bluuebunny/crossref_metadata_2025 huggingface dataset:
Applications of Human-Computer Interaction in the Field of Cultural Heritage Preservation
Authors: Wang Benxuan
Published: November 2024

The development of digital technologies has opened up some possibilities for practices across various fields, while the discipline of human-computer interaction has introduced new paradigms that enable humans to engage with digital technologies more conveniently. An increasing number of disciplines are seeking to intersect with the field of human-computer interaction, continuously advancing technology and exploring new research areas. This paper aims to assess the current applications of human-computer interaction technologies in the field of cultural heritage preservation and to provide guidance for potential future developments. To this end, this paper conducts a literature review to analyze and discuss the research progress in relevant academic journals. This paper specifically discusses three mainstream applications of human-computer interaction in the field of cultural heritage preservation: heritage information collection and preservation, restoration and display, and gamification. It analyzes the current research progress and key case studies for each application. Studies have shown that the introduction of human-computer interaction technologies in cultural heritage preservation primarily differs from traditional research in terms of public participation. The project cases documented in the literature mainly focus on conceptual designs. The conclusion of the article provides a summary of the entire text and offers an outlook for future developments.
A Review of Humor Recognition Research
Authors: Zhou Xiang
Published: November 2024

Abstract. Humor recognition is a popular research area in Natural Language Processing (NLP), with the fundamental goal of detecting whether humor is present. With the rapid development of artificial intelligence and the growing demand for human-computer interaction, humor recognition has broad applications in areas such as social media analysis, human-computer interaction systems, and intelligent question-answering assistants. However, due to the highly subjective and complex nature of humor, teaching computers to understand and recognize humor in a manner similar to humans is an exceptionally challenging task. This paper reviews the major research progress in the field of humor recognition and the construction of humor corpora. It discusses humor recognition methods based on traditional machine learning, deep learning, and multimodal approaches, and then highlights the advantages and disadvantages of each. Based on these analyses, the paper identifies the main challenges and difficulties in current research and provides suggestions and prospects for the future development of humor recognition systems.
Simple Light-sensitive and Voice-controlled Lighting System based on Arduino
Authors: Jiang Fangfei
Published: November 2024

Abstract. In recent years, corridor lighting has been widely used all over the world, as a simple lighting system, which provides great convenience for people to travel at night. However, with the increase in population and buildings, the number of lighting systems is increasing, and the disadvantage of low luminous efficiency of incandescent lamps is becoming more and more obvious, and the increase in electricity consumption has become a huge burden. How to reduce the electricity consumption of induction lamps in residential areas and corridors while ensuring the convenience of people's lives has become a prominent problem. This paper consulted the relevant information, chose sound and light control together, and set up a programmable delay LED lighting system. On the basis of basic lighting functions, people come to light at night, and people leave the light. By equipping the light-emitting element with higher luminous efficiency, the energy consumption is greatly reduced, and it has certain practical value. Through experiments in different scenarios, the above results are verified.
A New Way of Resolver to Digital Converter in a Steady System
Authors: Chen Shuliang , Zhao Fangting
Published: November 2024

This paper presents a simple method to detect the phase of a rotor based on the resolver equipped motor in a steady status. There are three pulses signals which are used to produce the phase edge at 0 degree, 90 degrees, 180 degrees and 360 degrees. This can be used to reset the integrator which is used to integrate the phase differences. Meanwhile the carrier edge can be used to counted as the phase angle of rotor. When the system is in a steady status it is easy to get the phase angle by using a digital counter.
Teachers' Experiences in Implementing the School Literacy Movement (GLS): An Investigation of Junior High School Literacy Programs in Indonesia
Authors: Lestari Puji , Gufron Anik , Surjono Herman Dwi
Published: November 2024

This study explores the experiences of junior secondary school teachers in Indonesia who have implemented the School Literacy Movement (GLS). The study focuses on teachers' perceptions of GLS, its implementation, and its challenges. This study used a phenomenological approach involving 20 teachers to share their insights on the research topic. Data analysis was conducted through a qualitative research paradigm using ATLAS.ti 9 software. The tool facilitated the study of participants' transcripts and documentation, enabling the verbal expression of essential phrases or sentences, the identification of meanings and themes, and the combination of these elements into a comprehensive and insightful description. This study found that teachers implemented incomplete stages of GLS, driven by their limited perception of the program, which focused more on general reading skills. Their planning and implementation of GLS was superficial, and they faced significant issues such as time, evaluation, teacher workload, limited interaction or lack of training, and low student interest in reading. Challenges include limited learning resources and access and an unsupportive environment, facilities, and infrastructure
Pengaruh Kepemimpinan Transformasional, Organizational Citizenship Behavior Dan Stres Kerja Terhadap Kinerja Karyawan
Authors: Sobari Denudin , Perkasa Didin Hikmah , Wahdiniawati Siti Annisa , Parashakti Ryani Dhyan , Yuliana Lingga
Published: November 2024

