bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Multilevel Feedback Queue Combinations and Regression-Based Time Quanta in Scheduling Algorithms
Authors: Luis William C. Meing
Published: February 2025

Much like day-to-day life, scheduling methods have roles in managing what to do and how much time or resources to invest. Multilevel Feedback Queues (MLFQ) are a widely used algorithm due to its capacity to handle a wide range of task types and execution times. There is increasing interest in exploring dynamic scheduling models that can adapt to live variables solved by machine learning. This study explores an approach to process scheduling by integrating linear regression into the dynamic adjustment of round robin time quanta within MLFQ systems. This paper identifies system resources that can be modelled using linear regression into dynamic round robin, introduces an algorithm using linear regression to optimize system performance in an MLFQ implementation, and explains how dynamic time quanta affect the performance of MLFQ scheduling algorithms. SJF and Round Robin are the most effective combination within the MLFQ system, while FCFS would be the last layer to ensure task completion. Average Waiting Time and Average Turnaround Time are the most appropriate metrics for evaluating MLFQ systems. The integration of linear regression into dynamic time quantum adjustments improves performance by reducing AWT, ATAT, and context switching.
Automated Grading of Essay Using Natural Language Processing: A Comparative Analysis with Human Raters Across Multiple Essay Types
Authors: Dennis C. Gabon
Published: February 2025

This study explores how well an automated essay grading (AEG) system, built with Natural Language Processing (NLP), aligns with human graders in assessing different types of essays. Using essays from 35 information technology (IT) students manually scored by human raters, the system’s performance was evaluated with statistical tools like weighted Cohen’s Kappa and the Friedman test. The results showed a moderate to substantial match between the automated essay grading system and human scores across essay types (argumentative, comparison and contrast, descriptive, narrative, and persuasive, suggesting that the system can reliably handle various writing styles. Also, no significant differences in grading reliability were found across essay formats, indicating that the system adapts well to different types of essays. These findings suggest that NLP-based essay grading systems could be valuable in educational settings, especially in large classes with high grading demands. While the system shows strong potential in the academic arena, focusing on assessment and further testing with a broader dataset is recommended to improve its generalizability and address complex writing elements, such as creativity and tone. This study contributes to educational technology by presenting a practical, scalable approach to consistent and objective essay grading, paving the way for the broader use of automated grading tools in education.
Exploring the Role of Female Leadership in Fostering Positive Organizational Behavior and Cooperative Learning Communities in Chinese Universities
Authors: Han Juan
Published: February 2025

This questionnaire-based research delves into the impact of female leadership on cultivating positive organizational behavior and cooperative learning communities within Chinese universities, with a sample size of 383 participants. Employing quantitative analysis methods, the study delves into the perceptions and experiences of students and faculty members to scrutinize the correlation between female leadership and organizational behavior, with a specific focus on its influence on cooperative learning environments. The findings highlight the pivotal role of female leadership in nurturing collaborative learning cultures and fostering positive behaviors within academic settings. By scrutinizing the dynamics of leadership gender, this research significantly contributes to the ongoing discourse on gender diversity and its profound implications for organizational dynamics and educational outcomes. The insights derived from this study offer invaluable implications for university administrators, policymakers, and educators striving to establish inclusive and productive learning environments within Chinese higher education institutions, with female leadership emerging as a critical component in this endeavor.
The Influence of E-Banking Service Quality Dimensions and E-Trust on E-Satisfaction and Its Impact on E-Customer Loyalty through E-Customer Satisfaction as an Intervening Variable in the Bank Jago Application in Indonesia
Authors: Jose Juang Tri Atmojo
Published: February 2025

Over the course of the past year, the electronic banking sector in Indonesia has encountered significant expansion. However, a paradox arises: despite numerous grievances over the quality of e-services, it does not impair electronic trust or satisfaction. The research. examines how various factors impact certain elements of Electronic-service Quality and E-Trust on E-Customer Loyalty, either directly or indirectly through E-Customer Satisfaction variable, specifically focused on the Bank Jago application. A purposive sample method was used to pick a total of 230 respondents who use the Bank Jago app in Greater Jakarta (Jabodetabek). Survey participants evaluated their views using a five-point scale across a total of 44 items. Analysis of data was conducted using PLS-SEM methods with SmartPLS ver 4. The outcomes of this study imply that E-Customer Satisfaction is not considerably affected by Site Organization, Reliability, Efficiency, and User Friendliness. However, Personal Needs, Responsiveness, and E-Trust have a major impact. The correlation on E-Trust and E-Customer Satisfaction and E-Customer Loyalty is favorable. This paper proposes methodology to augment loyalty within the expanding digital banking sector. This study's generalizability is limited to the digital banking industry, particularly focusing on Bank Jago. Furthermore, other significant determinants of E-Customer Loyalty, which were not explored in this study, warrant further examination. Subsequent research study suggested to test the Research approach within various industries or companies to expand the generalizability of the findings. Additionally, incorporating additional factors as independent variables impacting E-Customer Satisfaction would enhance understanding and broaden the model's applicability. Lastly, the study predominantly involved respondents from the private sector, suggesting future research should include a more diverse range of occupational backgrounds, such as students, government employees, or professionals, to provide a more comprehensive perspective on customer satisfaction.
Mobile Game Development on Mathematical Subject for Primary School Children
Authors: Farah Afifah Zulkefli
Published: February 2025

