bluuebunny/crossref_metadata_2025 huggingface dataset:
PENGEMBANGAN MARKETING DAN SUMBER DAYA MANUSIA SERTA PENINGKATAN LINGKUNGAN HIDUP DESA CIKELAT
Authors: Ilham Maulana
Published: February 2025

Desa Cikelat, terletak di Kecamatan Cisolok, Kabupaten Sukabumi, memiliki potensi besar di sektor pertanian dan peternakan, didukung oleh kondisi geografis dan sumber daya alam yang subur. Meskipun demikian, desa ini menghadapi tantangan ketidakstabilan ekonomi dan pengelolaan UMKM, serta risiko bencana alam. Untuk mengatasi tantangan tersebut, pendekatan holistik dan partisipatif diimplementasikan dalam pelaksanaan Kuliah Kerja Nyata (KKN), dengan metode pengumpulan data kualitatif seperti observasi, wawancara, dan dokumentasi. Hasil program KKN mencakup peningkatan pemasaran UMKM, pengelolaan limbah, dan pelestarian lingkungan. Upaya ini meliputi pembuatan kompos, sabun dari minyak jelantah, serta ecobrick, dan melibatkan masyarakat setempat secara aktif. Selain itu, program juga berfokus pada peningkatan kualitas hidup dengan penanganan stunting, mitigasi bencana, Upaya kenakalan pada remaja. Dengan strategi yang tepat dan kolaborasi antara berbagai pemangku kepentingan, Desa Cikelat berpotensi menjadi model desa yang memanfaatkan sumber daya dan potensi lokal secara efektif.
MENDUKUNG PENGEMBANGAN USAHA MIKRO DAN KECIL, MENGEMBANGKAN POTENSI PERTANIAN DAN PENANGGULANGAN STUNTING DESA GUNUNG KARAMAT
Authors: Afiyah Dinda , Rifqi Pamungkas  , Akbar fadillah  , Dio Damas Permadi  , Muhammad Hidyat  , Utmy Sukmayu Saputri
Published: February 2025

Community Service Program (KKN) is a form of community service based on the Tridharma of higher education. The purpose of this Community Service Program (KKN) is to provide opportunities for students to devote themselves to society and contribute to solving problems and developing potential in the village. After conducting observations, there are several problems such as, land shifting disasters, Gunung Karamat Village also faces the problem of high stunting rates among children, MSMEs in Gunung Karamat Village, namely Coffee, the sale of coffee has not entered online stores and well-known cafes so that it hampers marketing and in terms of education or academics, in Gunung Karamat Village it can be considered lacking because the level of education from schools is only PAUD, SD, and SMP as well as the facilities in the realm of schools are not optimal. Therefore, we carry out several activities such as conducting socialization about disaster mitigation, socialization about stunting prevention and providing vitamins for children who are indicated to be stunted, and we help facilitate sales such as making branding videos and creating Shopee accounts to make marketing easier.
PENINGKATAN KUALITAS HIDUP DI DESA PASIRBARU MELALUI PENDIDIKAN, KESEHATAN, LINGKUNGAN DAN UMKM
Authors: Rahayu Amaliyah Kamis  , Siti Alfiyyatuz Zakiyyah Alawiyyah  , Annisa Tasya Aulia  , Julhan Abdul Malik  , Amelinda Renjani  , M Fadya Amar Fadillah  , Selpia Meilani  , Dede Jaenal Irawan  , Restu Ramdani  , Akmal Nur Fauzan  , Muhammad Dafik Kholik Firdaus  , Della Aprilla  , Badul Haris Mau  , Putri Dewi Salehati  , Nurul Alkarimah  , Asri Rahmawati  , Silviani Mustika  , Suciati  , Dede Lima  , Tia Maharani
Published: February 2025

Desa Pasirbaru terletak di Kecamatan Cisolok, Kabupaten Sukabumi, Jawa Barat, berbatasan langsung dengan Provinsi Banten, dan memiliki kondisi geografis yang khas antara pesisir dan perbukitan. Seperti banyak desa di Indonesia, Pasirbaru menghadapi berbagai tantangan yang mempengaruhi kesejahteraan masyarakatnya. Beberapa masalah utama yang dihadapi desa ini adalah rendahnya keterampilan komputer di kalangan siswa sekolah dasar, tingginya angka stunting, kesulitan dalam memasarkan produk UMKM, serta permasalahan pengelolaan sampah yang belum terselesaikan. Melalui pendekatan partisipatif yang melibatkan masyarakat secara langsung, mulai dari tahap observasi hingga implementasi, solusi yang tepat sasaran dapat dirumuskan. Kegiatan pengabdian ini bertujuan untuk meningkatkan literasi TIK di kalangan siswa, menurunkan angka stunting, memperluas jangkauan pemasaran produk UMKM melalui pemanfaatan media digital, serta menciptakan solusi jangka panjang dalam pengelolaan sampah, dimulai dengan aksi pembersihan pantai sebagai upaya awal yang berkelanjutan.
PERAN PEMUDA DALAM PROKLAMASI KEMERDEKAAN INDONESIA
Authors: Lucia Kharisma Ivana , Kamdan  , Purnama Insany Gina , Putri Hanifa , Nuraini Desti , Zalukhu Eliadi , Fitri Ramadani Rizka , Ramdan Alkausar Ryan , Padilah Qurani Intan , Wardin Hia Srifen
Published: February 2025

