bluuebunny/crossref_metadata_2025 huggingface dataset:
Spiking Neural Network implementation of LQR control on underactuated system
Authors: Juárez-Lora J. A. , Sossa Azuela Juan Humberto , Ponce-Ponce Victor H. , Rubio-Espino Elsa , Barrón Fernández Ricardo
Published: December 2024

Adaptability, learning capabilities, and space-energy efficient hardware are required in robotic architectures, which must deal with changing dynamic environments. Nowadays, learning algorithms are implemented in Von Neumann Architectures, which separate storage from processing units, making them not appropriate for artificial neural networks (ANN), resulting in inefficient implementations. This writing presents a neural architecture proposal designed to implement a control loop in a mobile wheeled under-actuated inverted pendulum system, using spiking neural networks, linear quadratic regulator control technique, and a neural framework that allows us to define the neuron ensembles specification to represent specific control signals. The intention is to study how typical control theory algorithms can be translated into neural structures, aiming for neuromorphic implementation.
Implementation of a Nickel-Electroless Coating in Heat Exchanger Pipes Considering the Problem of the Environmental Conditions ofthe Cooling Water Without Recirculation to Increase the Effectiveness Under Uncertainty
Authors: Zezatti Victor Manuel , Ochoa Alberto , Urquiza Gustavo , Basurto Miguel , Castro Laura , García Juan
Published: December 2024

This research is based on the operation tube heat exchangers, their use and problematic on hydroelectric power plants. It is based on the design heat exchanger tubes for industrial use, which took the parameters of operation, design, working fluids (air and water) and conditions to assemble a monitoring equipment at appropriate scale for the laboratory, with the necessary measurement instruments to analyze the behavior of heat energy transfer by means of thermocouples, the velocity of the air with a hot wire anemometer and the flow of water with a turbine flow meter, in pipes of different materials: copper, steel 1018 and stainless steel 316L, all in ideal conditions, and with this to found a comparative parameter with pipes of the same materials but under conditions of deterioration with the presence of forced oxidation and with the data mining and support vector machine can be minimized the corrosion problems in pipes.
A Novel Method for Counting Independent Sets in a Grid Graph
Authors: De Ita Luna Guillermo , Tovar Vidal Mireya , Bernábe-Loranca Maria Beatriz
Published: December 2024

The problem of counting independent sets of a graph G is not only mathematically relevant and interesting, but also has many applications in physics, mathematics, and theoretical computer science. In this paper, a novel method for counting independent sets on grid-like structures is presented. It starts by explaining the recurrences used by the method to count independent sets on basic topologies of graphs. The method is extended to process grid-like structures of quadratic faces. The proposal has a lower time complexity than the required on the leading and current method based on the transfer matrix for counting independent sets on grids.
Extreme Topologies on Bipolygonal Graphs and Dinamic Trees
Authors: De Ita Guillermo , Bello López Pedro , Contreras González Meliza
Published: December 2024

We show how properties of the sequence βi,j, which represents the product between two Fibonacci's numbers Fi × Fj, can be used for the computation of the Merrifield-Simmons index on bipolygonal graphs and trees.
We show that the extreme values of the Merrifield-Simmons index on bipolygonal graphs are found in two consecutive columns of the table βi,j k=i+j=1,...,n. The minimum value in β3,k-3 and the maximum value in β4,k-4.  On the other hand we show that i(Tn ∪ {{vp, v}}) is minimum when v is a new leaf node, and its father vp was also a leaf node in Tn.
Our methods does not require the explicit computation of the number of independent sets of the involved graphs. Instead, it is based on applying the edge and vertex division rules to decompose the initial graph.
Exploring BERT-Based Pretrained Models for Polarity Analysis of Tweets in Spanish
Authors: Barrios González Erick , Tovar Vidal Mireya , Reyes-Ortiz José A. , Zacarias Flores Fernando , Bello López Pedro
Published: December 2024

This paper reviews the implementation of three pre-trained models based on BERT (“bert-base-multilingual-cased”, “IIC/beto-base-spanish-sqac” and “MarcBrun/ixambert-finetuned-squad-eu-en”) to solve tasks 1.1 and 1.2 of “Workshop on Semantic Analysis at SEPLN 2020” (TASS 2020), these tasks consist of the polarity analysis of tweets in Spanish from different Spanish-speaking countries. The proposed models are evaluated individually by pre-processing and replacing synonyms. This research is carried out to find the points to improve in the polarity analysis of tweets (tweets), mainly in how the pre-trained models interpret words that are not in their vocabulary due to variations in the language, regional expressions, misspellings, and use of emojis.
Using a novel XAI algorithm for Data Augmentation in image classification problems
Authors: Guerrero Velázquez Tonantzin Marcayda , Sossa Azuela Juan Humberto
Published: December 2024