Mathematics can be challenging for many children, particularly in grasping basic concepts like addition, subtraction, and number recognition, which can hinder their confidence and academic progress. Traditional teaching methods often feel tedious for preschoolers, who benefit more from interactive and playful learning experiences. This study focuses on developing a gamified educational tool to enhance preschoolers' math abilities by combining engaging game elements, like rewards and challenges, with foundational educational content. By integrating principles such as repetition and scaffolding, the tool aims to make math practice enjoyable, improve cognitive development, and foster a positive attitude toward math, ultimately supporting future academic success.
Empowering Future Engineers: Outcomes of Tecnologico de Monterrey’s Engagement in the NASA Human Exploration Rover Challenge
Authors: David Garcia-Suarez
Published: February 2025

Since 2013, Tecnolo´gico de Monterrey has partici- pated in the NASA Human Exploration Rover Challenge, provid- ing its students with a valuable learning experience through high- impact international challenges. This multidisciplinary project engages students from various undergraduate and engineering programs, who collaborate to solve complex problems. By 2024, over 200 students will have been part of this initiative, with many facing their first international challenge. Over the years, the team has garnered multiple awards, demonstrating their global competitiveness. This paper examines how participation in the challenge has fostered the development of critical skills such as complex problem-solving, digital transformation, teamwork, innovation, leadership, and English communication. Additionally, it has opened doors to significant academic and professional opportunities, including scholarships, exchange programs, in- ternships at leading companies, and enhanced job placements after graduation. Particularly noteworthy is the significant im- provement shown by students with initially lower academic performance, highlighting the transformative impact of this experience on their motivation and commitment to academic and professional success. The study’s unique contribution lies in its analysis of the long-term effects of such international challenges on students’ career trajectories and personal development, with a specific focus on the Latin American educational context.
Adopting Virtual Reality Learning in Higher Education Institution: Reviewing Literature from the Past Studies
Authors: Siti Hazyanti Mohd Hashim
Published: February 2025

Virtual reality is a new technology that has been applied in many different fields. Throughout the years, virtual reality has become incredibly popular. The use of virtual reality applications in higher education is still in its infancy, despite the fact that numerous researchers have outlined the advantages of these learning tools. In general, it took longer to gain the trust of different stakeholders to use virtual reality in the classroom. Virtual reality has recently taken on a more significant role as the nature of learning in higher education institutions becomes more competitive. This study aims to address the idea of virtual reality and its educational applications in light of this concern. In addition, the literature from the past is discussed in this article.
The Interpretation of Contemporary Additions in Reuse Practices Through Semiotics: The Case of the Louvre Pyramid
Authors: Göktürk Peker
Published: February 2025

This study focuses on analyzing contemporary additions in the reuse of cultural heritage through the lens of architectural language and semiotics. The reuse process is a complex one, aiming to preserve the cultural value of heritage while adapting it to contemporary use and ensuring its future sustainability. When the original structure is insufficient to meet modern functional requirements, contemporary additions become necessary, which raises questions about the integration of old and new. Semiotics, a discipline centered on the study of signs and symbols, offers a systematic approach to understanding how meaning is created through architectural interventions. The research examines the Louvre Pyramid as a case study, applying the theoretical frameworks of semioticians and architectural theorists such as Fischer, Zevi, and Eco. The analysis focuses on three key aspects: context, function, and symbolic value, aiming to explore how contemporary additions communicate with the historic fabric of the building and how they contribute to the overall architectural narrative. A comprehensive literature review revealed that there is a gap in the study of architectural language within the context of heritage reuse, particularly in relation to contemporary additions. The findings of the study suggest that when contemporary additions are thoughtfully integrated with historic structures, they contribute not only to the aesthetic and functional quality of the spaces but also reinforce the cultural, historical, and social sustainability of the heritage. The successful blending of old and new can enhance the cultural legacy, ensuring its relevance for future generations.
Synergies in Education: Simulation Techniques, Electronic Portfolios, and SDG for Future-Focused Learning
Authors: Ana da Silva
Published: February 2025