Perayaan 17 Agustus adalah untuk merayakan kemerdekaan, bersyukur karena telah terbebaskan dari penjajahan, serta menyadarkan masyarakat agar lebih mencintai tanah air dan menjaga persatuan bangsa. Kuliah   kerja   nyata   (KKN)   dilaksanakan   di   Desa   Gandasoli   yang   pada   dasarnya membutuhkan   peran   mahasiswa   dalam   melakukan   perubahan,   pengembangan,   atau memberikan  kegiatan  yang  bermanfaat  kepada  masyarakat  serta  mengembangkan  inovasi dalam  setiap  kegiatan  yang  dilaksanakan.  KKN  UNIVERSITAS NUSA PUTRA  melaksanakan program  pemberdayaan  masyarakat  secara  offline  berupa  upacara peringatan HUT kemerdekaan dilaksanakan pada pagi hari dengan upacara dan pengibaran bendera merah putih, karnaval dan ikut  terlibat  perlombaan  dalam rangka  memperingati  HUT  RI  ke  79  bersama  masyarakat  Desa  Gandasoli. Hal  ini  dilakukan untuk  meningkatkan  rasa  nasionalisme  dan  rasa  cinta  serta  bangga  terhadap  bangsa indonesia  yang  telah  merdeka  selama  79  tahun  serta  meningkatkan  jiwa  solidaritas  antar warga Desa Gandasoli.
Unveiling Public Sentiments in Crisis: The EHDSAF Approach to Dark Social Media Data during the 2010 Pakistan Flood
Authors: Tariq Fazal , Muhammad Tufail  , Taj Rehman
Published: February 2025

The flood in Pakistan has become one of the severe natural disasters in the country that has killed millions of people and made a wide impact on the economy, social life, and environment of the region. However, while the focus was mostly on the ground response, human emotions, and sentiments, which were shared on social media, known as dark social media data, were left untapped. In this research, federated querying involving the proposed approach EHDSAF (Enhanced Hybrid Dark Social Analytical Framework) is employed to aggregate and analyze unstructured social media data on the 2010 flood disaster. Thus, using the proposed approach, we reveal the unconscious emotions of people in different regions and aged within Pakistan. The study shows the ability to consistently monitor the emotional status of the population, differences in positive, neutral, and negative attitudes depending on the region and age category. These findings suggest a more profound understanding of the process of communication of the experiences and reactions during the crisis and provide the information that may prove useful for strategizing the future disaster management and the carrying out of humanitarian interventions.
PANDEMIC PORTRAITS AND GYMNASTICS FOR ALL ON SCREEN: WHAT DO CHOREOGRAPHIC COMPOSITIONS REVEAL?
Authors: Ferreira de Oliveira Michelle , Aguiar Rufino Thais , Nabeiro Minciotti Alessandra , Truzzi Luciano , De Toledo Eliana
Published: February 2025

The COVID-19 pandemic has had a global impact across multiple domains. This study aims to identify the characteristics of Gymnastics for All (GfA) choreographic compositions (CCs) performed virtually in 2020. This documentary research analyzed approximately 100 CCs presented in four Brazilian virtual festivals, focusing on three key aspects: theme, mise-en-scène, and music. The results revealed that predominant themes included reflections on life, resilience, and overcoming challenges. The mise-en-scène was notably simpler, utilizing indoor spaces such as rooms in homes and outdoor environments. Regarding music, there was a predominance of songs and international tracks. Overall, the pandemic influenced the profile of CCs, introducing new aesthetic perspectives while retaining core elements characteristic of Brazilian GfA compositions: collectivity, criticality, and creativity.
CONTEXTUAL FACTORS THAT INFLUENCE CHILDREN TO CHOOSE TO TRAIN RHYTHMIC GYMNASTICS
Authors: Reyno Freundt Alda , Meirone Matus Nicolás
Published: February 2025

Engaging in sports activity is influenced significantly by contextual factors, which can either encourage participation or lead to discouragement and disinterest. This is particularly true for sports with perceived exclusivity, such as rhythmic gymnastics, which is traditionally considered a sport for women. The present research adopts a collective case study approach, utilizing semi-structured interviews and a biographical-narrative methodology, focusing on the first Chilean children to practice this sport. The study seeks to uncover the contextual factors influencing their decision to participate and explore their experiences within the sport. Participants frequently highlighted the enjoyment derived from the sport, particularly the opportunity to manipulate various apparatus. Additionally, the study examines the crucial role of family support, experiences in school and clubs, and the influence of television and social media. In some cases, the resilience required to endure and overcome peer discrimination or ridicule is also discussed. The findings underscore that fostering an education free from gender bias can encourage broader participation in various activities, both recreational and athletic, without prejudice or fear—particularly in rhythmic gymnastics.
Analysis of Global Value Chains: Indonesia’s Pearl Industry Competitiveness
Authors: Ufairah  , Aisyah Sari Mutiara
Published: February 2025

