bluuebunny/crossref_metadata_2025 huggingface dataset:
ANFIS-AMAL: Android Malware Threat Assessment Using Ensemble of ANFIS and GWO
Authors: Nwasra Nedal , Daoud Mohammad , Qaisar Zahid Hussain
Published: September 2024

The Android malware has various features and capabilities. Various malware has distinctive characteristics. Ransomware threatens financial loss and system lockdown. This paper proposes a threat-assessing approach using the Grey Wolf Optimizer (GWO) to train and tune the Adaptive Neuro-Fuzzy Inference System (ANFIS) to categorize Android malware accurately. GWO improves efficiency and efficacy in ANFIS training and learning for Android malware feature selection and classification. Our approach categorizes Android malware as a high, moderate, or low hazard. The proposed approach qualitatively assesses risk based on critical features and threats. Our threat-assessing mechanism’s scale categorizes Android malware. The proposed approach resolves the issue of overlapping features in different types of malware. Comparative results with other classifiers show that the ensemble of GWO is effective in the training and learning process of ANFIS and thus achieves 95% F-score, 94% specificity, and 94% accuracy. The ensemble makes fast learning possible and improves classification accuracy.
A Systematic Review of Rapidly Exploring Random Tree RRT Algorithm for Single and Multiple Robots
Authors: Muhsen Dena Kadhim , Raheem Firas Abdulrazzaq , Sadiq Ahmed T.
Published: September 2024

Recent advances in path-planning algorithms have transformed robotics. The Rapidly exploring Random Tree (RRT) algorithm underpins autonomous robot navigation. This paper systematically examines the uses and development of RRT algorithms in single and multiple robots to demonstrate their importance in modern robotics studies. To do this, we have reviewed 70 works on RRT algorithms in single and multiple robot path planning from 2015 to 2023. RRT algorithm evolution, including crucial turning points and innovative techniques, have been examined. A detailed comparison of the RRT Algorithm versions reveals their merits, limitations, and development potential. The review’s identification of developing regions and future research initiatives will enable roboticists to use RRT algorithms. This thorough review is essential to the robotics community, inspiring new ideas, helping problem-solving, and expediting single- and multi-robot system development. This highlights the necessity of RRT algorithms for autonomous and collaborative robotics advancement.
Exploring the Efficacy of GenAI in Grading SQL Query Tasks: A Case Study
Authors: Hamtini Thair , Assaf Abdelbaset J.
Published: September 2024

Numerous techniques, including problem-solving, seeking clarification, and creating questions, have been employed to utilize generative Artificial Intelligence (AI) in education. This study investigates the possibility of using Generate AI (GenAI) to grade Structured Query Language (SQL) queries automatically. Three models were used which are ChatGPT, Gemini, and Copilot. The study uses an experimental approach to assess how well the models perform in evaluating student responses by comparing the models’ accuracy with those of human experts. The results showed that despite some inconsistencies, GenAI holds great promise for streamlining. Thus, further research is required in light of inconsistent GenAI performance. If these issues were resolved, GenAI can be utilized in education. However, human oversight and ethical issues must always come first.
Sentiment Analysis of Product Reviews Using Transformer Enhanced 1D-CNN and BiLSTM
Authors: Rana Muhammad Rizwan Rashid , Nawaz Asif , Ali Tariq , Alattas Ahmed Saleh , AbdElminaam Diaa Salama
Published: September 2024

The rapid growth of Internet-enabled applications, such as social media platforms, e-commerce sites, and blogs, has led to a surge in user-generated content. This vast amount of data has made sentiment analysis increasingly valuable. Modern Aspect-Based Sentiment Analysis (ABSA) offers a more detailed approach by identifying sentiment trends related to specific aspects within the text. However, the challenge lies in analyzing reviews that are often short, unstructured, and filled with slang and emotive language, making it difficult to gauge customer opinions accurately. To address these issues, we proposed an effective hybrid approach “RoBERTa-1D-CNN-BiLSTM” for ABSA. Initially, the pre-trained Robustly Optimized BERT approach (RoBERTa) and One Dimensional Convolutional Neural Network (1D-CNN) models are used to extract features at the aspect level from the context of the review, following which classification is performed using Bidirectional Long Short-Term Memory (BiLSTM). The approach is evaluated on three cross-domain standards datasets, yielding an accuracy of 92.33%. The results of the experiments show that it surpasses the current leading methods in sentiment analysis and product recommendation.
Managing Cybersecurity: Digital Footprint Threats
Authors: Ketipov Rumen , Schnalle Roman , Doukovska Lyubka , Dehez Dustin
Published: September 2024