Perusahaan retail modern merupakan salah satu bisnis yang mengalami berbagai perubahan dan tantangan khususnya pada industri ritel di Indonesia, Disamping itu terdapat bonus demografi yang dialami negara Indonesia dengan populasi Gen Z sebesar 27,94% dan mendominasi berdasarkan total penduduk di Indonesia. Dari keadaan ini pelaku bisnis ritel modern harus melakukan inisiatif yang tepat untuk mengelola sumber daya manusianya sehingga dapat meningkatkan performa bisnis yang mengarah kepada kemampuan bersaing secara optimal. Dengan situasi ini, Peneliti tertarik untuk meneliti beberapa faktor yang mempengaruhi employee performance di PT. Sumber Alfaria Trijaya. Tbk. Populasi yang digunakan penulis sebagai objek penelitian adalah karyawan Gen Z dengan status karyawan tetap dan masa kerja minimal satu tahun yang berjumlah 220 karyawan. Kemudian penelitian ini menggunakan metode deskriptif kuantitatif, dengan teknik probability sampling, berdasarkan judgement sampling. Data yang telah terkumpul kemudian diolah dengan metode variance based structural equation model dimana dalam pengelolaan datanya menggunakan program partial least square (Smart-PLS) versi 3.3.9. Hasil dari penelitian ini menunjukkan bahwa transformational leadership memiliki pengaruh yang positif dan signifikan terhadap employee performance, Sedangkan organizational citizenship behavior memiliki pengaruh positif dan tidak signifikan terhadap employee performance, Selanjutnya work stress memiliki pengaruh yang positif dan signifikan terhadap employee performance.
Corrosion Behaviour of Al2024 Metal Matrix Composites Reinforced with Al2O3
Authors: R Lakshmi , H.R Radha , P.V Krupakara , V Latha , P.V Elumalai , Qiuying Ren
Published: November 2024

In this study, Al2024 metal matrix composites reinforced with Al2O3 of 0.063 - 0.200 mm particle size varying from 0 to 6 weight percentage were fabricated by vortex method. The effect of the Al2O3 particle on Al2024's corrosion behaviour has been investigated. The distribution of particles in all metal matrix composites appears to be quite homogenous, according to the SEM study of the microstructures. Weight loss corrosion studies have been performed on both MMC and corresponding base alloys using 0.05N and 0.1N HCl as corrosive media. The composites have a less susceptibility to pitting and corrosion than the matrix alloy, potentially because of the passive Al2O3 layer found in the MMCs. Using the potentiodynamic polarization test, the effect of reinforcement on the corrosion characteristics of composites in 0.05N and 0.1N HCl media was examined. The weight loss method was used to conduct stress corrosion tests for varying acidic medium temperatures (30oC – 55oC), normalcy (0.025 N-0.1 N), and exposure times (10-60 min). The rate of corrosion of Al2024 alloy was found higher than the Al2O3 reinforced Al2024 alloy.
Occupational Stress and Turnover Intentions: Implication for Nursing Management
Authors: Tariq Kalash , Siddique Humaira , Jabeen Rubina , Tasneem Syeda
Published: November 2024

Most of the time, individuals have to endure many kinds of occupational stressors at their workplaces that challenge their serene and skilled personalities, disturbing their aptitude. Therefore, a person may quit their employment, which is their turnover intention. Objective: To assess the occupational stress and turnover intention: implications for nursing management. Methods: A descriptive cross-sectional research study design was used. The study used a purposive sampling technique. The study population was staff nurses, and the sample size was 133. Results: The study reported that the occupational stress to the staff nurses in the field, those who mostly agreed were 70% and strongly agreed were 20%, and 10% were uncertain about stress in their working setup. Most staff nurses agreed that nurses leave their jobs and turn over to the next hospital, which was 80%, and strongly agreed 10%, and those nurses who compromise on the field were 10%. Conclusions: The study concluded that most nurses have high occupational stress and turnover intention. Therefore, it’s the responsibility of the management to provide a favourable or soothing environment by lowering workload and providing several staff nurses by the related departments, which helps the staff nurses to lower their occupation stress and thus limit turnover intentions in the hospital setup.
Leaf diseases detection empowered with transfer learning model
Authors: Baig Muhamamd Daniyal , Ul Haq Hafiz Burhan , Asif Muhammad , Tanvir Aqdas
Published: November 2024

The detection of leaf diseases using modern technology has significant importance in agriculture and artificial intelligence. Deep learning, specifically, plays a crucial role in this field, as it enables accurate and efficient disease classification. Early detection of leaf diseases is vital to implementing timely treatments and preventing widespread damage to leaves. Leaf diseases can be caused by various factors, including bacteria, fungi, viruses, and other pathogens. Among them, bacteria and viruses are the most invasive and can lead to substantial yield losses if not identified and treated promptly. Bacterial and viral infections are common in agricultural settings, affecting leaves of all types and ages. Our research aims to propose a transfer learning-based model for predicting leaf diseases using a dataset of leaf images. The images will be classified into healthy or diseased leaves based on extracted features. The proposed model, named Leaf Disease Transfer Learning Algorithm (LDTLA), demonstrates promising results with an average accuracy of 97.37% on the dataset. Utilizing convolutional neural networks (CNN) and deep learning techniques, our LDTLA model outperforms previous quantitative and qualitative research studies in leaf disease detection. This advanced approach to leaf disease identification holds the potential to revolutionize agriculture by enabling farmers to make informed decisions, implement targeted treatments, and minimize leaf losses caused by diseases.
Self-Perceived Competence in Clinical Skills Among Fresh Graduates of Karachi Pakistan - A Comparative Study
Authors: Ali Syed Ahmed
Published: November 2024

