Association for Scientic Computing Electronics and Engineering (ASCEE): Open Journal Systems
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Academic writing challenges faced by chemistry doctoral students: A self-study informed by three writing theories
Get PDFThis research investigated the challenges faced by chemistry Ph.D. candidates writing in English as a second language. Drawing from Second Language Writing, Genre Theory, and Academic Writing Instruction and Support, we investigated the linguistic, cultural, and disciplinary factors that might affect these students' writing development. Nineteen doctoral students participated in the study, which relied on a self-study methodology. Attitudes towards writing, idea generation, revision, criticism, cooperation, and writing process awareness were only some topics covered in a seven-part online survey on academic writing. Language, method, outcomes, style, and substance were found to be the most salient aspects of academic writing as seen by graduate students. There were five major classes of issues with academic writing, including text, errors, competence, support, and dissemination medium. By drawing on the fields of Second Language Writing, Genre Theory, and Academic Writing Instruction and Support, we propose strategies for enhancing students' abilities in academic writing. These strategies range from providing more detailed instructions on the writing process to emphasizing the importance of close communication between faculty advisors and their students. The ramifications of these results for graduate education programs that want to help their students with their academic writing are substantial
Ethiopian EFL teachers’ classroom practice and learners’ view on teaching and learning English speaking skill
Get PDFCommunication capacity (Speaking skill) in English language education is a difficult task that needs effective guidance and sustainable practice. Therefore, this study aimed at exploring the Implementation of Teaching and Learning English Speaking Skills in Ethiopian EFL Classes. The design of the study was descriptive survey. There were 523 students included using a simple random sampling technique and 30 EFL teachers using an availability sampling technique. To collect data, questionnaire for students and Focus Group Discussions for teachers were used. Mixed method data analysis was used. The results showed that EFL teachers were not using different techniques to teach English speaking skills, and they were not making sustainable follow-ups on how learners performed. They also apply the teacher-centered method rather than the learner’s method. Learners face challenges from their mother tongue's influence, lack of confidence, and fear of making a mistake. EFL teachers were also challenged by student-related problems like being disinterested in being involved in the actual teaching and learning actively, uncomfortably of the school compound, absence of well-equipped English mini-media, and the bulkiness of the textbook. Thus, EFL teachers should use various techniques, school administration should avail the resource and students should be participatory in their learning
Forecasting learning in electrical engineering and informatics: An ontological approach
Get PDFThis research explores the vital role of ontology in learning forecasting in electrical engineering and informatics. As formally defined models of knowledge, ontologies are critical in organizing concepts for predictive learning. More than just an inquiry, our research reveals complex interconnections centered on Internet of Things (IoT) design, the semantic web, and knowledge modeling. Applications demonstrate the practical significance of ontologies in fostering intelligent connections, advancing information production, and improving interactions between computers, devices, and humans. This research introduces a comprehensive forecasting learning ontology to highlight the importance of ontologies in education, scientific inquiry, and developing systems for predictive analysis. Ontologies provide a structured framework for understanding the essence of predictive learning, encompassing key elements such as ideas, terminology, methodology, algorithms, data preprocessing, assessment, validation, data sources, application environments, interactions with technology, and learning processes. Emphasizing ontologies as indispensable instruments that drive technological development, our work underscores structured representation, semantic interoperability, and knowledge integration. In summary, this research improves the understanding of ontologies in forecasting by explaining practical applications and revealing new perspectives. Its unique contribution lies in its specific applications and natural consequences, laying the foundation for the future progress of ontology and learning forecasting, especially in educational contexts
Consecutive interpreting techniques studies on intercultural communication of Zhuang Medicine culture from the perspective of speech act theory
Get PDFThis paper aims to explore Consecutive Interpreting techniques needed to facilitate Intercultural Communication of Zhuang Medicine Culture from the Perspective of Speech Act Theory,based on ASEAN Guangxi International Workshop on TCM Zhuang and Yao Medicine. It is found that the Speech Act Theory can effectively guide the C-E International Zhuang Medicine Workshop classroom interpreting and contribute to better classroom communication. Meanwhile, the application of techniques such as semantic deverbalization, amplification and negation can facilitate imparting of Zhuang Medicine Culture knowledge
Finding and Tracking Automobiles on Roads for Self-Driving Car Systems
Get PDFRoad-object detection, recognition, and tracking are vital tasks that must be performed reliably and accurately by self-driving car systems in order to achieve the automation/autonomy goal. Other vehicles are one of the main objects that the egocar must accurately detect and track on the road. However, deep-learning approaches proved their effectiveness at the expense of very demanding computational power and low throughput. They must be deployed on expensive CPUs and GPUs. Thus, in this work, a lightweight vehicle detection and tracking technique (LWVDT) is suggested to fit low-cost CPUs without sacrificing robustness, speed, or comprehension. The LWVDT is suitable for deployment in both advanced driving assistance systems (ADAS) functions and autonomous-car subsystems. The implementation is a sequence of computer-vision techniques fused together and merged with machine-learning procedures to strengthen each other and streamline execution. The algorithm details and their execution are revealed in detail. The LWVDT processes raw RGB camera pictures to generate vehicle boundary boxes and tracks them from frame to frame. The performance of the proposed pipeline is assessed using real road camera images and video recordings under different circumstances and lighting/shading conditions. Moreover, it is also tested against the well-known KITTI database, achieving an average accuracy of 87%
Teachers’ perception of school based continuous professional development in Zambia
