affecting children's improvement through the first two years of elementary school on a population-based sample of children with autism in Taiwan. All the children were diagnosed with autism spectrum disorder (ASD) by clinical psychologists according to DSM-IV. Children's development was assessed by the Vineland Adaptive Behavior Scales-Chinese version (VABS-C) on the first and the third grade. Children's improvement was measured by the difference between the standardized total score of the third and the first year. In Taiwan, school-age children with special-education needs will be arranged into different classes, including normal classes (NC), resource classes (RC), and special classes (SC) by the government. Therefore, type of class was one of the independent variables. Moreover, as early intervention is considered to be crucial, the earliest age when intervention begins was collected from parents. Attention was also included in the analysis. Teachers were asked to evaluate children's attention with a 3-item Likert Scale. The frequency of paying attention to the class or the task was recorded and scores were summed up. Additionally, standardized scores of the VABS-C in the first grade were used as pretest scores representing children's developmental level at the beginning of elementary school. Multiple regression was conducted with improvement as the dependent variable. Results showed that children in special classes had smaller improvement compared to those in normal or resource classes. Attention positively predicted improvement yet the effect of earliest intervention age was not significant. Furthermore, scores in the first grade negatively predicted improvement, which indicated that children with higher developmental levels would make less progress in the following years. Results were to some degree consistent with previous findings through meta-analysis that the effectiveness of conventional intervention methods lacked sufficient evidence to support.

Keywords: attention, early intervention, elementary school, special education in Taiwan

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Authors: Xueming Xu, Jiahao Liu, Jichao Li, Kewei Yang, Minghao Li, Bingfeng Ge

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A combat system-of-systems (CSoS) comprises various types of functional combat entities that interact to meet corresponding task requirements in the present and future. Enhancing the resilience of CSoS holds significant military value in optimizing the operational planning process, improving military survivability, and ensuring the successful completion of operational tasks. Accordingly, this research proposes an integrated framework called CSoS resilience enhancement (CSoSRE) to enhance the resilience of CSoS from a recovery perspective. Specifically, this research presents a two-phase resilience optimization model to define a resilience optimization objective for CSoS. This model considers not only task baseline, recovery cost, and recovery time limit but also the characteristics of emergency recovery and comprehensive recovery. Moreover, the research extends it from the deterministic case to the stochastic case to describe the uncertainty in the recovery process. Based on this, a resilience-oriented recovery optimization method based on deep reinforcement learning (RRODRL) is proposed to determine a set of entities requiring restoration and their recovery sequence, thereby enhancing the resilience of CSoS. This method improves the deep Q-learning algorithm by designing a discount factor that adapts to changes in CSoS state at different phases, simultaneously considering the network’s structural and functional characteristics within CSoS. Finally, extensive experiments are conducted to test the feasibility, effectiveness and superiority of the proposed framework. The obtained results offer useful insights for guiding operational recovery activity and designing a more resilient CSoS.

Keywords: combat system-of-systems, resilience optimization model, recovery optimization method, deep reinforcement learning, certainty and uncertainty

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Authors: Stephanie Liu Lu

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With the proliferation of artificial intelligence tools in the field of education, it is crucial to explore their impact on language learning outcomes. This paper examines the use of AI tools, such as ChatGPT, in practical writing within business Chinese teaching to investigate how AI can enhance practical writing skills and teaching effectiveness. The study involved third and fourth-year university students majoring in accounting and finance from a university in Hong Kong within the context of a business correspondence writing class. Students were randomly assigned to a control group, who completed business letter writing independently, and an experimental group, who completed the writing with the assistance of AI. In the latter, the AI-assisted business letters were initially drafted by the students issuing commands and interacting with the AI tool, followed by the students' revisions of the draft. The paper assesses the performance of both groups in terms of grammatical expression, communicative effect, and situational awareness. Additionally, the study collected dialogue texts from interactions between students and the AI tool to explore factors that affect text generation and the potential impact of AI on enhancing students' communicative and identity awareness. By collecting and comparing textual performances, it was found that students assisted by AI showed better situational awareness, as well as more skilled organization and grammar. However, the research also revealed that AI-generated articles frequently lacked a proper balance of identity and writing purpose due to limitations in students' communicative awareness and expression during the instruction and interaction process. Furthermore, the revision of drafts also tested the students' linguistic foundation, logical thinking abilities, and practical workplace experience. Therefore, integrating AI tools and related teaching into the curriculum is key to the future of business Chinese teaching.

Keywords: AI-assistance, business Chinese, textual analysis, language education

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Authors: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar

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Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.

Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks

Procedia PDF Downloads 186

Authors: Yifan Hou, Haibo Liu, Le Jiang, Wandong Su, Binqing Wang

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Road defect detection is crucial for modern urban management and infrastructure maintenance. Traditional road defect detection methods mostly rely on manual labor, which is not only inefficient but also difficult to ensure their reliability. However, existing deep learning-based road defect detection models have poor detection performance in complex environments and lack robustness to multi-scale targets. To address this challenge, this paper proposes a distinct detection framework based on the one stage algorithm network structure. This article designs a deep feature extraction network based on RCSDarknet, which applies channel shuffling to enhance information fusion between tensors. Through repeated stacking of RCS modules, the information flow between different channels of adjacent layer features is enhanced to improve the model's ability to capture target spatial features. In addition, a multi-scale feature fusion mechanism with weighted dual flow paths was adopted to fuse spatial features of different scales, thereby further improving the detection performance of the model at different scales. To validate the performance of the proposed algorithm, we tested it using the RDD2022 dataset. The experimental results show that the enhancement algorithm achieved 84.14% mAP, which is 1.06% higher than the currently advanced YOLOv8 algorithm. Through visualization analysis of the results, it can also be seen that our proposed algorithm has good performance in detecting targets of different scales in complex scenes. The above experimental results demonstrate the effectiveness and superiority of the proposed algorithm, providing valuable insights for advancing real-time road defect detection methods.

