bluuebunny/crossref_metadata_2025 huggingface dataset:
Growth of Banana-Based Agribusiness in Indonesia
Authors: Haryono Haryono
Published: December 2024

This study examines the effects of market access, product innovation, and entrepreneurial experience on the growth of banana-based agribusinesses in Indonesia. Given the sector's significant potential in rural economic development, understanding the factors that drive agribusiness growth is essential. Using a quantitative approach, data were collected from 120 banana-based agribusinesses across various regions in Indonesia, with respondents rating each variable on a Likert scale of 1 to 5. Analysis was conducted using SPSS version 26, applying multiple regression to assess the significance and strength of each variable’s impact on business growth. Results indicate that market access, product innovation, and entrepreneurial experience each positively influence agribusiness growth, with product innovation emerging as the most significant predictor. These findings underscore the importance of market accessibility, continuous product innovation, and experienced entrepreneurship as key drivers of success in the agribusiness sector. This study provides actionable insights for policymakers and practitioners to enhance agribusiness performance through targeted support for market infrastructure, innovation, and entrepreneurial development.
Influence of IoT, Edge Computing, and Real-Time Analytics Systems on Optimizing Resource Management in the Indramayu Fisheries Industry
Authors: Utomo Bekti , Setiawati Rahmi , Vandika Arnes Yuli
Published: December 2024

The fisheries industry in Indramayu faces challenges in optimizing resource management due to inefficiencies and a lack of technological integration. This study examines the influence of the Internet of Things (IoT), Edge Computing, and Real-Time Analytics Systems on resource management optimization in the fisheries sector. Using a quantitative approach, data were collected from 150 respondents and analyzed with Structural Equation Modeling-Partial Least Squares (SEM-PLS 3). The results reveal that IoT has the most significant impact on resource management optimization, followed by Real-Time Analytics Systems and Edge Computing. The integration of these technologies demonstrates a synergistic effect, enabling real-time data collection, efficient processing, and actionable insights. These findings underscore the transformative potential of digital technologies in fostering sustainable and efficient resource utilization. Practical recommendations include investing in infrastructure, enhancing technical skills, and promoting technology adoption through policy support. This research contributes to the growing body of knowledge on digital transformation in resource-intensive industries.
Analysis of Content Innovation, Ease of Access, and Technology Support on Generation Z User Engagement on Educational Platforms in Indonesia
Authors: Judijanto Loso , Aldo Novian , Fildansyah Rully
Published: December 2024

This study examines the impact of content innovation, ease of access, and technology support on Generation Z user engagement with educational platforms in Indonesia. Employing a quantitative research approach, data were collected from 120 respondents using a structured questionnaire measured on a 5-point Likert scale. The Structural Equation Modeling-Partial Least Squares (SEM-PLS) method was used to analyze the relationships between the independent variables (content innovation, ease of access, and technology support) and the dependent variable (user engagement). The findings reveal that all three factors significantly and positively influence user engagement, with content innovation being the strongest predictor. These results underscore the importance of delivering innovative content, ensuring accessibility, and maintaining robust technology support to enhance user engagement. The study offers actionable insights for educational platform developers and contributes to the growing body of knowledge on digital education and user behavior, particularly in emerging markets such as Indonesia.
The Influence of Intergenerational Training, Information Technology, and Generational Conflict Management on Employee Engagement in a Jakarta Consulting Services Company
Authors: Wuryanti Lestari , Suhara Ade , Mayasari Nanny , Vandika Arnes Yuli
Published: December 2024

The rapid expansion of the crypto asset market presents significant challenges related to market transparency, this study examines the influence of intergenerational training, information technology adoption, and generational conflict management on employee engagement in a consulting services company in Jakarta. Using a quantitative approach, data were collected from 250 employees via a structured questionnaire and analyzed with SPSS version 25. The results reveal that all three factors significantly contribute to employee engagement, with intergenerational training being the strongest predictor, followed by information technology adoption and generational conflict management. The study highlights the importance of fostering collaboration across generations, leveraging technology for efficient workflows, and addressing generational conflicts to enhance workplace engagement. These findings offer actionable insights for organizations managing diverse workforces in similar contexts.
Bibliometric Insights into Women Entrepreneurship : A Global Perspective on Key Contributions and Challenges
Authors: Judijanto Loso , Arisanti Ivon
Published: December 2024

This study employs a comprehensive bibliometric analysis to explore the landscape of research on women's entrepreneurship using VOSviewer software. Through a series of visualizations, we examine the co-authorship networks, key thematic focuses, geographical distributions, and the temporal dynamics of the field from 2000 to 2022. Our findings reveal significant collaborative dynamics among scholars, with central figures acting as pivotal nodes in the academic network. Thematic analysis highlights "women empowerment," "SMEs," and "entrepreneurship" as foundational research areas, alongside emergent topics like "digital entrepreneurship" and "COVID-19," which respond to contemporary global challenges. Geographical visualization underscores the global reach and diversity of the research, with notable contributions from across various continents. The study’s temporal overlays demonstrate the field’s adaptability to shifting global economic and social contexts, particularly in response to the pandemic. These insights not only reflect the current state of women's entrepreneurship research but also suggest directions for future inquiry, emphasizing the need for enhanced international collaboration and adaptation to emerging global trends. This work contributes to the strategic development of women's entrepreneurship research, offering a scaffold from which to enhance academic collaborations and integrate emergent research themes effectively.
The Impact of Working Capital Management, Product Innovation, and Financial Management on MSME Business Sustainability in South Sulawesi
Authors: Syamsu Rijal  , Supriandi Supriandi
Published: December 2024

