Research Paper Research Articles

Enhancing students’ learning experience in mathematics class through ChatGPT

This research paper explores the integration of ChatGPT as a tool for interactive learning of numerical methods in a differential equations (DEs) course. DE course is crucial for engineering students to model real-world phenomena. However, many DE courses focus only on analytical solutions and neglect important numerical solutions. To overcome this gap, an active learning approach was adopted, where students were asked to select a real-life phenomenon in their field of interest, find an appropriate model to describe it using DEs, and subsequently solve DE numerically using various numerical methods. The authors allowed students to use ChatGPT to generate codes and learn how to adapt them to their personalized learning needs. The findings derived from the students’ survey responses demonstrated that ChatGPT significantly enhanced their interests and improved their coding skills. Students reported increased engagement and excitement in their learning journey with the integration of ChatGPT. By sharing this experience, we aim to inspire other educators to explore the potential of innovative technologies and instructional methods to enhance their own courses.

Introduction

The June 2023 issue of our journal brings together our valuable readers with six different articles. In this issue, there are two research articles, one focusing on the continent of Europe and one on the Asian continent, two opinion articles focusing on the migration issue, which is one of the most important agenda items of Turkey and indeed the world, and two book reviews. The first research paper, authored by John Conrad Masabo, examines the potential repercussions of the COVID-19 pandemic on the future of European Union (EU) integration and its global impact. Exploring different views on whether the EU can become the most influential power in the post-COVID-19 world, the author suggests that while this possibility exists, there are significant hurdles that the EU must overcome before achieving such status. Merve Özten Yıldız, the author of the second research article, which aims to reveal how India is trying to construct a South Asian identity with Indo-Pacific discourses, examines the rise of India as the second most influential power in Asia. In his article, the author analyzes the official and practical discourse of India to understand its role in shaping regional identity and its growing influence on the international scene. The first review essay, authored by Müzeyyen Okyay, focuses on the issue of migration. The author dealt with the refugee and migrant problem, which has recently become the primary agenda item in EU-Turkey relations. In this study, the situation of people who have to migrate from their homeland, which is a common problem of Turkey and the EU and requires joint efforts to solve, has been examined within the framework of local laws and international agreements, and the effects of migration on the relations between Turkey and the EU have been analyzed. The second review essay belongs to Ufuk Tok. In this article, Tok examines the uncertainties that arose in Afghanistan following the US withdrawal and the Taliban takeover in August 2021. The author, who has the expectation that the integration of the country under the rule of the Taliban with the contemporary world will not be easy and quick, but will be gradual, also analyzes the effect of the long-lasting war on irregular migration from Afghanistan to the west and explores the possibilities of preventing the migration movement towards Turkey. The first review in the publication review section belongs to Selin Çınar. Çınar presents a comprehensive review of the compilation book The Routledge Handbook of Ideology and International Relations, edited by Jonathan Leader Maynard and Mark L. Haased and published in 2022. The second publication evaluation was made by Ahmet Emin Yıldız and is on the book titled Post-Cold War China-India Relations, written by Nezir Oğuş, the first edition of which was published in 2021. We would like to thank all the authors who have contributed to this issue of our journal by sending their works, and all the referees who have put effort in the evaluation process of these works; we hope that the continuing interest in our journal from the national and international academic community will continue.

Suspension Based on Magnetic Effect for Vehicles

Abstract: Suspension systems are integral to vehicle performance, playing a critical role in enhancing ride comfort, stability, and handling. By absorbing shocks and vibrations, suspension systems ensure a smoother ride for occupants, improve traction, and maintain optimal tire contact with the road. Effective suspension systems also contribute to overall vehicle safety by optimizing braking performance and manoeuvrability. This research paper explores the benefits of magnetic suspension systems and their applications across various fields. Magnetic suspension offers significant advantages over traditional mechanical systems, including superior stability, quick dynamic responses, and efficient thermal management. Through detailed analysis and comparative studies, this paper highlights the potential of magnetic suspension to revolutionize modern transportation and other industries requiring precise control and stability.