Keywords: roads, defect detection, visualization, deep learning

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Authors: Felice De Luca, Vincenzo Galdi, Piera Stella, Vito Calderaro, Adriano Campagna, Antonio Piccolo

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Sustainable mobility has become one of the major issues of recent years. The challenge in reducing polluting emissions as much as possible has led to the production and diffusion of vehicles with internal combustion engines that are less polluting and to the adoption of green energy vectors, such as vehicles powered by natural gas or LPG and, more recently, with hybrid and electric ones. While on the one hand, the spread of electric vehicles for private use is becoming a reality, albeit rather slowly, not the same is happening for vehicles used for public transport, especially those that operate in the congested areas of the cities. Even if the first electric buses are increasingly being offered on the market, it remains central to the problem of autonomy for battery fed vehicles with high daily routes and little time available for recharging. In fact, at present, solid-state batteries are still too large in size, heavy, and unable to guarantee the required autonomy. Therefore, in order to maximize the energy management on the vehicle, the optimization of driving profiles offer a faster and cheaper contribution to improve vehicle autonomy. In this paper, following the authors’ precedent works on electric vehicles in public transport and energy management strategies in the electric mobility area, an eco-driving strategy for electric bus is presented and validated. Particularly, the characteristics of the prototype bus are described, and a general-purpose eco-drive methodology is briefly presented. The model is firstly simulated in MATLAB™ and then implemented on a mobile device installed on-board of a prototype bus developed by the authors in a previous research project. The solution implemented furnishes the bus-driver suggestions on the guide style to adopt. The result of the test in a real case will be shown to highlight the effectiveness of the solution proposed in terms of energy saving.

Keywords: eco-drive, electric bus, energy management, prototype

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Authors: Catherine Mangan, Beth Anderson

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There has been a significant drive to use online or hybrid learning in Higher Education (HE) over recent years. HEs with a virtual presence offer their communities a range of benefits, including the potential for greater inclusivity, diversity, and collaboration; more flexible learning packages; and more engaging, dynamic content. Institutions can also experience significant challenges when seeking to extend learning spaces in this way, as can learners themselves. For example, staff members’ and learners’ digital literacy varies (as do their perceptions of technologies in use), and there can be confusion about optimal approaches to implementation. Furthermore, the speed with which HE institutions have needed to shift to fully online or hybrid models, owing to the COVID19 pandemic, has highlighted the significant barriers to successful implementation. HE environments have been shown to predict a range of organisational, academic, and experiential outcomes, both positive and negative. Much research has focused on the social aspect of virtual platforms, as well as the nature and effectiveness of the technologies themselves. There remains, however, a relative paucity of synthesised knowledge on the psychology of learners’ relationships with their institutions; specifically, how individual difference and interpersonal factors predict students’ ability and willingness to engage with novel virtual learning spaces. Accordingly, extending learning spaces remains challenging for institutions, and wholly remote courses, in particular, can experience high attrition rates. Focusing on the last five years, this pragmatic review summarises evidence from the psychological and pedagogical literature. In particular, the review highlights the importance of addressing the psychological and relational complexities of students’ shift from offline to online engagement. In doing so, it identifies considerations for HE institutions looking to deliver in this way.

Keywords: higher education, individual differences, interpersonal relationships, online learning, virtual environment

Procedia PDF Downloads 175

Authors: Wafula Simon Peter, Kimuli Nabayego Ibtihal, Nabaggala Kimuli Nashua

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The worldwide use of information and communications technology (ICT) equipment and other electronic equipment is growing and consequently, there is a growing amount of equipment that becomes waste after its time in use. This growth is expected to accelerate since equipment lifetime decreases with time and growing consumption. As a result, e-waste is one of the fastest-growing waste streams globally. The United Nations University (UNU) calculates in its second Global E-waste Monitor 44.7 million metric tonnes (Mt) of e-waste were generated globally in 2016. The study population was 80 respondents, from which a sample of 69 respondents was selected using simple and purposive sampling techniques. This research was carried out to investigate the problem of e-waste and come up with a framework to improve e-waste management. The objective of the study was to develop a framework for improving e-waste management at the College of Engineering, Design, Art and Technology (CEDAT). This was achieved by breaking it down into specific objectives, and these included the establishment of the policy and other Regulatory frameworks being used in e-waste management at CEDAT, the determination of the effectiveness of the e-waste management practices at CEDAT, the establishment of the critical challenges constraining e-waste management at the College, development of a framework for e-waste management. The study reviewed the e-waste regulatory framework used at the college and then collected data which was used to come up with a framework. The study also established that weak policy and regulatory framework, lack of proper infrastructure, improper disposal of e-waste and a general lack of awareness of the e-waste and the magnitude of the problem are the critical challenges of e-waste management. In conclusion, the policy and regulatory framework should be revised, localized and strengthened to contextually address the problem. Awareness campaigns, the development of proper infrastructure and extensive research to establish the volumes and magnitude of the problems will come in handy. The study recommends a framework for the improvement of e-waste.