As global value chain practices continue to spread worldwide, concerns about competitiveness emerge within prevailing policies, emphasizing long-term productivity and attractiveness. Indonesian South Sea pearls embody both economic potential and challenges affecting their bargaining power. This research aims to present a comprehensive overview of the Indonesian government's efforts to enhance south sea pearl’s competitiveness. Utilizing global value chain analysis, it explores the policies implemented by both central and local authorities to enhance the pearl industry's competitiveness, investigating their impact on company governance and upgrading practices through a focused case study on NMJ LLC. Results underscore substantial strides where the central government establishes legal foundations and enhances South Sea pearls quality. While the local government focuses on improving productivity in both downstream and upstream sectors. Additionally, both levels of government facilitate platforms for global market access. Moreover, the NMJ LLC case study analysis underscores policy implementation’s influence on its governance and upgrading, classified as retail buyer-driven value chain governance and product upgrading, respectively.
Urgensi Penegakan Hukum Dan Penguatan Peran Pengawasan KPPU Di Era Industri Digital
Authors: Nur Kholis
Published: February 2025

The advent of the digital age brought great change in many aspects including the field of commerce. Trading activities initially done directly become online. Such activities have taken a toll on the implementation of the joint venture control carried out by the commission of the joint venture supervisory the Indonesia Competition Commission (KPPU). Article 30, 1999 rule number 5 on the ban on monopoly practices and unhealthy business competition. This journal was written in order to, first, analyze the importance of law enforcement in preventing unhealthy business competition in the digital industrial age. Second, to analyze the contribution of the KPPU to monitor the unhealthy business competition in the digital market. The study is conducted with qualitative research methods, with a normative-law approach. And providing the basis for law enforcement, the unsound competition for business is the Law. Number 5 chapter 30 in 1999 on the ban on monopoly practices and unhealthy business rivalries. But at its implementation it is still under maximum, still deselect. Therefore needs to be more intensified. In practice, the contribution of the KPPU is less than optimal, requiring new legitimacy and legality that give more authority or authority to the KPPU to be capable of performing maximum, iron-to-profit surveillance duties and minimizing the fraudulent practices of digital trade in the digital age.
Analysis of AI Beauty Tech Patent Trends by Cosmetic Type
Authors: Ki Jin-Sun , Jung I-Han , Jeong Yu-Mi , Kim Haeng-Eun
Published: February 2025

The purpose of this study is to investigate the technical characteristics and trends of AI beauty tech patents by cosmetics type, analyze them by cosmetics type, and evaluate technological competitiveness and marketability through patent analysis. Through this, it is expected to be able to contribute to the development of the industry through strategic implications for strengthening the technological competitiveness of the domestic beauty industry, suggest the direction of development of the AI technology-based beauty tech industry, and make policy suggestions to strengthen the competitiveness of the domestic beauty industry. This study analyzed the patent trends in the beauty sector to which AI technology was applied by cosmetics industry and investigated the patent status. The patent search used the KIPRIS and Kewart databases, and only published and registered patents among the searched patents were selected for analysis. Using the patent search databases of KIPRIS and Kewart, this study performed a more accurate patent analysis by complementing the advantages and disadvantages of the two databases. In addition, by cross-verifying the search results of the two databases, the reliability of the data was increased through the process of removing duplicate patents and adding missing patents. Patent search and data collection were conducted for 14 days from November 3 to 16, 2024, and domestic patents were targeted. Through this, 449 patents were finally selected as analysis data. The collected data were analyzed focusing on the current status of patent applications by 13 cosmetic types and the patent share by cosmetic type. As a result, in this study, the result that the number of AI beauty tech patents was high in the order of color cosmetics products and basic cosmetics products, which will contribute to the development of the beauty field itself and the search for expansion to other industries at the same time.
Application and Educational Effectiveness of a Personal Color Education Program Based on Virtual Reality (VR)
Authors: Kim Sun-Hyoung
Published: February 2025