Students’ development as effective dental practitioners are based on their happiness and self-awareness with their ability to conduct various dental operations. This study evaluated the self-perceived competence level among fresh dental graduates who are currently completing their house jobs in different dental institutes in Karachi, Pakistan. This was a descriptive, cross-sectional study, conducted in January and February 2022. Data was collected from a total of 330 fresh graduates working as house officers in six different dental colleges in Karachi. The participants were asked to fill out the questionnaire, after acquiring informed consent. The mean overall score was 75.75/100 + 11.60. Most of the participants had a firm grip on 18 out of 24 clinical procedures while bitewing radiographs and production of mechanically sound cast partial denture (CPD) were two items that most of the participants lacked. The cognitive skills in part B were absent in most of the participants. House officers were able to perform clinical duties confidently during their house job while there was a lack of interest shown in performing cognitive responsibilities which showed that there is room for improvement. The findings of this study could be applied to dental schools in Pakistan in uplifting their clinical and cognitive skills to make them better clinicians, as multiple dental schools participated in this survey. The effects should be assessed carefully as the reported competence is self-perceived, not clinically proven.
Causes of Internal Migration and Its Impact on Poverty: A Case Study from Kurigram District in Bangladesh
Authors: Salam Md. Abdus , Kiron Md Asduzzaman
Published: November 2024

Internal migration plays a pivotal role in poverty reduction, and this phenomenon is widespread in Bangladesh. While some studies based on secondary data have been published on internal migration, the definitive conclusions drawn from this data remain unclear. Therefore, to address this gap, our study fills the void by utilizing primary data. The research primarily relies on data collected through interviews, encompassing 300 respondents who migrated, 100 family members of migrants, and 82 individuals from their kinship networks. The study uncovers crucial findings regarding the causes of internal migration and its impact on poverty. Furthermore, it sheds light on the theoretical underpinnings of migration theory. One significant discovery of the study is that the living standards of respondents improve after migration compared to their pre-migration living conditions. Additionally, this paper delves into the examination of socioeconomic and socio-demographic factors that influence the decision-making process of internal migration. By employing primary data and conducting in-depth analyses, this research provides a more comprehensive understanding of the intricacies surrounding internal migration and its effects on poverty alleviation.
PREVALÊNCIA E FATORES DE RISCO DA TUBERCULOSE LATENTE EM PACIENTES COM HIV: UMA REVISÃO SISTEMÁTICA
Authors: Silverio Gabriela Amorim da Mota , Farias Gardenia Monteiro , Sá Argentina Santos de , Lima Denise Girão Limaverde , Alves Helen Kathia de Souza , Leite Luan Novaes , Araujo Victoria Souza , Rezende Jamile Mamed Monteiro
Published: November 2024

A tuberculose (TB) continua sendo uma das infecções oportunistas mais prevalentes e perigosas entre pessoas vivendo com o vírus da imunodeficiência humana (HIV). Este artigo apresenta uma revisão sistemática que tem como objetivo principal analisar a prevalência e os fatores de risco associados à tuberculose latente em pacientes com HIV. Os resultados obtidos na revisão indicaram uma prevalência de tuberculose latente que variou de 9,4% a 30% entre os pacientes com HIV analisados, com fatores de risco significativos identificados, como sexo masculino e contagem de células T CD4+ reduzida. Além disso, foi identificada a necessidade premente de intervenções direcionadas para o rastreamento e tratamento da tuberculose latente, considerando as particularidades demográficas, sociais e clínicas dos indivíduos afetados. A conclusão ressalta a urgência de mais pesquisas na área, que possam contribuir para um entendimento mais profundo da relação complexa entre HIV e tuberculose, promovendo políticas de saúde pública mais eficazes para o controle dessas infecções que afetam de maneira desproporcional populações vulneráveis.
Effectiveness of SAIs as an International Anticorruption Practice
Authors: Bin Wabar Waled
Published: November 2024

Corruption is any dishonesty undertaken by an individual or an entity entrusted with a position of authority to acquire benefits illegally or abuse power for personal gain (Luna-Pla et al., 2022). Corruption has been recognized as a global concern affecting economic growth and development, social stability, and public trust in institutions (Wen et al., 2023). Some common forms of corruption that have been documented are perpetrated by public institutions and commercial entities. In public institutions, the common forms of corruption include bribery, extortion, blackmail, influence peddling, illegal lobbying, collusions, gratuities, and graft (Bahoo et al., 2021). These practices violate public trust for personal gain and are considered criminal offenses nationally and internationally. Commercial entities may also engage in corrupt practices such as embezzlement, insider trading, money laundering, bribery, and price fixing (Bahoo et al., 2021). These practices undermine the principle of fair competition, distort the market process, and ultimately cause economic harm to a nation (Ho et al., 2019). The problem of corruption is aggravated by the fact there are no generally globally accepted practices to fight corruption. Several countries have recorded the highest level of corruption at public and private levels. Transparency International, a non-government entity that publishes an annual corruption index, ranks countries based on the level of perceived corruption in the public sector (Akimov et al., 2020). The organisation uses an index based on a scale of 100 for very clean and 0 for highly corrupt (Akimov et al., 2020). As at 2021, the three most corrupt nations in their respective order are Iraq, Columbia, and Mexico (Transparency International, 2021). Transparency International has also noted other countries with high levels of corruption, including Brazil, Russia, Guatemala, Kazakhstan, Lebanon, El Salvador, Azerbaijan, Venezuela, Afghanistan, North Korea, Yemen, Equatorial Guinea, and Libya (Transparency International, 2021). In contrast, Denmark, Finland, New Zealand, Singapore, and Norway are some of the least corrupt nations (Transparency International, 2021).
Tối ưu ngưỡng phát hiện phân tán cho hệ thống ra đa nhiều vị trí
Authors: Hùng Phạm
Published: November 2024