Keywords: e-waste, treatment, disposal, computers, model, management policy and guidelines

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Authors: Tan Lay Cheng (Cheryl), Low Huiqi

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Background: All children learn at different pace. Individualized learning is an approach that tailors to the individual learning needs of each child. When implementing this approach, educators have to base their lessons on the understanding that all students learn differently and that what works for one student may not work for another. In the current early childhood environment, individualized learning is for children with diverse needs. However, a typical developing child is also able to benefit from individualized learning. This research abstract explores the concept of utilizing DNA-MILE, a patented (in Singapore) DNA-based assessment tool that can be used to measure a variety of factors that can impact learning. The assessment report includes the dominant intelligence of the user or, in this case, the child. From the result, a personalized learning plan that is tailored to each individual student's needs. Methods: A study will be conducted to investigate the effectiveness of DNA-MILE in supporting individualized learning. The study will involve a group of 20 preschoolers who were randomly assigned to either a DNA-MILE-assessed group (experimental group) or a control group. 10 children in each group. The experimental group will receive DNA Mile assessments and personalized learning plans, while the control group will not. The children in the experimental group will be taught using the dominant intelligence (as shown in the DNA-MILE report) to enhance their learning in other domains. The children in the control group will be taught using the curriculum and lesson plan set by their teacher for the whole class. Parents’ and teachers’ interviews will be conducted to provide information about the children before the study and after the study. Results: The results of the study will show the difference in the outcome of the learning, which received DNA Mile assessments and personalized learning plans, significantly outperformed the control group on a variety of measures, including standardized tests, grades, and motivation. Conclusion: The results of this study suggest that DNA Mile can be an effective tool for supporting individualized learning. By providing personalized learning plans, DNA Mile can help to improve learning outcomes for all students.

Keywords: individualized, DNA-MILE, learning, preschool, DNA, multiple intelligence

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Authors: Udomporn Pangnakorn, Settawut Prasatporn, Sombat Chuenchooklin

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The effect of biopesticide on growth, yield and pest infestation of maize (Zea mays Linn.) (variety DK 6818) was evaluated during the drought season. The experimental plots were located at research station of Faculty of Agriculture, Natural Resources and Environment, Naresuan University, Phitsanulok, Thailand. The extracted substance from plants was evaluated in the plots in 4 treatments: 1) water as control; 2) bitter bush (Chromolaena odorata L.); 3) neem (Azadirachta indica A. Juss), 4) golden shower (Cassia fistula Linn.). The experiment was followed a Randomized Complete Block Design (RCBD) with 4 treatments and 4 replications per treatment. The results showed that golden shower gave the highest growth of maize in term of height (203.29 cm), followed by neem and bitter bush with average height of 202.66 cm and 191.66 cm respectively with significance different. But neem treatment given significantly higher average of yield component in term of length, width, and weight of pod corn with 18.89 cm 13.91 cm and 166.46 g respectively. Also, treatment of neem showed the highest harvested yield at 284.06 kg/ha followed by the golden shower and bitter bush with harvested yield at 245.86 kg/ha and 235.52 kg/ha respectively. Additionally, treatment of neem and golden shower were the highest effectiveness for reducing insects pest infestation of maize: corn leaf aphid Rhopalosiphum maidis Fitch, corn borer Ostrinia fumacalis Guenee and corn armyworm Mythimna separata Walker. The treatment of neem, golden shower, and bitter bush given reduction insect infestation on maize with leaves area were infested at 5,412 mm², 6,827 mm² and 8,910 mm² respectively with significance different when compared to control.

Keywords: maize, Zea mays Linn., biopesticide, bitter bush, Chromolaena odorata L.), neem, Azadirachta indica A. Juss, golden shower, Cassia fistula Linn.

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Authors: Sohal Latif

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Solar power is in the form of photovoltaic, also known as PV, which is a form of renewable energy that applies solar panels in producing electricity from the sun. It has a vital role in fulfilling the present need for clean and renewable energy to get rid of conventional and non-renewable energy sources that emit high levels of greenhouse gases. Solar energy is embraced because of its availability, easy accessibility, and effectiveness in the provision of power, chiefly in country areas. In solar charging, device charge entails a change of light power into electricity using photovoltaic or PV panels, which supply direct current electric power or DC. Here, the solar charge controller has a very crucial role to play regarding the voltages and the currents coming from the solar panels to take up the changing needs of a battery without overcharging the same. Certain devices, such as inverters, are required to transform the DC power produced by the solar panels into an AC to serve the normal electrical appliances and the current power network. This project was initiated for a project of a solar charge controller and power converter with the MULTISIM. The formation of this project begins with a literature survey to obtain basic knowledge about power converters, charge controllers, and photovoltaic systems. Fundamentals of the operation of solar panels include the process by which light is converted into electricity and a comparison of PWM and MPPT chargers with controllers. Knowledge of rectifiers is built to help achieve AC-to-DC and DC-AC change. Choosing a resistor, capacitance, MOSFET, and OP-AMP is done by the need of the system. The circuit diagrams of converters and charge controllers are designed using the Multisim program. Pulse width modulation, Bubba oscillator circuit, and inverter circuits are modeled and simulated. In the subsequent steps, the analysis of the simulation outcomes indicates the efficiency of the intended converter systems. The various outputs from the different configurations, with the transformer incorporated as well as without it, are then monitored for effective power conversion as well as power regulation.