Replication in Requirements Engineering: The NLP for RE Case

Natural language processing (NLP) techniques have been widely applied in the requirements engineering (RE) field to support tasks such as classification and ambiguity detection. Despite its empirical vocation, RE research has given limited attention to replication of NLP for RE studies. Replication is hampered by several factors, including the context specificity of the studies, the heterogeneity of the tasks involving NLP, the tasks’ inherent hairiness , and, in turn, the heterogeneous reporting structure. To address these issues, we propose a new artifact, referred to as ID-Card , whose goal is to provide a structured summary of research papers emphasizing replication-relevant information. We construct the ID-Card through a structured, iterative process based on design science. In this article: (i) we report on hands-on experiences of replication; (ii) we review the state-of-the-art and extract replication-relevant information: (iii) we identify, through focus groups, challenges across two typical dimensions of replication: data annotation and tool reconstruction; and (iv) we present the concept and structure of the ID-Card to mitigate the identified challenges. This study aims to create awareness of replication in NLP for RE. We propose an ID-Card that is intended to foster study replication but can also be used in other contexts, e.g., for educational purposes.

A Survey on Primary Students’ Attitude toward Teachers’ Use of Mother Tongue in English Classrooms at Primary Schools in Binh Duong

It is a controversial issue whether to use or not to use mother language in teaching English in primary classrooms. The purpose of this research paper is to investigate the reality of speaking Vietnamese in English classrooms in several primary schools in Binh Duong province. 23 primary students in Binh Duong were asked to answer a list of questions to learn about their attitude toward L1 in L2 lessons. It turned out that nearly 70% of teachers at primary schools in Binh Duong usually used L1 in their L2 classes to explain new words and difficult terms. The majority of primary students preferred L1 use and had a positive attitude toward teachers’ use of Vietnamese when appropriate use of L1 to support and facilitate EFL classroom. We recommend that the teacher’s intensity of using L1 in L2 context should be taken into consideration in accordance to the students’ proficiency.

Evaluating Gesture Generation in a Large-scale Open Challenge: The GENEA Challenge 2022

This article reports on the second GENEA Challenge to benchmark data-driven automatic co-speech gesture generation. Participating teams used the same speech and motion dataset to build gesture-generation systems. Motion generated by all these systems was rendered to video using a standardised visualisation pipeline and evaluated in several large, crowdsourced user studies. Unlike when comparing different research articles, differences in results are here only due to differences between methods, enabling direct comparison between systems. The dataset was based on 18 hours of full-body motion capture, including fingers, of different persons engaging in a dyadic conversation. Ten teams participated in the challenge across two tiers: full-body and upper-body gesticulation. For each tier, we evaluated both the human-likeness of the gesture motion and its appropriateness for the specific speech signal. Our evaluations decouple human-likeness from gesture appropriateness, which has been a difficult problem in the field. The evaluation results show some synthetic gesture conditions being rated as significantly more human-like than 3D human motion capture. To the best of our knowledge, this has not been demonstrated before. On the other hand, all synthetic motion is found to be vastly less appropriate for the speech than the original motion-capture recordings. We also find that conventional objective metrics do not correlate well with subjective human-likeness ratings in this large evaluation. The one exception is the Fréchet gesture distance (FGD), which achieves a Kendall’s tau rank correlation of around -0.5. Based on the challenge results we formulate numerous recommendations for system building and evaluation.

Is ‘Common Prosperity’ Badly Needed in Mainland China? Evidence on the Variance Convergence of Per-Capita GDP among 31 Cities and Provinces

ABSTRACT This research paper examines the necessity of implementing “common prosperity” in mainland China, as emphasized by Xi Jinping during the 20th Congress of CCP on October 16, 2022. The issue of provincial income divergence remains a challenge to China’s sustainable growth. The new concept of “common prosperity” stresses the requirement of reducing income inequality for the balance of growth and stability in the next development phase of China. This study analyzes regional income inequality and convergence using the club convergence approach. This method offers more precise indications of economic symmetry than traditional unit root tests, enabling clearer policy implications. The empirical analysis reveals that while full cross-provincial variance convergence is unsustainable, the 31 cities and provinces can be grouped based on club variance convergence of the per capita GDP. The past and current public policies could have an impact on the imbalanced convergence, such as “the richer got more” from the fiscal transfers, the hukou system, and the educational and tax justice among cities and provinces.