This study examines the impact of Capital Management, Financial Management, and Product Innovation on the sustainability of Micro, Small, and Medium Enterprises (MSMEs) in South Sulawesi, Indonesia. Amid increasing economic challenges, MSMEs must adopt effective financial and innovation strategies to achieve long-term sustainability. A quantitative approach was employed, using data from 255 MSMEs and analyzed through Structural Equation Modeling with Partial Least Squares (SEM-PLS). The findings indicate that all three factors positively and significantly affect MSME sustainability, with Financial Management showing the strongest influence, followed by Capital Management and Product Innovation. These results suggest that MSMEs need to balance financial planning, efficient capital management, and innovation to foster resilience and competitiveness. This study contributes to the literature by applying the Resource-Based View (RBV) theory to MSME sustainability, providing actionable insights for MSME managers and policymakers in resource-constrained environments.
Effect of Green Transformational Leadership and Green Knowledge on Environmental Performance with Green Creativity as Intervening Variable in Tourism Villages in DIY
Authors: Hidayati Nida Urrahma , Effendi Mohamad Irhas , HC R Heru Kristanto
Published: December 2024

This study aims to examine the effect of green transformational leadership and green knowledge on environmental performance of tourism village. It also examine the mediating of green creativity on their relationship. Data was collected from 69 tourism village in the Special Region of Yogyakarta (DIY). This study used primary data collected through closed-ended questionnaires that was distributed via google forms (online) and directly (offline). The data itself were analyzed using PLS. The results show that green transformational leadership and green knowledge have positive effect on green creativity and environmental performance on tourism village. Furthermore, green creativity is also found to have mediating effect that significant between both green transformational leadership and environmental performance, also between green knowledge and environmental performance on tourism village. The main implication of this study is that tourism village need to foster both green transformational leadership and green knowledge to promote sustainability, ultimately leading to improved environmental outcomes.
A Bibliometric Study on the Impact of Social Media Use on Mental Health in a Socio-Cultural Context
Authors: Judijanto Loso , Setiawati Rahmi , Bunyamin Ilham Akbar
Published: December 2024

The growing prevalence of social media has sparked significant academic interest in understanding its impact on mental health. This bibliometric study explores the relationship between social media use and mental health within various socio-cultural contexts, highlighting prevailing themes, trends, and gaps in the literature. Using data from major academic databases, the study identified key research areas, including the association between social media and mental health issues such as depression, anxiety, and addiction, as well as the role of interventions in mitigating these impacts. The findings reveal a strong focus on the negative effects of social media, particularly among adolescents and university students, and emphasize the importance of cultural factors in shaping these outcomes. While interventions and policy recommendations are increasingly being explored, gaps remain in understanding long-term effects, culturally diverse contexts, and potential positive outcomes of social media use. This study underscores the need for continued, multidisciplinary research to inform culturally sensitive practices and policies that address the complexities of social media's impact on mental health.
Uluslararası Göç ve Siyaset Neoliberalizm, Popülizm, Göçmen Karşıtlığı
Authors: Uygur Mehmet Nazım
Published: December 2024