Keywords: solar charge controller, MULTISIM, converter, inverter

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Authors: I GD Yudha Partama, A. Kanno, Y. Akamatsu, R. Inui, M. Goto, M. Sekine

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The aerial photogrammetry of shallow water bottoms has the potential to be an efficient high-resolution survey technique for shallow water topography, thanks to the advent of convenient UAV and automatic image processing techniques Structure-from-Motion (SfM) and Multi-View Stereo (MVS)). However, it suffers from the systematic overestimation of the bottom elevation, due to the light refraction at the air-water interface. In this study, we present an empirical method to correct for the effect of refraction after the usual SfM-MVS processing, using common software. The presented method utilizes the empirical relation between the measured true depth and the estimated apparent depth to generate an empirical correction factor. Furthermore, this correction factor was utilized to convert the apparent water depth into a refraction-corrected (real-scale) water depth. To examine its effectiveness, we applied the method to two river sites, and compared the RMS errors in the corrected bottom elevations with those obtained by three existing methods. The result shows that the presented method is more effective than the two existing methods: The method without applying correction factor and the method utilizes the refractive index of water (1.34) as correction factor. In comparison with the remaining existing method, which used the additive terms (offset) after calculating correction factor, the presented method performs well in Site 2 and worse in Site 1. However, we found this linear regression method to be unstable when the training data used for calibration are limited. It also suffers from a large negative bias in the correction factor when the apparent water depth estimated is affected by noise, according to our numerical experiment. Overall, the good accuracy of refraction correction method depends on various factors such as the locations, image acquisition, and GPS measurement conditions. The most effective method can be selected by using statistical selection (e.g. leave-one-out cross validation).

Keywords: bottom elevation, MVS, river, SfM

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Authors: Abdullah Al Farwan, Ya Zhang

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In today’s educational arena, it is critical to understand educational data and be able to evaluate important aspects, particularly data on student achievement. Educational Data Mining (EDM) is a research area that focusing on uncovering patterns and information in data from educational institutions. Teachers, if they are able to predict their students' class performance, can use this information to improve their teaching abilities. It has evolved into valuable knowledge that can be used for a wide range of objectives; for example, a strategic plan can be used to generate high-quality education. Based on previous data, this paper recommends employing data mining techniques to forecast students' final grades. In this study, five data mining methods, Decision Tree, JRip, Naive Bayes, Multi-layer Perceptron, and Random Forest with wrapper feature selection, were used on two datasets relating to Portuguese language and mathematics classes lessons. The results showed the effectiveness of using data mining learning methodologies in predicting student academic success. The classification accuracy achieved with selected algorithms lies in the range of 80-94%. Among all the selected classification algorithms, the lowest accuracy is achieved by the Multi-layer Perceptron algorithm, which is close to 70.45%, and the highest accuracy is achieved by the Random Forest algorithm, which is close to 94.10%. This proposed work can assist educational administrators to identify poor performing students at an early stage and perhaps implement motivational interventions to improve their academic success and prevent educational dropout.

Keywords: classification algorithms, decision tree, feature selection, multi-layer perceptron, Naïve Bayes, random forest, students’ academic performance

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Authors: Pankaj Kumar Jha, Saroj Sapkota, Dil Bahadur Gurung, Raju Kadel, Neena Amatya Gorkhali, Bhola Shankar Shrestha

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The study was conducted to evaluate the seminal attributes, effectiveness of cooling process and post-thawed semen quality of a Nepalese indigenous Khari buck. Thirty-two ejaculates, 16 from each buck were studied for seminal attributes of fresh semen: volume, color, mass activity, motility, viability, sperm concentration, and morphology. The pooled mean values for each seminal attributes were: volume 0.7±0.3 ml; colour 3.1±0.3 (milky white); mass activity 3.8±0.4 (rapid wave motion with formation of eddies at the end of waves to very rapid wave motion with distinct eddies formation); sperm motility 80.9±5.6%; sperm viability 94.6±2.0%; sperm concentration 2597.0±406.8x106/ml; abnormal acrosome, mid-piece and tail 10.7±1.8% and abnormal head 5±1.7%. For freezing semen, further 6 ejaculates from each buck were studied with Tris based egg yolk citrate extender. The pooled mean values of motility and viability of post diluted semen for 90 and 120 minutes each for cooling and glycerol equilibration were 73.8±4.8%, 88.1±2.6% and 69.2±6.0%, 85.0±1.7%, respectively. The pooled mean values of post thaw motility and viability with advancement of preservation time were: 0hour 49.0±4.6%, 81.2±1.9%; 2nd day 41±2.2%, 79±1%; 5th day 41±2.2%, 78.6±0.9% and 10th day 41±2.2%, 78.6±0.9%. We concluded from the above study that the seminal attributes and results of post-thaw semen quality were satisfactory and in accordance with other work in foreign countries, which indicated the feasibility of cryopreserving buck semen. For more validation, research with large number of bucks, different types of diluents and freezing trials by removing seminal plasma followed by pregnancy rate is recommended.