Managing cybersecurity and protecting data assets remain top priorities for businesses. Despite this, numerous data breaches persist due to malicious human actions, resulting in significant financial setbacks. However, many cybersecurity strategies overlook invisible or indirect threats within their scope, such as digital footprints. This paper examines the relationship between personality traits and user behavior concerning cybersecurity. The study suggests that human personality can be predicted using innovative techniques based on the digital hints individuals leave on the internet. Consequently, this information can be exploited for malicious actions against entities. As proposed, an effective strategy for improving behaviors and cultivating a security-oriented culture involves continually identifying relevant sources of cyber risks and implementing continuous awareness initiatives.
AHT-QCN: Adaptive Hunt Tuner Algorithm Optimized Q-learning Based Deep Convolutional Neural Network for the Penetration Testing
Authors: Railkar Dipali , Joshi Shubhalaxmi
Published: September 2024

Penetration Testing (PT), which mimics actual cyber attacks, has become an essential procedure for assessing the security posture of network infrastructures in recent years. Automated PT reduces human labor, increases scalability, and allows for more frequent evaluations. Real-world exploitation still challenges RL-based penetration testing because the agent’s many possible actions make it hard for the algorithm to converge. To resolve these shortcomings, a deep learning- model named Adaptive Hunt Tuner algorithm optimized Q-learning based deep Convolutional neural Network (AHT-QCN) is developed for efficient PT. Specifically, the Q-learning employed in this model improves its efficiency by enabling optimal policy learning for decision-making. In addition, the Adaptive Hunt Tuner (AHT) algorithm enhances the model’s performance by tuning its parameters with reduced computational time. The experimental outcomes demonstrate that the developed model attains 95.25% accuracy, 97.66% precision, and 93.81% F1 score.
Game Theory in the Realm of Pop Culture: A Novel Approach to Social Media Strategy
Authors: Talajić Mirko , Vrankić Ilko , Matić Lucia
Published: September 2024

This paper explores the intersection of game theory and pop culture as a potent strategy for amplifying social media engagement. A methodological analysis demonstrates how game theory principles can be effectively applied to social media campaigns by leveraging the universal appeal of pop culture. The study introduces a simple yet illustrative model that outlines the strategic use of pop culture elements to attract new followers and maximise net profit, considering variables such as potential follower base, cost of pop culture integration, and the preferences of different audience segments towards pop culture-infused products. Findings underscore the untapped potential of conscious game theory application in social media strategy design, offering a fresh perspective on achieving optimal engagement through a balance of appeal to pop culture enthusiasts and those favouring traditional content. This contribution is novel in its approach. It provides a comprehensive review of game theory’s utility in pop culture and presents a detailed framework for its application in social media campaigns. By bridging theoretical concepts with practical application, this research opens new avenues for strategic engagement in the digital age, making a significant addition to both academic research and practical marketing strategies.
A New Application with Conditional Risk Matrix and Decision Rules: An Assessment of the Sustainability and Performance Electric Power Company
Authors: Couto Ayrton Benedito Gaia do , Rangel Luís Alberto Duncan
Published: September 2024

The 2030 Agenda for Sustainable Development of the United Nations General Assembly focuses on economic development, poverty cessation, environmental sustainability, and good governance at all levels, including peace and safety. For electric power distribution concessionary companies in Brazil, it is necessary to evaluate their sustainability and performance according to the parameters laid by the National Electric Power Agency (ANEEL). For that purpose, sixty-two indicators were assembled that were directly and indirectly associated with sustainability for 38 companies in the period–2013-2021. This study proposes a new application with a conditional risk matrix and decision rules aimed at the integrated assessment of sustainability and performance of electric power companies using the conditional probability of indicators in the ascent or descent of the companies’ classification. A set of “if..., then...” decision rules were inferred by the algorithm VC-DomLEM using concepts from the Rough Sets Theory and the Dominance principle, Dominance-based Rough Set Approach (DRSA).
CC-De-YOLO: A Multiscale Object Detection Method for Wafer Surface Defect
Authors: Ma Jianhong , Zhang Tao , Ma Xiaoyan , Tian Hui
Published: September 2024

Surface defect detection on wafers is crucial for quality control in semiconductor manufacturing. However, the complexity of defect spatial features, including mixed defect types, large scale differences, and overlapping, results in low detection accuracy. In this paper, we propose a CC-De-YOLO model, which is based on the YOLOv7 backbone network. Firstly, the coordinate attention is inserted into the main feature extraction network. Coordinate attention decomposes channel attention into two one-dimensional feature coding processes, which are aggregated along both horizontal and vertical spatial directions to enhance the network’s sensitivity to orientation and position. Then, the nearest neighbor interpolation in the upsampling part is replaced by the CAR-EVC module, which predicts the upsampling kernel from the previous feature map and integrates semantic information into the feature map. Two residual structures are used to capture long-range semantic dependencies and improve feature representation capability. Finally, an efficient decoupled detection head is used to separate classification and regression tasks for better defect classification. To evaluate our model’s performance, we established a wafer surface defect dataset containing six typical defect categories. The experimental results show that the CCDe-YOLO model achieves 91.0% mAP@0.5 and 46.2% mAP@0.5:0.95, with precision of 89.5% and recall of 83.2%. Compared with the original YOLOv7 model and other object detection models, CC-De-YOLO performs better. Therefore, our proposed method meets the accuracy requirements for wafer surface defect detection and has broad application prospects. The dataset containing surface defect data on wafers is currently publicly available on GitHub (https://github.com/ztao3243/Wafer-Datas.git).
On feature extraction using distances from reference points
Authors: Piernik Maciej , Morzy Tadeusz , Susmaga Robert , Szczęch Izabela
Published: September 2024