Nowadays, Machine learning solutions are increasing their presence in the industry, and the benefits associated with the use of this technology are reflected in a reduction of time, costs, and a clear economic benefit, also most of these solutions use supervised learning, where a dataset with labeled real examples is needed.
 However, the many challenges associated with the implementation of a supervised machine learning solution are sometimes difficult to overpass, so one of the most important challenges is the creation of a big labeled dataset to feed the algorithms, since most of the time there is no any dataset available for the proposed solution, and most companies cannot afford to have a hand-created dataset with tens of thousands of records, also because they even cannot be sure that the model will work.
And the problem is that current machine learning techniques fail to improve the problem understanding on training with very small datasets, so here it is shown how by using a novel XAI method used to explain the decisions of a machine learning model in a computer vision problem, we can augment the labeled dataset focused on the important regions for the image classification, and increase the model performance, not just for training but for validation and testing, also this method turns out to be superior to the most used data augmentation methods if we further reduce the amount of information.
Soccer Training Scheduling Problem
Authors: Fuentes-Penna Alejandro , Ruiz-Vanoye Jorge A. , Trejo-Macotela Francisco R. , Ramos-Fernández Julio C. , Díaz-Parra Ocotlán , González-Ibarra Juan de Dios , Simancas-Acevedo Eric , Espejel Flores Porfirio
Published: December 2024

This article aims to present a new problem of planning of resources and activities related to soccer, which is a variant of the Project Scheduling Problem. Soccer projects are intended to meet the requirements and expectations of time, cost and quality of the processes of the Soccer-related activities. In this article, original and unique in the world to date, is presented the mathematical modelling based on the Project Scheduling Problem of soccer in order to make optimal use of the resources of time, money and human resources of enterprises that you take care to engage in Soccer. The CPLEX model was used to find the optimal use of resources of the Soccer Project Scheduling Problem.
Optimization of terrestrial distribution routes for mass consumption products using genetic algorithm
Authors: Bustos-Rivera Víctor Hugo , Lezama León Myrna Hortencia , Figueroa-Urrea Hector Armando , Cruz-Aldana Eduardo
Published: December 2024

This research aims to show the results of applying optimization in the distribution network of high consumption products, using metaheuristics for the design of distribution routes, applying genetic algorithms, performing the simulation in the HeuristicLab software. Achieving the optimization of the distribution processes of high consumption products which has grown in recent years to the increase of the population and the increase of the vehicular congestion, in the big cities, hindering the achievement of common objectives between the different actors in Urban Distribution of Merchandise (DUM).
The research was quantitative cross-sectional non-experimental, because the situations and subjects of study, could not be manipulated by the researcher, the information was provided by the company, which, for reasons of confidentiality, will not be named.
Analysis of water coverage in the municipalities of the State of Guanajuato
Authors: Torres González Miguel Angel , Hernández Veleros Zeus Salvador , Ramírez Rosas José Gonzálo
Published: December 2024

The urbanization that most of the municipalities in the State of Guanajuato are undergoing has made it imperative to generate strategies that allow an adequate administration and management of the drinking water service [1]. In this research, the water marginalization index for the State of Guanajuato is constructed using data from the 1990, 2000, 2010 and 2020 Population and Housing Censuses, which allowed for an analysis of the evolution of the effects of the policies adopted by the authorities to meet this challenge.
The results indicate a favorable evolution of supply, however, the increase in the percentage rate of the use of rivers or community wells as a source of water supply is noteworthy, going from 6.99 to 31.21 percent from 2010 to 2020, this result indicates an increasing overexploitation of the aquifers, which will cause complications in the future supply of water.
Digital skills in Mexico's gig economy. A temporary employment option
Authors: Guzmán Escorza Lizbeth Elena , Torres González Miguel Angel , Olivera Pérez Emmanuel
Published: December 2024

The objective of the research is to categorize the demand for digital skills in the online digital job market in Mexico in the period December 2019-February 2020.  For the development of the study, three digital job platforms Workana, Freelance and Freelancer Writing Jobs were considered. The study was developed considering the vacant projects published on gig platforms on a daily basis that allowed identifying the skills demanded, through content analysis. This allowed quantifying the participation of digital skills and grouping them according to their characteristics based on the literature review. The findings of the research for the gig job market mediated by platforms in Mexico, were the following, Workana is the leading platform with the highest demand for digital skills, Graphic Design was the digital skill with the highest frequency in demand, finally; the category of specialized digital skills represented the greatest opportunity for freelance and temporary employment.
Complexity on Fuzzy set and Fuzzy Logic for Air Quality
Authors: Fuentes-Penna Alejandro , Díaz-Parra Ocotlán , González-Ibarra Juan de D. , Espejel Flores Porfirio , Simancas-Acevedo Eric , Aguilar-Ortiz Jaime , Ruiz-Vanoye Jorge A.
Published: December 2024

The Air quality measurement is reported as micrograms per cubic meter or parts per million. In this article, we proposed a survey of the complexity on Fuzzy Logic for air quality. The traditional air quality assessment is estimated using air quality indices as mean values of selected air pollutants, where the ambient environment has given limits without considering specific local conditions and synergic relations between air pollutants and other meteorological factors. Different models analyze the structure of data to find the characteristics of air quality similarities and to interpret the classification results by means of fuzzy logic.
THE EFFECT OF OPERATING CYCLE AND DEFAULT RISK ON PROFIT QUALITY WITH GOOD CORPORATE GOVERNANCE AS A MODERATION VARIABLE
Authors: Yayah Syahriyah  , Iin Rosini  , Nofryanti
Published: December 2024