The "Competence-based Training and Simulation in Healthcare" project aims to transform healthcare education by integrating simulation techniques, electronic portfolios, and the Sustainable Development Goals (SDGs) into teaching practices across partner institutions. Key activities include needs analysis, teacher training, student mobilities, and the creation of electronic portfolio templates and simulation exercises, all aligned with market needs and fostering collaboration, critical thinking, and innovative pedagogy. By engaging with the 17 SDGs, the project produces a guide for their application in healthcare education, enhancing the professional and personal development of educators and students while strengthening transnational collaboration. This initiative seeks to establish a dynamic, responsive educational framework to prepare healthcare professionals for emerging challenges, with this paper focusing on the project's implementation in the Portuguese context.
Tax Revenue, Cost of Governance, and Sustainable Development Goals (SDGS) in Nigeria
Authors: Abosede Ifeoluwa Adelusi
Published: February 2025

This study examines the relationship between Tax revenue, cost of governance, and Sustainable Development Goals (SDGs). The study's information was sourced mainly from secondary data. A longitudinal research design was employed for the quantitative data from the Central Bank of Nigeria (CBN) statistical bulletins of various issues from 2010 to 2022, and Federal Inland Revenue Service (FIRS)bulletins of different problems. Through graphs and charts, descriptive statistics are used to interpret the data gathered. The findings revealed that tax revenue and cost of governance affect Sustainable Development Goals for the sustainable development of Nigeria. Therefore, we recommended that the federal government of Nigeria be more intentional in their budgetary expenditure, and the actual spending should focus now on welfare programmes like health care services and making drugs available to the citizens at subsidized rates, massive investment expenditure on agriculture to reduce hunger and poverty.
Integrating IoT and Civic Education: SKILIKET System as an Approach to Environmental Monitoring and Awareness
Authors: Jorge Sanabria-Z
Published: February 2025

The integration of Internet of Things (IoT) technologies to address environmental sustainability exemplifies the current need for innovative data collection and community involvement. At the same time, the citizen science movement fosters voluntary participation to democratize science. However, access to robust training and large-scale deployment remains limited. This study proposes the SKILIKET system, a flexible training tech kit that monitors environmental variables in real time using IoT capabilities and a citizen science approach. The initiative seeks to foster participants' technical and civic competencies, using the system to help them understand socio-ecological phenomena. Drawing on Design-Based Research methodology, the authors describe co-creation activities that will be further conducted with higher education student teams to develop the ideal use of the system. This first stage (experimental design) anticipates the expected system interactions in a controlled environment, where students are encouraged to actively collect data from their immediate environment. This engagement aims to nurture a deeper understanding of socio-environmental issues, enhance public awareness, and support data-driven decision-making and public policy development. SKILIKET incorporates educational objectives and promotes civic skills, data literacy, and community-oriented problem-solving. This paper discusses the initial design, implementation strategies, and expected educational and societal impact of SKILIKET, highlighting its dual role in environmental monitoring and educational enhancement to achieve the U.N. Sustainable Development Goals (SDGs).
Exploring the Moderating Effect of Employee Autonomy on Moral Traits and Ethical Behaviour in the Logistics Sector
Authors: Mohammad Shamshul Arefin
Published: February 2025

This work explores the moderating role of employee autonomy on moral traits with a view of learning their impact on ethical behaviour in the logistical industry. Accordingly, for the purpose of the current study a quantitative research design was adopted and data was collected from one hundred respondents with the use of a structured questionnaire. The following Employee variables were measured: Employee Empowerment, Autonomy & Ethical Practice. Descriptive statistics showed no relationship between}'", age, position, and work experience as well as the tested variables in the ANOVA analysis. Studies underscore the importance of the implementation of the organizational solutions regarding the strengthening of ethical behaviour and the optimum level of the employee’s autonomy. Future work should to further reveal external factors affecting ethical plans to enhance organizational environment.
Fostering Media and Information Literacy Among Youth as a Means of Countering Information and Psychological Operations
Authors: Anastasiia Bessarab
Published: February 2025

Introduction: The topic's relevance is driven by the need to increase society's resilience to disinformation and manipulative content in the digital information environment.
Objectives: The article examines the role of media literacy in countering information and psychological operations. They are actively used in modern geopolitical conflicts, especially after the outbreak of a full-scale war in Ukraine in 2022.
Methods: The study was based on synthesis, generalisation, deduction, induction, and statistical analysis, which allowed us to analyse media literacy dynamics in Europe and Ukraine.
Results: The article outlines the need for further development and improvement of educational programmes to reduce the impact of PSYOP.
Conclusions: In the future, the study envisages a detailed analysis of the effectiveness of integrating media education at all levels of education and the development of new methods to increase the level of critical thinking and resistance to manipulation among different social and age groups.
Impact of Social Media on Political Campaigns: Management, Strategies and Results
Authors: Yan Medviedev
Published: February 2025