Re-assessment of the subcellular localization of Bazooka/Par-3 in Drosophila: no evidence for localization to the nucleus and the neuromuscular junction.

Bazooka/Par-3 (Baz) is an evolutionarily conserved scaffold protein that functions as a master regulator for the establishment and maintenance of cell polarity in many different cell types. In the vast majority of published research papers Baz has been reported to localize at the cell cortex and at intercellular junctions. However, there have also been several reports showing localization and function of Baz at additional subcellular sites, in particular the nuclear envelope and the neuromuscular junction. In this study we have re-assessed the localization of Baz to these subcellular sites in a systematic manner. We used antibodies raised in different host animals against different epitopes of Baz for confocal imaging of Drosophila tissues. We tested the specificity of these antisera by mosaic analysis with null mutant baz alleles and tissue-specific RNAi against baz. In addition, we used a GFP-tagged gene trap line for Baz and a bacterial artificial chromosome (BAC) expressing GFP-tagged Baz under control of its endogenous promoter in a baz mutant background to compare the subcellular localization of the GFP-Baz fusion proteins to the staining with anti-Baz antisera. Together, these experiments did not provide evidence for specific localization of Baz to the nucleus or the neuromuscular junction.

The Playful Karoo: Translating a South African Story into the Metaverse

ABSTRACT This research paper explores different game design methodologies that can be used to translate the South African novel Souvenir by Jane Rosenthal, set in the semi-desert region known as the Karoo into a Virtual Reality experience, which can live on the Metaverse. The paper suggests that the translated Virtual Reality experience can be used as a tool for climate change action and awareness, as well as a way to preserve South African stories on the Metaverse. The paper focuses on various narrative design methodologies for storytelling in game design, suggesting which would work best for the translation of a novel into a Virtual Reality experience. Additionally, it explores practical methodologies for the production of 3D game objects and assets required to recreate the Karoo landscape as described in the novel. This encompasses an exploratory excursion conducted within the Karoo region itself, wherein the collection of primary data is executed for the creation of game assets. Additionally, this involves a comprehensive examination of Henry Jenkins’ methodologies in game design, particularly focusing on narrative elements within gaming. A meaningful impact on the Metaverse is pursued through the translation of this Karoo-based South African novel, into Virtual Reality.

Online Pravda’s Communicative Intentions Regarding the War in Ukraine: A CDA-Based Study of the Website’s Opinion Articles

This research paper, based on Critical Discourse Analysis (CDA), aimed to uncover how the opinion articles published on Pravda.ru discursively depicted the war in Ukraine and the parties involved. To achieve this, two elements of CDA analysis, namely presupposition and structural opposition, were examined. The first element was scrutinized to determine how Pravda.ru depicted the war in Ukraine (RQ1), while the second element was analyzed to understand how Pravda.ru portrayed the parties involved, whether directly or indirectly, in the war (RQ2). For this study, 83 articles were subject to critical discourse analysis, covering the period from February 25, 2022, to February 24, 2023, the first year of the war. The results obtained from this study indicated that Pravda.ru employed various techniques to construct presuppositions and structural oppositions. Pravda.ru portrayed the war as a 'special military operation' and a 'proxy war.' The former, characterized as a euphemism, aimed to mitigate the impact of the word, presupposing that the events did not constitute aggression against Ukraine. The latter presupposed that Russia was a victim of a conspiracy. Furthermore, the results revealed that Pravda.ru used stigmatization and religious affiliations and terms to construct structural oppositions.