Keywords: cryopreservation, Nepalese indigenous Khari (Hill goat) buck, post-thaw semen quality, seminal attributes

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Authors: Homa Hedayat

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Public spaces have been a central concern of urban planners for centuries but have been neglected for a long time. In the modernist planning, the focus has been on the requirements of cars rather than the needs and expectations of pedestrians, and therefore, cities have lost many qualities. Urban public space is a space within the city area which is accessible to all people and is the ground for their activity. People’s public life occurs in urban public spaces in a complex set of forms and functions. These spaces must facilitate diverse behavior, uses, and activities such as shopping, walking, conversation, entertainment, relaxation or even passing the time during festivities and events. One of the public spaces is the surrounding space of public transportation stations. Subway stations, although potentially encompass many different groups of people accommodate few social interactions. Making the surrounding areas of subway stations pedestrian-oriented, potentially increases the socialization capacity. The Sadeghieh Subway Station can be considered as the most important subway station in Tehran, which on the one hand is the rail port of Tehran's western entrance, and on the other is the port for railway journeys inside the city. The main concern of this study is to assess the success or failure of the interventions made by the municipality for changing the surrounding area of the Sadeghieh Subway Station into a pedestrian-oriented space and examine the amount of the area's improvement into a desirable space. The method used in this study is surveying, in which the data were collected using a questionnaire and interview. The study's population is all people who use Sadeghieh Subway, and the sample size for the study was 140 subjects. Using parametric one-sample t-test, we found improvement in factors such as transportation, security, pedestrian infrastructure, vitality and climate comfort. However, there was no improvement in mix use, recreational activity, readability.

Keywords: public space, public transportation stations, pedestrian-oriented space, socialization

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Authors: L. Sun, C. Hardacre, A. Garforth, N. Zhang

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Higher Education (HE) degrees in the UK are attractive for international students. The recognized reputation of the HE and the world-leading researchers in some areas in the UK imply that the HE degree from the UK might be a passport to a successful career for abroad students. However, it is a challenge to inspire outstanding students applying for the universities in the UK. The incentives should be country-specific for undergraduates and postgraduates. The potential obstacles to stop students applying for the study in the UK mainly lie in these aspects: different HE systems between the UK and other countries, such as China; less information for the application procedures; worries for the study in English for those non-native speakers; and expensive international tuition fees. The hybrid incentives have been proposed by the efforts from the institutions, stuffs, and students themselves. For example, excellent students from top universities would join us based on the abroad exchange programs or ‘2+2 programme’ with discount tuition. They are potential PhD candidates in the further study in the UK. Diversity promotions are implemented to share information and answer queries for potential students and their guardians. Face to face presentations, workshops, and seminars deliver chances for students to admire teaching and learning in the UK, and give students direct answers for their confusions. WeChat official account and Twitter as the online information platform are set up to post messages of recruitment, the guidance for the application procedures, and international collaboration in teaching and research as well. Students who are studying in the UK and the alumni would share their experiences in the study and lives in the UK and their careers after obtaining the HE degree would play as a positive stimulus to our potential students. Short term modules in the UK with exchangeable credits in summer holidays would give abroad students firsthand experiences of the study in the reputable schools with excellent academics, different cultures and the network with international students. Successful cases at the University of Manchester illustrated the effectiveness of these presented methodologies.

Keywords: abroad students, degree study, high education, hybrid incentives

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Authors: Naylya Djumaeva

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Since the end of 2019, the world has been shaken by an infection that has claimed the lives of more than six and a half million patients. Currently, SARS-CoV-2 not only causes acute damage but has long-term consequences affecting every organ and has brought a wave of a new chronic disabling condition called Long-Covid..This preliminary study describes an application of un-explored properties of low-level laser radiation with laser- light emitter in the field of which is placed Copegus (Ribavirin) with the aim of treatment of patients with Long-Covid syndrome. The difference from the traditional use of the drug is that Copegus was not prescribed to the patient by the traditional method - orally or intravenously, and the medicinal properties of the drug were introduced into the patient’s body using the un-explored properties of low-power laser radiation. Ninety eight patients with Long- Covid syndrome were observed. The obtained findings suggest that under the influence of the field formed into the laser- light emitter with a Copegus placed inside the field, the remote transfer of pharmacological properties of Сopegus occurs. Conclusions about the produced effect of exposure were made based on improvement in the condition of patients, the disappearance of complaints, and positive changes in various diagnostic tests performed by the patients. Biography: Djumaeva N completed her PhD from the Institute of Epidemiology, Microbiology and Infectious Diseases in 2000. In her dissertation work devoted to the treatment of patients with chronic hepatitis B virus infection, she presented data on the possible influence of Complex Homeopathic Preparations on the organization of bound intracellular water in the cells of the body. She is the Consultant (Neurologist) at the Scientific-Research Institute for Virology, Uzbekistan, and an expert in “medicament testing” method (30 years). She has published 43 papers, including 2 patents.

