bluuebunny/crossref_metadata_2025 huggingface dataset:
Accelerated soil moisture drought onset link to high temperatures and asymmetric responses associated with hit timing
Authors: Liu Yi , Wang Zhimin , Zhang Xinyu , Zhu Ye , Ren Liliang , Yuan Shanshui , Jin Junliang
Published: February 2025

Abstract. Frequent record-high temperatures in recent years have led to a rise in both the frequency and the intensity of drought events while also altering the formation process of droughts. The worldwide occurrences of flash droughts during the past decade are evidence that droughts may evolve in an unusually rapid manner. Such a change in droughts challenges existing drought monitoring and early-warning systems typically designed for monthly scale purposes. This leads to a query regarding to what extent the formation process of droughts would be accelerated at high temperatures. Based on the reanalysis product, we identified historical drought events across China during 1950–2021 and defined a new drought characteristic, the duration of the drought onset (DDO; defined as the time period it takes for moisture to transition from a normal state to below-average condition) to measure how rapidly the drought develops. A two-stage experimental framework was then designed to establish the relationship between DDO and antecedent soil moisture, precipitation, and air temperature and to estimate the impacts of high temperatures with different warming scenarios and varied hitting time (pre- and post-drought onset) on DDO. Results showed that DDO would shorten by 10–50 d at 35 °C (high temperatures in meteorology) in relative to that of annual mean temperature scenarios. Overall, the impacts of high temperatures were greatest during the first 4 weeks (or 1 month) of the drought onset stage. High temperatures in the pre-drought and post-drought onset exhibited asymmetrical effects on DDO. In areas with a high normalized difference vegetation index (high-NDVI areas), pre-drought high temperatures presented a leading role in accelerating the formation of drought, while in low-NDVI areas, high temperatures after the drought onset were favourable for the ongoing development of drought. The findings in this study may supplement the process of understanding of drought in the future warming environment.
A privatização da Sabesp e o Fundo de Apoio à Universalização do Saneamento no Estado de São Paulo (FAUSP)
Authors: Tavares Danilo
Published: February 2025

This article analyzes the creation of the Fund for Supporting the Universalization of Sanitation in the State of São Paulo (FAUSP) within the context of the privatization of the São Paulo State Basic Sanitation Company (SABESP). The article addresses the uncertainties regarding the use of federal funds in regional basic sanitation units and the role of the universalization fund.”
Uma análise pragmática da gestão da inovação
Authors: Miró Ziliotto Mirela
Published: February 2025

Esta análise tem como finalidade realizar uma avaliação pragmática sobre a adoção de soluções inovadoras pela Administração pública, com destaque para a utilização de ferramentas de gestão da inovação, visando assegurar sua implementação de forma eficaz. Nesse contexto, por meio do método hipotético-dedutivo, foram inicialmente explorados conceitos fundamentais sobre inovação, ressaltando a relevância de sua incorporação pelo Estado. Em seguida, foram examinadas as implicações associadas à implementação de soluções inovadoras na esfera pública, enfatizando a necessidade de garantir uma execução ética e transparente, com vistas à promoção do desenvolvimento sustentável, indo além da mera eficiência econômica em seu sentido restrito. Para tanto, destacou-se o papel crucial das ferramentas de gestão da inovação, que não apenas ajudam a mitigar os riscos de insucesso, mas também permitem monitorar e controlar a implementação, desde a etapa de planejamento até a avaliação dos resultados alcançados. Por fim, foram apresentadas reflexões finais, alertando para a importância de se adotar uma postura cautelosa na introdução de inovações na Administração Pública, evitando que o entusiasmo ofusque a racionalidade, uma vez que nem sempre as opções mais rápidas ou econômicas se revelam as mais vantajosas.
URBAN FURNITURE DESIGN THROUGH THE IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE AND ADDITIVE MANUFACTURING
Authors: FERNANDEZ CORDERO ALEJANDRA , SANCHEZ MORENO DANIEL , MOLINA RUBIO SERGIO IGNACIO
Published: February 2025

The growing development and massive advancement of artificial intelligence (AI) is changing the way and method of working. Furthermore, additive manufacturing (AM) or 3D printing are taking new paths to the production of increasingly functional and aesthetic elements in the industry. This work shows how artificial intelligence can be part of the urban furniture design process. The manufacturing of the resulting designs will be done using large format additive manufacturing technologies, allowing the creation of more complex, unique, and functional pieces. This communication investigates the different types and possibilities of AI in image generation and shows study cases in which its capacity is evaluated, to select the one that is most appropriate for outdoor objects (benches). The process is investigated and shown until the AI generates a quality image from a text that will also be designed. This text or prompt is designed considering a series of requirements that will be based on different investigations and a questionnaire carried out among the population. Finally, the adapted 3D models of outdoor furniture are generated so that the printing process can be as efficient as possible and pro-vides the best results.
APPLICATION OF 3D PRINTING IN THE PRODUCTION OF MULTIMATERIAL HOLLOW POLYMERIC PARTS
Authors: GOMEZ ALONSO JOSÉ ANTONIO , ALLUE SALVADOR ALEXANDRA , NEIRA HERNANDEZ SANTIAGO , PINEDA MATABUENA DIEGO
Published: February 2025