Göç konusu, çağdaş toplumlarda tartışmalı bir konu haline gelmeyi ve dünya çapında siyasi gündemi şekillendirmeyi sürdürmektedir. Bu kitap, göçmen karşıtı duyguların ve politikaların hem Anglosakson hem de Kıta Avrupası üzerindeki etkilerini inceleyerek, iki gelenekteki pratiklerin karşılaştırmalı bir analizini sunmaktadır. Kitap bunu yaparken göçün, siyasi, sosyal ve ekonomik boyutlarına inerek, bu iki gelenekteki göçmen karşıtı hareketlerin nedenler, sonuçlar, benzerlikler ve farklılıklarına ışık tutmayı amaçlamaktadır. Kitap, göçmen karşıtı anlatıların kamuoyu, siyasi söylem ve politika oluşturma üzerindeki etkisini analiz etmek için kapsamlı bir bilimsel literatür incelemesinden yararlanmıştır. Popülist aşırı sağ partilerin yükselişine ve göçmen karşıtı duyguları körüklemedeki rollerine özel önem verilmiştir. Bu amaçla kitapta neoliberalizm, küreselleşme ve bunun yarattığı göç ve eşitsizliklere odaklanılarak bunların günümüz göç krizlerine ve yabancı düşmanlığına etkileri de tartışılmıştır. Çalışmada göçmen karşıtlığının siyasete etkisini belirleyebilmek amacıyla Dünya Değerler Araştırması (WVS), Avrupa Değerler Araştırması (EVS) ve Küresel Parti Araştırması (GPS) verileri ampirik olarak analiz edilmiştir. Kitap, ekonomik şikayetler, kültürel kaygılar, güvenlik endişesi ve ırksal tehdit algısı dahil olmak üzere göçmen karşıtı hareketlerin büyümesine katkıda bulunan temel ajitasyon unsurlarını tanımlamıştır. Ek olarak, ajitasyon araçları olarak ele alınan medyanın ve siyasi retoriğin kamuoyunu şekillendirme ve göçmen karşıtı anlatıları sürdürmedeki rolü vurgulanmıştır. vi Sonuçlar, göçün bir kriz halini almasında neoliberal küreselleşmenin etkili olduğunu göstermektedir. Neoliberal düzenin oluşturduğu eşitsizliklerin ve yarattığı endişelerin günah keçileri olarak göçmenlerin işaret edilmesinde medya ve aşırı sağın aracılık rolü üstlendiği tespit edilmiştir. Öte yandan sosyal devlet anlayışının var olduğu Kıta Avrupası ülkelerinde, neoliberal düzenin tesis edildiği Anglosakson ülkelerinden farklı olarak göçmen karşıtı partilerin anaakım olamadığı da ortaya konmuştur. Fakat söz konusu partiler anaakım partileri etkileyebilmiş ve anaakım siyasette göçmen karşıtı partilerin popülist retoriğini kullanmalarına yol açabilmiştir. Sonuçlar ayrıca ekonomik şikâyet, güvenlik kaygısı, kültürel tepki ve ırksal tehdit algısı gibi ajitasyon unsurlarının aşırı sağ partiler ve medya gibi ajitasyon araçları aracılığı ile göçmen karşıtlığı oluşturmada ve böylece aşırı sağ partilere desteği arttırmada etkili olduğunu göstermiştir. Kitap böylece göçmenlere yönelik düşmanca tutumun dinamiklerini ortaya koymuş ve bu anlayışın ortadan kalkması için birtakım önerilerde bulunmuştur.
Din Eğitimi ile Kadın Algısı İlişkisine Yönelik Bir Araştırma
Authors: Aşık Ev Hacer , Ev Halit , Kartal Burak , Mollaoğulları Batuhan Fatih
Published: December 2024

Betimsel nitelikli tarama modeli ile gerçekleştirilen bu araştırmanın amacı kadına yönelik olumsuz algıda geleneksel kodların ve olumsuz din anlayışının etkisinin ne olduğu; bölüm, sınıf ve cinsiyet değişkenlerinin kadın algısını nasıl etkilediğini ortaya çıkartmaya çalışmaktır. Bu araştırma ile kadına yönelik olumsuz algının nereden kaynaklandığı ve etkilendiği, iddia edildiği gibi dini temellerinin bulunup bulunmadığı ortaya konmaya çalışılmıştır.
Araştırmanın evrenini MCBÜ İlahiyat Fakültesi, MCBÜ İktisadi ve İdari Bilimler Fakültesi ve Balıkesir Üniversitesi İlahiyat Fakültesi öğrencileri oluşturmaktadır. Örneklemini de 2019-2020 eğitim-öğretim yılı güz döneminde söz konusu fakültelerde öğrenime devam eden ve kota örneklemesi yöntemiyle seçilmiş olan 612 öğrenci oluşturmuştur.
Araştırmanın öncelikle, toplumsal cinsiyete dayalı ayrımcılığa dikkat çekmeye çalışarak bu konuda bir farkındalık oluşmasına ve bilinç düzeyinin yükselmesine, ikinci olarak da kadının toplumdaki değer ve konumunun iyileştirilmesi yönünde de katkı sağlayacağı beklenmektedir. Ayrıca olumsuz kadın algısının iddia edildiği gibi dini temellerinin bulunup bulunmadığı anlaşılmaya çalışılmakta ve böyle bir ilişki var ise de din eğitiminin niteliğinin iyileştirilmesi yönündeki çalışmalara da vesile olması düşünülmektedir. Son olarak, çalışmanın toplumda din olarak kabul edilen oysa dinin özü ile hiçbir ilgisi olmayan yanlış bilgilerin düzeltilmesine de katkı sağlaması beklenmektedir. Çalışmanın önemli bulgularından birisi ise daha bilimsel temellere dayanan din eğitiminin kadınlara yönelik olumsuz algıları azaltmaya yardımcı olması ihtimalidir.
Mastering IB Assessment: Strategies for Excellence in the Diploma Programme
Authors: Shukur Inji
Published: December 2024

The International Baccalaureate (IB) Diploma Programme (DP) is an extraordinary educational journey that equips students with the skills, knowledge, and values needed to excel in both academia and life beyond school. However, the path is not without its challenges. With rigorous assessments, demanding coursework, and the responsibility of balancing extracurricular activities, students can often feel overwhelmed by the expectations of the program. This book, Mastering IB Assessment: Strategies for Excellence in the Diploma Programme, is designed to be your companion through this journey. It oﬀers practical advice, proven strategies, and insights that will help you navigate the complex world of IB assessments while fostering your personal and academic growth. From tackling exam preparation to completing the Extended Essay (EE) and fulfilling Creativity, Activity, Service (CAS) requirements, this guide provides tools to help you achieve excellence in every area of the IB DP. At the heart of this book is the belief that the IB is about more than just academic success. The program encourages students to develop critical thinking, resilience, and a global perspective, preparing them to become thoughtful, engaged citizens of the world. The strategies outlined in this book will help you master the challenges of the IB DP while developing the lifelong skills you need to succeed in higher education and beyond.
Proposed solutions to increase the reliability and goodness of fit of the Thurstone method
Authors: Dębicka Joanna , Mazurek Edyta , Ostasiewicz Katarzyna
Published: December 2024