Trong bài báo này, chúng tôi đề xuất một phương pháp để tối ưu ngưỡng phát hiện phân tán cho hệ thống ra đa nhiều vị trí. Dưới tiêu chuẩn Neyman-Pearson, ngưỡng phát hiện thành phần được tối ưu sử dụng thuật toán tối ưu bầy đàn (PSO). Các mức ngưỡng thành phần được tối ưu để cực đại xác suất phát hiện tổng thể dưới sự ràng buộc của xác suất báo động lầm tổng thể cho trước. Ưu điểm của PSO là tính đơn giản, ít tham số và tìm kiếm toàn cục hiệu quả. Ví dụ mô phỏng số được đưa ra đối với trường hợp hệ thống ra đa gồm 2 trạm thành phần phát hiện phân tán đối với mục tiêu trong nhiễu Gauss độc lập thống kê. Các kết quả chỉ ra rằng, quy tắc hợp nhất OR luôn tối ưu và mức ngưỡng được xác định linh hoạt cho phép duy trì chất lượng phát hiện tổng thể khi có sự thay đổi không đồng nhất của tỉ số tín/nhiễu (SCR) ở mỗi trạm thành phần. Trong một số trường hợp, có thể bỏ qua việc tối ưu ngưỡng thành phần mà chất lượng phát hiện toàn hệ thống giảm không đáng kể.
Research evaluation of some properties of HDX-24 porous metal mechanical frame material
Authors: Lương Trung Thiện , Lê Ngọc Hoan , Nguyễn Cao Tuấn , Vũ Ngọc Toán
Published: November 2024

This paper introduces the results of the research on the fabrication of HDX-24 porous metal-mechanical framework material using 4,4'-Bipyridine-2,6,2',6'-tetracarboxylic acid (H4L). The properties of post-fabrication materials are studied through a number of modern research methods such as Scanning electron microscopy (FE-SEM), BET-specific surface area determination, TGA thermogravimetric analysis, X-ray diffraction spectroscopy (XRD), X-ray energy scattering spectroscopy (EDS), etc. Fourier Transform Infrared Spectroscopy (FT-IR). The results show that HDX-24 material has a specific surface area-BET of 239.06 m2/g, the adsorption capacity of the material reaches 5.2 mmol/g, the particle size reaches 75-78 mm, and the pore volume is 0.202 cm3/g.
Developing a method to generate an adaptive real-time camouflage pattern based on electro-chromic active devices
Authors: Nguyễn Thành Lâm , Nguyen Anh Tuan , Nguyen Manh Thang
Published: November 2024

Traditional camouflage faces limitations in modern combat, especially with moving targets or rapidly changing backgrounds. Adaptive camouflage, which adjusts colors and patterns in real time, provides a more flexible and effective solution. This paper presents a comprehensive study of popular adaptive camouflage principles worldwide and proposes a camouflage model for the visible light spectrum based on active electro-chromic principles. Evaluation results indicate that adaptive patterns achieve the lowest Camouflage Similarity Index (CSI) and the highest Universal Image Quality Index (UIQI) across various backgrounds, demonstrating the clear effectiveness of the proposed model. With 3 to 5 dominant colors, pattern generation time is under 1 second, and adaptive patterns exhibit the highest similarity to the background compared to fixed patterns.
AI-Driven Network Traffic Optimization and Fault Detection in Enterprise WAN
Authors:   Chicago, USA, Nagpure Vaishali
Published: November 2024

In the contemporary landscape of
enterprise-Wide Area Networks (WANs), managing
complex interconnections between multiple data
centers and branch offices poses significant challenges.
This paper explores an innovative AI-driven approach
to network traffic optimization and fault detection,
utilizing knowledge graphs to enhance network
performance and reliability. The proposed framework
integrates real-time data collection, reinforcement
learning algorithms, and graph-based machine
learning to dynamically optimize traffic routing while
ensuring low latency and high availability for critical
applications such as financial transactions and video
conferencing. A detailed knowledge graph
representation is introduced, capturing essential
network elements, including devices, links, traffic
flows, policies, faults, and geographical regions. This
facilitates a comprehensive understanding of the
intricate relationships within the network
infrastructure. Cypher queries are employed to extract
relevant insights from the knowledge graph, enabling
proactive fault detection and routing optimization
based on historical patterns and current network
conditions. The methodology emphasizes dynamic
route adjustments based on real-time telemetry,
minimizing disruption during link failures.
Additionally, predictive modeling leverages historical
fault data to forecast potential future issues, allowing
for preemptive measures to maintain operational
integrity. The benefits of this AI-driven approach
include real-time traffic optimization, proactive fault
management, compliance with security and QoS
policies, and scalability to accommodate network
growth. Overall, this research demonstrates how
combining AI algorithms with knowledge graph
models can revolutionize wired network management,

significantly improving the resilience and efficiency of
enterprise WANs.
Keywords— Network Traffic Optimization, Fault
Detection, Enterprise WAN, AI-Driven Analytics
Role of AI in Security Compliance
Authors: Reddy Haritha Madhava
Published: November 2024