Feature extraction is the key to a successfully trained classifier. Although many automatic methods exist for traditional data, other data types (e.g., sequences, graphs) usually require dedicated approaches. In this paper, we study a universal feature extraction method based on distance from reference points. First, we formalize this process and provide an instantiation based on network centrality. To reliably select the best reference points, we introduce the notion of θ-neighborhood which allows us to navigate the topography of fully connected graphs. Our experiments show that the proposed peak selection method is significantly better than a traditional top-k approach for centrality-based reference points and that the quality of the reference points is much less important than their quantity. Finally, we provide an alternative, neural network interpretation of reference points, which paves a path to optimization-based selection methods, together with a new type of neuron, called the Euclidean neuron, and the necessary modifications to backpropagation.
Prioritizing Vulnerability Factors of Global Food Supply Chains by Fermatean Fuzzy Analytical Hierarchy Process
Authors: Yalcin Selin , Ayyildiz Ertugrul
Published: September 2024

In response to heightened competition arising from globalization, companies are crafting strategies to sustain their operations. However, these strategies also introduce risks that require meticulous management. The onset of the COVID-19 pandemic has exacerbated disruptions in supply chains, including the vulnerable food supply chain (FCS), strained further by escalating food prices and resource depletion in recent times. Within this context, the vulnerability of global FSCs has escalated significantly due to government-imposed lockdowns during the pandemic. This study aims to comprehensively investigate the multifaceted disruptions in global FSCs caused by the COVID-19 pandemic. By delving deep into the complexities of these disruptions, it seeks to uncover the key factors contributing to the vulnerability of supply chains. Employing a blend of literature review and expert opinions, the study identifies and prioritizes factors using the Fermatean Fuzzy Analytical Hierarchy Process (FF-AHP). A two-level criteria framework consisting of three main criteria and eleven sub-criteria has been developed, taking into account expert recommendations and previous studies. According to the results obtained, it has been revealed that the Managerial factors within the main criteria are the most significant factors in the fragility of the FSC. Among these factors, it has been observed that Technology, Corporation, and Inventory Management are the leading criteria causing to the vulnerability of the FSC. This is the first study to investigate the vulnerabilities of FSC using fuzzy logic. The research underscores the imperative of comprehensive risk management strategies that encompass all stakeholders within the supply chain, particularly during unanticipated crises like pandemics.
Occurrence of Ochratoxin in Complete Feed Mixtures for Monogastric Animals
Authors: Harčárová Michaela , Naď Pavel , Šamudovská Alena Hreško , Bujňák Lukáš
Published: September 2024

Ochratoxin A is a foreign substance of natural origin. It can be found in a wide range of commodities, including animal feed. Ochratoxin A is a dangerous contaminant, which can have a negative effect on the health and production of animals. In this study, the incidence of ochratoxin A in a complete feed for broilers (n = 25) and pigs (n = 6) was determined. Ochratoxin A was detected in one sample of pigs feed (16.67 %) and its concentration was 1.221 µg.kg−1. This mycotoxin was not detected in the broiler feed samples. These results indicate that the feed samples collected were safe and do not pose a risk of acute mycotoxicosis in animals.
Occurrence of Cryptosporidium Oocysts in Faeces, Milk and Water Sources in Sedentary Fulani Herds in Selected Local Government Areas of Kaduna State, Nigeria
Authors: Esonu Daniel O. , Kabir Junaidu , Jatau Isa D. , Lawan Mohammed K. , Yusuf Mohammed S. , Aliyu Mohammed B. , Yusuf Fatima L.
Published: September 2024

Cryptosporidiosis is a neglected tropical zoonotic disease, commonly associated with a diarrhoea, caused by a protozoan parasite of the genus Cryptosporidium. The aim of this study was to determine the occurrence of Cryptosporidium oocysts in faeces, milk, and water sources, and its associated risk factors in sedentary Fulani herds. Seven hundred and fifty faecal samples (240, 180, 240 and 90 from cattle, sheep, goats and dogs, respectively), and 120 samples each, of milk and water were collected for this study. Faecal samples were concentrated by formol ether concentration technique, then stained using Modified Ziehl Neelsen staining method, to detect Cryptosporidium oocysts. Cryptosporidium oocysts in milk and water samples were also concentrated and stained with same stain. The prevalence of Cryptosporidium oocysts in (cattle, dog, sheep and goat faeces were 18.3 %, 15.6 %, 13.9 % and 4.2 %, respectively.), Significantly higher prevalence was observed in calves ≤ 1 year (P = 0.002), female cattle (P = 0.007) and animals with poor body condition (P < 0.001) than in the other groups. Goats with poor body condition scores had significantly higher prevalence (P = 0.008) than other groups while dogs ≤ 6 months of age also had significantly higher prevalence (P = 0.03) than older dogs. The prevalence of Cryptosporidium oocysts in bulk cow milk was 11.7 % while a prevalence of 13.3 % was observed in the water bodies sampled. Hence the findings of this study are of great public health significance, therefore, inhabitants of these LGAs should be informed and educated on the need for improvement of sanitary measures during the course of milking these animals, and the need for adequate pasteurization, of milk before consumption.
Serum Biochemistry and Haematology Alterations in Sled Dogs Before and After a Race
Authors: Faixová Zita , Lyng Cecilie , Faixová Dominika , Szabóová Renáta
Published: September 2024