Geometric features and traffic dynamic analysis on 4-leg intersections

AbstractWith the escalating density of vehicles converging at road intersections, the surge in road accidents, traffic conflicts, and traffic congestion has emerged as a pressing concern. This research paper addresses these challenges by employing MC (manual control) techniques to mitigate encroachment issues at three selected intersections. These intersections were identified through a comprehensive analysis of the Ranking-based Instance Selection (RIS), enabling the design of suitable measures to facilitate smooth traffic flow and minimize the occurrence of crashes. In order to gather pertinent data, the study incorporates various parameters such as traffic volume, peak flow rate (PFR), traffic conflicts, accidents, and intersection inventory. Through the implementation of our proposed approaches, which involve both MC techniques and signalized operation, a supreme level of service (LOS) is attainable. Notably, our findings demonstrate a remarkable reduction in the volume-to-capacity ratio (v/c ratio) of up to 0.62. This paper thus serves as a significant contribution to the field of traffic management, offering practical insights for optimizing intersection design and effectively addressing the challenges posed by increased traffic density.

Indigenous, ethnic, and racial diversity and climate justice: New Zealand’s climate adaptation policies and policy approaches

This research paper interrogates the extent to which indigenous, ethnic, and racial diversity is substantively integrated into climate justice discussions with a focus on New Zealand’s climate change adaptation policies. A qualitative research design is used, employing a documentary analysis and summative content analysis to scrutinise New Zealand climate change adaptation policies and their responsiveness to indigenous, ethnic and racial diversity within the ambit of climate justice. This study aims to measure the extent to which these policies promote inclusive and equitable climate adaptation outcomes. This study makes a significant contribution to the nuanced understanding of climate justice research, particularly regarding indigenous and ethnic minority communities. The study is expected to contribute to the existing knowledge base and inform the formulation of inclusive policies that integrate the diverse perspectives of these communities into climate adaptation and policy-making processes. The research findings highlight existing gaps and emphasise the importance of incorporating indigenous, ethnic, and racial diversity into policy development and implementation. The aim is to shape climate adaptation strategies that are representative of aware of insights from various communities in contemporary cities.

Development of optimised software fault prediction model using machine learning

Software fault prediction is a crucial task, especially with the rapid improvements in software technology and increasing complexity of software. As identifying and addressing bugs early in the development process can significantly minimize the costs and enhance the software quality. Software fault prediction using machine learning algorithms has gained significant attention due to its potential to improve software quality and save time in the testing phase. This research paper investigates the impact of classification models on bug prediction performance and explores the use of bio-inspired optimization techniques to enhance model results. Through experiments, it is demonstrated that applying bio-inspired algorithms improves the accuracy of fault prediction models. The evaluation is based on multiple performance metrics and the results show that KNN with BACO (Binary Ant Colony Optimization) generally outperform the other models in terms of accuracy. The BACO-KNN fault prediction model attains the accuracy of 96.39% surpassing the previous work.

The effect of Human Resource Management on employee Performance – A Systematic Literature Review

Purpose – Human resources management is considered the heartbeat of organizations and institutions in the field of business administration in particular. Good management ensures the retention of employees who are creative and skilled. This affects the organization’s productivity, profits, and competitive position in the market. Aims – This paper aims to develop a suitable systematic review on the research literature that has been undertaken to investigate how on human resource management influences employee performance within an organization. Growth in employee performance, through good management and its practices is an important factor that affects the organization and its production. Design/methodology/approach – This systematic literature review, analysed publications and articles published over the past two decades (2005–2023) on the human resources management in Northern Cyprus. Based on the comprehensive research analysis of 18 articles, employees are motivated to perform effectively through commitment, loyalty, discipline, innovation and self-learning. Their performance has been thoroughly investigated in numerous research papers. Findings – All hypotheses were supported by data collected from 18 research papers that showed that human resources management works to improve employee roles and job performance and human resources management is considered a means to enhance the relationship with employees and develop them. Limitations of the study – The research is limited to studies on human resources management that were done in Northern Cyprus. Originality/value – This systematic review of literature is significant because it presents insights on the importance of human resources management in the realms of an organisation.