This study aims to examine the influence of operating cycle and default risk on profit quality with good corporate governance as a moderator. The research method used is an associative quantitative method. The data used in this study is panel data, which is a combination of time series data and cross section data. The population in this study is companies in the consumer goods industry sector listed on the Indonesia Stock Exchange in 2019-2023. The determination of samples by purposive sampling technique was obtained from 16 companies with 80 observation data. The analysis technique and hypothesis testing were carried out by panel data regression analysis through EViews ver-12. Based on the results of the T test, it is known that the operating cycle has a significant effect on the quality of profits. On the other hand, default risk has no effect on the quality of profits. Meanwhile, good corporate governance cannot moderate the influence of operating cycle variables and default risk variables on profit quality.
ANALYSIS OF THE EFFECT OF DIVERSIFICATION AND INTELLECTUAL CAPITAL ON CORPORATE FINANCIAL PERFORMANCE WITH GOOD CORPORATE GOVERNANCE AS A MODERATOR
Authors: Mohamad Ghofur  , Nofryanti  , Iin Rosini
Published: December 2024

This study aims to explore the relationship between diversification strategy, intellectual capital, and firm performance, with good corporate governance as a moderating variable. This study was conducted on companies listed in the Kompas 100 index during the period 2018 to 2022. The purposive sampling method was used to collect 140 samples, and data analysis was conducted using the Random Effect method using EViews 12 software. The results showed that diversification strategy has no significant influence on the performance of companies in the Kompas 100 index. In contrast, intellectual capital shows a significant positive influence on firm performance. Good corporate governance does not moderate the relationship between diversification strategy and firm performance, and is unable to moderate the effect of intellectual capital on firm performance. These findings provide important insights for corporate managers and researchers interested in understanding the factors that influence firm performance in the context of the dynamics of the global business environment.
BEHAVIORAL INTENTION TO ADOPT FINTECH: STUDY OF MILLENIALS’ AND GEN-ZS’ READINESS IN INDONESIA
Authors: Zahra Ayunita Mulia  , Nurhastuty Kesumo Wardhani
Published: December 2024

As the financial technology (fintech) landscape develops rapidly, it is important to understand the factors that influence the adoption behavior of the Millennial and Gen-Z generation in Indonesia. This study uses a quantitative method approach to investigate the readiness of this demographic group to accept fintech solutions and identify the key determinants that shape their behavioral intentions. A structured questionnaire was administered to a representative sample of the Millennial and Gen-Z generations in Jakarta, Indonesia, to gather insights into their awareness, perceptions and attitudes towards fintech. This study draws on existing theories such as the Unified Theory of Acceptance and Use of Technology (UTAUT) to develop a theoretical framework for analyzing the factors that influence fintech adoption. This research examines variables such as performance expectations, effort expectations, social influences, and facilitating conditions to understand their impact on the behavioral intentions of Millennials’ and Gen-Zs’. The findings of this research show that the use of technology is able to contribute to achieving performance in financial transactions, apart from that the influence of the social environment is also proven to be able to increase behavior in using fintech technology. This research only tests the four core determinants of UTAUT and the data obtained is not able to represent fintech adoption behavior as a whole in Indonesia.
THE IMPACT OF CONSUMER ATTITUDES ON ONLINE SHOPPING, INCLUDING SOCIAL MOTIVATIONS, ESCAPISM MOTIVATIONS, AND VALUE MOTIVATIONS, IN RELATION TO ONLINE PURCHASE INTENTIONS
Authors: Cen Lu  , Chandra Kuswoyo  , Reicheana Koesala Zirho
Published: December 2024

The development of technology and the internet has changed people's shopping behavior, especially the millennial generation. This study aims to analyze the attitude on online shopping of the millennial generation and compare it with the population as a whole. This study also provides an explanation of the online shopping behavior of consumers in the millennial generation group, as well as being the basis for developing teaching materials in customer insight and consumer behavior courses. The Millennial generation is a group of individuals who have different awareness of the impact of historical events they experience. They tend to be more tech-savvy and spend less money on purchases. The study highlights the need to understand the Millennial generation further because they are not monolithic. Understanding generational differences and their impact on online shopping is important for effective target audience segmentation. Meanwhile, purchasing behavior describes whether consumers actually buy the products they want, with purchase intention as a proxy variable to measure purchasing behavior. This study is a type of quantitative research that uses a survey method to collect data from the West Java millennial generation who are involved in online purchase intention. The population is the West Java millennial generation, and the sample was taken using a purposive sampling technique. Testing of the research instrument was carried out with validity using the Pearson Correlation test and reliability with Cronbach's alpha. The data was processed using Moderate Regression Analysis (MRA) with SPSS version 25. The results of the study showed that attitudes on online shopping and value motives influence online shopping intention. Social motives and escapism motives do not affect online shopping intention.
GOOD CORPORATE GOVERNANCE, GREEN INOVATION AND SUSTAINABILITY PERFOMANCE
Authors: Kautsar Mubarak  , Holiawati  , Sugiyanto
Published: December 2024