Long-distance sled dogs are known for their great endurance and ability to run several hundred kilometres over the course of a few days. There are several factors to consider when selecting a team of high-performing sled dogs, including their physique, body score condition, appetite, paws, and ability to adapt to unknown environments and situations. The most common breed used in sled dog racing, Alaska Huskies, are known for their great work diligence, and determined mindset. It has previously been researched how well these dogs endure such intense physical activity using observation of behavioural patterns, physical examinations, and the analysis of alterations in blood parameters. This study aimed to evaluate serum chemistry and haematology alterations in dogs before and after completing a 300 km race in Norway. Changes were observed in haematology and serum chemistry between pre- and post-race blood sampling. Significant increases were observed in the white blood cell count, haemoglobin in blood and creatine phosphokine activity in serum (CK), and significant decreases were seen in the electrolytes (e.g., chlorides, potassium), cholesterol levels, liver (e.g., alkaline phosphatase) and pancreatic enzymes (α-amylase, lipase), and total red blood cell count. Several other parameters were measured, and resulted in insignificant changes. Our results indicated that long-distance racing, in fact, has an impact on the physiology of the dog, influencing muscular system, the gastrointestinal tract, electrolyte balance and haematopoiesis among others.
Breeding Perspective and Analysis of Utility Parameters of the Suffolk Sheep Breed
Authors: Gondová Martina , Zigo František , Farkašová Zuzana , Vargová Mária , Lacková Zuzana , Regecová Ivana , Récky Andrej , Pecka-Kielb Ewa
Published: September 2024

Due to insufficient appreciation for the breeding of dairy sheep, breeds of sheep without market milk production have started to gain popularity in Slovakia. Particularly, meat breeds are coming to the forefront, with their breeding being less demanding and more efficient, reflected mainly in the daily weight gains of growing lambs. Study aimed to analyse the utility and reproductive parameters of breeding the meat breeds Suffolk, located in central Slovakia, in the Rimavská Sobota district. Analysis is supplemented by a detailed description of the breed standard and devotes attention to all the tasks carried out on the farm during the sheep farming year. It focuses mainly on a simple year-round grazing system without housing, utilizing only shelters for protection against adverse weather conditions. Analysed utility and reproductive parameters such as average daily gains, loin muscle thickness, backfat thickness, and fertility were compared and evaluated over the last seven years. Results indicate that the evaluated parameters are mainly influenced by the size of the flock, the number of ewes put to ram, the individual approach to each breeding ewe, and environmental factors. Number of offspring is mainly influenced by the nutrition of the dam in the last third of pregnancy. Despite the simplicity of the breeding system, monitored breeding can achieve above-average results with proper management and innovative approaches.
Effect of Electromagnetic Wi-Fi Radiation On The Development Of Chicken Embryo
Authors: Almášiová Viera , Andrašková Sandra , Bučko Matúš , Holovská Katarína
Published: September 2024

Significant technological progress in the field of wireless devices that were primarily intended for military purposes, has resulted in their common manipulation by the general population. Wi-Fi, mobile phones, and other modern devices offer many advantages to their users. On the other hand, their excessive usage creates an environmental burden, also known as electrosmog. The objective of our current study was the observation of the Wi-Fi radiation effect on the histo-logical structure of the organs in the 9-day-old chicken embryo. On day 9 of incubation, the embryological material was routinely processed for preparation of hematoxylin-eosin, picrosirius red and periodic acid Schiff stained histological sections. Radiation with a frequency of 2.4 GHz and average power density of 300 µW.m−2 applied during the entire development up to the 9th embryonic day did not fundamentally affect general organogenesis. However, in the parenchyma of organs such as the liver, spleen, lungs, kidneys, and gonads, as well as in the developing mesenchyme, obvious vascular congestion of the blood vessels of different caliber was observed. Also, an increase in collagen and glycosaminoglycans production in the cartilaginous matrix and perichondrium of the future bone skeleton as well as developing connective tissue was noted. Although these morphological changes were just subtle, they point to the Wi-Fi radiation’s ability to influence the histogenesis of the individual.
Analyzing the Impact of Fiscal and Monetary Policies on Income Distribution in Central Asian Economies
Authors: Azam Muhammad , Khan Zulfiqar , Ibrahim Yusnidah
Published: September 2024