This study was conducted to apply a VR-based personal color education program to college students majoring in beauty and to confirm the positive effects of the VR-based color education program on beauty education. After applying the VR-based personal color education program, awareness of VR and interest and usefulness by sub-factors were improved, and educational content, instructor, self-direction, and learning efficiency factors were all improved. Educational effectiveness also improved learning satisfaction and learning transfer by sub-factors. As a result of analyzing the effect on educational effectiveness, it can be seen that the higher the awareness of the usefulness of VR, the higher the learning satisfaction and learning transfer. As a result of analyzing the effect of class factors on educational effectiveness, it was found that among the class factors, the higher the learning efficiency factor and instructor factor, the higher the learning satisfaction, and among the class factors, the higher the self-direction factor, learning efficiency factor, and instructor factor, the higher the learning transfer. This study conducted a class by applying a virtual reality-based personal color education program, and analyzed the correlation between the perception of virtual reality, class factors, and educational effectiveness to confirm the positive effect on beauty education.
Herbal Drugs: Role in the Treatment of Cancer
Authors: Jodave Rushiraj R. , Bamane Dinesh R. , Jambhale Aviraj B , Khelbude P. , Hotkar N.
Published: February 2025

Cancer encompasses a collection of diseases marked by the unrestrained growth and spread of abnormal cells. When this growth unchecked, it may lead to tumors, harm to bodily tissues, and the dissemination (metastasis) to various other areas of the body. There are numerous cancer types, such as breast cancer, lung cancer, prostate cancer, skin cancer, each different regions. Typically, cancer originates from genetic mutations that interfere with normal cellular regulation, prompting cells to multiply uncontrollably. These mutations may be inherited, triggered by environmental influences (including smoking, radiation, or exposure to cancer-causing agents), or they can occur spontaneously. Treatment alternatives vary based on the cancer type and stage, potentially involving surgery, chemotherapy, radiation therapy, immunotherapy, and targeted therapies. Detecting cancer early through screenings can significantly enhance the prospects for effective treatment. Synthetic drugs for cancer therapy aim to precisely focus on cancer cells, prevent tumor advancement, or enhance the body’s immune system in combating the disease. Herbal medicines, sourced from natural plants, have been utilized in traditional medicine for centuries and are increasingly recognized in contemporary healthcare due to their potential healing properties. These natural substances provide a broad array of pharmacological advantages, such as antioxidant, anti-inflammatory, antimicrobial, and anticancer effects. Their capacity to influence various biological pathways makes them essential in managing intricate conditions, including cancer, heart diseases, and neurodegenerative disorders.
Enhanced Spectrum Sensing with Self-Organizing Maps and Deep Belief Networks: A Time-Efficient Approach
Authors: Suraj Shete
Published: February 2025

In today’s wireless communication era, Cognitive radio systems (CRS) report two pressing problems: the shortage or scarcity of usable frequencies and second is the efficient use of those frequencies by the legal (or "licensed") users. Spectrum sensing (or “Spectrum detection”) is the key process in the CRS that allows these systems to be "cognitive." Demand of wireless communications is not narrowing and in fact, it is accelerating day by day, particularly in emerging economies. An increasing number of methods, both classical and modern, are being developed for the robust and timely spectrum sensing. Classic methods for spectrum sensing, like MLP, CNN, and LSTM, routinely encounter difficulties in a balancing between two main design targets as: accuracy and computational efficiency. The real-time nature of typical application scenarios makes this operational challenge particularly noticeable. In this paper's introduction and the review of related work we underline the same. Thus, a very strong approach should use to explore the new deep learning techniques which preferably have relatively low in required computational overhead at same time secure high detection accuracy. The application of Deep Belief Networks (DBNs) and Self-Organizing Maps (SOMs) for enhanced spectrum sensing in CRNs is the subject of our study. The critical task is to evaluate these two models for accuracy and speed in detecting spectrum availability. Insights into the trade-offs between detection performance and computational efficiency are especially vital concerning SOM and DBN models because they are fairly new as compared to traditional spectrum sensing methods. Challenging conditions for spectrum sensing were utilized to assess the performance of DBN and SOM models, and the results were compared to benchmarks established by traditional methods. The obtained results shows that SOM gets to an amazing accuracy of 95.77% with an execution time of only 0.02 seconds, makes it extremely suitable for real-time applications. Meanwhile, DBN achieves a supreme accuracy of 99.85%, but with a moderate execution time of 147.08 seconds, demonstrating its ability to extract features hierarchically and in a very deep way. Both models outperform traditional methods, and they strike a superior balance between accuracy and computational requirements with modern hardware. These gained results spotlight SOM and DBN based methods are next-generation CRN system competitors. SOM’s architecture required low processing and power, and DBN’s near-perfect detection capabilities. This meant that CRN systems using deep learning could handle the RF spectrum under even the worst conditions also. Their potential gains offered insights into several key trade-offs.
A Hybrid Multi-Objective Evolutionary Optimization Algorithm for Next-Release Problem
Authors: Divya K V
Published: February 2025