This study aims to examine the influence of Good Corporate Governance and Green Innovation on Sustainability Performance. This type of research is quantitative associative. The data used is secondary data obtained from the company's www.idx.co.id and website. The population in this study is companies that are members of the Sri Kehati Index Listed on the IDX for the period of 2019 – 2023. Meanwhile, the sample of this study was determined by the purposive sampling method so that 20 sample companies were obtained. The analysis method used is Panel Data Model Regression analysis. The results of this study show that Good Corporate Governance and Green Innovation have an effect on Sustainability Performance, Good Corporate Governance has an effect on Sustainability Performance and Green Innovation has an effect on Sustainability Performance.
Impact of Financial Inclusion on Household Empowerment: Mediating role of Entrepreneurship Intentions in Pakistan
Authors: Raja Shahnawaz Sarfraz , Raja Shahjahan Sarfraz , Raja Sania Sarfraz
Published: December 2024

The purpose of this research is to examine how access to financial services influences the social and economic well-being of households, as well as their propensity to pursue entrepreneurial opportunities. In addition, to investigate how aspirations for business ownership affect the financial and social standing of families. The hypothesis that an individual's desire to start a business plays a moderating role in the connection between financial inclusion and a family's capacity to effect social change is tested. For this study, surveyed a random sample of 98 business owners, equal numbers of men and women. All responders were given a questionnaire that they may fill out on their own time. It has been shown that the ambition to start a business mediates the connection between financial inclusion and economic empowerment. It is suggested that creating an encouraging atmosphere and an entrepreneurial ecosystem might help inspire people to take the plunge.
THE EFFECT OF TECHNOLOGICAL COMPETENCE AND KNOWLEDGE MANAGEMENT ON SUSTAINABLE ORGANIZATIONAL PERFORMANCE
Authors: Syed Shahid Hussain  , Dr. Alia Amed  , Dr. Abdul Rauf Qureshi
Published: December 2024

This research article investigates the impact of Knowledge Management (KM), Technological Competence (TC) on Sustainable Organizational Performance (SOP), with a by examining the mediating role of OI. Using a sample of 314 respondents from IT-based companies and software houses, the research explores how KM and TC contribute to enhancing SOP with OI serving as a mediator in these relationships. The study employs SEM to test the direct and indirect associations of the study variables. The research findings show positive interconnections between KM and SOP, TC and SOP and OI and SOP. Furthermore, OI is found to mediate the relationship between KM and SOP as well as between TC and SOP emphasizing its pivotal role in enhancing sustainable performance. The study underscores the importance of integrating KM practices and technological capabilities with OI acting as a key enabler, to achieve sustainable organizational performance. These insights offer valuable guidance for managers seeking to leverage knowledge management and technological innovation to drive long-term success in this digital age.
Deep Learning Based Attack Classification on IoMT Devices
Authors: Awais Muhammad , Hussain Tajummul , Rehman Tayyab
Published: December 2024

This study gives an in-depth evaluation of deep learning algorithms for threat classifying in the Internet of Medical Things, or IoMT, devices, a rapidly expanding subset of the Internet of Things (IoT) essential for modern healthcare systems. IoMT devices are more susceptible to cyberattacks as they gather, send, and process sensitive medical data, endangering patient security and privacy. Due to particular limitations like low processing power and strong privacy regulations, traditional security solutions usually need to catch up in IoMT circumstances. Consequently, deep learning algorithms offer viable substitutes for real-time, adaptive attack classification due to their capacity to identify intricate patterns in big datasets. Our evaluation and classification of state-of-the-art deep learning algorithms for IoMT security focuses on classification accuracy, computational efficiency, and threat adaption. We discuss significant challenges and opportunities, compare strategies, and assess success metrics. We examine CNNs, RNNs, and hybrid architectures, highlighting how well they can withstand various assaults. This survey will be a thorough resource to direct future studies and advancements in deep learning-based IoMT security.
Automated Image Forensics Based on Deep Learning for Discriminating Photorealistic Computer Graphic and Photographic Images
Authors: Akram Misbah , Yousaf Maya Bint , Nafees Muhammad Hassan , Ahmed Burhan , Abbas Muhammad , Arif Tabeer
Published: December 2024

The rapid advancement in the field of digital image forensics from the recent few years is becoming very crucial nowadays. As it become easier to generate computer graphic images and forge the whole of the image or just part of image to perform illegal activities. Distinguishing Computer generated stuff with the Natural images is quite difficult task with naked human eye.
In this research thesis we proposed the CNN-based Neural Network model for the identification of images. For the classification of images Columbia image dataset is used which includes Photorealistic Computer Generated (PRCG) images and Photographic Images (PIs). Original, resized, filtered and patched images with different modification are used to feed in Convolutional Neural Network (CNN) before training and testing phase.
The proposed method used five convolutional layers. All of the experimental results and analysis shows that proposed method achieved 99% training accuracy and 98.5% validation accuracy on different types of images which is although sufficient enough for this proposed method with adequate amount of dataset.
The Role of Education in Prevailing Extremism and Promoting Peace
Authors: Rashid Zarina , Rashid Shahir , Rashid Minahil
Published: December 2024