This study examines the impacts of macroeconomic policies (i.e. fiscal policy through government consumption spending and total tax revenue, and monetary policy through broad money and real interest rate) along with other regressors such as inflation, Gross Domestic Product (GDP) per capita, remittances, exchange rate, and financial development on income distribution in four Central Asian countries from 1995 to 2020. After conducting unit root tests, the Autoregressive Distributed Lag (ARDL)/Pooled Mean Group (PMG) approach was implemented for empirical analysis. The results show that both fiscal and monetary policies have positive and negative effects on income inequality. Moreover, inflation is found to increase income inequality, while financial development, higher levels of per capita income, and foreign remittances decrease inequality in the panel and individual country analyses. These findings suggest that coordinated policies, along with increased remittances and financial sector development, are needed to reduce income inequality.
Decision-Making Framework for Improving Bank Performance in Emerging Markets: The Analysis of AHP-TOPSIS and AHP-GRA Models
Authors: Hussain Sabbor , Chen Jo-Hui , Hussain Talib
Published: September 2024

This study utilizes the Analytic Hierarchy Process (AHP) in combination with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Grey Relational Analysis (GRA) models to thoroughly assess the performance of banks in China, India, Pakistan, and Thailand. The integrated results offer significant insights into the relative rankings of various banks in each country. In China, Bank of China Ltd (BOC) emerges as the top performer, setting a benchmark for others. Similarly, in India, the State Bank of India is consistently identified as the leading bank. The National Bank of Pakistan stands out as the top performer in Pakistan. In Thailand, despite minor deviations in results, Kasikornbank PCL (KBANK) consistently shows strong performance. The alignment of results between AHP-TOPSIS and AHP-GRA underscores the reliability of both models, providing stakeholders and decision-makers with a comprehensive understanding of bank performance. This enables them to identify benchmarks, leverage strengths, and address areas for improvement within each country’s banking sector.
Does an Independent Central Bank Smooth Exchange Rate Volatility? Evidence from Time-Varying Panel Causality Analysis
Authors: Yıldırım Durmuş Çağrı , Esen Ömer , Çınar Uğur
Published: September 2024

This paper empirically examines the effect of the central banks independence on exchange rate volatility by using a large data-set for the E7 (7 emerging countries) covering the period 1998-2017. This paper applies the time-varying panel causality analysis to obtain country-based results. The results show that the policy design, with relatively independent central banks, provides supportive results for macroeconomic stability. It is concluded that policies focusing on current problems by ignoring macroeconomic stability, such as the 2008 crisis, have eliminated the relationship between bank independence and stability.
Military Command In Multi-Domain Environment
Authors: Fazekas Ferenc
Published: September 2024

The practice of military command roots in the past. There were always trends to follow the footsteps of the great captains of earlier eras such as Alexander the Great, Caius Julius Caesar or Napoleon Bonaparte. With the birth of the modern scientific method historians and theorists tried to identify the essence of good leadership and the personal requirements of being a good leader. In the 18th century the notion of coup d’oeil and of the military genius were considered the key to success on the battlefield. The military education traditionally focused on the development of leadership skills, but the skills and practices being taught were drawn from experiences of previous military engagements and exercises. In periods of peace command experience stagnates or even deteriorates due to lack of combat experience, meaning that the command practices lose their touch with the realities of the present. This article argues that the growing complexity of the operational environment requires the alteration of the existing command practices and military education agenda to create leaders capable of achieving the desired successes in future wars. In our view a highly digitalized multi-domain command post requires a certain kind of leaders that beside tactical and operational proficiency must have a skill to efficiently apply the available high-tech assets, the digital coup d’oeil.
Psychological Operations During the Russian War of Aggression in Ukraine
Authors: Stancu Marian Nicușor , Căzănaru George
Published: September 2024

The article analyzes the way and motivation of the Russian Federation to carry out psychological operations in the war of aggression that it has unleashed in Ukraine from the perspective of the information environment. These operations are specific to the cognitive layer of the information environment and are aimed at influencing the perceptions, behavior, and decisions of both the Ukrainian population and the international community by using disinformation, propaganda, and manipulation. By analyzing these operations, it highlights how Russia has exploited the lack of robust regulation of social networks. The analysis underlines the importance of developing effective strategies to counter these operations by increasing information resilience and strengthening protection mechanisms against harmful external influences.
Leveraging Geo-Profiling to Address Rape as a Public Health and Criminal Epidemic in the United States
Authors: Haley Patricia , Burrell Darrell Norman
Published: September 2024

Rape, as a pervasive societal issue, transcends the boundaries of public safety, criminal justice, legal jurisprudence, and public health, casting a long shadow of fear, trauma, and profound consequences across communities. This article delves into the multifaceted nature of rape, recognizing it not solely as a criminal phenomenon but as a complex public health crisis demanding comprehensive intervention. In response to the imperative of addressing rape and serial rapists as a criminal and public health epidemic, this study introduces an innovative approach that harnesses the potential of artificial intelligence (AI) and geo-profiling. Through synthesizing criminological and epidemiological insights, this research elucidates the transformative role of geo-profiling in understanding, preventing and solving rape crimes. Geo-profiling data analytics capabilities are harnessed to dissect the intricate details, patterns and dynamics of rape incidents, offering a data-driven foundation for preventive strategies.