Abstract—Artificial Intelligence (AI) has emerged as a
pivotal tool in enhancing security compliance across
various industries. Its ability to analyze vast datasets,
detect intricate patterns, and automate complex
processes significantly improves risk management and
regulatory adherence. AI enables real-time data
analysis, promptly identifying potential violations and
flagging security threats, thereby strengthening an
organization’s overall security framework. However,
while AI offers transformative advantages, its
integration into existing security systems introduces
new challenges, such as data privacy concerns,
algorithmic bias, and the need for transparent
decision-making. This paper explores the dual role of
AI in both enhancing compliance efforts and
presenting risks that require careful management. By
adopting a balanced approach—leveraging AI’s
capabilities while ensuring robust oversight—
organizations can optimize compliance processes,
address regulatory challenges, and mitigate associated
risks. Achieving this balance is critical to securing
long-term success in an increasingly regulated and
digitized landscape.

Keywords—Artificial Intelligence (AI), security
compliance, risk management, regulatory compliance,
data privacy, algorithmic bias, real-time data analysis,
threat detection, automation, cybersecurity,
transparency, decision-making, compliance
automation, AI integration, ethical AI deployment,
organizational security, regulatory frameworks.
AutoWatcher: a Real-Time Context-Aware Security Alert System using LLMs
Authors:   University of Arizona, Tucson, USA, Vadlapati Praneeth
Published: November 2024

Ensuring the safety of every person is a necessity. Burglaries are frequent across residential and
commercial spaces. Criminals frequently use weapons and are a serious threat to the common people who are
innocent. The best solution to safety is alertness. Computer Vision (CV) is frequently implemented through neural
networks that use a process of training to gain abilities to detect humans. Multimodal Large Language Models
(LLMs) capable of vision-based tasks are common and are capable of processing images similar to humans who use

their analytical abilities. With the ongoing research, LLMs are becoming smaller, faster, more accurate, and cost-
effective, making them usable in security systems to detect threats in an intelligent way based on custom instructions.

Existing research does not explore the usage of multimodal LLMs for real-time monitoring. This paper proposes a
system called “AutoWatcher” to monitor a place using a camera in real-time, constantly detect humans, and use
LLMs to assess potential threats. The system is designed for two levels of alerts, one when a person is detected and
another when the LLM declares them as suspicious. This ensures alertness of the people who can proactively protect
their lives and valuable assets on time before a security breach occurs at their home or workspace. This enables the
residents to alert the emergency service authorities in their locality. The system has successfully detected suspicious
people with an accuracy of up to 90%. The accuracy is 100% in some test cases. The code is available at
github.com/Pro-GenAI/AutoWatcher.
Keywords: large language models (LLMs), computer vision (CV), multimodal LLMs, neural networks, edge AI,
automated surveillance
Healthcare Services Marketing: A Systematic Literature Review and Future Research Directions
Authors:   Albertian Institute of Management, Ernakulam., Sankar Dr. Mahalakshmi
Published: November 2024

Purpose – This paper aims to review articles on healthcare services marketing published in the past decade to
identify research gaps created in the backdrop of the recent pandemic and propose a future research direction
necessitated by the global crisis.
Design/methodology/approach – A literature review is performed based on the search term "healthcare services
marketing" applied to the Scopus database, resulting in a final pool of 65 articles. The authors conducted the
analysis based on Callahan's 6 W framework (2014).
Findings – In the last decade, healthcare service marketing research emphasised medical tourism and concentrated
on service quality. Towards the end of the last decade, the research on online healthcare service marketing saw a
rise indicating a trend in the field. Based on this and considering the recent pandemic, the paper proposes possible
topics for future research.
Originality/value – The growing importance of global healthcare services is well-understood post-pandemic, and
there is a growing interest in this area. A comprehensive review exploring topics researched in healthcare services
marketing in the preceding decade before the pandemic will help identify research trends that will need further
exploration to handle future global health crises.
Keywords Healthcare services marketing, Healthcare marketing, Literature review
Dijitalleşme, Kültür ve Psikoloji Üçgeninde Değer Algısı
Authors: Çakır Aydın , Dilci Tuncay
Published: November 2024