The Thurstone method is a method of aggregation of preferences that leads to ordering objects at an interval scale, in contrast to other methods of aggregation, the application of which results in obtaining the ordinal scale only. However, we demonstrate that the interval scale obtained by means of the Thurstone method is not fully reliable, as it is strongly susceptible to the problem of irrelevant alternatives, i.e., the order of two objects might be dependent on whether there is or not a third, completely independent object in the studied collectivity.
The other issue examined in the paper is the formula that is to be minimised in the Thurstone method. Thurstone proposed a formula easy to be minimised with tabularised values of normal distribution. However, today’s calculation powers of computers make it possible to minimise another formula, which allows a better fit of observed frequencies to the predicted ones, and makes it possible to avoid the problem with empirical frequencies close to 1.
The aim of the paper is to propose two improvements to the Thurstone method. The first one involves the application of the rule of thumb to the minimal spacing (in terms of standard deviations), below which the ordering of objects cannot be regarded as reliable, and the use of the method of empirical examining of the stability of order. The second of the proposed improvements consists in minimising a formula other than the original one, especially in the cases where empirical frequencies reach very high values.
Próba reprezentatywna – potrzeba i propozycja definicji
Authors: Szreder Mirosław
Published: December 2024

A ‘representative sample’ is one of few terms used in statistical inference which do not have a precise and commonly recognised definition. The need for such a definition is less nagging in sciences and natural sciences, where empirical experimental research has exploratory objectives, and thus rarely requires obtaining representative samples. On the other hand, descriptive and confirmatory objectives of social sciences and economics necessitate samples on the basis of which it would be possible to make generalisations of relevant estimates for a given population and assess their errors.
The aim of this paper is to discuss the role of a representative sample in scientific and statisti-cal inference, and additionally to propose its definition and show its specificity in comparison to non-random samples, whose representativeness is limited to some specified variables only. In the proposed definition, the author focuses on the consistency of the sample structure with the structure of the population and the possibility of making inference in which estimates obtained from the sample have numerical error values assigned to them. It is also argued that samples which show convergence of the distributions of only some characteristics with their population distributions should be called ‘representative samples in terms of specified variables’ instead of just ‘representative samples’. Moreover, it is demonstrated that the category of a random sample which is inseparably linked to statistical inference does not need any equivalents.
Cloud Computing Revolution: Enhancing Teaching and Learning in South African TVET Colleges
Authors: Moloja Dina
Published: December 2024

This theoretical paper explores the adoption of cloud computing framework to enhance teaching and learning in South African Technical and Vocational Education and Training (TVET) colleges. These institutions face traditional educational barriers, including limited access to resources and infrastructure, and financial constraints. Cloud-based technologies offer solutions that are flexible, scalable, and costeffective, enabling TVET colleges to overcome these challenges. The study investigates the current state of cloud computing adoption in South African TVET colleges, highlighting key challenges and opportunities. Guided by Everett Rogers' Diffusion of Innovations theory, which explains how new ideas and technologies spread within a culture, this paper identifies factors that influence technology adoption. A thorough analysis reveals the potential of cloud computing to promote collaborative learning, improve access to educational resources, and support innovative teaching methods. The findings emphasize the importance of strategic planning using the Diffusion of Innovations stages to fully leverage the benefits of cloud computing in South Africa's educational sector. This paper contributes to knowledge and literature on using Diffusion of Innovations as a lens for cloud computing adoption in TVET colleges.
Bayesian Convolutional Neural Network for Detection of Cataract Ocular Disease
Authors: Michael Taryn , Nimy Eli , Nyamane Seipati , Olusanya Micheal
Published: December 2024

Ocular disease diagnosis using fundus images is one of the most challenging tasks in the medical field but is necessary for early screening and treatment. This manual process is extremely time consuming, complex and error prone. Currently there is an increased demand for the utilization of deep learning techniques for the automated detection of ocular diseases, especially for use on biomedical images. However, these conventional techniques such as Deep Neural Networks and Convolutional Neural Networks (CNNs) present some challenges, such as its tendency to overfit on smaller datasets and its inability to measure the uncertainty of its predictions. This is crucial in the medical field to determine the reliability of the predictions made by the automated systems. Thus, in this paper a Bayesian Convolutional Neural Network (BCNN) is implemented for Cataract disease detection to provide the reliability (uncertainty) estimates sought after in the medical field. The BCNN is benchmarked against the implementation of a standard Convolutional Neural Network. The BCNN model was compiled using the negative log-likelihood loss function and an Adam optimizer with a learning rate of 0.001 trained over 100 epochs. The CNN was compiled similarly except for the loss function which was the categorical cross entropy loss. The test results indicate that the BCNN model achieved 93.16% accuracy, while the standard CNN achieved an accuracy of 95%. Both models achieved comparable accuracy results to existing studies that utilized CNN architectures to predict ocular diseases. Although the CNN gave a slightly better accuracy, it cannot account for the uncertainty measurements of its predictions, would be more useful for ophthalmologists.
The Face of Surveillance: A Systematic Review of Ethical and Legal Implications in Public Facial Recognition
Authors: Beya Boanerges , Hanslo Monique , Hanslo Ridewaan
Published: December 2024