The combined application of polymeric 3D printing technologies along with post-processing methods also based on the application of polymeric resins enables the rapid production of multi-material parts with complex geometries. In these parts, materials that provide various functionalities and performance can be combined. It is possible to combine rigid and flexible, solid and foamed materials, or materials that combine mechanical, thermal, acoustic, gas barrier, or thermal and electrical conductivity properties.
In this work, using extrusion, laser sintering of thermoplastic resins, and digital light processing of photopolymerizable resins as 3D printing technologies, the production of a hollow multi-material part has been explored through its combination with reactive resin casting post-processing.
The selected hollow part represents a demonstrator liner for the subsequent manufacturing, by filament winding, of a tank for the storage of pressurized gases. In hydrogen tanks, the liner provides impermeability to the tank, minimizing hydrogen leakage.
In the field of mobility and transport, type IV hydrogen tanks are commonly used. These are lightweight and resistant tanks formed by an inner plastic lining, usually produced by injection molding, extrusion-blow molding, or rotational molding, surrounded by an external composite wrapper that provides mechanical properties.
The study has successfully applied 3D printing to obtain a multi-material liner capable of providing additional functionalities to the entire tank, in which materials from the same family as those used in the composite envelope can be used. It has been verified that the hollow multi-material structure can withstand the stresses generated in the application by filament winding of the external carbon composite layers. This opens the possibility of using 3D printing technologies as an additional tool in the manufacturing of tanks for the storage of pressurized gases.
Key Words: 3d printing, multimaterial, multifunction, liner, filament winding, hydrogen tank.
TECHNIQUE AND AESTHETICS: LIVED EXPERIENCE IN RHYTHMIC GYMNASTICS BY AN ATHLETE WITH DOWN SYNDROME
Authors: Frazão da Silva Enoly Cristine , Celli Mota Kaio César , Carbinatto Michele	Viviene
Published: February 2025

Access to and provision of sports opportunities for people with disabilities have expanded globally across various levels of practice, from promoting active living to fostering high performance. Within gymnastics, initiatives for rhythmic gymnastics tailored to this audience are still in their infancy. However, the Special Olympics movement has made significant strides in offering rhythmic gymnastics programs for girls and women with Down syndrome. Drawing inspiration from phenomenological studies, this article explores the lived experiences of a high-performance athlete with Down syndrome in rhythmic gymnastics. Data was constructed through a triangulation of methods, including an informative questionnaire, phenomenological interviews, visual methodologies, and non-participant observation. Our analysis identified two key themes: sports technique as a catalyst for athlete recognition and aesthetics as a source of empowerment and a platform for the athlete’s agency in the world. By focusing on the lived experience of a disabled athlete, this study underscores the importance of supporting and empowering this community within sports. It challenges ableist perspectives and emphasizes a vision of sports as an inclusive domain, shaped and enriched by all.
VALIDITY AND RELIABILITY OF TWO STRAIN GAUGES TO MEASURE UPPER-BODY RELATIVE STRENGTH IN GYMNASTICS STILL RINGSGTH IN GYMNASTICS STILL RINGS
Authors: Lecocq Tom , Mochizuki Luis , Gouelle Arnaud , Tordi Nicolas
Published: February 2025

The still rings routine has evolved over the last century, emphasizing increasing strength. What is paramount is not absolute but relative strength, as each gymnast hangs from the still rings and must overcome the effect of gravity on their body using their own upper limb characteristics: strength and dimension. While the vertical force produced by the gymnast is easily measured on a force plate, a specific computation is required when the force is measured in the cable, as the cables are not perfectly vertical. No publication has yet investigated the impact of cable length or the distance between the rings (i.e., the gymnast's arm span) on the tension measured in the cable. The purpose of this study is to validate strain gauges in comparison with a force plate and to provide recommendations for their use in assessing a gymnast's relative strength. To address this, a static loading procedure was performed with weights ranging from 50 to 80 kg, increasing in increments of 10 kg (50, 60, 70, 80 kg). Different distances between the still rings were tested, ranging from 50 cm (vertical cables – 0.0° angle) to 170 cm (31.1° angle), with increments of 20 cm (i.e., 10 cm on each side). Each weight was first placed on a pair of force plates (K-Deltas, Kinvent Biomécanique) before being hung in the middle of the rings with cables equipped with 1-axis strain gauges (K-Pull traction dynamometers, Kinvent Biomécanique). The largest discrepancy between the two methods was 10.31 N, which could be attributed to the sensor as well as the distance between the rings. This article provides a clear answer to the questions regarding the effects of the angle and the length of the cable on tension. Strain gauges are a smaller, lighter, and more affordable alternative to force plates while remaining reliable, valid, and discriminative, provided that the cable angle is known.
Analisis Struktural Perdagangan di Indonesia: Pendekatan Bayesian VAR
Authors: Fadlilah Annastia Abqiatul , Kurniawan Mahrus Lutfi Adi
Published: February 2025