The software requirements selection process, a crucial step in software development, is a complex task. It involves identifying the most beneficial set of requirements for a software release while adhering to budget constraints. This problem, known as the next release problem (NRP), is challenging and classified as a non-deterministic polynomial (NP) hard problem. Interdependencies and other limitations further complicate the specified criteria. Selecting a specific set of requirements for the upcoming software release is a computationally challenging issue, falling under the category of NP-Hard problems. This paper proposes a hybrid method called MO-ACO-DE, which combines Multi-Objective Ant Colony Optimization with Differential Evolution to solve the multi-objective NRP. This work defines the NRP as a multi-objective optimization problem with two challenging objectives: customer satisfaction and development cost. Additionally, three constraints are introduced to address two real-world instances of the NRP. The proposed approach combines the management techniques of ant colony optimization (ACO) with the operators of the differential evolution (DE) algorithm to balance the exploitation and exploration stages of the optimization process. Both benchmark and real-world classic and realistic datasets were used for the experimental analysis of the proposed model. The results indicate that MO-ACO-DE outperforms other methods and enhances the fairness of requirement selection, especially when budget limitations are decreased.
A Study on an Impact of Remote work environment on Employee Job Satisfaction With reference to Software Industry– India
Authors: R. Emmaniel
Published: February 2025

Telecommuting is becoming increasingly popular as it offers benefits for both employers and employees. It's also received a lot of renewed attention in the wake of the COVID-19 pandemic, which has forced many organizations to rapidly shift from traditional in-person work environments to a completely remote workforce for health and safety reasons. The long-term popularity of telecommuting is linked to the benefits it can provide, including reduced or eliminated commuting time, recruiting and hiring benefits, and increased productivity. Therefore, the purpose of the study is to understand the impact of a remote work environment and to identify factors influencing employee job satisfaction. Quantitative research will be conducted to conduct the study. Primary data was collected using a structured questionnaire. A stratified random sampling technique is used to select a sample of 75 employees from five software companies in India who participated in a pre- and post-test assessment. Statistical techniques including comparison chart, normality tests and paired t-test were used to analyze the data. Later findings from the implementation of STATA v.12 also highlight the impact of the remote work environment and the factors affecting employee job satisfaction. After its validity and reliability has been tested by the researcher. Limitations include the absence of a control group, which rules out the influence of potential extraneous factors on learning outcomes, which is a new avenue for future research.
Distributed Intrusion Detection System using Ensemble Learning Technique for Securing IoT Environments
Authors: B. Karthikeyan
Published: February 2025

Introduction: Conventional anomaly detection systems fall short in Internet of Things (IoT) as the range of possible normal behaviors for devices is much wider and more dynamic compared to traditional environments. Main issues of attack detection in IoT include dataset management and optimal feature selection. But existing Intrusion Detection Systems (IDSs) did not concentrate on this issue.
Objectives: The main objective is to classify the data as normal or anomaly using Machine Learning (ML) based algorithms and to test the dataset against an ensemble model involving number of ML classifiers.
Methods: In this paper, a Distributed Intrusion Detection System (DIDS) for IoT environments, using Ensemble learning technique is designed. Principal Component Analysis (PCA) technique is applied for reducing the dimension of data. For classifying the data as normal or anomaly, the classifiers Decision Tree, Gaussian Naive Bayes and XGBoost are applied. Ensemble Learning technique based on maximum voting is used, which combines the multiple learners in order to improve accuracy.
Results: By experimental results, it has been shown that the proposed maximum voting ensemble technique has higher attack detection accuracy with low false positives. 
Conclusion: This DIDS  can detect and classify nearly 32 attacks..
Optimized Dynamic Protocol Adaptation in SoC Architectures for Data Transfer using Coretex-M33 processor
Authors: Gundu Ramachandra Kumar
Published: February 2025

Introduction: The proposed work presents a dynamic protocol adaptation framework within a System-on-Chip (SoC) architecture to improve energy efficiency and performance
Objectives: It integrates components like processors and communication protocols (AXI, AHB, APB) essential for data transfer. The design features a Cortex-M33 processor and a Real-Time Monitoring System that evaluates workload and performance metrics for optimal communication protocol selection.
Methods: The Protocol Adaptation Mechanism dynamically adjusts protocol settings, while the Protocol Configuration Manager facilitates transitions among various protocols. To ensure efficient data transfer, AXI-to-APB, and AHB-to-APB bridges are included. The SRAM module enhances memory performance with 1500-location depth.
 Results: Results show significant improvements: for the 32-bit processor, slice register usage drops from 4201 to 3491, delay improves from 7 ns to 4.35 ns, and power consumption decreases from 18.34 mW to 10.96 mW. For the 64-bit processor, slice register usage declines from 4913 to 3891, delay improves from 11.45 ns to 7.35 ns, with power reduced from 17.34 mW to 10.42 mW. The area is also minimized, while throughput increases significantly.
Conclusions: Validated through obtained results in Vivado Design Suite 2018.1 on the Zynq 7000 board with comprehensive testing, this framework demonstrates enhanced adaptability and efficiency for various applications.
LLM for Automated Root Cause Analysis in Microservices Architectures
Authors: Amruta Mhatre, Afrid Shaikh
Published: February 2025