Due to its use of biometric data, which can be abused to exploit people, facial recognition technology (FRT), which is becoming more and more integrated into our daily lives, raises serious ethical and legal problems. To determine these consequences for the usage of FRT in public areas, this research conducts a systematic literature review. The public is frequently harmed by FRT, as seen by the recurrent themes of privacy, bias, and consent that emerged from the analysis of twenty different ethical and legal implications derived from the synthesized literature. Furthermore, the study shows that research on these topics come primarily from a small number of countries, none of which are African. This therefore provides a gap for future research into the potential
implications of using FRT in African communities. The findings aim to inform policymakers to protect individual rights and ensure that FRT's advancement aligns with societal values and human rights.
Bibliometric Analysis of Ethics in Embedded and Mobile Systems
Authors: Malele Vusumuzi , Sekwatlakwatla Sello Prince , Kiefer Tibo
Published: December 2024

When it comes to commonplace gadgets like cell phones, automobiles, household appliances and medical equipment, embedded systems ethics place a higher priority on privacy, security, dependability and possible abuse. The desire for convenience in family life has risen because of its comfort, control and safety. Smart houses alter interior areas with computers and artificial intelligence (AI), while embedded technologies provide minimal power consumption and many functionalities. As a result of social and technical improvements, smart homes and embedded systems are becoming more and more popular around the world and developing countries are adopting this technology, which aligns with ethics. However, the incorporation of ethics in embedded systems and mobile systems tends to be ignored in Africa. The purpose of this study is to investigate the prevalence of ethics in embedded and mobile systems, looking at the African context. The data was collected from the Scopus database and the Web of Science between 2002 and 2023. To recognize the trends in ethics in embedded and mobile systems, bibliometric analysis is used to judge the current situation and development trends in the African region. The results revealed the keywords with the highest occurrence and countries and affiliations that are contributing to the ethics in embedded and mobile systems. Additionally, embedded and mobile systems have been identified as an active area of research, experiencing an annual growth rate of 5.37% in Africa, with 30% of contributors being international co-authors. The results of this study will facilitate an understanding of the progress and trends in embedded and mobile systems for researchers interested in understanding them from an African perspective.
A Comprehensive Review of Multi-Domain Sentiment Analysis: Techniques, Models and Future Directions
Authors: Naidu Gireen , Zuva Tranos , Sibanda Elias
Published: December 2024

The increase in user-generated content on online platforms has underscored the significance of advanced sentiment analysis methods that can effectively function across various fields. Sentiment analysis, a component of natural language processing (NLP) focuses on recognising and organisi ng subjective information within text data. While there have been strides in domain-specific sentiment analysis, developing models that can excel across diverse domains remains a notable challenge. This comprehensive review of 19 research papers aims to summarise the current status of research on sentiment analysis spanning multiple domains examining the strategies, models and datasets employed to enhance performance across various areas. Techniques like domain adaptation, including transfer learning and adversarial training have shown promise by refining trained models such as BERT with target domain data thereby improving their capacity to generalise across domains. The study also sheds light on future research directions concerning domain shift, feature variations and lexical and semantic aspects to optimise multi-domain sentiment classification.
The Developments and Challenges in Agriculture Towards the Adoption of Smart Irrigation Technologies: A Review of the Most Cited Literature
Authors: Kgopa Alfred , Munchusi Bessie
Published: December 2024

This study critically reviews the top 10 most widely cited publications on farmers' use of smart irrigation systems. The systematic literature review was conducted through extracting data using a python code. The python algorithm was intended to use the CrossRef API to retrieve 50 academic publications on a related subject of "adoption of smart irrigation technologies by farmers". After the 50 journals were extracted, we manually selected the top 10 papers based on highest citation counts, recent publications, and talks about the related topic. The aim was to learn about the latest trends and technological advancements and in identify key themes that encourages the adoption of smart irrigation technologies. It was found that smart irrigation solutions such as IoT and AI, incorporate sensors, controls, and algorithms, to improve water management and crop yields by delivering accurate water volumes at the right moment. It was also highlighted that in the face of global agricultural concerns such as water shortages and climatic variability, these technologies are critical to sustainable farming practices. This review's findings will inform future research initiatives and policy decisions aimed at improving agricultural water efficiency, food security and sustainability.
CNN Defect Detection Using Image Classification Falls Short in Assembly
Authors: Smit Janré , Burger Leon E. , Schutte Corne S. L.
Published: December 2024