This research aims to determine the response of central government expenditure, government debt, government capital expenditure, population growth to international trade. The dependent variable in this research is the international trade variable and the independent variables include government debt, central government spending, government capital spending and population growth. The data in this research includes time series data in the form of percentages from 1971-2020 which were analyzed using the VAR (Vector Autoregressive) method. The results of this research are that all variables have a significant and positive response to international trade shocks. Based on the variance decomposition test, all variables contribute to international trade and have an increasing contribution until the final period. This is shown by the S.E value in period one of 12,242 and increasing in period ten of 27,282. Then the state debt variable has a high contribution to international trade and is continued with the government spending, capital learning and population growth variables.
Impact Analysis of Rules of Origin on Indonesia Export Performance: Case Study on Indonesia-Japan
Authors: Andiani Desy
Published: February 2025

Japan is one of main Indonesia’s trading partners. This research aims to analyse the impact of ROO’s restrictiveness on the Indonesia export performance and the utilisation of preferential schemes for both IJEPA and AJCEP. This study constructs ROO Index based on Product Specific Rules (PSR), as proxy of ROO, at 6-digit HS level to measure the restrictiveness level. This research found that the restrictiveness of ROO has a negative impact on total exports and utilisation for both FTAs. Increasing rate of applied tariff would reduces the total export, while the rate of margin tariff positifely impacts the utilisation rate. Providing facilitative PSR would likely improve export performance and utilisation of international trade agreements.
Tinjauan Sistematis : Transformasi Pelayanan Metrologi di Era Digital (Metrologi Digital4.0)
Authors: Lumbanraja Penny Chariti , Lumbanraja Pretty Luci
Published: February 2025

Legal metrology services are very important to answer the need to ensure fairness in trading activities, especially during the weighing and measuring process. Metrology as an important element in trade must also face challenges in adapting to changing times. The application of legal metrology services in trade transaction activities is aimed at protecting every citizen's rights as a whole, whether acting as a business actor or consumer. The rapidly developing transformation is changing society, industry and the economy. Transforming metrology services in the digital era certainly requires a long process. In solving this problem, developing quality digital metrology infrastructure is important. The data analysis technique used in this research is a systematic literature review. From the results of reviews conducted in several studies, it was found that the focus of metrology transformation is on improving the quality of infrastructure for the establishment and development of metrology clouds so as to provide economic benefits and create digital confidence in measurements. The important aim of improving infrastructure quality in digitalization of metrology is to strengthen the three main pillars, namely metrology services, accreditation and standardization.
Study of Beauty Consumer Behavior on Social Media: The Effectiveness of Beauty Influencer Marketing Targeting Generation Z
Authors: Jeong Sun-Hee
Published: February 2025

This study investigates the impact of social media on beauty consumer behavior, with a specific focus on the effectiveness of influencer marketing targeting Generation Z. As one of the most digitally engaged demographics, Generation Z actively shapes beauty trends on platforms such as Instagram, TikTok, and YouTube. Their engagement with these platforms is influenced by several key factors, including information availability, trustworthiness, interactivity, and timeliness. These factors were examined to determine their impact on Gen Z’s satisfaction and recommendation behaviors. The findings revealed that satisfaction among Generation Z consumers is significantly influenced by information availability, interactivity, and timeliness, while trustworthiness did not show a notable effect. Conversely, recommendation behaviors were positively affected by information availability, trustworthiness, and timeliness but were not influenced by interactivity. These results highlight the unique digital consumption patterns of Generation Z, where dynamic and accessible content plays a critical role in driving satisfaction and recommendation intentions. Additionally, their tendency to engage passively spending more time observing than actively sharing content was identified as a characteristic behavior. This study contributes to the understanding of Generation Z’s beauty consumption behavior and provides foundational insights for developing effective influencer marketing strategies. Future research should examine platform-specific behaviors to design more targeted and sophisticated approaches for engaging Generation Z consumers in the beauty market.
A Study on Career Identity and Innovative Behavior of Beauty Workers: The Mediating Effects of Work-Life Balance and Job Crafting
Authors: Seon Sook-Hyun , Jeon Hyun-Jin
Published: February 2025