The adoption of microservices architectures has introduced significant challenges in diagnosing and resolving system issues efficiently, as multiple services handling millions of requests generate vast volumes of exceptions, including business errors and critical runtime failures. Traditional manual approaches for error analysis and Root Cause Analysis (RCA) are time-consuming, error-prone and lack scalability. Existing tools often aggregate exceptions but fail to effectively classify or diagnose root causes, leading to prolonged system downtimes and reduced developer productivity. This research proposes an automated solution leveraging fine-tuned Large Language Models (LLMs), combined with an Exception Classifier powered by Natural Language Processing (NLP) and machine learning techniques. The system adopts a layered architecture where exceptions are aggregated through a Kafka cluster. The Exception Classifier preprocesses error messages, extracts contextual information and categorizes exceptions into business and runtime errors. Classified runtime errors are forwarded to the RCA service, where fine-tuned LLMs perform detailed diagnostics by analyzing exception stack trace and tokenized code repository. The solution targets over 90% precision for business exceptions and 89.6% recall for runtime exceptions in Exception Classification and less than a second for RCA diagnostics per exception and gives over 85% accuracy in human qualitative evaluation. By automating error classification and RCA, the proposed system promises faster fault resolution, improved RCA accuracy and enhanced developer productivity, contributing to more resilient and efficient microservices environments.
Transformer-Based Image-to-LaTeX Conversion: Improving Mathematical Equation Recognition with Self-Attention
Authors: Neeta P. Patil
Published: February 2025

Automating the transfer of mathematical equations from photos to LaTeX code is difficult because to handwriting diversity, formatting issues, and structural difficulties. Traditional CNN and RNN models struggle with long-term dependency and input variability. To overcome these challenges, we present a transformer-based encoder-decoder architecture that uses self-attention to increase contextual comprehension and sequence alignment. The model is trained on the im2latex dataset using token-level cross-entropy loss and sequence-level BLEU-based reinforcement learning, followed by Adam and beam search for inference. Compared to existing models, the proposed model has the greatest BLEU score, competitive MED performance, and better robustness against noisy and handwritten inputs, however the Exact Match (EM) score shows space for improvement. This study demonstrates the efficacy of transformer-based architectures for improving LaTeX conversion accuracy and mathematical document processing.
Influence of Sustainable Human Resource Practices on ITES Organizational Culture
Authors: Suma, K. Rajesh Kumar
Published: February 2025

The Information Technology Enabled Services (ITES) sector has undergone significant transformation due to rapid technological advancements, globalization, and shifting workforce dynamics. The sustainability of human resources (HR) in this evolving scenario has emerged as a critical factor for organizational success. ITES organizations face challenges such as employee burnout, skill obsolescence, and high attrition rates, which require innovative HR strategies for workforce retention, reskilling, and well-being. This study investigates the sustainability of HR in the changing ITES landscape, focusing on the interplay of technological adaptation, employee engagement, and organizational practices.The research utilizes primary data collected from 250 respondents through a Google-based survey. The objectives include analyzing the impact of digital transformation on HR sustainability, identifying key factors influencing employee satisfaction, and evaluating the effectiveness of current HR practices. The study proposes three hypotheses to examine correlations between HR strategies and employee outcomes, aiming to provide actionable insights for enhancing workforce resilience and adaptability in the ITES sector. Statistical analysis the result indicated that while the factors related to sustainable HR practices have the potential to positively influence employee retention, the hypothesis that these practices significantly reduce attrition rates was moderate. However, the overall trends suggest that HR practices do play a critical role in shaping employee satisfaction and retention, and improvements in these areas could eventually lead to a reduction in attrition rates in the ITES sector. The findings contribute to the growing body of knowledge on HR sustainability and offer practical recommendations for industry stakeholders.
Comparative Study and Detection of Lymphoma through Medical Imaging and modified ResNet and VGG Models
Authors: Kirtida Naik, Bindu Garg
Published: February 2025

Diagnosis and treatment of lymphoma, an aggressive neoplasm of the lymphatic system, becomes extremely difficult when the patients present with various sub-types of lymphoma because of their peculiar heterogeneity in clinical presentation. The most probable chances of successful management or curing patients depend on early and accurate diagnosis. Most of the traditional tools they used like; biopsy and histopathological examination are invasive, long duration test procedures. This will reduce the time of diagnosis of lymphoma by using the combination of convolutional neural networks (CNN)-particularly modified ResNet and VGG models with the medical imaging into detecting and classifying lymphoma.The research is motivated to leverage the machine learning medical imaging technology advancement in developing a non-invasive, faster, and accurate diagnostic tool, which would be relied upon by clinicians to make better-informed decisions, eventually benefiting the patients with improved prognosis and reduced health costs. Transfer learning is the technique used to fine-tune the pre-trained weights of VGG16 and ResNet50 on the lymphoma dataset. The whole training phase is accelerated, and the performance of the model is also boosted when fine-tuned in this manner regarding the target task. Modification has been suggested in VGG16 and ResNet50 Models with pretrained weights to get optimum results on said dataset. The model is trained using optimization algorithms such as Adam and stochastic gradient descent (SGD), and its performance is evaluated using metrics like accuracy, precision, recall and kappa coefficient. The results indicate the effectiveness of Modified_VGG16-adam optimizer yielded 0.82 Precision, Recall 0.81,Kappa 0.7 and Accuracy 80.5 than VGG16 Models and Modified_ResNet50_adam optimizer gave 0.80 Precision, Recall 0.80,Kappa 0.58 and Accuracy 58.92 against ResNet50 Model. In future,other latest pretrained Models along with nature optimization algorithms can be integrated to improve overall accuracy
Plant Disease Detection Using Hybrid MobileNetV2- Compact CNN Architecture with LIME Integration
Authors: Venugopal Boppana
Published: February 2025