Get PDFThis study aimed to explore teachers' perceptions, practices, and challenges in Zambia school based teacher professional development programs. The survey sample consisted of four primary schools, four school principals, four schools’ continuous professional development (CPD) coordinators, one DEBS official, and 198 teachers. The major findings show that there is a positive perception of teachers toward school-based CPD programs. In addition, the results show that even though teachers have positively perceived school-based CPD well, the practice of CPD program implementation is at a low level in secondary schools. Furthermore, the study findings indicated the lack of teachers' support from school management and supervisors and lack of collaboration with teachers and school leaders were among the factors that affected the implementation of the CPD program. The study also shows that teachers with more teaching experience positively perceive the school-based CPD programs, and teachers with degree holders practice more CPD activities than diploma holders
The discursive construction of spiritual values and cultural standards in Sang Pemimpi Film
Get PDFSpirituality is a contentious human phenomenon that encompasses personal, sociocultural, and transcendent interconnection. In Indonesian society, spiritual experiences are often associated with religion. They are also part of the cultural standards, the way of thinking, feeling, and behaving shared by most of a culture's members. This research aims to examine the spiritual and cultural values of Belitung's Muslim society through the Sang Pemimpi film. The research method in this study was critical discourse analysis, a qualitative approach based on a critical paradigm. This study combines Theo van Leeuwen's critical and multimodality discourse analysis techniques. Spiritual values and cultural standards are used as theoretical elements. The character in the film's text with the background of the Muslim society and the Belitung people's culture is the focus of this study. According to the film analysis, spirituality is formed by socio-cultural interactions in people's daily lives. The Muslim community in Belitung adapts well to religious and cultural differences in their social relationships with other ethnic groups, including the Chinese ethnic groups. According to the findings of this study, religiosity and communal domains are the aspects that appear the most in the film
Optimizing Solar Energy Harvesting: Supervised Machine Learning-Driven Peak Power Point Tracking for Diverse Weather Conditions
Get PDFSolar Power is one of the significant prevalent forms of clean energy due to its perceived to be pollution-free and easily accessible. The market for renewable energy was established by the rapid development in electrical energy consumption and the diminution of conventional energy resources (CER). Under varying weather condition extracted energy from solar system is not constant and maximum. This study suggests the applicability of machine learning algorithm (MLA) in Peak power point tracking (P3T) methods to maximize power of a PV arrangement under varying weather conditions. Machine learning methods optimize peak power point tracking in solar photovoltaic systems by bringing agility, data-driven decision-making, and increased accuracy. MLAs improve the overall efficiency, stability, and dependability of these systems by handling the unpredictability of solar energy production under varying weather circumstances and PSCs Because MLAs are able to learn and adjust to non-linear relationships between solar intensity and PVS output. In this study, the squared multiple squared exponential Gaussian process regression method SGPRA tested in three rapidly varying ecological conditions. The performance of ML-P3T methods is validated using Matlab/Simulink, and the simulation outcome are compared with one of the most used algorithms, the variable step size incremental conductance algorithm (VINA). The Matlab/Simulink findings show that SGPRA operates significantly better under varying weather circumstances, harnessing more peak power efficiency 90%, shorter tracking time 0.13 sec, a mean error of 0.042, and superior stability
Mining the public sentiment for wayang climen preservation and promotion
Get PDFIndonesia is a country that has a variety of cultural arts, one of which is shadow puppetry (Wayang). Wayang, in a staged, simple, and minimalist manner, is called Wayang Climen. Wayang Climen has been performed since the COVID-19 pandemic as a solution to keep working while still complying with health protocols. Utilization through YouTube social media attracts people to watch and provide opinions through comments. This opinion is beneficial and can be used as a feasibility study through sentiment analysis information classified as positive, negative, and neutral opinions. Sentiment analysis determines a person's opinion and tendency to opinionated sentences. The methods used are Random Forest (RF), Support Vector Machine (SVM), and Naïve Bayes (NB). The dataset comes from YouTube comments of Dalang Seno and Ki Seno Nugroho. The best accuracy is generated by SVM (70.29%). The positive sentiment shows the public's appreciation for the Wayang Climen performance, which ultimately represents the performance even though it is staged densely. This research contributes to effectively utilizing digital platforms for cultural preservation and audience engagement during challenging times, demonstrating the potential for innovative solutions in traditional arts and entertainment
Artificial Potential Field Path Planning Algorithm in Differential Drive Mobile Robot Platform for Dynamic Environment
Get PDFMobile robots need path-planning abilities to achieve a collision-free trajectory. Obstacles between the robot and the goal position must be passed without crashing into them. The Artificial Potential Field (APF) algorithm is a method for robot path planning that is usually used to control the robot for avoiding obstacles in front of the robot. The APF algorithm consists of an attractive potential field and a repulsive potential field. The attractive potential fields work based on the predetermined goals that are generated to attract the robot to achieve the goal position. Apart from it, the obstacle generates a repulsive potential field to push the robot away from the obstacle. The robot's localization in producing the robot's position is generated by the differential drive kinematic equations of the mobile robot based on encoder and gyroscope data. In addition, the mapping of the robot's work environment is embedded in the robot's memory. According to the experiment's results, the mobile robot's differential drive can pass through existing obstacles. In this research, four test environments represent different obstacles in each environment. The track length is 1.5 meters. The robot's tolerance to the goal is 0.1 m, so when the robot is in the 1.41 m position, the robot's speed is 0 rpm. The safe distance between the robot and the obstacle is 0.2 m, so the robot will find a route to get away from the obstacle when the robot reaches that safe distance. The speed of the resulting robot decreases as the distance between the robot and the destination gets closer according to the differential drive kinematics equation of the mobile robot