The use of Convolutional Neural Networks (CNNs) for image classification is wellestablished in defect detection within manufacturing environments. However, their application in assembly processes remains underexplored. This study investigates the effectiveness of using relatively smaller CNNs for detecting assembly defects by testing multiple existing pre-trained CNNs and a custom CNN on a dataset of model train seat assembly images. The dataset includes common assembly defects such as missing, rotated, and swapped parts. Despite implementing various data augmentation and image processing techniques, such as cropping, normalization, and image transforms, and making several modifications to the models, the existing techniques struggled to accurately predict defects while providing the correct rationale for their predictions. The Grad-CAM analysis revealed that the models often focused on irrelevant features, highlighting the challenges of defect detection in complex assembly environments. These findings indicate the need for more robust machine learning approaches capable of handling high levels of noise and variations typical of realworld assembly conditions. This study underscores the limitations of current CNN-based defect detection methods in uncontrolled assembly settings and the necessity for further research to develop more reliable solutions.
Integrating IoT and AI for Precision Agriculture: Enhancing Water Management and Crop Monitoring in Small-Scale Farms
Authors: Monchusi Bessie Baakanyang , Kgopa Alfred Thaga , Mokwana Tlhokaboyo Innocentia
Published: December 2024

Water management is a major issue in agriculture, particularly for small-scale farms that frequently confront resource limits and changing environmental circumstances. Implementing a smart irrigation system using IoT devices has various advantages but also presents some problems. The purpose of the study was to create a smart irrigation system that uses IoT sensors and machine learning algorithms to optimize water usage in small-scale farms, decreasing waste while increasing crop output. The suggested system uses IoT sensors to monitor soil moisture and meteorological conditions, with data processed in real time via edge computing. Machine learning methods, notably Decision Trees and Support Vector Machines (SVMs), are trained to anticipate optimal irrigation schedules using gathered data. The system design incorporates connection infrastructure that enables seamless data transmission and real-time decision-making. Preliminary field studies on a small-scale tomato farm showed a 25% boost in crop output and a 35% reduction in water usage while using the smart irrigation system. The results illustrate the efficacy of merging the Internet of Things and machine learning. The smart irrigation system developed in this study efficiently optimizes water utilization in agriculture, making it a feasible alternative for small-scale farmers confronting water constraint. This study advances the field of precision agriculture by proving the practical use of IoT and machine learning in smart irrigation systems as a main contribution.
Lightweight Scheme for Security and Privacy in Smart Grids Applications
Authors: Khumalo Philani , Tsoeu Mohohlo Samuel , Moloi Katleho
Published: December 2024

In the evolving landscape of smart grid technology, the need for robust, efficient, and scalable security solutions is paramount. This paper presents a lightweight cryptographic scheme based on the Nth Degree Truncated Polynomial Ring (NTRU) designed to enhance security and privacy in smart grid applications. Unlike traditional cryptographic methods that our proposed NTRU-based scheme offers a quantum-resistant solution with minimal overhead, making it ideal for deployment in resource-constrained environments such as smart meters and distributed sensors. The scheme provides strong protection against various cyber threats, ensuring data confidentiality, integrity and authenticity while maintaining high operational efficiency. Through comprehensive analysis and comparison with existing schemes, we demonstrate the effectiveness of our approach in balancing security with the practical demands of smart grid infrastructure. Our findings indicate that the NTRU-based scheme not only meets the stringent security requirements of smart grids but also preserves user privacy, making it a viable solution for future- roofing smart gridncommunications against emerging threats.
Mönster för arbete
Authors: Axelsson Jonas
Published: December 2024

I denna essä presenteras arkitekten Christopher Alexanders resonemang om mönster för arbete och arbetsliv, men också för samhället generellt. Alexanders idéer har fått genomslag på vitt skilda områden – bland annat inom programmering, och hans tankar om mönster har varit viktig för Wikipedias utveckling. Dock har inte hans tankar om arbete och arbetsliv blivit särskilt uppmärksammade tidigare.
Opportunities and challenges with the protection of ancient mining sites in mountain landscapes: A case study of the Kopaonik
Authors: Marić M.
Published: December 2024

The remains of ancient mining activities represent a significant part of Serbia's archaeological sites in the mountain landscapes, which are not yet officially treated as cultural heritage. This type of assets poses a significant challenge for cultural heritage protection services, as it requires cooperation between experts for the protection of natural and cultural values and other stakeholders, which is not yet established. In addition, the concept of mining landscapes is not recognized in current legislation, which further complicates the legal protection of the remains of ancient mines, which are recognized by scholars as an essential segment in the interpretation of historical processes of significance, such as Roman imperialism in the Balkans. Against this background, the paper presents the decades of archaeological research at Kopaonik, which has led, among other aspects, to an attempt to establish a uniform practice of treating ancient mines, together with settlements and associated infrastructure, as an integral part of the mountain landscape, despite the absence of any legal regulation. The study examines the challenges associated with the formal-legal preservation of sites with historic mining, taking into account the possibility of permanent destruction. Finally, an outlook is given on the future of the protection of (pre)historic mines in Serbia as an important element of the country's geocultural resources.
Trigonometric approximation of periodic functions in Morrey spaces using matrix means of their Fourier series
Authors: Jafarov Sadulla
Published: December 2024