Dijital çağın getirmiş olduğu yenilikler her yaştan bireyin yaşamında derin izler bırakmaktadır. Teknolojik araçların yaşamın ayrılmaz parçası hale gelmesi ile birlikte bireylerin davranışlarında değişimler gözlenmiştir. Dijital uygarlığın ortaya koymuş olduğu yeni yaşam biçimi ve buna bağlı kültürel türevler her ortamda varlığını hissettirmeye başladı. Özellikle subliminal mesajlarla şekillenen yeni neslin doğuşu toplumda yalnızlaşmayı, yabancılaşmayı ve kültürel yozlaşmayı da beraberinde getirmektedir. Diğer yandan dijital psikoloji toplumu narsist, bencil ve pragmatist yeni bir varlık olmaya sürüklemektedir. Toplum içinde kendi kabuğuna çekilen bireyler dijital platformlarda sosyalleşme çabası içerisine girmiştir. Dijitist dünya değersiz nesillerin niceliğini artırırken, nitelik sorununu da beraberinde getirmiştir. İşte bu noktada hızla ilerleyen dijital teknoloji insan hayatını yapay zekâ uygulamalarıyla adeta kuşatmaya başlamıştır. İnsanların hayatını kolaylaştıran dijital dünya; ayrıca kendi içsel varlık sorunları ve çelişkileri ile toplumsal insani ilişkileri yeniden dizayn etme rolünü üstlenmiştir. Bu çerçevede dijital kültür, psikoloji ve değer algısı arasındaki ilişkinin incelenmesi amacıyla bu çalışma gündeme alınmıştır. Çalışma kapsamında, dijitalleşme, kültür ve psikoloji, dijital psikoloji, değer algısı ve dijitalleşme, dijitalleşme ve toplumsal değişim kavramları ele alınmıştır. Derleme olarak yazılan bu çalışmada veri toplama aracı olarak doküman analizinden yararlanılmıştır. Konuya ilişkin dokümanların incelenmesi ile elde edilen çalışma betimsel analiz yoluyla tasvir edilmiştir. Sonuç olarak; dijital kültür psikolojisi ve değer algısı arasındaki ilişkiyi incelemek adına yapılan araştırmalarda dijitalleşmenin bireyleri derinden etkilediği; bireylerin davranışlarında ve alışkanlıklarında değişikliklerin olduğu dile getirilirken; bu durumun derinliğini analiz eden makalemiz dijitalleşme, kültürü ve psikolojisi üçgeninde geçmişten geleceğe inanç, inanç psikolojisi ve değer odaklı yaşantı biçimini sentezleyerek bu değişimin olası olması gerekenlerini ifşa etmiştir.
Evaluating the alternative learning system in Biliran, Philippines: A systemic approach to educational change and sustainability for marginalized learners
Authors: Espejon, Jr. Nonilon C. , Niez Roland A. , Sabonsolin Beltram C. , Cabas, Jr. Carlito C. , Calles Analiza B. , Magno Jelyn M. , Plecerda Lanie P. , Concepcion Grace L.
Published: November 2024

This study examines the implementation and impact of the Alternative Learning System (ALS) in the Division of Biliran, Philippines, which plays a vital role in extending educational opportunities to out-of-school youth, illiterate adults, and marginalized communities. Despite ALS's significant contributions to increasing educational access, the program faces challenges that limit its effectiveness, highlighting the need for a comprehensive evaluation to guide future policy enhancements and practical improvements. Employing a Convergent Mixed Methods design, this study was conducted across fourteen districts within the Division of Biliran. The sample comprised 399 respondents, including mobile teachers, district ALS coordinators, successful ALS completers, and the division ALS supervisor. Data collection involved surveys and interviews to capture learners’and educators’ perspectives on program delivery, curriculum effectiveness, and the challenges and strategies in program implementation. The findings indicate that learners valued the programs ‘learner-centered discussions and flexible scheduling, although they perceived support services, particularly online guidance and counseling, as insufficient. The curriculum was commended for fostering critical communication and problem-solving skills; however, it was noted to lack emphasis on community awareness and sustainable resource management. Teaching approaches incorporating Individual Learning Agreements and ALS modules were well-received, though group interactions and experiential learning methods were less effectively executed. Assessment methods, such as portfolios and quizzes, were positively reviewed, while assessments involving social interaction were perceived as less beneficial. In terms of outcomes, the program successfully contributed to learners ‘personality development but showed only moderate success in enhancing employability and entrepreneurial skills. Key challenges identified included learners’ attitudes toward schooling and limited systemic support for ALS teachers. To overcome these obstacles, teachers employed adaptive strategies such as community collaboration and flexible teaching approaches. This study provides critical insights into the strengths and areas for improvement within the ALS program, suggesting a foundation for policy reforms and strategic interventions to enhance educational outcomes for its target populations.
Unlocking artificial intelligence for strategic market development and business growth: innovations, opportunities, and future directions
Authors: Hossain Fahim , Ahmed G. M Selim , Shuvo Shree Pritom Paul , Kona Abeda Najmin , Raina Mostarifa Umme Hani , Shikder Fisan
Published: November 2024

This study explores the role of Artificial Intelligence (AI) in strategic market development and business growth. It aims to examine how AI innovations create new opportunities, enhance operational efficiencies, and drive competitive advantages for businesses across various sectors. This study relies significantly on previously published literature and secondary data sourced from esteemed academic databases, including Web of Science, SCOPUS, Google Scholar, and Research gate. Initially, we collected a dataset of 300 papers spanning the period from January 2020 to 2024. After a rigorous screening process, we narrowed it down to 65 papers to derive the desired insights and produce robust results. AI is revolutionizing market strategies by enabling personalized marketing, optimizing supply chains, and improving decision-making through predictive analytics. Companies are leveraging AI for automating customer service, enhancing product development, and discovering new business models. The study also highlights AI’s potential in facilitating global market expansion and localized product offerings. The findings suggest that AI is central to enhancing business efficiency, innovation, and customer satisfaction. However, ethical concerns such as data privacy, algorithmic bias, and regulatory challenges remain significant barriers to AI adoption. Companies must balance innovation with responsible AI use to ensure long-term success and sustainability. Businesses adopting AI technologies can gain a competitive edge by improving operational efficiency and creating more tailored customer experiences. However, they must invest in AI transparency, employee reskilling, and regulatory compliance to mitigate risks associated with AI deployment. Further research is needed to explore the ethical and societal impacts of AI, including its role in job displacement and its potential for environmental sustainability. The integration of AI with emerging technologies like blockchain and IoT also offers exciting opportunities for future growth. Organizations should invest in AI solutions aligned with business objectives, ensuring ethical practices and continuous innovation to maintain a competitive edge in the evolving market landscape.
The program to institutionalize meritocracy and excellence in human resource management in the Bangsamoro autonomous region in Muslim Mindanao
Authors: Salipada Tahir , Sam Radzak A. , Abdula Sajid P. , Salipada Julmaherria M. , Bayog Maricor G. , Sam Solayha A. , Abdula Datuali P.
Published: November 2024