Introduction: The relevance of this topic is that social media has become a crucial tool for communication and political campaigns. As a significant portion of society now resides in the online space, it is crucial to study the strategies and outcomes of using social media in politics to understand the impact of these platforms on public opinion and electoral processes. Analysing this issue enables the identification of significant trends and the development of approaches for the optimal use of social media in a political context. This research aims to comprehensively analyse and systematise the strategies used in political campaigns on social media. Additionally, it seeks to evaluate the influence of these strategies on public opinion and electoral processes.
Objectives: The study aims to uncover the critical aspects of social media usage in politics, identify vital strategies, assess their impact on voters, and examine the formation of political leaders' images. The objective also includes studying the positive and negative aspects of using social media in political campaigns and determining opportunities for optimising this processin line with legalandso cialre quirements.
Methods: There search methodology in volvesan alysing literary our cesto identify critical theories and concepts related to social media interaction with political campaigns. Case studies are used to explore actual examples of social media usage in political campaigns. Expert surveys are conducted to gather specialist opinions. The content analysis method is applied to thoroughly study textual and visual content on social media during political campaigns. This approach aims to comprehensively analyse the impact of social media on political campaign sand determine the factors that contribute toits effectiveness.
Results: The article reveals strategies for influencing social media on political campaigns based on obtained data. It highlights key aspects of their impact, such as interactivity, microtargeting, and the use of viral content. The research also considers legal and sociological aspects of this phenomenon, including the regulation of social campaigns and criteria for the acceptability or unacceptability of certain strategies.
Conclusions: Thearticleanalyses social media's influence on political campaigns, exploring different strategies for utilising these platforms and their outcomes. Various methods, such as literature analysis, case studies, expert surveys, and content analysis, have enabled the systematisation of knowledge about the interaction between social media and political campaigns. Various aspects that influence the effectiveness of social media usage in politics have been identified, including microtargeting, viral content, and interactivity. The text discusses different types of political campaigns, such as electoral, lobbying, and socio-activist, providing the reader with a deep understanding and contextualisation of the issue.
Management information-Communication Technologies in Modern Political Conflicts: An Analysis of Their Impact on Society
Authors: Valentyn Koliechkin
Published: February 2025

Introduction: The article examines the place of communication and broadcasting in today's political conflicts and draws attention to their impact on society. At the same time, political speech, social mobilisation, and affective polarisation are singled out as three essential aspects of the impact of political communication on society.
Objectives: The article aims to examine the place of communication and broadcasting in today's political conflicts, emphasizing their impact on society. The objective is to understand how media and political speech shape the public's perception of conflicts, as well as how these forms of communication affect societal engagement and economic change.
Methods: The first part of the study reflects how the media and the style of political speech influence the public's understanding of political conflicts. At the same time, the second part of the paper presents the results of the impact of political communication on affective polarisation and social mobilisation. The third part of the study focused on political conflicts as catalysts for economic change.
Results: According to this, it was determined that the main trends in the reflection of political conflicts in the media are a decrease in the content load in speeches, the use of emotional narratives, and an increase in influence on voters by demonstrating a strategy for future actions. The Coleman-Liau case study found that political speeches of the last 50 years are less complex in form and content, making it easier for voters to understand the essence of the message. However, the quality of political speeches has declined significantly.
According to the results, citizens are mobilised to increase their political engagement mainly through social media. This can be explained by the fact that social media allow for the public display of information and, simultaneously, grouping voters into specific categories.
This revealed that such conflicts impact the decline in sales of certain goods, the refusal of buyers to use certain goods, and a decrease in tourist flows in certain areas. In addition, it was determined that the study's novelty lies in the study of political speech and communication comprehensively, and thus their impact on society. At the same time, the study was limited to clear regional zones and a specific period for data analysis.
The Influence of Cutting-Edge Technologies on Cybersecurity in Contemporary Public Governance and Management
Authors: Oleksandr Yaremenko
Published: February 2025