Moreover, integrating geo-profiling techniques empowers law enforcement and public health agencies to map high-risk behaviors, areas and optimize resource allocation geographically. This holistic approach advances our understanding of rape as a public health crisis and informs targeted, evidence-based interventions to reduce its prevalence. In a contemporary landscape marked by the imperative of innovation and interdisciplinarity, this article contributes a nuanced perspective to the discourse surrounding rape. By unifying law enforcement, criminal justice, legal, and public health paradigms and harnessing geo-profiling as a powerful tool, we embark on a path to address rape comprehensively, recognizing its profound impact on individuals and society.
Do Students Know How to Learn? Differences Between Students Regarding the Dimensions of Learning to Learn Competence
Authors: Matei Florentina Lavinia , Lincă Florentina Ionela
Published: September 2024

The ability to learn how to learn is essential for academic performance. The objective of this study was to identify the differences between the 1st, 2nd and 3rd year undergraduate students depending to the dimensions of learning to learn competence. The results showed that there are statistically significant differences between the students from the 1st, 2nd and 3rd year of studies according to the dimensions of the competence to learn how to learn. Our results can be used by teachers. They can adapt the information so that the students develop this competence.
Incorporating Social and Emotional Learning in the English Classes at Military Academies
Authors: Mihăilă Lică Gabriela
Published: September 2024

As military students navigate the demanding transition to the post-pandemic learning environment, there is a growing recognition of the importance of addressing social and emotional learning (SEL) needs. Drawing on existing literature as well as on empirical evidence, the present paper focuses on the unique benefits that this type of learning has for cadets and on the potential that foreign language classes can have as a platform for promoting Social and Emotional Learning competencies such as more involvement in the English classes, an increased resilience level, better relationship skills, or increased academic performance. The article also presents some potential challenges for the implementation of SEL in English classes at military academies, including alignment with existing curriculum standards, faculty training and support, and assessment of SEL outcomes. Furthermore, the paper suggests modalities in which SEL can be incorporated in the English classes by means of projects, role-plays, problem solving, etc. and pinpoints the role that educators play in facilitating SEL integration. By addressing these challenges and capitalizing on the expertise of teachers and military leaders, academies can create inspirational learning environments that promote the social, emotional, and academic growth of their cadets, preparing them for the 21st century.
Aspects of the Developing Process Organization and Handling Changes in the Automotive Industry − Enhancing Risks and Safety Principles
Authors: Hugyi Milán , Takács István
Published: September 2024

The relationship between the basic elements of the enterprise (5M) is again worth focusing on, as the scarcity of resources (tangible and intangible) is increasing and the management of these resources within the walls of companies is becoming more and more acute. In this context, the issue of security permeates our daily lives, not only in the corporate world. The question is: how can we create greater security in our daily and professional lives, and what can fundamentally determine our opportunities in the corporate hierarchy? In the following, you can read about my research on the corporate security climate in automotive companies in Hungary.
The Impact of Blockchain on Critical Transport Infrastructure – The Case of Aviation
Authors: Vevera Adrian-Victor , Georgescu Alexandru
Published: September 2024

Critical Infrastructures produce critical goods and services for society and cover a wide range of sectors according to the governance frameworks in place in the United States, in the European Union (EU) and in EU Member States including Romania. Aviation is a particular case for the critical transport infrastructure, with a high degree of technical complexity, economic productivity and complex supply and production chains. Blockchain or Distributed Ledger is an already famous digital emerging technology with the possibility of disintermediating numerous system processes, thereby reducing costs, increasing security and reducing risk in a world where cumbersome and expensive intermediaries are required for trust in all sorts of transactions. This article provides a brief overview of the critical air transport infrastructure and of the blockchain technology, traces the possible uses of blockchain in aviation, gives real world examples and concludes with recommendations for practitioners moving forward.
INTERNATIONAL AGENCY INVOLVEMENT WITHIN HANDLING ROHINGYA REFUGEES IN ACEH: FOR THE FUTURE SOLUTIONS
Authors: Kadir M. Yakub Aiyub , Kesuma T. Meldi , Siregar M. Ridha , Halim Hendra , Siregar Muhammad Rizqi , Humaira Radhia , Nisva Raisa Ullya , Saddaq Mizan
Published: September 2024