Through education is a transformative tool for positive social change, and is the way to mitigate extremism and promote peace in the society, this study takes a look at this pivotal role in education. This research does a thorough examination of the literature of the existing and determines how education can fight violent ideologies and critical thinking, all while teaching empathy, justice, and equality. Education is shown to possess the dual capacity to enable individuals to obtain the intellectual tools both to resist extremist narratives and to promote social cohesion through the spread of civic values and peaceful coexistence, as the study demonstrates. This study analyzes previous research to determine the key mechanisms through which education is able to reduce social tensions: challenging stereotypes, promoting dialogue and instilling a sense of common humanity. It also looks at the part of formal and informal educational system in shaping those people ideas and to create environment to make with each other and respectably. One contribution of this study is that it takes advantage of the synthesis of different academic disciplines, linking theories of education, sociology, and conflict resolution. It lays bare the need to embrace peace education within our curricula, and the need for inclusion in our educational practices to address the underlying causes of radicalization. This study hopes to provide policymakers, educators, and stakeholders a range of nuanced understandings of education’s role in contributing to peace and countering extremism through highlighting the boundaries of existing practices and suggesting future initiatives. Overall, this work confirms that education should remain the key stone for ensuring sustainable development, building harmonious societies, and global stability. It urges people's collective effort to improve educational system as a way for creating tolerance and understanding and lasting peace.
A Study in the Contamination of Desalinated Water with Microorganisms, and Analysis of Chemical and Physical in Western Libya
Authors: Zwaghi Ayman , al-Rawi Qutaiba , Abdulla Amira Khaled , Khalifa Maryam Aboajela , Abdelmola Aisha Salem , Bashir Fatima Farag , aljaghmani Retaj Ramadan
Published: December 2024

Monitoring the changes that occur to water during distribution is vital to ensure water safety. The biological stability of reverse osmosis (RO) produced drinking water, characterized by low cell concentration and low assailable organic carbon, in combination with chlorine disinfection was investigated. Water quality at several locations throughout the existing distribution network was monitored to investigate whether microbial water quality changes can be identified. Libya is located in an arid and semi-arid region of Africa with no permanent rivers or true freshwater lakes and average annual rainfall of less than 100 mm. Limited access to surface water resources has led to a heavy reliance on groundwater. Extensive use of conventional water resources such as groundwater, poor awareness of how to optimally use and save water, and seawater intrusion into coastal aquifers have all contributed to a severe water crisis in Libya. The water crisis issues in Libya are exacerbated by the population distribution relative to available water resources. 75% of Libya’s population is concentrated in only 1.5% of the total land area in the western coastal centers of Jufra and Misrata, and the eastern coastal area of ​​Jebel Akhdar. The results from this study highlight the importance of implementing multiple barriers to ensure water safety. Changes in water quality detected even when high-quality disinfected reverse osmosis (RO) -produced water is distributed highlight microbiological challenges that chlorinated systems endure, especially at high water temperatures. The aim of this paper is to shed light on the conventional and non-conventional water resources in Libya. In this context, the research aims to provide an overview of seawater desalination technology in Libya and why desalination should be embraced as a strategic and ultimate solution to the water shortage problem. In addition to the bacterial contamination of desalinated water in western Libya. This study was investigated the quality of drinking water supplied in Some Commercial Water Purification Systems at Sabratha area. Water samples were collected from five stations at Sabratha region. The physicochemical parameters were mainly, pH, Alkalinity, Chloride, Nitrate, Sulfate, Magnesium, Calcium, Sodium, Potassium and TDS. The result shows that all these parameters were fall below WHO guidelines, except pH. The bacteriological result revealed that one of the studied stations was contaminated by E. coli bacteria.
EVALUATING THE AWARENESS AND UPTAKE OF PRE- EXPOSURE PROPHYLAXIS (PrEP) AMONG THE YOUTHS IN LILONGWE URBAN- A CASE OF AREA 25 HEALTH CENTRE
Authors: Munjili Bwalya , Hankombo Wanda , Katendema Lindani , Nyahoda Isabel
Published: December 2024