Keywords: long covid, low level laser, copegus, laser- light emmiter

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Authors: Hadeer Ibrahiem, Mahmoud Nasr, Masarrat M. M. Migahid, Mohamed A. Ghazy

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The release of textile wastewater loaded with 1,4 dioxane into aquatic ecosystems has been associated with various human health risks and adverse environmental impacts. In parallel, phytoremediation has been recently employed to treat highly polluted wastewater because various plant species tend to produce certain enzymes as a defense mechanism against a toxic environment. To our best knowledge, this study is the first to investigate the ability of phytoremediation using Eichhornia crassipes for the removal of various pollutants, including 1,4 dioxane, from textile wastewater. A phytoremediation system composed of Eichhornia crassipes was acclimatized for 10 d, and then operated in four lab-scale hydroponic systems, viz., negative control, positive control, and two different 1,4 dioxane concentration (400 and 500 mg/L). After 11 d of operation, the phytoremediation system achieved removal efficiencies of 67.5±3.4%, 89.4±4.4%, 83.6±3.8% for 1,4 dioxane (at initial concentration 400 mg/L), chemical oxygen demand (COD) (at initial concentration 679 mg/L), and cumulative heavy metals, respectively. The removal of these pollutants was mainly supported by the phyto-sorption and phytodegradation mechanisms. The economic feasibility of this phytoremediation system was validated by estimating the capital and operating costs, requiring 4.6 USD for the treatment of 1 m3 textile wastewater. The study concluded that the phytoremediation process could be used as a practical and economical approach to treat textile wastewater laden with various organic and inorganic pollutants. Due to the observed pollution reduction and human health protection, the study objectives would fulfill the targets of SDG 3 “Good Health and Well-being” and SDG 6 “Clean Water and Sanitation”. Further studies are required to (i) investigate the ability of plant species to withstand higher concentrations of 1,4 dioxane for an extended operation time and (ii) understand the biochemical pathways for the degradation of 1,4 dioxane via the action of plant enzymes and the associated microbial community.

Keywords: 1, 4 dioxane concentrations, hydrophytes, Eichhornia crassipes, phytoremediation effectiveness, SDGs, textile industrial effluent

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Authors: Abdullah Ansari, Sinika Rambaran, Sirpaul Jaikishun

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Vermiwash could be used to enhance plant productivity and resistance to some harmful plant pathogens, as well as provide benefit through the disposal of waste matter. Alternaria rot caused by the fungus Alternaria alternata (Fr.) Keissl., is a common soil-borne pathogen that results in postharvest fruit rot of cucumbers, peppers and other cash crops. The production and distribution of Cucumis sativus L. (cucumber) could be severely affected by Alternaria rot. Fungicides are the traditional treatment however; they are not only expensive but can also cause environmental and health problems. Vermiwash was prepared from various medicinal plants (Ocimum tenuiflorum L. {Tulsi}, Azadirachta indica A. Juss. {neem}, Cymbopogon citratus (DC. ex Nees) Stapf. {lemon grass} and Oryza sativa L. {paddy straw} and applied, in vitro, to A. alternata to investigate their effectiveness as organic alternatives to traditional fungicides. All of the samples of vermiwash inhibited the growth of A. alternata. The inhibitive effects on the fungus appeared most effective when A. indica and O. tenuiflorum were used in the production of the vermiwash. Using the serial dilution method, vermiwash from O. tenuiflorum showed the highest percent of inhibition (93.2%), followed by C. citratus (74.7%), A. indica (68.7%), O. sativa, combination, and combination without worms. Using the sterile disc diffusion method, all of the samples produced zones of inhibition against A. alternata. Vermiwash from A. indica produced a zone of inhibition, averaging 15.3mm, followed by O. tenuiflorum (14.0mm), combination without worms, combination, C. citratus and O. sativa. Nystatin produced a zone of inhibition of 10mm. The results indicate that vermiwash is not simply an organic alternative to more traditional chemical fungicides, but it may in fact be a better and more effective product in treating certain fungal plant infections, particularly A. alternata.

Keywords: vermiwash, earthworms, soil, bacteria, alternaria alternata, antifungal, antibacterial

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Authors: Andrew Hargreaves, Peter Vale, Jonathan Whelan, Carlos Constantino, Gabriela Dotro, Pablo Campo

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As a consequence of their potential to cause harm, there are strong regulatory drivers that require metals to be removed as part of the wastewater treatment process. Bioavailability-based standards have recently been specified for copper (Cu), lead (Pb), nickel (Ni) and zinc (Zn) and are expected to reduce acceptable metal concentrations. In order to comply with these standards, wastewater treatment works may require new treatment types to enhance metal removal and it is, therefore, important to examine potential treatment options. A substantial proportion of Cu, Pb, Ni and Zn in effluent is adsorbed to and/or complexed with macromolecules (eg. proteins, polysaccharides, aminosugars etc.) that are present in the colloidal size fraction. Therefore, technologies such as coagulation-flocculation (CF) that are capable of removing colloidal particles have good potential to enhance metals removal from wastewater. The present study investigated the effectiveness of CF at removing trace metals from humus effluent using the following coagulants; ferric chloride (FeCl3), the synthetic polymer polyethyleneimine (PEI), and the biopolymers chitosan and Tanfloc. Effluent samples were collected from a trickling filter treatment works operating in the UK. Using jar tests, the influence of coagulant dosage and the velocity and time of the slow mixing stage were studied. Chitosan and PEI had a limited effect on the removal of trace metals (<35%). FeCl3 removed 48% Cu, 56% Pb and 41% Zn at the recommended dose of 0.10 mg/L. At the recommended dose of 0.25 mg/L Tanfloc removed 77% Cu, 68% Pb, 18% Ni and 42% Zn. The dominant mechanism for particle removal by FeCl3 was enmeshment in the precipitates (i.e. sweep flocculation) whereas, for Tanfloc, inter-particle bridging was the dominant removal mechanism. Overall, FeCl3 and Tanfloc were found to be most effective at removing trace metals from wastewater.