An approach based on open research knowledge graph for knowledge acquisition from scientific papers

PurposeThis paper aims to curate open research knowledge graph (ORKG) with papers related to ontology learning and define an approach using ORKG as a computer-assisted tool to organize key-insights extracted from research papers.Design/methodology/approachAction research was used to explore, test and evaluate the use of the Open Research Knowledge Graph as a computer assistant tool for knowledge acquisition from scientific papers.FindingsTo extract, structure and describe research contributions, the granularity of information should be decided; to facilitate the comparison of scientific papers, one should design a common template that will be used to describe the state of the art of a domain.Originality/valueThis approach is currently used to document “food information engineering,” “tabular data to knowledge graph matching” and “question answering” research problems and the “neurosymbolic AI” domain. More than 200 papers are ingested in ORKG. From these papers, more than 800 contributions are documented and these contributions are used to build over 100 comparison tables. At the end of this work, we found that ORKG is a valuable tool that can reduce the working curve of state-of-the-art research.

Challenges for the development of sustainable SMEs in the cement industry: a SWARA–WASPAS approach

Purpose This study aims to examine the obstacles and approaches to achieving sustainable development in India’s cement solid and hollow brick production business, with a specific emphasis on incorporating the triple bottom line (TBL) concept into strategies for small and medium-sized enterprises (SMEs). Design/methodology/approach Using the step-wise weight assessment ratio analysis (SWARA)–weighted aggregated sum product assessment (WASPAS) approach, the study prioritized 11 economic, 9 environmental and 14 social sustainability indicators based on information collected from literature and expert opinions. Findings The study provides valuable insights into the difficulties encountered by SMEs while implementing strategies that focus on the TBL. By putting emphasis on the sustainability criteria, the key areas that require attention to promote sustainability get identified and addressed. Research limitations/implications The study’s focus on SMEs in this industry limits its generalizability. To have a more complete picture, future studies may include many areas. Practical implications The identified and prioritised sustainability characteristics help small and medium-sized firms (SMEs) design strategies to address sustainable development concerns. The research findings could also inform policymakers and regulatory bodies about the challenges faced by SMEs in the cement and brick production sector regarding sustainability. It could highlight the need for supportive policies and regulations to promote sustainable practices and incentivize SMEs to adopt the TBL approach. The paper can offer practical insights for SME owners and managers on integrating sustainability principles into their business strategies. Actionable recommendations and best practices for enhancing environmental performance, social impact and economic viability within the context of cement and brick production are outlined. Social implications TBL policies improve the sustainability and profitability of small and medium-sized firms (SMEs) and promote environmentally and socially responsible practices that benefit the industry and society. The research paper may facilitate greater engagement and collaboration among various stakeholders involved in the cement and brick production industry, including SMEs, larger corporations, government agencies, non-governmental organizations (NGOs) and local communities. This cooperative approach can encourage open communication, the establishment of trust and coordinated actions to tackle sustainability challenges, ultimately improving social cohesion and collaboration. Originality/value This study provides new and valuable insights by investigating the development of TBL strategies in SMEs in the cement solid and hollow brick manufacturing sector in India. The utilization of the SWARA–WASPAS technique brings novelty to research on sustainable development in this field.

A new technique for solving regular and singular coupled Burgers’ equation

The primary objective of this research paper is to introduce a novel technique known as the double ARA transform (DARAT) for effectively solving a broad spectrum of problems, encompassing both linear and nonlinear scenarios. This study specifically explores the application of DARAT to address the regular and singular one-dimensional coupled Burgers’ equations. Significant enhancements have been made to the original ARA transform to improve its precision and accuracy in handling linear problems. Additionally, DARAT has been seamlessly integrated with the well-established Adomian decomposition technique, which is renowned for its efficacy in solving nonlinear issues. The effectiveness of our proposed method is demonstrated through its remarkable ability to solve partial differential equations (PDEs), with the results clearly illustrated through graphical representations and detailed tables. These outcomes affirm the method’s robustness in deriving accurate solutions for both regular and singular coupled Burgers’ equations.