We examine the generalized methods of summability of Fourier series of functions belonging to Morrey spaces L p,l , 0 < l ≤ 2, 1 < p < ∞. In this study, the approximation of functions by matrix means in terms of the continuity modulus in Morrey spaces L p,l , 0 < l ≤ 2, 1 < p < ∞, is investigated.
Council
Authors: Xygka A.
Published: December 2024

This overview highlights the political agreement reached by ECOFIN on the ViDA package.
Explorando los predictores de éxito en los Cursos en Línea Masivos y Abiertos (MOOC)
Authors: Aznar-Díaz Inmaculada , Ayllón-Salas Patricia , Fernández-Martín Francisco D. , Ramos-Navas-Parejo Magdalena
Published: December 2024

Los Cursos en Línea Masivos y Abiertos (MOOC) desempeñan un papel importante en la equidad educativa y el aprendizaje permanente, promoviendo un aprendizaje sin barreras de entrada, limitaciones de tiempo, o restricciones geográficas. En consecuencia, el número de matrículas de los MOOC es elevado, así como su índice de abandono. De hecho, la tasa media de finalización con éxito suele ser inferior al 10 %, lo que hace evidente la necesidad de identificar cuáles son los factores que estimulan el abandono temprano. La presente investigación tuvo como objetivo analizar hasta qué punto las competencias sociales y emocionales, el estrés percibido, las expectativas, y la satisfacción predicen la finalización del MOOC. Se adoptó un diseño metodológico ex post facto en el que 416 estudiantes cumplimentaron la Escala de Aprendizaje Social y Emocional, el Cuestionario de Datos Sociodemográficos, el Cuestionario de Expectativas, la Escala de Estrés Percibido y el Cuestionario de Satisfacción. Asimismo, se recogieron datos sobre la finalización con éxito del MOOC de cada uno de los participantes. Posteriormente, se construyeron cinco modelos mediante el análisis de regresión logística binomial. A pesar de que la satisfacción demostró ser el predictor más robusto de la finalización del curso, las competencias sociales y emocionales, el estrés percibido, y las expectativas también obtuvieron resultados significativos. Este estudio constituye la única investigación hasta la fecha que ha explorado la capacidad predictiva de estas variables, ofreciendo una nueva perspectiva sobre los predictores del éxito en los MOOC.
Evaluación del uso y aceptación de apps móviles en educación superior mediante el modelo TAM
Authors: León-Garrido Antonio , Gutiérrez-Castillo Juan Jesús , Barroso-Osuna Julio Manuel , Cabero-Almenara Julio
Published: December 2024

El uso constante de la tecnología, los dispositivos y las aplicaciones móviles (apps) ha desencadenado un auge sustancial y de gran importancia en las industrias de las apps y la tecnología. Por estos motivos surgió la necesidad de estudiar y comprender profundamente el impacto y la adopción de las apps móviles por parte de los estudiantes de magisterio, quienes son los futuros docentes. Para abordar esta necesidad, se llevó a cabo una investigación utilizando un cuestionario de aceptación de las apps basado en el Modelo de la Aceptación Tecnológica diseñado y validado para este estudio. La investigación involucró a un total de 205 estudiantes matriculados en la asignatura de Tecnologías de la Información y Comunicación Aplicadas a la Educación del Grado de Educación Primaria. Los datos se recogieron mediante un cuestionario validado a través del análisis factorial exploratorio y confirmatorio en base al Modelo TAM. Los resultados revelaron percepciones altamente positivas de las apps por parte de los estudiantes, cuya media fue de 4.4 sobre 5 puntos y una fiabilidad del 94.5 %. Esto respalda la fuerte repercusión de las apps móviles para el aprendizaje de un contenido en los contextos universitarios. En conclusión, las percepciones altamente positivas de los estudiantes indican que las apps deben integrarse en su formación. Esta integración no solo facilita el aprendizaje de contenidos específicos, sino que también promueve el desarrollo de nuevas competencias clave y diversas habilidades, esenciales para la formación de los futuros docentes.
Escala de autoevaluación de competencias docentes en enseñanza virtual: Un estudio sistemático de diseño y validación
Authors: Reyes-Vásquez Maynor Noel
Published: December 2024

El Sistema de Educación Superior de Honduras carece de instrumentos que evalúen diversos constructos asociados a la modalidad a distancia en su expresión virtual los cuales se constituyan como modelos de evaluación encaminados al monitoreo y aseguramiento de la calidad en esta modalidad. Este estudio estuvo orientado a diseñar un instrumento que reuniera las propiedades psicométricas necesarias para la medición válida y confiable de las competencias en enseñanza virtual del profesorado universitario, durante el año 2023. Para este fin se empleó un enfoque de investigación mixto, con un mayor peso cuantitativo. La muestra fue de tipo no probabilística, por conveniencia y estuvo compuesta por 650 profesores universitarios de la UNAH, UPNFM y EAP Zamorano. La Escala de autoevaluación de competencias docentes en enseñanza virtual (ECODEV) fue construida mediante revisión sistemática de la literatura bajo tres factores teóricos: competencias pedagógicas, tecnológicas y de gestión y manejo del curso. Los hallazgos ratificaron que el constructo en medición se compone de estos factores con un total de 49 ítems. El modelo factorial de la ECODEV corresponde a un modelo jerárquico y es explicado por una varianza total acumulada de 0.66, un Ω total de 0.99 y con índices de ajuste CFI = 0.999, RMSEA = 0.043 y SRMR = 0.045. En conclusión, la ECODEV posee una calidad psicométrica satisfactoria por lo que aporta una robusta y pertinente información sobre su constructo medible en profesores universitarios en el contexto hondureño.
Conectados fuera, desconectados dentro. Las redes sociales en la formación inicial docente
Authors: Marcelo-Martínez Paula , Yot-Domínguez Carmen , Yanes Cabrera Cristina
Published: December 2024