This study analyzed the mediating effects of work–life balance and job crafting on the relationship between beauty workers’ occupational identity and innovative behavior to provide basic data to promote innovative thinking and improve job satisfaction among beauty workers. A total of 429 questionnaires were used for Mean and standard deviation, skewness, kurtosis for each variable, frequency analysis and correlation analysis using Spss 24.0 WIN, and the model fit indices of the structural equation model were RMSEA index, which is an absolute fit index, and IFI, TLI, and CFI index, which are incremental fit indices. The mediation effect was tested by Bootstrap using phantom variables. The resulting path coefficients showed that the effect of occupational identity on innovative behavior was insignificant, and the effects of occupational identity and work–life balance, occupational identity and job crafting, work–life balance and innovative behavior, and job crafting and innovative behavior were significant and static. In addition, the indirect effects of occupational identity on innovative behavior through work–life balance and the indirect effects of occupational identity on innovative behavior through job-crafting were confirmed, and the indirect effects of work–life balance and innovative behavior were statistically significant.
AI-based Beauty Tech and Personalized Marketing Through Beauty Apps Impact on Perceived Values and Consumption Attitudes
Authors: Seo Eun-Hee , Kwon Oh-Hyeok
Published: February 2025

Recently, it can be seen that a large paradigm in the world, such as artificial intelligence (AI), companion robots, and chatbots, is making a big wave. For the beauty industry, which has been complacent about beauty, considering beauty as an inviolable zone that cannot be automated in a turbulent environment, this study aims to study the impact and applicability of AI-based beauty technology and personalized marketing through beauty apps on the development of the beauty industry, and to suggest the direction of personalized marketing through AI-based beauty technology and beauty apps.For the study, 300 men and women in their teens or older who have experienced personalized marketing through AI-based beauty tech and beauty apps living in the metropolitan area were surveyed for about a month from November 1, 2024 to November 30, 2024, and 282 copies were used for statistical analysis. As a result of frequency analysis, factor analysis, reliability analysis, and regression analysis using SPSS 25.0, it was confirmed that there was a positive (+) effect on both perceived value and consumption attitude of personalized marketing through AI-based beauty technology and beauty apps. Based on the results of this study, the beauty industry should actively utilize AI-based beauty technology and beauty apps to actively accept personalized marketing tailored to the needs and circumstances of customers, and beauty companies and beauty shops are expected to see the effect of increasing sales through active marketing such as installing AI-based beauty technology experience spaces in stores or shops. In addition, if consumers can actively use beauty apps to see how to use products, management methods, and effects, it will be easier and more friendly to appeal to consumers to choose products or services that suit them, and accordingly, it will be possible to add synergies to the increase in sales.
A Study on the Effect of Sociocultural Pressure of Adult Women on Appearance Management Behavior by Mediating Consideration for Others
Authors: Mun Hee-Jung
Published: February 2025

This study aims to develop effective marketing strategies and programs that can promote appearance management behavior by analyzing the effects of sociocultural pressures on adult women’s appearance management behavior through social orientation. For empirical analysis, a questionnaire survey was conducted on adult women aged 20 to 50 living in Daejeon, Chungnam, and Sejong, and Gyeonggi regions, and 204 valid copies were investigated. The collected data were analyzed using SPSS WIN 26.0, and frequency analysis and reliability analysis were performed to confirm the demographic characteristics and reliability of the measurement tool, respectively. In addition, multiple regression analysis mediating effects were conducted to confirm the mediating effect of social orientation in the relationship between socio-cultural pressure, social orientation, and appearance management behavior. The research results accordingly are as follows. First, the research hypothesis that socio-cultural pressure affects appearance management behavior was adopted, and specifically, there was an influence of the mass media. Second, the research hypothesis that socio-cultural pressure affects social orientation was also adopted, and specifically, there was an influence of the mass media and lover consciousness. Third, the research hypothesis that social orientation affects appearance management behavior was also adopted, and the influence was influenced in the order of hair (β=0.381), makeup (β=0.351) > skin (β=0.302). Fourth, it is investigated that socio-cultural pressure affects appearance management behavior through social orientation, indicating that social consideration is necessary because socio-cultural pressure decreases through social orientation.
Effect of Core Competencies of Beauty Service Workers on Job Enthusiasm
Authors: Kim Kyoung-In
Published: February 2025

This study verified the relationship between major variables based on previous studies for the purpose of examining the relationship between the core competencies and job enthusiasm of beauty service workers. The subjects of the survey were beauty service workers in Seoul and Gyeonggi Province, and 458 copies were used for the final analysis by conducting an online survey from July 1, 2024 to October 30, 2024. As a result of the analysis, five competencies recognized by beauty service workers were identified: professionalism, self-management, communication, personal characteristics, and knowledge and information processing, and three factors were derived for job enthusiasm. As a result of verifying the effect of the core competencies of beauty service workers on job enthusiasm, the core competency factor that has the highest influence was professionalism, which showed a high correlation of increasing immersion and commitment vitality. Self-management competency showed an influence on immersion and vitality, communication competency showed an influence on immersion and commitment, and personal characteristics were confirmed to have an effect on commitment. Through this study, it was confirmed that core competencies are organizational performance indicators that can bring a competitive advantage in the beauty service industry, and it is necessary to develop and develop the core competencies of beauticians according to the times and environment.
Unveiling Front Running : A Detailed Examination of Replay Attacks and Decentralized Oracle Vulnerabilities in Blockchain Systems
Authors: Kamiya Sharma
Published: February 2025