This study explores the management of Rohingya refugees in Aceh, focusing on the roles and responsibilities of key stakeholders such as UNHCR and IOM. Utilizing qualitative methods, including interviews and field observations, the research identifies challenges and potential solutions related to refugee management. Findings reveal that UNHCR is pivotal in providing protection and essential aid to Rohingya refugees, including registration, documentation, and necessities. Meanwhile, IOM plays a crucial role in facilitating orderly migration and human rights advocacy. The study also highlights a shift in local attitudes towards refugees, influenced by media misinformation and political motivations. Both organizations collaborate with the Indonesian government and local NGOs to address these issues, but there is a pressing need for more comprehensive and long-term strategies. Recommendations include improving communication strategies, enhancing integration programs, and addressing the root causes of displacement. The study underscores the necessity for a coordinated approach to support and protect Rohingya refugees and suggests avenues for future research to refine these strategies and improve outcomes for displaced populations.
Exploring Natural Convection and Entropy Generation in a Closed Water Tank Utilizing Nanofluid: a Computational Study
Authors: Benabderrahmane Amina , Boukhari Ali , Siqueira Antonio Marcos de Oliveira , Brito Rogério Fernandes , Khechekhouche Abderrahmane , Campos Julio Cesar Costa , Smakdji Nafila , Mostefaoui Omar , Silva José Antônio da
Published: September 2024

Theoretical framework: This study presents a comprehensive investigation into three-dimensional natural convection within a confined cavity filled with an alumina-water nanofluid.
 
Objective: Utilizing numerical simulations, we explore the influence of nanoparticles' volume fraction and Rayleigh number () on entropy generation, heat transfer efficiency, and fluid behavior within the water tank.
 
Method: The study delves into the conservation equations governing mass, momentum, and energy within the context of three-dimensional laminar natural convection. It focuses on steady, incompressible flow, employing the Boussinesq approximation to account for variations in fluid density due to temperature gradients.
 
Results and conclusion: Our findings indicate that increasing Rayleigh numbers lead to heightened entropy generation, with values ranging from  to, primarily driven by intensified buoyant flow. However, the presence of nanoparticles significantly mitigates entropy generation, enhancing the overall thermal performance of the system. Moreover, nanofluids demonstrate superior heat transfer capabilities compared to pure fluids, with higher nanoparticle concentrations resulting in increased heat transfer rates, ranging from  to  alumina.
 
Research implications: As a result of such thorough research, qualitative examinations of velocity fields and entropy generation patterns further highlight the role of nanofluids in improving heat transfer efficiency while reducing irreversible processes within the cavity.
Assessment of Climate Change Mitigation Potential for Heating System in Kosovo
Authors: Kola Luan , Ajredinin Fadil , Bajraktari Egzon , Kabashi Skender
Published: September 2024

Objective: In this study is we have provided a prediction model for the improvement of heating system in Kosovo, following the implementation of an energy efficiency program, the consumption of energy commodities in heating system will decrease and the problem of deforestation will be mitigated.
 
Theoretical Framework: We suppose a degree of reduction variable due to the renewable energy sources use, new technology options and energy efficiency toward GHG and air pollution reduction and policy initiative for District Heating in Kosovo.
 
Method: For modelling impacts of the technology and policy options for reducing GHG and air pollution due to improvement of heating system in Kosovo, the model STELLA software has been used. Projection for emission factors and total annual emission for Air Pollutants and GHG (CO2) are calculated with US EPA methodology
 
Results and Discussion: The resulting reductions of Air pollutants and greenhouse gas emissions by reducing the loss of heat and water and increasing the energy efficiency will have a direct and positive impact on the environment and climate change.
 
Research Implications: Implementing the emission reduction policies EE, Renewable energy and introducing new technologies in heating system in Kosovo for the total emission of CO2, we will have reduction for about 20% (3.36 Mt CO2) in 2025 in comparison with (4.41 Mt CO2) in year 2015; also, we will have a significant reduction for other GHG.
 
Originality/Value: This study contributes to the literature by impruvemment of heating system in Kosovo.
Technological Scenarios for Educational Inclusion: Digital Gaps in Colombia and Guatemala
Authors: Santos Alba Ruth Pinto , López Ana María Saavedra , Velásquez Olga Lucia Agudelo
Published: September 2024

Objective: The purpose of this study is to characterize and compare the main technological scenarios for digital inclusion in educational institutions in Colombia and Guatemala.
 
Method: The methodological approach of the study was empirical-analytical, with a non-experimental, cross-sectional descriptive design. A non-probabilistic sample of 469 Educational Institutions from the countries under study was used. The data collection instrument was a questionnaire titled "Characterization of ICT Scenarios," which was previously validated by 8 experts.
 
Results and Discussion: Among the main results of the study are the digital gaps detected between rural and urban areas, the limited availability of technological equipment and internet connectivity, and the lack of training for their use in educational inclusion processes.
 
Research Implications: This study helps to understand that both countries face similar challenges in optimizing technological scenarios in educational institutions and the need to implement specific policies and strategies to improve access to technology to promote digital inclusion processes.
 