Keywords: coagulation-flocculation, jar test, trace metals, wastewater

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Authors: Tahar Tayachi, Ahlam Alrehaili

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Purpose: The purpose of this paper is to investigate the relationship between the corporate board characteristics and the dividend policy among firms on the Saudi Stock Exchange. Design/Methodology/Approach: This paper uses a sample of 103 nonfinancial firms over a time period of 4 years from 2015 to 2018. To investigate how corporate governance mechanisms such as board independence, the board size, frequency of meetings, and free cash flow impact dividends, the study uses Logit and Tobit models. Findings: This paper finds that board size, board independence, and frequency of board meetings have no influence on a firm’s decision to pay dividends, while board size has a significantly positive impact on the levels of cash dividends paid to investors. This study also finds that the level of free cash flows has a positively significant influence on both the decision to pay dividends and the magnitude of dividend payouts. Research Limitations/Implications: This paper attempts to study the effectiveness of dividend policy among some firms on the Saudi Stock Exchange. Practical Implications: The findings reveal that board characteristics, which represent one of the crucial mechanisms of corporate governance, were found to be complementary to corporate laws and regulations imposed on the Saudi market in 2015. The findings also imply that capital market authorities should revise their corporate regulations and ensure that protection laws are adequate and strong enough to protect the interests of all shareholders. Originality/Value: This paper is among the few studies focusing on dividend policy in Saudi Arabia. Finally, these findings suggest that the improvements in corporate laws in Saudi Arabia led to such an outcome, and it has become prevalent in dividend policy decisions and behaviors of Saudi firms.

Keywords: agency theory, Tobit, corporate governance, dividend payout, Logit

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Authors: Laxmi R. Kasaraneni

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The Internet connects all the networks, including the nation’s critical infrastructure that are used extensively by not only a nation’s government and military to protect sensitive information and execute missions, but also the primary infrastructure that provides services that enable modern conveniences such as education, potable water, electricity, natural gas, and financial transactions. It has become the central nervous system for the government, the citizens, and the industries. When it is attacked, the effects can ripple far and wide impacts not only to citizens’ well-being but nation’s economy, civil infrastructure, and national security. As such, these critical services may be targeted by malicious hackers during cyber warfare, it is imperative to not only protect them and mitigate any immediate or potential threats, but to also understand the current or potential impacts beyond the IT networks or the organization. The Nation’s IT infrastructure which is now vital for communication, commerce, and control of our physical infrastructure, is highly vulnerable to attack. While existing technologies can address some vulnerabilities, fundamentally new architectures and technologies are needed to address the larger structural insecurities of an infrastructure developed in a more trusting time when mass cyber attacks were not foreseen. This research is intended to improve the core functions of the Internet and critical-sector information systems by providing a clear path to create a safe, secure, and resilient cyber environment that help stakeholders at all levels of government, and the private sector work together to develop the cybersecurity capabilities that are key to our economy, national security, and public health and safety. This research paper also emphasizes the present and future cyber security threats, the capabilities and goals of cyber attackers, a strategic concept and steps to implement cybersecurity for maximum effectiveness, enabling technologies, some strategic assumptions and critical challenges, and the future of cyberspace.

Keywords: critical challenges, critical infrastructure, cyber security, enabling technologies, national security

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Authors: Naziema Begum Jappie

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In higher education, particularly within South African universities engaged in regional and global collaborations, the integration of intercultural competencies into teaching, learning, and assessment is essential for student success. Intercultural competencies and the digital platform are intwined in the fabric of teaching, learning, and assessments for student success in higher education. These are integral to virtual learning and exchange within higher education, which are expected to develop these competencies. However, this is not always the case because these are not always explicitly integrated into the academic agenda. Despite the prevalence of international students and exchange programmes, there is often a lack of deliberate integration of these competencies into academic agendas, even for South African students from different cultural, ethnic and language groups. This research addresses this gap by examining the impact of infusing intercultural activities into both face-to-face and digital learning platforms. Adopting an intersectional perspective, the study recognizes how social identities interact to shape individuals' self-perceptions and experiences in a university. Methodologically, this study employs a mixed-methods approach, combining quantitative surveys and qualitative interviews to assess the effectiveness of integrating intercultural competencies into digital platforms. Surveys administered to students and faculty measure changes in intercultural skills and attitudes before and after the implementation of targeted interventions. In-depth interviews with participants will provide further insights into the qualitative aspects of these changes, including their experiences and perceptions of the integration process. The research evaluates whether the strategic integration of intercultural competencies into digital platforms enhances students' intercultural skills and social justice awareness. The findings provide valuable insights for higher education academics and internationalization practitioners seeking to develop effective strategies for cultivating intercultural competencies among students.