Although blockchain technology has made decentralization possible for the storage of data, openness, security, and truth are essential in a blockchain network. Oracles, which serve as bridges between blockchains and external data feeds, can also threaten the blockchain’s integrity by storing bad or inaccurate data.Additionally, Miner Extractable Value (MEV) has emerged as a major concern in the DeFi space.MEV is the profit obtained due to manipulating the order of operations in blockchain with MEV bots, causing financial losses from transaction fees and commissions. DeFi systems need to remain secure from such attacks as the oracle attacks that expose the system to substantial risks of losing money. Additionally, insufficient knowledge of how Oracle works increases the risks of compromising the DeFi system on a protocol level. This paper will use the example of how to move assets from Ethereum to Polygon and will focus on the possible dangers. It also offers an implementation model of a replay (front-running) attack and demonstrates how an attacker may choose transactions and benefit from the system at higher costs. This compromises decentralized oracles and results in losses in transactions through the reversal of order.
Predictive Modeling of Customer Satisfaction in Computer Hardware Product Returns: A Case Study in Bengaluru, India
Authors: Bhavya N.
Published: February 2025

Reverse logistics, particularly in the realm of computer product returns, has become a critical factor in modern business operations. With the rapid expansion of e-commerce, businesses must navigate the complexities of return policies to maintain both customer satisfaction and operational efficiency. This study examines the impact of consumer satisfaction with return policies for computer products in Bengaluru, India, a major technology hub. By employing a quantitative research approach, data from 223 customers were collected and analyzed using various machine learning models, including Random Forest, K-Nearest Neighbors, Logistic Regression, and Support Vector Machines. The study identifies key factors influencing customer satisfaction and determines the best-performing model for predicting consumer behavior related to product returns. Findings highlight significant influences such as ease of return, processing time, payment methods, and competition from alternative providers. The research provides actionable insights for businesses to optimize their reverse logistics strategies, enhance customer satisfaction, and foster long-term loyalty in the competitive e-commerce landscape.
Exploring the Potential of Royal Animal Optimization Algorithms for Diabetes prediction in Indian population data
Authors: Pawan Kumar Patidar
Published: February 2025

Introduction: Diabetes remains a major public health concern, particularly in India, where its prevalence is rising due to lifestyle and genetic factors. Advanced AI-driven optimization techniques can enhance predictive models, improving early diagnosis and intervention strategies.
Objectives: The objective of this study to explore the potential of Royal Animal Optimization (RAO) Algorithms, including the Lion Optimization Algorithm (LOA), Cheetah Optimization Algorithm (COA), and Polar Bear Optimization Algorithm (PBOA), to enhance predictive performance of ensemble algorithms. The prediction outcome of ensemble model is further explained with explainable artificial intelligence (XAI) model.
Methods:

Data Collection: The life style related data was collected from north east part of Rajasthan between July 2024 to December 2024.
Feature Selection: The RAO algorithms are compared with evolutionary Optimization (EO) and Swarm Intelligence (SI) based algorithms by selecting the most relevant features, with logistic regression (LR) as the objective function.
Predictive Model: An XGBoost classifier was implemented to perform diabetes classification. The RAO-based feature selection were integrated to optimize the model for high accuracy.
Performance Metrics: The model's performance was evaluated using classification accuracy to ensure reliability and precision in diabetes risk assessment.

Results: The XGBoost ensemble classifier along with ROA demonstrated superior performance, achieving a classification accuracy of 97.91%. This high-performance metric underscores the effectiveness of the proposed approach in identifying diabetes risk factors and predicting diabetes in the target population.
Conclusions: This study demonstrates that the outcome of XAI model depressed, severely anxious and aged people found at high risk of diabetes. RAO outperformed than other optimization techniques such as, evolutionary and swarm optimization. The findings emphasize the role of AI-driven optimization techniques in addressing the growing burden of diabetes and other lifestyle-related diseases.
Fuzzy based Congestion Control and Congestion Aware Routing Technique for IoT Networks
Authors: G. Srinivasan
Published: February 2025

Introduction: In Internet of Things (IoT) networks, the existing congestion control mechanisms did not often scale efficiently or maintain the heterogeneity of devices, causing performance bottlenecks and uneven network performance. Existing congestion control protocols may not adjust well to these dynamics, causing increased packet loss, suboptimal performance, and higher latency. 
Objectives: The main objectives of this work are to detect congestion at node level or link level and to determine congestion aware routing paths. 
Methods: A Fuzzy-based congestion control and congestion aware routing (FCC-CAR) technique for IoT networks is proposed. In this technique, Q-learning is applied at each node to select the parent node based on the link quality, node degree and hop distance metrics. Then, congestion at any intermediate node is detected by means of congestion degree, packet processing delay and packet loss, by applying Fuzzy logic decision model. Depending on the detected congestion status, appropriate congestion control mechanisms are applied. 
Results: Experimental results have shown that FCC-CAR technique minimizes the packet drop and delay while increasing the throughput.
Conclusion: Thus the proposed technique performs congestion control by means of congestion detection and congestion aware routing.
A Deep Dive into Training Algorithms for Deep Belief Networks
Authors: S. Manoha
Published: February 2025