Introduction: This research is relevant because it needs to study the impact of innovative technologies on cybersecurity in modern public administration. With the constant development of the digital environment and the increase in cybersecurity threats, maintaining information security becomes a critical task for public institutions.
Objectives: The research aims to analyse and systematise data regarding the impact of innovative technologies on cybersecurity in modern public administration.
Methods: In the course of this research, the method of expert analysis was used to assess the impact of innovative technologies on cybersecurity in public administration. Based on the results of a survey of academic experts in the field of public administration (8 persons) and IT specialists (7 persons), a correlation analysis was conducted between the assessments of the level of cyber protection and the significance of innovative technologies for ensuring cybersecurity.
Results: According to the results of the correlation analysis, a significant degree of correlation with current cybersecurity challenges was found between blockchain technologies and the implementation of remote work (r=0.77 at p<0.05), biometric systems and the shortage of qualified specialists (r=-0.86 at p<0.05), as well as the Internet of Things and the transition to remote work (r=0.93 at p<0.05).
Conclusions: The expert survey results showed that academic experts in public administration (Group 1) focus on adapting national security policies, developing complex cyberattack methods, and needing a systematic approach to digital literacy. At the same time, IT experts (Group 2) emphasise the need to prevent the negative consequences of using cryptocurrencies in financial pyramids and the low level of users’ knowledge of basic cybersecurity principles.
The Potential of IoT for Efficient Environmental Management: An Exploration of IoT Technologies for Precise Monitoring and Resource Management
Authors: Ruslan Ovcharenko
Published: February 2025

Introduction: Given the global environmental pollution, depletion of natural resources, and climate change issues, it is crucial to prioritise stabilising the environmental situation and implementing the concept of sustainable development. In this context, using an efficient environmental monitoring system in conjunction with the fundamentals of environmental management and incorporating modern information technologies is considered a powerful tool for environmental conservation.
Objectives: This research aims to analyse the potential of Internet of Things (IoT) technologies for effective monitoring and resource management with precision aimed at improving environmental productivity.
Methods: The research process employed general methods such as generalisation, systematisation, abstraction, analysis, synthesis, and concretisation.
Results: The study analysed mechanisms for ensuring sustainable development by implementing environmental innovation activities. The functionality of environmental monitoring was identified, and trends in its implementation using IoT were analysed. During the research, software for developing an effective environmental monitoring algorithm was analysed, and the principles of its functioning were determined. The dynamics, issues, and prospects of resource management with precision were substantiated. It has been demonstrated that utilising IoT for effective monitoring enables the tracking of dynamics and identification of potential problems. The aggregated data format is suitable for further analysis.
Conclusions: These research findings can be applied to optimise Ukraine's environmental development strategy by implementing precision resource management, environmental conservation elements, and innovative city management systems.
Enhancing Bandwidth, Gain, and Efficiency of a Compact Cylindrical CDRA Antenna through Geometric Modifications at 28 GHz
Authors: Hussein Turki Alateewe
Published: February 2025

This article presents the design and analysis of a compact Cylindrical Dielectric Resonator Antenna (CDRA) optimized for operation at 28 GHz, a key frequency for 5G and millimeter-wave (mm-wave) applications. The antenna utilizes a compact dielectric resonator with an outer radius of 2 mm and a height of 1.156 mm, made from a material with a relative permittivity (????????) of 12.7. These dimensions and material characteristics ensure a compact size suitable for modern communication technologies and maintain good radiation and field confinement properties. At a feed height (ℎ) of 4.75 mm and width (????????) of 0.7 mm, the feeding structure properly couples to the resonator with a good bandwidth, moderate gain, and radiation efficiency. The proposed design, with the adequate bandwidth for 28 GHz mm-wave transmission, presents a good tradeoff in size versus performance that ensures interoperability with 5G networks. The ???????? values chosen have conserved enough bandwidth and thermal stability along with improved field confinement as well as downsizing of the proposed antenna. Simulation and analysis ensure the suitability of the antenna for high-performance, small-sized applications including satellite communications, IoT, and mobile devices. It has been demonstrated how CDRA designs can be utilized for next-generation wireless systems, which require broadband, small, and efficient antennas, using the CST program in this article. This finding holds significant practical ramifications, especially with the advancement of next-generation wireless communication technologies. For such stringent requirements from 5G and mm-wave technologies, the small Cylindrical Dielectric Resonator Antenna exhibited excellent performance in terms of gain, high bandwidth, and efficiency. Its high bandwidth allows it to offer stable connectivity and fast data transfer, thus allowing for seamless communication in applications that include satellite systems, mobile networks, and the Internet of Things. Its small size easily integrates it in phased array systems and portable devices, which keep up with an increasing demand to have more compact and effective antennas in areas such as space restrictions. The signal losses are much reduced by increased impedance matching as well as an improved radiation efficiency, and as a result, the system performs well overall. These results demonstrate the potential of this proposed design as critical to advancing modern wireless infrastructure through the creation of a practical, high-performance solution for demanding, high-bandwidth applications.
Image Encryption Algorithm Using Differential Equations
Authors: Mohammed Abdul Hameed Jassim Al-Kufi
Published: February 2025