This paper presents an advanced approach to plant disease detection by implementing explainable AI techniques that combine MobileNetV2 architecture with transfer learning and compact convolutional neural networks (CNN). The study compares three distinct models' performance on a plant leaf disease dataset, revealing MobileNetV2's superior accuracy of 95% with 94% precision in disease classification, despite requiring 850 seconds for training. The Compact CNN achieved 82% accuracy with minimal training time of 420 seconds, demonstrating its efficiency for resource-constrained applications. Disease-specific analysis showed exceptional detection rates for common plant diseases, with Apple Scab at 96.5%, Black Rot at 94.8%, and Cedar Rust at 95.2%. The integration of LIME (Local Interpretable Model-agnostic Explanations) provided transparent insights into the model's decision-making process, while the Compact CNN demonstrated 45% reduced memory usage compared to MobileNetV2. This implementation establishes a robust framework for practical agricultural applications, balancing high accuracy with computational efficiency and interpretability.
Marketing Strategies in the Age of Social Media Harnessing Digital Platforms for Customer Engagement
Authors: Ashish Chandra
Published: February 2025

Social networking sites like LinkedIn, Facebook, Instagram, and TikTok have changed the way businesses advertise in the modern day by increasing connection with customers, strengthening brand loyalty, and generating more revenue. “This research uses data collected from 120 respondents via in-person interviews to examine how social media marketing affects consumer involvement, happiness, and loyalty. To assess the efficacy of social media marketing initiatives, statistical tests such as analysis of variance (ANOVA), t-tests, chi-square tests, and correlation analyses were used. Instagram in particular benefits greatly from the research showing that personalised and immersive content greatly increases engagement and happiness. Customers' reactions to social media ads vary by age and gender, but the research finds a robust positive association between involvement and loyalty to the company. In order to maximise engagement and loyalty across all demographic categories, marketers should implement platform-specific tactics, as shown by these studies.
Computer Geometric Modeling and CFD Simulation of Air Permeability in Knitted Fabrics
Authors: Wasit Chaikumming
Published: February 2025

The purpose of this study is to model the geometry of knitted fabric structures to predict air permeability using computational fluid dynamics (CFD). Rib 1×1 and interlock structures were simulated with varying loop densities and plain weft-knitted fabric models. The geometrical models of plain weft-knitted fabrics were studied using the Peirce model, the Leaf and Glaskin model, the Vassiliadis model, and Kurbak model, which considers the real shape of knit loops in three-dimensional space. A unit cell for each model was created with a single line of yarn path using SolidWorks software. Computational fluid dynamics analysis was then conducted on all samples using the SolidWorks Flow Simulation package. The numerical results demonstrated good agreement with the experimental data. The presented models provide a useful framework for predicting the air permeability of knitted fabrics by employing unit cells of the knitted fabric structure. This approach reduces operational complexity and significantly shortens solution time.
Comparison of Business Law in Developing and Developed Countries: A Case Study of Indonesia and Singapore
Authors: Siregar Boni , Giawa Fransisko , Ginting Meilani Amanda br. , Situmorang Olyhabana
Published: February 2025

This study aims to compare the characteristics of business law between countries, namely Indonesia and Singapore. Indonesia and Singapore have different legal systems; Indonesia uses civil law while Singapore uses common law, which affects regulations in business activities between the two countries. This study focuses on three main aspects: corporate regulation, intellectual property rights, and investor protection. This study found that Singapore is superior in terms of legal certainty and efficiency, while Indonesia still faces challenges in implementing regulations that often change. The results of this study are expected to provide further understanding of the implications of different legal systems and become input for policymakers in Indonesia in improving the investment climate.
Father's Responsibility for Child Maintenance in Divorce
Authors: Marbun Nismayani , Simamora Janpatar
Published: February 2025