Keywords: digital platform, higher education, intercultural competencies, interventions

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Authors: Nacera Yassa, Abdelmalek Saidoune, Ghania Ouadfel, Hamza Houassine

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The rapid advancement in electrical technologies has underscored the increasing importance of multiphase machines across various industrial sectors. These machines offer significant advantages in terms of efficiency, compactness, and reliability compared to their single-phase counterparts. However, early detection and diagnosis of electrical faults remain critical challenges to ensure the durability and safety of these complex systems. This paper presents an advanced analytical model for multiphase machines, with a particular focus on dual stator asynchronous machines. The primary objective is to develop a robust diagnostic tool capable of effectively detecting and locating electrical faults in these machines, including short circuits, winding faults, and voltage imbalances. The proposed methodology relies on an analytical approach combining electrical machine theory, modeling of magnetic and electrical circuits, and advanced signal analysis techniques. By employing detailed analytical equations, the developed model accurately simulates the behavior of multiphase machines in the presence of electrical faults. The effectiveness of the proposed model is demonstrated through a series of case studies and numerical simulations. In particular, special attention is given to analyzing the dynamic behavior of machines under different types of faults, as well as optimizing diagnostic and recovery strategies. The obtained results pave the way for new advancements in the field of multiphase machine diagnostics, with potential applications in various sectors such as automotive, aerospace, and renewable energies. By providing precise and reliable tools for early fault detection, this research contributes to improving the reliability and durability of complex electrical systems while reducing maintenance and operation costs.

Keywords: faults, diagnosis, modelling, multiphase machine

Procedia PDF Downloads 63

Authors: Xiao-Yan Li, Takashi Hashimoto, Guanhong Li, Shuo Yang

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In Japanese, onomatopoeia is an important element in the lively expression of feelings and experiences. It is very difficult for students of Japanese to acquire onomatopoeia, especially, its nuances. In this paper, based on traditional L2 learning theories, we propose a new method to improve the efficiency of teaching the nuances – both explicit and tacit - to non-native speakers of Japanese. The method for teaching the tacit nuances of onomatopoeia consists of three elements. First is to teach the formal rules representing the explicit nuances of onomatopoeic words. Second is to have the students create new onomatopoeic words by utilizing those formal rules. The last element is to provide feedback by evaluating the onomatopoeias created. Our previous study used five-grade relative estimation. However students were confused about the five-grade system, because they could not understand the evaluation criteria only based on a figure. In this new system, then, we built an evaluation database through native speakers’ narrative interpretation. We asked Japanese native speakers to describe their awareness of the nuances of onomatopoeia in writing. Then they voted on site and defined priorities for showing to learners on the system. To verify the effectiveness of the proposed method and the learning system, we conducted a preliminary experiment involving two groups of subjects. While Group A got feedback about the appropriateness of their onomatopoeic constructions from the native speakers’ narrative interpretation, Group B got feedback just in the form of the five-grade relative estimation. A questionnaire survey administered to all of the learners clarified our learning system availability and also identified areas that should be improved. Repetitive learning of word-formation rules, creating new onomatopoeias and gaining new awareness from narrative interpretation is the total process used to teach the explicit and tacit nuances of onomatopoeia.

Keywords: onomatopoeia, tacit nuance, narrative interpretation, e-learning system, second language teaching

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Authors: Hui-Yi Wang, Shu-Mei Chen, Mei-Fang Liu

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Background and purpose: Providing clinical experience in medical education is an important discipline method where students can gradually apply their academic knowledge to clinical situations. The purpose of this study was to establish self-assessment questionnaires for students to assess their learning outcomes for two fields of physical therapy, orthopedic physical therapy, and pediatric physical therapy, in a clinical fieldwork course. Methods: The questionnaires were developed based on the core competence dimensions of the course. The content validity of the questionnaires was evaluated and established by expert meetings. Among the third-year undergraduate students who took the clinical fieldwork course, there were 49 students participated in this study. Teachers arranged for the students to study two professional fields, and each professional field conducted a three-week clinical lesson. The students filled out the self-assessment questionnaires before and after each three-week lesson. Results: The self-assessment questionnaires were established by expert meetings that there were six core competency dimensions in each of the two fields, with 20 and 21 item-questions, respectively. After each three-week clinical fieldwork, the self-rating scores in each core competency dimension were higher when compared to those before the course, indicating having better clinical abilities after the lessons. The best self-rating scores were the dimension of attitude and humanistic literacy, and the two lower scores were the dimensions of professional knowledge and skills and problem-solving critical thinking. Conclusions: This study developed questionnaires for clinical fieldwork courses to reflect students' learning outcomes, including the performance of professional knowledge, practice skills, and professional attitudes. The use of self-assessment of learning performance can help students build up their reflective competencies. Teachers can guide students to pay attention to the performance of abilities in each core dimension to enhance the effectiveness of learning through self-reflection and improvement.

Keywords: physical therapy, clinical fieldwork course, learning outcomes assessment, medical education, self-reflection ability

Procedia PDF Downloads 116