The study was conducted in the city of Lilongwe in Malawi, specifically, in Area 25.The catchment area was the areas surrounding Area 25 Health Centre. The main objective of the study was to evaluate the awareness and uptake of pre-exposure prophylaxis (PrEP) among the youths in Lilongwe Urban: a case of Area 25 Health Centre. A total of 100 interviews were conducted with the youths in the area using a questionnaire.Data was analyzed using SPSS version 21. It was established that just 44% of the respondents are aware of PrEP. Based on the different perception questions that were asked, it was noted that some of the perceptions that the youths have over PrEP are actually not true; for example, taking of PrEP within 24 hours as the only period within which PrEP can be effective. However, most of the perceptions the youth have on PrEP are positive and encouraging. It has been found that 31% of the youths that are aware of PrEP (14% of the total sample) has ever used PrEP. Of these that have ever used PrEP, 42.9% of them (6% of the total sample) are still using PrEP. Lack of awareness, lack of access, inconvenient outlets and negative perceptions are some of the barriers to PrEP usage. Wide implementation of the PrEP communication strategy and making the PrEP easily accessible as well as ensuring privacy in the PrEP collection points will increase the uptake by the youths.
Türkistan’daki Stratejik Geçitlerin Askeri Tedarik Zincirleri Açısından Önemi ve Güvenliği
Authors: Kaya Özge Seçil
Published: December 2024

Yeryüzünün en büyük kara parçası olan Asya Kıtası’nın merkezinde yeralan Türkistan, Asya ile Avrupa ve Asya’nın çeşitli bölgeleri arasında bir kara köprüsü konumundadır. Türkistan, geniş düzlüklerin yanısıra sarp dağları ve hem ticaret hem de askerî harekâtlar açısından hayati öneme sahip doğal geçitleri barındırır. Bu çalışmada Cungarya Geçidi, Torugart Geçidi, İrkeştam Geçidi, çok sayıda doğal geçidi barındıran Pamir Yolu ve Fergana Vadisi askeri tedarik zincirleri açısından incelenmektedir. Bu kapsamda ilk olarak askeri tedarik-coğrafya ilişkisi, askeri coğrafya literatürü üzerinden ele alınmaktadır. Daha sonra, söz konusu geçitlerin konumuna ve hangi noktalar arasında geçişi sağladığına dair kuşbakışı bir görüntü sunmak amacıyla Türkistan bağlantılı uluslararası ulaşım koridorları, yapımında inisiyatif alan ülkelere göre gruplandırılarak ortaya konulmaktadır. Türkistan’daki doğal geçitler ve bağlı oldukları lojistik hatları incelendiğinde, tarihte Almanya ve Rusya örneklerinde olduğu gibi, barış zamanı inşa edilip gerektiğinde askeri amaçlar için kullanılabilecek çift kullanım altyapılar olabilecekleri görülmüştür. Çalışma kapsamında incelenen Türkistan’daki geçitlerinin başta Rusya olmak üzere bölgede ulaşım altyapısına yatırım yapan Çin, Avrupa Birliği ve Türkiye için büyük önem taşıdığı sonucuna varılmıştır. Türkistan bağlantılı mevcut uluslararası ulaşım koridorları, bu geçitleri zorunlu olarak kullanmak durumundadır. Bu makalede incelenen Türkistan geçitlerinin dağlık koşullar nedeniyle bazılarının ikamesi olmadığı ve bu sebeple doğu-batı ve kuzey-güney askeri tedarik zincirleri açısından stratejik öneme sahip oldukları tespit edilmiştir.
The use of Chat GPT for Obesity Management in Greece: A PESTEL Analysis
Authors: Vourdoubas John
Published: December 2024

The treatment of obesity in Greece, which has undesired health, economic and social impacts, requires a holistic approach while the use of strategic management tools such as SWOT and PESTEL analysis can facilitate the fight against the pandemic. The use of Artificial Intelligence in several sectors has increasing applications nowadays. A PESTEL analysis has been realized using the Chat GPT instead of asking the opinion of experts and stakeholders of the healthcare industry. Chat GPT was asked to identify the main political, economic, social, technological, environmental and legal factors affecting obesity management in Greece. It was found that its quick answers were satisfactory although some additional factors which were not identified by Chat GPT have been proposed. Taking into account that the use of Chat GPT has various limitations related with its training in recent scientific advancements and information it is suggested that it should be used combinedly with human analysis for the achievement of optimum results. Our findings could be used by policy makers, experts and several stakeholders of the obesity management industry in Greece for the improvement of the policies used for treating the contemporary pandemic of obesity.
Relation of pine chip-n-saw to sawtimber and pulpwood prices in the Southeastern United States: direction of influence
Authors: Misztal Maciej D. , Siry Jacek , Mei Bin , Harris Tom , Bowker J Mike
Published: December 2024

Relationships among prices of pine sawtimber (PST), pine pulpwood (PP), and chip-n-saw (CNS) were examined for southeastern markets in the United States. The data were extracted from the Timber Mart-South database and included quarterly prices of pine products from 1979 to 2016 for markets in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, and Texas. The data were separated into two regions in each State. Both regions were used for Alabama, Florida, Georgia, Mississippi, and South Carolina, but only single regions were used for Arkansas, Louisiana, North Carolina, and Texas. The number of significant lags indicated by the Akaike information criterion varied between one and three for all markets, and those lags were used for further analysis. The Granger causality test using the Yamamoto–Toda method indicated significant predictability of PST by CNS in four regions, PST by PP in three regions, CNS by PST in three regions, CNS by PP by three regions, and PP by PST by two regions. The Granger causality test using a differencing method indicated significant predictability for two fewer regions than the Yamamoto-Toda method, with eight regions in common. Of all the regions, the highest number of significant causalities was in region 1 of Alabama and region 2 of Georgia; no causalities were significant in regions 1 of Arkansas and Louisiana. Based on the number of significant predictabilities, the strongest causality was for prediction of CNS by PST, and the weakest was for prediction of PP by CNS. The results help better understand price relationships among timber stumpage products, the degree of substitutability among them, and the importance of individual market characteristics.
The Distorted Views of William Muir on Prophet Muhammad (saw)’s Character: A Critical Evaluation
Authors: Aliyu Kabir  , Mohammed Muneer’deen Olodo Al-Shafi’I  , Ahmad Bazli Bin Shafie  , Hammed Isiaka Raji Folohunsho  , Ridwan Olawale Olagunju-Ibrahim
Published: December 2024