After several prior works in image encryption, where we utilized algebraic mathematical tools within matrix algebra to perform operations that scatter the color values of the image, transforming the image into an encrypted matrix that no longer represents the original image, we decided to explore the field of differential equations as a mathematical tool for image encryption. In this algorithm, we employed third-order ordinary differential equations along with first-degree equations to encode the image. We treated the color values of the original image as coefficients for the independent variable ????. Then, we selected another image as an encryption key, considering its color values as the powers associated with the independent variable ????. This process yielded a system of third-order differential equations, the number of which elements equaled the number of color values in the original image.
We approached this system of differential equations by integrating with respect to the independent variable ???? three times for each system of differential equations obtained, treating the integration constant as zero. Ultimately, we obtained a system of ordinary equations with the independent variable ????, where the coefficients of this variable represented alternative values for the color values of the original image. These coefficients represented a scattering of the color values of the original image, and the new matrix formed by these values represented the encryption matrix for the original image.
For the purpose of decryption and recovering the original image, we referred to the key image used during the encryption process. We followed these steps: We took the numerical values of the encrypted matrix and converted them into coefficients for the independent variable ????. We considered the color values of the key matrix as the powers associated with the independent variable ???? after adding 3 to them. This step yielded a system of ordinary equations with the number of elements corresponding to the number of color values in the original image. Subsequently, we differentiated each equation in the system of ordinary equations mentioned above. We repeated the differentiation process three times, ultimately obtaining a system of differential equations with the independent variable ????, where the coefficients of this variable represented the color values of the image after decryption. These values matched the color values of the original image prior to decryption, confirming that the error value equaled zero.
The results we obtained were excellent and matched high standards of accuracy, which we will discuss later.
Marketing Research of the Territory's Image: on the Example of the ISSYK-KUL Region of Kyrgyzstan
Authors: Nukeeva Medina Anarbekovna
Published: February 2025

This article discusses the process of determining a favorable image and development of a territory (region), as well as its practical development and further functioning.  The image of a region is a spontaneously formed and/or artificially created image of a region that is steadily entrenched in the mass consciousness, under the influence of a set of emotional, rational characteristics, beliefs and feelings of people who arise about the characteristics of a given territory. Image is one of the determining factors of the perception of the territory. The image of the territory allows local authorities effectively to interact with various target groups: the population, tourists, investors, etc.
A positive image of the territory is an important element of ensuring socio-economic stability. This article is devoted to the study of the image of the Issyk-Kul region of Kyrgyzstan.  Issyk-Kul region is a region located in the central part of Kyrgyzstan. It got its name from Lake Issyk-Kul, which is one of the largest mountain lakes in the world. The region is known for its unique nature, picturesque mountain landscapes, clean air and diverse types of vegetation.
From Concept to Application: The Implementation of Slurry Infiltrated Fiber Concrete in Steel Arched Truss Structures
Authors: Mohammed Hadi Jebur
Published: February 2025

The present work focuses on applying Slurry Infiltrated Fiber Concrete (SIFCON) in steel-arched truss construction systems to increase its structural performance and sustainability. SIFCON is a high-performance cement composite containing continuous discrete fibers and possesses attractive mechanical properties such as tensile strength, ductility, and energy absorption capacity. In this study, SIFCON is investigated experimentally as well as numerically with the help of ABAQUS software to determine the effectiveness of this mixture on the bearing capacity, durability, and crack resistance compared to normal concrete. Variations of thickness, fiber mass fractions, and bonding between steel-arched trusses and SIFCON laminates serve as the experimental configuration. The results presented in this study prove that the use of SIFCON laminated structures results in a substantial increase in load-bearing capacity and crack initiation time along with increased durability of the structure and its resistance to failure. These results propose SIFCON as an innovative material for composite construction systems and argue that current infrastructural problems offer a sustainable solution with this material.
The Role of Resonant Leadership in Enhancing Organizational Brilliance Through Organizational Trust (An Exploratory Study at Tikrit University)
Authors: Mohammed Hameed Nayyef
Published: February 2025