The Civil Service Commission implemented the Program to Institutionalize Meritocracy and Excellence in Human Resource Management to enhance the performance levels of government agencies throughout the Philippines. This study aimed to examine and analyze the program’s implementation, focusing on the local government units of Parang, Maguindanao del Norte, and Datu Abdullah Sangki, Maguindanao del Sur, both within the Bangsamoro Autonomous Region in Muslim Mindanao. Utilizing a qualitative approach, the study focused specifically on the implementation of the four-core human resource management systems: recruitment, selection, and placement; learning and development; performance management; and the challenges encountered during the program’s execution. The findings revealed that the municipalities of Parang and Datu Abdullah Sangki had achieved human resource management system maturity level 2, indicating that the program was effectively implemented. While challenges were encountered during the implementation, they provided a valuable impetus for developing an organizational development intervention specifically tailored to address the needs of these local government units.
Exploring the role of teachers and the community in the inclusion of migrant students in the contemporary Greek school context
Authors: Zoe Karanikola , Magdalini Nikolopoulou
Published: November 2024

The present research study seeks to examine secondary teachers’ perceptions regarding migrant students’ inclusion in the contemporary Greek school environment. Qualitative methodology was followed, and a semi-structured interview tool was used to collect the necessary data. Using the convenience sampling technique, eight teachers participated, and the data were analyzed through thematic analysis. The findings emphasize the important role of teachers, since they shape the classroom environment, provide emotional support and enhance academic learning. They seem to have a positive attitude toward migrant students’ inclusion, and they do their best to facilitate academic progress and emotional well-being. They find ways to overcome language barriers by providing differentiated material, individualized teaching and, when possible, use English as lingua franca or multimedia, videos, diagrams and collaborative learning. However, despite their good intentions and initiatives, they claim that migrant students’ academic and social inclusion meets a lot of obstacles and challenges. There are not enough reception classes and supporting structures, the material is inadequate, time and curriculum are pressing, and the educational process is lacking a spirit of interculturalism. Finally, the community role of migrants remains unknown, and there is a strong demand for teachers to undergo further professional development and training.
The Relationship Between Reading English Attitude and Students’ Reading Achievement in General
Authors: Hasan Mousa O. M.
Published: November 2024

Reading English has become a global trend in twenty first century because of its professional use worldwide. Students are motivated to improve their reading skills because they know that doing so would help them get better-paying jobs and advance in their chosen fields. Therefore, it is crucial to investigate how reading proficiency and views regarding general English reading are related among university students. Students’ positive attitudes about reading were reflected in recent research findings. General English, since there is a present need to understand and read English. The new research is crucial because it shows that kids need to devote more time to reading in English to succeed academically and build a successful future career. According to the results, students in Saudi Arabia believed that learning English was essential for their academic growth and exposure to new ideas. In this case, educational institutions should set clear regulations permitting students to acquire English outside of the course requirement.
ESG controversies and banking performance: The moderating effect of board activity
Authors: Mahyoub Mugahed , Ja’afar Roslan , Ghani Nur Laili Ab
Published: November 2024

The present study examines the influence of ESG controversies on the financial performance of listed banks in the Asia-Pacific region (APAC). The nexus between environmental, social, and governance (ESG) metrics and financial performance has garnered significant attention from academics, corporations, executives, and regulators in the present era. In addition, this study investigates whether board activity moderates the relationship between ESG controversies and bank performance. This study adopts a quantitative approach and employs a cross-country sample of 54 banks with 540 bank-year observations from 2013 to 2022. The data were compiled from the London Stock Exchange Group (LSEG) database and examined using panel data regression techniques. The findings indicate that the ESG controversies have a notable adverse effect on the performance of banks, as measured by Tobin's Q. Interestingly, the study discovered that board activity alleviates the negative influence of ESG controversies on bank performance. These empirical findings aid investors and managers in assessing the impact of ESG controversies and board activity on bank performance. Moreover, the empirical findings can aid bank managers in implementing a proactive governance-oriented approach. Particularly, board activity should be regarded as a method to reduce the negative effects of ESG controversies on performance.
Innovation capability and firm competitiveness in Ethiopian industrial parks: The moderating role of human capital
Authors: Yusuf Abadir Abrahim , Zewdie Shimelis , Kero Chalchisa Amentie
Published: November 2024