Originality/Value: The importance of this research is manifested in the comparative presentation of digital gaps in terms of accessibility, connectivity, and use of digital technology in educational institutions in two Latin American countries.
Development of a methodology for increasing the efficiency of determining defects in rolling bearings of shipboard equipment
Authors: Лойко Дмитрий Владимирович , Куценко Наталья Владимировна , Грибиниченко Матвей Валерьевич
Published: September 2024

Цель данного исследования – увеличение сроков безаварийной эксплуатации, повышение межремонтного ресурса механизмов путем своевременного вывода его в ремонт, снижение расхода запасных частей, сокращение объемов резервирования. Для достижения поставленных целей необходимо повысить эффективность определения дефектов и текущего состояния подшипников в судовом оборудовании. Одним из наиболее распространенных методов, позволяющим с высокой степенью достоверности выявить дефекты подшипников качения на стадии зарождения, является метод вибрационной диагностики. Анализ вибрационных сигналов, получаемых при замере вибрации в различных точках агрегата, их сравнение с действующими для этого типа оборудования нормами позволяет получить объективное заключение об общем техническом состоянии оборудования. От того, насколько точно определено текущее состояние подшипников, зависит правильность построения прогноза остаточного ресурса механизма, что позволит снизить сроки простоя оборудования из-за неожиданной поломки, сократить межремонтный интервал и тем самым уменьшить финансовую нагрузку на судовладельца.

The purpose of this research is to increase the period of trouble-free operation, to increase the inter-repair resource of mechanisms by means of its timely repair, to reduce the consumption of spare parts, to reduce the amount of redundancy. To achieve the set goals, it is necessary to increase the efficiency of defects and current state of bearings in shipboard equipment.One of the most widespread methods, allowing to reveal defects of rolling bearings at the stage of origin with a high degree of reliability, is the method of vibration diagnostics. Analysis of vibration signals received at vibration measurement in different points of the unit, their comparison with the norms valid for this type of equipment allows to get an objective conclusion about the general technical condition of the equipment.The accuracy of the current condition of the bearings determines the accuracy of the forecast of the remaining life of the mechanism, and this will reduce the downtime of the equipment due to unexpected breakdowns, will reduce the time between repairs, and thus will reduce the financial burden on the shipowner.
Experimental studies of the model cable-stayed covering structure
Authors: Чесноков Андрей Владимирович , Михайлов Виталий Витальевич , Долматов Иван Викторович
Published: September 2024

Исследование и совершенствование вантовых строительных конструкций, обладающих малым собственным весом и хорошей архитектурной выразительностью, является важной и актуальной задачей. Выполнены экспериментальные исследования нового конструктивного решения вантового покрытия, предназначенного для прямоугольных в плане зданий с редкой сеткой несущих колонн. Апробирована методика возведения вантовой конструкции. Подтверждена работоспособность конструкции при действии симметричных и несимметричных внешних нагрузок. Результаты работы вносят вклад в развитие облегченных строительных конструкций вантового типа, эффективных при возведении зданий гражданского и промышленного назначения на отдаленных и труднодоступных территориях.

Research and development of cable building structures is a modern and important task due to low own weight and good architectural appearance. Experimental studies of a novel design solution of a cable roof are performed. The roof is proposed to be used for rectangular buildings with enlarged column spacing. Construction technique for the cable roof is tested. The operability of the structure under the action of symmetrical and asymmetrical external loads is confirmed. The results of the work contribute to the development of lightweight cable structures which are efficient for construction of civil and industrial buildings in remote regions.
An artificial canal on Russky Island (Sea of Japan) to intensify circulation and self-purification of Novik Bay
Authors: Кильматов Талгат Рустемович
Published: September 2024

Предлагается комплекс сооружений, включающий искусственный канал, соединяющий бухту Новик острова Русский Японского моря c Уссурийским заливом. Цель сооружения – защита прилегающих к острову акваторий от загрязнения как компенсация антропогенной нагрузки вследствие ускоренной урбанизации острова. Канал приводит к усилению естественной циркуляции и самоочищению бухты Новик. Приводятся количественные оценки циркуляции с учетом особенностей муссонного климата в регионе. Одновременно предполагается использовать данное нестандартное строение как единый туристический комплекс острова совместно с океанариумом, набережной, сафари. Отмечается необходимость шлюза для мониторинга и регулирования экологического состояния бухты Новик.

The creation of an artificial canal to connect Novik Bay and Ussuri Bay on Russky Island in the Sea of Japan is proposed. The purpose of the structure is to protect the sea area around the island as compensation for the accelerated urbanization of the island. The canal leads to increased natural circulation and self-purification of Novik Bay. Quantitative estimates of circulation are provided taking into account the characteristics of the monsoon climate in the region. At the same time, it is planned to use this non-standard structure as a single tourist complex of the island together with an oceanarium, an embankment and a safari. The need for a gateway to monitor and regulate the ecological state of Novik Bay is noted.