The research focuses on "Resonant Leadership and Its Impact on Organizational Brilliance Through Organizational Trust" at Tikrit University in Iraq. The study aims to understand and analyze the influence of resonant leadership styles in enhancing institutional performance, emphasising the role of organizational trust as an intermediary element contributing to this brilliance. The thesis highlights the importance of resonant leadership as a modern framework that enables leaders to foster innovation and institutional cohesion, thereby improving the organization's overall performance. The study adopted a descriptive-analytical approach, designing a questionnaire consisting of 58 items distributed across various axes to survey the opinions of the sample participants regarding the effects of resonant leadership and organizational trust. Among the most significant findings is a positive and influential relationship between resonant leadership and organizational trust, underscoring the necessity of fostering trust within the workplace to achieve exceptional institutional performance. Based on these findings, the study recommends investing in training programs to develop leaders with resonant leadership skills and create a work environment that enhances mutual trust between employees and leaders, thereby positively impacting overall performance.
A Hybrid Domain-Based Digital Watermarking Technique for Robust and Imperceptible Image Copyright Protection
Authors: Omer Bin Hussain
Published: February 2025

This work provides a strong digital watermarking method to attain undetectable and robust watermark embedding by combining many domain transformations and decomposition methods. To guarantee good watermark embedding and retrieval, the technique uses Discrete Wavelet Transform (DWT), Discrete Fourier Transform (DFT), Onion Peel Decomposition (OPD), Discrete Cosine Transform (DCT), and Singular Value Decomision (SVD). Using a strength value, the single values of the carrier picture are changed to incorporate the watermark, therefore guaranteeing low distortion and great imperceptibility. The sequence of transforms is reversed during extraction to faithfully retrieve the watermark. Under several assault scenarios—including JPEG compression, Gaussian noise, salt-and-pepper noise, scaling, cropping, and blurring—a thorough investigation was done to assess resilience. Performance was evaluated using the normalised cross-correlation (NCC) metric—which measures the resemblance between the original and extracted watermark. With an average NCC of 0.99 over all attacks, the proposed system matched or surpassed present state-of- the-art methods. The technique also generated a strong Mean Structural Similarity Index Metric (MSSIM) of 0.9966, the lowest Mean Absolute Error (MAE) of 4.2729, and the highest Peak Signal-to-- Noise Ratio (PSNR) of 36.0477.Comparatively with both random and non-random distribution approaches, comparison with average NCC values of 0.98 and 0.99 correspondingly indicated significant resilience. The random spread method exhibited higher resistance to blurring attacks, even if the non-random spread strategy was best in scaling and cropping attacks. Visual examinations confirmed considerable similarity between the watermarked and retrieved images under all attack scenarios. These results show how effectively the proposed approach balances imperceptibility and robustness, hence ensuring dependability for safe digital watermarking applications in demanding surroundings.
Scaling Influencer Marketing Operations: Legal and Financial Challenges In Managing Large Scale Influencer Network
Authors: Prachi Chaturvedi
Published: February 2025

This study examines the intersection of legal compliance and the use of artificial intelligence (AI) in influencer marketing campaigns. With the growing popularity and reach of influencer marketing, brands are increasingly relying on AI tools to manage large-scale campaigns more efficiently. The research explores the role of legal regulations in influencer marketing and how AI can enhance operational efficiency while ensuring adherence to legal standards. A survey of 647 respondents revealed that legal compliance is viewed as essential for maintaining brand reputation, consumer trust, and avoiding regulatory penalties. The findings show that brands that adhere to legal guidelines in influencer marketing are perceived more favorably by consumers, fostering long-term loyalty. Furthermore, AI’s role in automating the influencer selection process, optimizing campaign performance, and improving decision-making was highlighted as a key driver of efficiency. AI-enabled tools allow organizations to manage influencer networks effectively, reduce time spent on manual tasks, and improve overall campaign outcomes. The study concludes that integrating AI with a strong focus on legal compliance offers a strategic advantage for brands, enabling them to manage influencer marketing campaigns with greater precision and impact. This balance between technological innovation and ethical standards is crucial for the sustained success of influencer marketing in a rapidly evolving digital landscape. The research contributes valuable insights for marketers and organizations aiming to optimize their influencer marketing strategies while ensuring legal and ethical responsibility.
Feature and Decision Levels Fusion for the Synergistic Analysis of Facial Expressions and EEG Signals in the Context of Discrete Emotion Recognition
Authors: Amit S. Ufade
Published: February 2025