Deep Belief Networks (DBNs) have emerged as powerful tools for feature learning, representation, and generative modeling. This paper presents a comprehensive exploration of the various training algorithms employed in the training of DBNs. DBNs, composed of multiple layers of stochastic hidden units, have found applications in diverse domains such as computer vision, natural language processing, and bioinformatics. The paper begins by delving into the pre-training phase, where Restricted Boltzmann Machines (RBMs) play a central role. We review the Contrastive Divergence (CD) and Persistent Contrastive Divergence (PCD) algorithms, shedding light on their strengths and weaknesses in initializing deep networks. Emphasis is placed on their applicability to different data types and scales. Moving to the fine-tuning stage, the paper explores the use of backpropagation with gradient descent, discussing modern optimization techniques, including stochastic gradient descent and adaptive learning rate methods. We also examine regularization techniques like dropout and weight decay to address overfitting concerns. Furthermore, we discuss architectural variants of DBNs, such as Convolutional Deep Belief Networks (CDBNs) for image data and Recurrent DBNs for sequential data. We highlight the adaptation of DBNs for specific tasks, including classification, regression, clustering, and generative modeling.
Exploring the Drivers of Impulsive Shopping on TikTok Shop: An SOR Model Perspective
Authors: Thi Hong Minh Trinh
Published: February 2025

Introduction: This study examines the factors influencing impulsive shopping behavior on TikTok Shop among university students in Ho Chi Minh City, Vietnam.
Objectives: Anchored in the Stimulus-Organism-Response (SOR) model, the research integrates additional constructs, including Shopping Addiction, Urge to Buy, and Subjective Norms, to offer a holistic understanding of the drivers and underlying mechanisms of impulsive shopping behavior within the context of social commerce platforms.
Methods: Data were collected through an online survey involving 350 university students in Ho Chi Minh City and analyzed using Smart PLS4.
Results: The findings reveal that Price, Reference Groups, Functional Benefits, Shopping Addiction, Urge to Buy, and Subjective Norms exert significant direct and indirect effects on impulsive shopping behavior on TikTok Shop.
Conclusions: This study extends the SOR model by identifying unique factors shaping impulsive shopping behavior on social commerce platforms, thereby contributing to the existing body of knowledge. The findings have practical implications for businesses and marketers aiming to optimize strategies on social commerce platforms. The study concludes by addressing its limitations and proposing directions for future research.
A Participatory and Integrated Urgent Flood Management Plan for Chiang Rai Municipality
Authors: Nawin Promjisa
Published: February 2025

This study aimed to investigate the management of local organizations regarding flood effects in Chiang Rai Municipality. The stakeholders of the participatory integrated management plan included a total of 500 supervisors or staff from government agencies concerned with fundamental information and development of Chiang Rai province, community leaders, relevant agencies and organizations, religious leaders, philosophers (folk philosophers), volunteer mainstays for flood management, and representatives of local people who had flood effects. A questionnaire was used as the research tool. Collected data were analyzed with mean and Standard Deviation (S.D.). The research results found that the management of local organizations regarding the impact of flooding in Chiang Rai Municipality, the research results were moderately demanding after the flood (M=3.33 and SD=0.83). They recommended that the participatory operations within the Chiang Rai Municipality area, the action and mitigation plan, and the restoration phases integrate the execution in multiple dimensions to drive the area-based mechanism to handle problems and cope with all risks.
Effect of Cryogenic Heat-Treated Honing Gears on Surface Quality Improvement of Bevel Gears in P-ECH Process
Authors: Anilkumar Kaldate, Ravindra Edlabadkar
Published: February 2025

In this paper, bevel gears made of 20MnCr5 alloy steel are finished using pulse electrochemical honing (P-ECH) process. The honing gears used during finishing process were made of same material, which obtained higher hardness than the workpieces through two distinct heat treatments. The two different heat treatments viz. (i) case hardening through a carburizing process (CP) alone, and (ii) a combination of CP followed by deep cryogenic treatment (DCT), (referred to as CP_DCT) were utilised to improve the surface characteristics of the honing gears. These honing gears were used in P-ECH process for finishing workpiece bevel gears. The experimental results indicates that the hardness of honing gears is crucial factor in improving surface quality of the workpiece bevel gears. Surface quality of workpiece bevel gears was assessed in terms of surface finish. The results show that, honing gears underwent through CP_DCT improves the surface roughness of workpiece gears by over 50% compared to those processed with CP alone. The enhancement will increase the service life and operating performance, reducing noise levels and the chances of premature failures of the finished bevel gears.
Refined Machine Learning Approach for IoT and Fog Computing Based Health Care Monitoring System
Authors: P.Karthikeyan, N.Balajiraja
Published: February 2025