The purpose of this paper is to evaluate the inaccurate assertions made by the Western Orientalist William Muir regarding the Character attributed to the Prophet Muhammad (saw). Muir’s portrayal of the character of the Prophet (saw) may attract the interest of his readers. In his many works, he presented the character of the Prophet (saw) in an embarrassing way. Muir associated him with a figure of moral failure who used false revelations to justify immoral actions such as violence, cruelty, and hostility. In an attempt to evaluate the distorted assertions made by Muir, the paper analyses his evidence and observations. At the same time, it conducts a careful examination of Islamic historical records about the character of Prophet Muhammad (saw) to prove the authenticity of his character. According to the findings of historical evidence, it can be said with good reason that Muir’s denial of the Prophet’s good personality was part of his distortion of Islam, and since the claim is not substantiated by real and accurate historical evidence, therefore, it must be baseless.
The Application of Musical Instruments in Uzbek Musical Art
Authors: Arabov Ilyos  , Ziyoyeva Malikakhon  , Makhmudova Farangiz Nuriddin kizi  , Makhmudov Vosidjon Valijonovich  , Hakimov Qudratjon Qurbonaliyevich
Published: December 2024

Each of our instruments has its own place in our national music. Sometimes they complement each other, sometimes they cannot be replaced. It should be especially noted that the world of Uzbek national instruments is rich and diverse both spiritually and materially. Moreover, instrumental performance stands as an art form deeply rooted in the rich spiritual traditions of our people, with its origins tracing back to ancient times. Musical compositions, serving as the foundation of this genre, became inseparably intertwined with the daily lives and labor of the populace.
Optimizing Software Cost Estimation: A Hybrid Approach Integrating Soft Computing Techniques for Enhanced Accuracy and Efficiency
Authors: Veerpal Kaur  , Sunny Arora
Published: December 2024

In software engineering, software cost estimate is a necessary process directly affecting project deadlines, budget planning, and resource allocation. Conventional estimating methods could overlook the inherent complexity and uncertainty of software development, therefore causing mistakes and maybe project failures. To optimise software cost estimation and so address these challenges, this work proposes a hybrid framework incorporating fuzzy logic, artificial neural networks (ANN), and genetic algorithms (GA). Although fuzzy logic models imprecise and ambiguous information to control uncertainty, ANN is employed for its ability to learn and generalise patterns from past data. GA guarantees accurate and effective assessment of the process by strengthening already used techniques with strong optimising characteristics. Combining these techniques makes use of their respective benefits to generate a synergistic plan beyond more traditional methods. The proposed framework is investigated using industry-standard datasets exhibiting appreciable increases in prediction accuracy, computational efficiency, and flexibility to varied project situations. Comparatively, for complex and large-scale projects the hybrid approach not only reduces estimating errors but also enhances scalability and dependability. Additionally included in the paper is a case application for a practical project, therefore stressing the relevant usefulness of the framework. By addressing the limitations of present approaches, this work reduces the gap between theoretical breakthroughs in soft computing and their pragmatic use in software engineering. stressing the need of applying contemporary computing techniques to solve evolving challenges in cost estimation, the outcomes provide useful information for scholars and business practitioners. At the end of this work is explored the possibility of new machine learning models and the investigation of domain-specific customisations to increase the applicability of the framework.
Beyond Traditional Skills: The Link between Innovative Entrepreneurship Education and Employability Outcomes in Chinese Universities
Authors: Xiaoli Yang  , Muhammad Shahid Khan
Published: December 2024

This study examines the impact of innovation and entrepreneurship education (IEE) on the employment paths of college students, focusing specifically on two key objectives. First, it explores how IEE influences the entrepreneurial mindset of Chinese university graduates and enhances their employability in an increasingly competitive job market. Findings reveal that students exposed to IEE are more likely to develop creativity, adaptability, and resilience, traits that align well with employer demands and boost employability. The second objective investigates how IEE affects the overall educational quality and self-efficacy of students, which serves as a mediating factor in their post-graduation career success. The quantitative data collected demonstrate a positive relationship between IEE and employability, with IEE also significantly improving students' comprehensive educational quality, critical thinking, and confidence. These results underscore the role of IEE not only in shaping career readiness but also in enriching educational outcomes, ultimately positioning graduates for success in a dynamic job market.
Secured Blockchain framework using deep learning to reduce the service latency in a 5G based distributed networking environment
Authors: Anju Raveendran  , Dr. R. Dhanapal
Published: December 2024