The undertaking of brain-computer interface emotion recognition represents a challenging task that demands meticulous thinking in order for machines to discern human emotions and respond appropriately. This work aims to improve the efficacy of individual modalities by incorporating multimodality for emotion recognition, which employs two distinct modalities. Electroencephalogram (EEG) data and facial expressions are used as independent modalities for emotion identification, with each modality evaluated separately. To combine the modalities, decision- and feature-level fusion algorithms are used. While EEG-derived emotions are primarily classified as continuous domains of valence and arousal, facial emotions are primarily classified as discrete emotions, which presents a considerable hindrance to the fusion process. Ashford Bird[10]. present the dataset used for EEG experiments at UKCI-2019.the CFEE dataset serves as the foundation for face emotion recognition for the proposed work[9]. EEG signals are analyzed for statistical properties such as mean, standard deviation, skewness, and kurtosis, while the face emotion dataset is used to identify various action units. Given the large number of features, redundant feature removal approaches are used to determine feature efficacy. Using the product rule, decision-level fusion obtains an accuracy of 80%. Accuracy in feature-level fusion is 94.48% for KNN and 98.66% for SVM classification which are comparatively higher than individual average accuracy of facial expression 88.04% and 90.73% for EEG signal.
The Role of Community Social Capital in Sustainable Peat Management: A Case Study from Tanjung Leban Village, Bengkalis Regency, Indonesia
Authors: Ashaluddin Jalil
Published: February 2025

This study aims to identify activities and challenges as well as analyze the social capital of Disaster Concerned Communities (DCC) in sustainable peat management in Tanjung Leban Village, Bengkalis Regency. This study uses a qualitative methodology to systematically analyze community social capital in sustainable peat management, where the Nvivo 12 Plus software is used to analyze data and answer research questions posed. The results of this study indicate that the activities of the Disaster Concern Community (DCC) in Tanjung Leban Village in preventing forest and peatland fires include three phases of activity, namely the prevention phase (conducting routine patrols in finding hotspots and conducting outreach and education to the community), the extinguishing phase (collective fire suppression activities), and the peatland restoration phase of former burnt areas (planting and land rewetting activities). In the process, these activities still face challenges due to natural factors such as the structure of peat soils and hot weather which tend to be highly flammable, as well as internal (lack of solidarity) and external factors (lack of local government support). Then, the success of Tanjung Leban Village in recent years in reducing the number of land fires is the result of social capital which is dominated by aspects of institutional norms (30.76%), followed by 3 (three) other aspects, namely institutional social networks (23.08 %), institutional identification (23.08%), and trust in institutions (23.08%). Therefore, social capital is a crucial instrument in influencing the success of sustainable peatland management activities. Therefore, this research has an urgency and contribution to peatland management efforts that require strong social capital to influence the success of sustainable peatland management activities.
Spontaneous Micro-facial Expression Detection using Attention-based Convolutional Gated Recurrent Neural Networks with RMSProp Optimization
Authors: Ramakrishna Gandi
Published: February 2025

Introduction: Facial micro expressions have a significant role in communicating hidden emotions, offering profound implications in multiple areas such as psychology, cybersecurity, and the study of human-computer interaction. However, recognizing micro-expressions is tough because of their transient nature. Furthermore,Micro expressions are significantly shaped by the visual characteristics of the face and the interactions among its various sub-regions. Recent advances in computer vision have improved self-supervised learning.
 Traditional CNNs for vision disorders learn only from whole photos or videos and cannot consistently distinguish facial micro expressions. Some existing CNN models might  lack advanced attention mechanisms to effectively prioritize subtle micro-expression features within the complex facial data. They may leading to potential misinterpretation of expressions.
Objectives: This research offers the Attention Convolutional Gated Recurrent Neural Network with RMSProp (ACGRNN- RMSProp) classifier aims to achieve high accuracy and robustness in micro facial expression recognition. The attention mechanism sharpens the model's emphasis on important facial regions, while convolutional layers gather spatial features, and GRUs effectively capture temporal dynamics. The RMSProp optimizer ensures efficient and stable training, making this approach well-suited for the complex task of recognizing subtle and fleeting micro expressions.. This suggested approach is applied to the FER2013 dataset and compared to conventional micro expression recognition baseline methods.
Methods: The FER2013 dataset is initially loaded and processed. Facial landmarks in this dataset are detected using a Multi-Task Cascaded Convolutional Neural Network, after which features are extracted from the processed data using EfficientNetB3 and InceptionResNetV2. The features obtained from extraction are then fused and subsequently classified using an Attention Convolutional Gated Recurrent Neural Network with RMSProp optimization.
Results:This hybrid model demonstrates exceptional classification performance, achieving precision, recall, and F1-score of 94.5% each, along with an accuracy of 96.43%. Furthermore, it includes additional metrics such as the Matthews Correlation Coefficient (MCC), Receiver Operating Characteristic(ROC) Curve in this field.
Conclusions:This study showcases enhanced recognition accuracy when compared to a range of leading models in the field,eliminated the requirement for system preprocessing procedures such as contrast enhancement, gradient operators, or dimensionality reduction for accurate results.Leverage the inherent relationships between face identification and other face analysis tasks to enhance future performance.