Las redes sociales se han convertido recientemente en espacios privilegiados en los que los docentes comparten información e intercambian recursos y materiales, así como se relacionan, colaboran y crean comunidad. En este artículo nos ha interesado conocer si los futuros profesores utilizan las redes sociales para su aprendizaje y desarrollo, identificar los motivos para su uso y analizar posibles diferencias en ellos. Para responder a estos objetivos, diseñamos y validamos un cuestionario de 33 ítems que fue respondido por 231 profesores en formación de Educación Infantil, Primaria y Secundaria matriculados en 10 centros de estudios universitarios o universidades españolas públicas y privadas. Los resultados evidencian que hay redes sociales que los docentes en formación dicen no utilizar nunca en un porcentaje alto como Linkedin, Facebook, TikTok o X (Twitter), mientras que otras redes sociales como Instagram o YouTube son utilizadas de forma continua. Los docentes en formación utilizan las redes con tres objetivos principales: encontrar recursos y personas para aprender, como medio para su aprendizaje académico y como herramienta para obtener apoyo mutuo. Encontramos diferencias destacables en relación con la edad y el nivel educativo para el cual se preparan, siendo los docentes jóvenes que cursan un Grado quienes perciben más positivamente los motivos que aquellos con mayor edad que estudian un Máster. Se concluye destacando la necesidad de integrar en los programas de formación inicial docente el conocimiento y uso de las redes sociales como herramientas útiles para los docentes conectados del siglo XXI.
Modelo de competencias para el aprendizaje online en educación superior: un análisis bibliométrico y revisión sistemática
Authors: Garcés Gonzalo , Bastías Elena
Published: December 2024

Con el auge de la educación online, las universidades buscan optimizar la experiencia de los estudiantes a distancia. Para ello, es crucial desarrollar competencias clave en los futuros profesionales, como habilidades transferibles, regulación emocional, desarrollo profesional, autogestión y autoeficacia. La comprensión del impacto del entorno online en el compromiso es fundamental para la implementación exitosa de programas online. Este artículo presenta una revisión sistemática de la literatura y un análisis bibliométrico de 781 artículos, explorando tendencias en publicaciones, revistas de alto impacto, países, instituciones y análisis de palabras clave con VOSviewer. Se analiza el estado actual del arte y las últimas tendencias educativas para impulsar el aprendizaje online. Finalmente, se propone un modelo que integra los principales conceptos del mapa de coocurrencia de VOSviewer en el contexto del aprendizaje online en educación superior para estudiantes graduados. Este marco ofrece una representación concreta para integrar las herramientas y tecnologías del aprendizaje online en la educación superior. Además, este marco será fundamental para comprender las habilidades necesarias en la educación en línea, especialmente la reflexión crítica y las competencias profesionales. Combina conceptos teóricos innovadores y ofrece una visión prometedora para el futuro de la educación. Si bien el e-learning presenta un gran potencial, es necesario abordar sus limitaciones y trabajar para asegurar que todos los estudiantes tengan las mismas oportunidades de desarrollo en este entorno educativo en constante transformación.
Understanding ChatGPT adoption in universities: the impact of faculty TPACK and UTAUT2
Authors: Alzahrani Abdulaziz , Alzahrani Amal
Published: December 2024

The objective of the field of technology known as artificial intelligence (AI) is to create intelligent devices that can perform tasks that have traditionally required human intelligence. ChatGPT is a program based on AI that provide virtual instructors and personalized learning environment for students. It raises the bar for top performers by presenting cutting-edge information and encouraging intellectual development. This study aimed to investigate the significance of instructors' Technological Pedagogy Content Knowledge (TPACK) to determine the intention to use ChatGPT in the light of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. The methodology of the study was a quantitative approach and the data was collected from 569 male and female instructors in Saudi universities. The data was analyzed by Path analysis and Smart PLS. The results of the study showed that Effort Expectancy, Social Influence, Hedonic Motivation, and Information Quality did not have a significant influence on Behavioral Intention. However, Facilitating Condition, Learning Value (negatively), and Privacy Risk have significant effects on Behavioral Intention. Moreover, there was a significant moderating role of Instructors' TPACK on the relationship between Privacy Risk and Behavioral Intention. The results shed a light on the effect of instructors’ TPACK and the lack of the relation among the three knowledge. Instructors’ TPACK should be improved with professional development programs in order to adapt a positive intention of using ChatGPT in Saudi universities. Universities are recommended to facilitate sufficient support and resources for the instructors to emerge new technology in their teaching.