The Internet of Things (IoT), which is also represented as Internet of Health Things (IoHT), has witnessed numerous progresses in recent existences, particularly in the management of healthcare-related data. Because those healthcare statistics ensure greater accuracy, security with improvedreliability, and higher data feature, supplying those data to those healthcare apps is a time-consuming difficulty this organisation is facing. To developstatisticsestablishing, data must be more secure and privacy-protected, as deep learning and privacy policies are enabled with 5G network. If the information is private, the information owner may be able to learn about it. The data process flow associated with IoHT is now connected to a variety of IoT devices as edge nodes, thanks to recent advancements. Learning at the nodes is more difficult because of the issue of a missing or insufficient amount of training data, which necessitates a completely distributed setting, as well as new, better datasets, their establishing, and their security. In this work, a Hy-FL-based Blockchain strategy is proposed since it is enabled with blockchain, which maintains trust ability and skilled data based on deep learning with enhanced validation. With the help of the suggested method, training information on the deep nodes can be encrypted and aggregated. In the analysis, data management is managed securely based on IoHT in terms of projected value, energy usage, and data correctness.
Cutting Parameter Optimization of Single Point Cutting Tool of CNC Lathe Machine Using Machine Learning Algorithm
Authors: Sunil Kumar Patidar  , Vishal Sharma
Published: December 2024

In this study, two machine learning models, Random Forest Regressor (RFR) and Decision Tree Regressor (DTR), were applied to predict surface roughness (SR) in machining processes (turning) based on key input parameters: spindle speed (SS), feed rate (FR), and depth of cut (DOC). The performance of both models was evaluated using R² (R-squared), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). The Decision Tree Regressor achieved near-perfect accuracy with an R² score of 0.9999 and minimal error metrics. The Random Forest Regressor also performed exceptionally well, with an R² of 0.9988 and similarly low error values. Visual analyses, including residual and radar plots, confirmed the high accuracy of both models, with the Decision Tree Regressor slightly outperforming the Random Forest model. However, the Random Forest Regressor's ensemble structure provides better generalization and robustness, making it a more reliable model for larger or more complex datasets. This study concludes that both models are highly effective for predicting surface roughness, but the choice between them should depend on the specific trade-offs between accuracy and generalization needed in a given application.
THE ISSUE OF LANGUAGE AND STYLE IN THE MEDIA: ANALYSIS, CLASSIFICATION, COMPARISON
Authors: Akhmedova Matluba , ERGASHEVA Shahlo
Published: December 2024

THE PLACE OF NATIONAL-ARTISTIC CULTURE IN THE ASPECT OF AESTHETIC EDUCATION OF ADOLESCENT STUDENTSIn this article, the author shares his views on the role of lessons and extracurricular activities conducted by social science teachers in secondary schools in the aesthetic education of adolescent schoolchildren.
AILE - TOPLUMUN KALITELI TEMELINI GÜÇLENDIRIRHer aile, toplumun kaliteli temelini güçlendiren önemli bir yapı taşıdır. Aileler yalnızca çocukların yetiştirilmesinde değil, aynı zamanda toplumsal refahın yeniden inşasında ve ekonomik kalkınmada da önemli bir rol oynar. Bu tezde, ailenin sosyal ve manevi önemi, devletteki rolü ve toplum üzerindeki etkisi analiz edilmektedir. Ayrıca, ailelerin güçlendirilmesi için modern eğilimler ve stratejiler ele alınmaktadır.
Media Convergence and the Development of Interactive Broadcasting with Metaverse Technology
Authors: Ritonga Maisaroh , Farid Ahmad Salman , Manda Vijaya Kittu
Published: December 2024

The convergence of traditional media with metaverse technology has revolutionized interactive broadcasting by blending immersive experiences with real-time interactivity. This study explores the integration of media convergence and metaverse-driven platforms, highlighting their transformative impact on audience engagement, technological innovations, and the challenges related to infrastructure, cost, and ethical considerations. A mixed-methods approach was employed, combining qualitative and quantitative research. A comprehensive literature review established the theoretical foundation, while case studies of metaverse-enabled events, such as virtual concerts and immersive news reports, provided real-world insights. Semi-structured interviews with industry professionals offered expert perspectives on adoption barriers and strategies. Quantitative metrics, including audience retention rates and interaction times, were analyzed alongside industry reports to validate findings. The findings reveal a significant increase in audience engagement, with metaverse-driven platforms achieving 150% longer interaction times and a 20% higher retention rate than traditional formats. Technological enablers, such as VR, AR, Blockchain, and AI, were identified as key drivers of this transformation, facilitating immersive storytelling, secure digital transactions, and personalized content delivery. However, challenges persist, including high infrastructure costs, regional disparities in technological access, and ethical concerns over data privacy and intellectual property disputes. Metaverse broadcasting redefines audience interaction by enabling users to participate actively in content creation and exploration.