Analyzing the Effectiveness of Non-remote Monitoring Telemedicine Within the United States After 2019, Including Future Implications as a Healthcare Medium, Regarding Its Statistical and Analytical Disciplines: A Systematic Review

Telemedicine is the utilization of healthcare services remotely via numerous applications that connect the patient with a qualified physician. Telemedicine plays a vital role in providing accessible healthcare to individuals who are unable to do an in-person visit, and its involvement in healthcare is analyzed through the analytical/statistical lens, financial lens, and ethical lens. Telemedicine systems have demonstrated their potential to serve as a functional healthcare medium, but many barriers to an increase in its implementation and efficacy still exist after the COVID-19 pandemic. Despite the importance of telemedicine, knowledge of its implied efficacy and efficiency in providing healthcare is poor, and already existing research doesn’t address solutions to the barriers of telemedicine. The research aims to address this gap by doing a comprehensive, systematic literature review on the efficacy, barriers to implementation, practicality, and future implications of telemedicine’s utilization in the healthcare sphere. Furthermore, by adding a unique perspective on this topic and consolidating research data for the general healthcare field to utilize, this further addresses missing medical knowledge regarding telemedicine consultations. This research screened 737 different articles and papers to gather information regarding telemedicine and its efficacy. Results were filtered and screened using the PRISMA method to maintain a standard of high-quality, impartial, and accurate data throughout the research paper. Only the sources which pertained to the research question were chosen to be included in the paper. Trends were identified in the chosen articles, which were viewed by the contributors and referenced in the paper. Telemedicine has demonstrated profound evidence of benefits for both patients and healthcare administrations. However, concerns regarding its accessibility and efficacy remain. Suggestions are made for medical administrations and for public knowledge to provide solutions for these concerns.

Real-time edge computing design for physiological signal analysis and classification

Physiological Signals like Electromography (EMG) and Electroencephalography (EEG) can be analysed and decoded to provide vital information that can be used in a range of applications like rehabilitative robotics and remote device control. The process of acquiring and using these signals requires many compute-intensive tasks like signal acquisition, signal processing, feature extraction, and machine learning. Performing these activities on a PC-based system with well-established software tools like Python and Matlab is the first step in designing solutions based upon these signals. In the application domain of rehabilitative robotics, one of the main goals is to develop solutions that can be deployed for the use of individuals who need them in improving their Acitivities-for-Daily Living (ADL). To achieve this objective, the final solution must be deployed onto an embedded solution that allows high portability and ease-of-use. Porting a solution from a PC-based environment onto a resource-constraint one such as a microcontroller poses many challenges. In this research paper, we propose the use of an ARM-based Corex M-4 processor. We explore the various stages of the design from the initial testing and validation, to the deployment of the proposed algorithm on the controller, and further investigate the use of Cepstrum features to obtain a high classification accuracy with minimal input features. The proposed solution is able to achieve an average classification accuracy of 95.34% for all five classes in the EMG domain and 96.16% in the EEG domain on the embedded board.

IMPROVING STUDENTS’ ENGLISH SPEAKING SKILLS THROUGH THE GALLERY WALK TECHNIQUE

With the requirements of the curriculum outcome and also the workplace, English skills are increasingly receiving special attention. The ability to communicate in English fluently is especially thought to help candidates find a good job after graduation. This research paper is conducted with the aim of improving student’s speaking skills through the Gallery Walk technique. The activity provides an opportunity for students to be exposed to the language regularly, which can help them foster and develop pronunciation, vocabulary, grammar and fluency. The participants of the study are 36 first-year English major students at a university in Hung Yen. The data collection process was carried out during eight periods over two cycles. Research data collection tools are speaking tests, the action and questionnaires. Both quantitative and qualitative results have shown that students’ English-speaking ability has improved significantly in terms of vocabulary, grammar and pronunciation. Moreover, adopting the gallery walk technique also helps students not be afraid of being judged when speaking English and be able to communicate actively in the real world.