This research examines the innovation capability and firm competitiveness in Ethiopian industrial parks. Extant empirical literature has demonstrated the crucial role of innovation capability for competitiveness. However, only a few studies have examined the interplay between human capital and innovation capacity in terms of the competitive performance of firms. To this end, this study examines how innovation capability in Ethiopian industrial parks affects firm competitiveness by considering the moderating role of human capital. By adopting a quantitative approach, cross-sectional survey data was collected from 81 active manufacturing firms by targeting firm managers. Partial least squares structural equation modeling (PLS-SEM) using SmartPLS 4 was employed to analyze the data and test the study hypotheses. The results reveal that human capital does not moderate the relationship between innovation capability and firm competitiveness but rather partially mediates it. The findings highlighted that the development of firm human capital quality—creativity and innovative skills—is essential for enhanced firm innovation capacity and competitiveness. Therefore, firms aspiring to develop their competitiveness—operational capability, dynamic capability, and market performance—need to focus not only on developing innovation capacity but also on developing their human capital competencies for innovation. The study helps organizations develop effective innovation capacity development strategies to ensure greater firm competitiveness.
EVOLUTION OF THE STRUCTURE AND PROPERTIES OF CU-56AU (AT %) ALLOY DURING L10-TYPE ATOMIC ORDERING
Authors: NOVIKOVA O.S. , VOLKOVA E.G. , PODGORBUNSKAYA P.O. , ZGIBNEV D.A. , GAVRILOVA A.A. , KRUGLIKOV N.A. , VOLKOV A.YU.
Published: November 2024

The ordered gold-copper alloy Cu-56 at % Au is widely used in instrument engineering as conductors of weak electrical signals in control devices. However, microstructural evolution and changes in the physicomechanical properties of the alloy during the disorder → order phase transformation (A1 → L10) are still poorly understood. In the present paper, we study the evolution of the microstructure and properties of the quenched Cu-56 at % Au alloy during the disorder → order phase transformation. The annealing time at 250°C ranged from 10 min to 4 months. Microstructural studies were performed using transmission electron microscopy, the ratio of volume fractions of the ordered and disordered phases was determined using X-ray diffraction analysis and resistometry, and material properties were measured in mechanical tensile and microhardness tests. The fraction of the ordered phase, strength properties, and specific electrical resistivity were plotted as a function of the annealing time. It is found that the maximum strength properties correspond to the two-phase state (A1 + L10) of the alloy with an approximately equal phase ratio. It is shown that, with an increase in the fraction of the ordered phase, the tensile strain hardening coefficient almost doubles.
Penalaran Matematis Siswa SMP pada Materi Aritmatika Sosial melalui Pembelajaran Berdiferensiasi Ditinjau dari Gaya Belajar
Authors: Okviani Erisa , Candra Hastari Ratri
Published: November 2024

Pendidikan di Indonesia saat ini dirancang oleh kurikulum, untuk beradaptasi dengan perkembangan teknologi dan ilmu pengetahuan. Kurikulum pendidikan yang digunakan di Indonesia saat ini adalah kurikulum Merdeka dimana siswa diberikan kebebasan untuk mengatur pembelajaran mereka sendiri. Model pembelajaran yang relevan sesuai kurikulum saat ini ialah model pembelajaran berdiferensiasi. Banyak siswa yang masih belum dapat memaksimalkan penalaran matematis mereka dan masih mengandalkan penjelasan dari guru. Kemampuan penalaran matematis yang dikuasai oleh siswa dalam menyelesaiakan soal aritmatika sosial dikategorikan rendah, dikarenakan siswa kurang memahami pertanyaan pada soal. Kurangnya kemampuan penalaran matematis siswa juga dipengaruhi oleh beberapa faktor, salah satunya gaya belajar. Penelitian ini bertujuan untuk mendeskripsikan penalaran matematis siswa pada materi aritmatika sosial melalui pembelajaran berdiferensiasi ditinjau dari gaya belajar. Penelitian ini dilaksanakan di SMP Negeri 2 Gondang pada tahun ajaran 2023/2024. Metode penelitian yang diguanakan adalah penelitian deskriptif kualitatif. Teknik pengambilan data melalui observasi, amgket gaya belajar, tes, dan wawancara. Metode analisis data yang digunakan reduksi data, penyajian data, dan penarikan kesimpulan. Uji keabsahan data pada penelitian ini dilakukan berdasarkan triangulasi teknik dan sumber data. Hasil penelitian ini menunjukkan bahwa pembelajaran berdiferensiasi dapat meningkatkan penalaran matematis siswa. Empat indikator penalaran matematis yaitu: kemampuan dalam menyajikan soal, kemampuan membuat dugaan untuk mencari solusi permasalahan, kemampuan memanipulasi matematika, dan kemampuan menarik kesimpulan secara logis. Subjek V1 dengan gaya belajar visual memenuhi keempat indikator, subjek V2 memenuhi ketiga indikator, selanjutnya subjek A1 dengan gaya belajar auditori memenuhi keempat indikator, subjek A2 memenuhi ketiga indikator, kemudian subjek K1 dengan gaya belajar kinestetik memenuhi kedua indikator, dan subjek K2 memenuhi satu indikator.
 
Kata kunci: Aritmatika Sosial; Gaya Belajar; Pembelajaran Berdiferensiasi; Penalaran Matematis