The integration of Internet of Things (IoT) and Fog Computing technologies has paved the way for advanced healthcare monitoring systems that offer real-time, efficient, and scalable solutions for patient care. This paper proposes a refined machine learning (ML) approach to enhance the performance of IoT-based health monitoring systems, leveraging the computational power of fog nodes for data processing and analysis. The system collects health data from various IoT-enabled medical devices, including sensors for heart rate, blood pressure, glucose levels, and respiratory patterns. These data are pre-processed, filtered, and sent to fog nodes, where ML algorithms, such as decision trees, support vector machines (SVM), and deep learning models, are applied to detect anomalies, predict health conditions, and provide timely alerts. The refined ML approach involves optimizing feature selection, improving model accuracy, and reducing the latency of decision-making, all while ensuring efficient use of network resources. By distributing computational tasks to fog nodes close to the data sources, the system reduces the need for cloud-based processing, ensuring faster response times and lower bandwidth requirements. The proposed framework is evaluated in terms of its scalability, accuracy, and real-time performance in diverse healthcare scenarios. Experimental results show significant improvements in health condition prediction, anomaly detection, and energy efficiency when compared to traditional cloud-based solutions. This research highlights the potential of combining IoT, fog computing, and machine learning to build a robust, efficient, and real-time healthcare monitoring system, improving patient outcomes and facilitating continuous health management in smart environments.
Gaussian Iterated Map-Lyrebird Optimization Algorithm (GIM-LOA) and SPIHT Encoding Based Blind Dual Watermarking Scheme for Image
Authors: M. Subashini, P.V Ravindranath
Published: February 2025

A prominent area of study in digital Multimediaresearch is the Digital Watermarking (DWM) method, which has shown promise as a copyright protection tool. Blind watermarking schema and non-blind Water mark schema are the two classifications under which watermarking algorithms fall. The dual blind WaterMark (WM) technique in this work employs the Stucki Kernel halftone (SKH) algorithm, Set Partitioning in Hierarchical Trees (SPIHT), and selfrecoveries in images to detect tampering. and the Gaussian Iterated Map-Lyrebird Optimization Algorithm (GIM-LOA). SPHIT is used to rebuild the image. SPHIT can produce a bitstreams at desired rates including coefficientsof Wavelet Transforms. In the event that the received bit stream is interrupted, sound progressive transmission can be used to reconstruct the image. GIM-LOA is introduced for watermark bit mapping in an iteration-based method, utilizing its members' searching skills in water embedding. Each lyrebird, as a member of the LOA, determines the values of the Watermark bits according to its bit position. Updating the optimal bit solution should also be made easier by comparing the Objective Function (OF) values and authentication bit are generated using recovery bits prior to inserting the watermark, shuffle the WM components using GIM-LOA and Arnold Cat Mapping (ACM) and thus improving security and quality of the image recovery. The suggested algorithm performs better than current methods in terms of many statistical metrics and security elements of Tampering Detection (TD) techniques, and it is protected against various attacks.
Exploring the Nexus: How Bureaucracy Influences Community Participation in Decision-Making in Makassar
Authors: Delly Mustafa
Published: February 2025

This study explores the relationship between bureaucracy and community participation in decision-making in Makassar. In the context of democratic governance, community participation is crucial to ensure that the policies enacted reflect the needs and aspirations of the people. However, the level of involvement is significantly influenced by the bureaucracy's structure and functions. Using a qualitative approach, this research collects data through in-depth interviews with various stakeholders, including government officials, community members, and non-governmental organisations. The study focuses on understanding how bureaucratic processes, such as transparency, accountability, and responsiveness, impact the willingness of community members to engage in decision-making. The findings indicate that a transparent, accountable, and responsive bureaucracy can enhance community participation, fostering a sense of ownership and responsibility among citizens. Conversely, a rigid and unresponsive bureaucracy hinders community engagement, creating a disconnect between the government and the people. This research highlights the importance of reforming bureaucratic practices to promote active community involvement. By identifying barriers to participation and proposing strategies for improvement, these findings are expected to provide valuable recommendations for local governments in designing more inclusive policies that actively involve the community in the decision-making process. Ultimately, enhancing community participation not only strengthens democratic governance but also leads to more effective and equitable policy outcomes.
Approach to Handle Compound Out of Vocabulary Words in Hindi Web Queries
Authors: Amit Asthana
Published: February 2025

Introduction: Detection and handling Out of Vocabulary (OOV) words in information retrieval is a challenging task. This problem may become more challenging in case of Cross-Lingual Information Retrieval (CLIR) due to the complications with query translation. Compound Hindi OOV word problem has been less discussed in literature and no appropriate solution has been provided to overcome the issue in CLIR with web queries having such words. These words if not identified, may restrict to understand the proper meaning.
Objectives: The objective of this paper is to understand the impact and to handle web queries involving compound Hindi out of vocabulary words on the retrieval effectiveness.
Methods: This paper proposes an algorithm to detect and handle the compound Hindi OOV words in web queries. The algorithm has been applied on two categories of web query (i.e. having only compound Hindi OOV word and having ateast one such word in it) and the retrieval efficiency is calculated in terms of precision and average precision.
Results: Result highlight an improvement of 8.53% for one-word web queries having only OOV word and 15.68% with queries having more than one word involving at least one OOV word respectively.
Conclusions: The results of the work indicate that the proposed approach detects and handles specific type of OOV words present in Hindi web queries. Improvement in retrieval effectiveness for both types of queries has been observed. Queries having more than one word show better improvements than the queries with single OOV word. This could be attributed to the contextual information offered by the neighboring words.
An Attention-Based Deep Learning System for Text Detection and Information Retrieval from Images
Authors: Subhakarrao G, B Sujatha, L Sumalatha
Published: February 2025

This paper presents a new automatic approach to the extraction of textual information from natural photographs, addressing issues such as cluttered backgrounds, uneven lighting, and distortions. The system combines advanced computer vision techniques with OCR to detect, extract, and process text embedded in complex scenes. A deep learning-based text detection module identifies the text regions with high precision, and a robust OCR pipeline is used for extracting the detected text into a machine-readable form.Experimental evaluations indicate how well the system works under practical real-world applications, including obtaining an average text detection precision of 92% and accuracy for character recognition to be about 88%. Broad applications for this proposed method involve real-time translation, augmented reality, tools on accessibility for visually impaired persons, intelligent traffic monitoring, and even automated content indexing. It makes a new standard for information retrieval systems by being able to correctly extract text from natural scenes and opens the gates to innovative applications in artificial intelligence and digital data processing.
Assessing the Influence of Shopping Experiences on Customer Loyalty: A Study of Indian Jewellery Retail Brand
Authors: Vasudevan Sundararajan
Published: February 2025

Purpose - This Study aims to develop a framework by investigating the interrelationship between dimensions, shopping experiences, store preference dimensions, retail brand images, customer patronage, and advocacy.
Design/Methodology/Approach - In this model, store preference is a mediating variable around the other four constructs: shopping experiences, retail brand images, retail patronage, and advocacy. Extant literature has not studied the interrelations among these four variables. A path model is proposed to capture the five dimensions' direct and feedback effects using a simultaneous-equation rank-ordered logistic regression model. We capture the impact of demographic and geographic variables, buying occasions, and five dimensions. The results have been tested for reliability and validity.
Findings - Store ambience, product knowledge, staff courteousness, and presentation positively shape customers’ shopping experiences. The impact of loyalty and advocacy on shopping experiences has a favorable feedback effect. Store image attributes enhance retail patronage. Demographic variables, customers’ geographical locations, and situational factors affect shopping experiences and loyalty. Perception of overall product quality, finish of the products, and service responsiveness builds trust and positive word-of-mouth amongst customers.
Practical Implications - The study prescribes positive ways of utilizing shopping experiences to enhance store patronage, store image attributes, and customer advocacy. It also gives positioning ideas based on buying occasions and targeting ideas based on demographic variables.
Originality/Value - The study shows the feedback relationships amongst the five dimensions, which have not been studied using the simultaneous equations model framework. Jewellery-buying occasions were not considered in previous research studies and are a unique feature of this study.
Attitudes of Mothers of Primary School Students towards the Use of Smartphones in Education
Authors: Khaled Mahgoub Abdullah Mahmoud
Published: February 2025

The aim of the research is to know the attitudes of mothers of primary school students. In primary school Towards the use of smartphones in education, and the relationship between each of (the mother’s educational level, and the work of the mother, The average daily use of a smartphone by the mother, the gender of the student (male/female), and the school affiliation of the student (government/ private) And its trends towards the use of smartphones in education. The researcher used the descriptive approach and the questionnaire tool to collect data. And The research community consists of all mothers of primary school students in Wad Madani, the capital of Al-Jazeera State, Sudan. A representative sample of the research community was taken using the random sampling method, amounting to (300) individuals (mothers). Data were statistically processed using the Statistical Package for the Social Sciences (SPSS) program.(SPSS), and the research reached the following results: The attitudes of mothers of primary school students towards using smartphones in education are positive. There are statistically significant differences between the attitudes of mothers of primary school students towards using smartphones attributed to the variable of mother's work in favor of working mothers. There are no statistically significant differences between the attitudes of mothers of primary school students towards using smartphones in education attributed to the variables (the mother's educational level, the mother's average daily use of smartphones, and the student's gender "male/female"). In light of these results, the researcher presented a number of recommendations and proposals for future research in the conclusion of the research.