The responsibility of fathers for child maintenance in divorce is a crucial issue in family law in Indonesia, regulated by the Civil Code (KUHPerdata) and Law Number 1 of 1974 concerning Marriage. This journal aims to analyze the legal obligation of fathers in providing maintenance to children after divorce, as well as factors that affect their fulfillment. This study uses a normative juridical method with an analytical approach to relevant legal provisions and case studies from court decisions. The results of the study show that fathers have the responsibility to meet the basic needs of children, including food, clothing, shelter, and education, until the child reaches adulthood or can be independent. Despite clear legal provisions, in practice, many fathers do not fulfill their obligations for various reasons, such as difficult economic conditions and a lack of understanding of legal responsibility. The court has an important role in enforcing this maintenance obligation through a fair judgment and in accordance with the father's ability. The study also found that communication between ex-spouses and support from legal institutions is essential to ensure that children's rights are met. It is hoped that the results of this study can be a reference for policymakers and legal practitioners in an effort to improve the protection of children's rights after divorce.
Bawaslu as Law Enforcer in Maintaining Democratic Elections in Indonesia
Authors: Manik Anre , Siregar Hisar
Published: February 2025

Regional Head elections in Indonesia are a real manifestation of direct democracy, where the people have a right to choose their regional leaders. The regional heads election is meant to be a very important thing in the discussion in society, where the regional heads election in Indonesia which is held every 5 (five) years is a momentum in determining who becomes the leader of the region. Often there are problems in regional head elections such as SARA issues, money politics to the issue of campaigns carried out outside the predetermined schedule. This makes the state through the law form an institution in terms of supervising regional head elections and elections. To overcome this, the existence of the general election Supervisory Agency (Bawaslu) as an independent supervisory institution is very crucial. In supervising the implementation of elections, ensuring that the democratic process rus fairly, honestly, and transparently. This journal will discuss the role of Bawaslu as a law enforcer in maintaining regional election democracy in Indonesia, focusing on the authority, challenges, and efforts made to increase the effectiveness of supervision.
Actas del Libro de Profesiones del Monasterio de San Leandro de Sevilla (1700-1868)
Authors: Guijo Pérez Salvador
Published: February 2025

With the present work we make known the seats of the third book of professions of the monastery of San Leandro that covers from 1700 to 1868. It contains exams of habit and profession, as well as certificates of the own taking of habit, profession, licenses and commits. The article consists of a transcription of its most relevant data and a description of the volume. It is generally collected the type of act that is registered, name of the religious, name of their parents (profession), date of the act, place of birth and age of the religious.
Las exclaustraciones del siglo XIX en los conventos agustinos de Jerez, Sanlúcar y Chipiona
Authors: Jordán Fernández Jorge Alberto
Published: February 2025

We want to show the development of the process of reduction of the religious of three Augustinian convents nestled in the province  of Cádiz. We begin our exhibition summarizing the three processes of exclaustration that the religious lived in Spain during the first third of the nineteenth century. We stop at how these processes were lived in each of the three convents under study, approaching the vital trajectory of some of the religious inhabitants of these convents to know what happened to them after their expulsion.
Sexto libro de profesiones del convento San Agustín de Zaragoza (1701-1730)
Authors: Lazcano González Rafael
Published: February 2025

The books of religious professions are a first-rate documentary source for the knowledge of the human, cultural and social characteristics of the members of a religious province. Throughout seven consecutive works, each of the books of professions that are conserved from the San Agustín de Zaragoza convent (1605-1834; except the seventh book, 1730-1799, due to being lost) and the basic data of the professors will be presented: name(s) and surnames, what were their parents’ names, place of origin or birth, baptism parish, date of religious profession, name of the prior (or subprior) of the house and the prior general of the Order of St. Augustine, who was the novice master, and even the notary who attests to the fact of the profession. At the same time, the  profession records offer other details of no less importance for the multifaceted work of the historian. This article is about the sixth book of professions of the San Agustín de Zaragoza convent (1701-1730).
Reseñas bibliográficas
Authors: Lazcano González Rafael
Published: February 2025

Hans van den BERG, Alipio de Tagaste. Historia y ficción. OALA, México 2018, 677 p., ilustraciones. [Recensión de Rafael Lazcano].
Antonio ITURBE SAIZ, Roberto TOLLO (coordinadores). San Juan de Sahagún. Culto, historia y arte. Editorial Agustiniana-Biblioteca Egidiana, Guadarrama (Madrid)-Tolentino (Italia) 2019, 569 p., ilustraciones [Recensión de Rafael Lazcano].
Martín LUTERO, Obras reunidas. 2. El siervo albedrío y otros escritos polémicos. (Torre del Aire), ed. Gabriel Tomás, Trotta, Madrid 2019, 418 p. [Recensión de Rafael Lazcano].
Ramon PLANES ALBETS. El bisbe de Solsona Rafael Lasala i Locela  i l'historiador Domènec Costa i Bafarull. Presència il.lustrada valenciana a Catalunya. COSTA Y BAFARULL, Domingo, Breve historia y sencilla narración de la vida exemplar y muerte edificante del Ilmo. y Rmo. Señor Don Fr. Rafael Lasala y Locela, del Orden del G.P. S Agustín, obispo de Solsona, marqués de Olius, del Consejo de su Magestad, etc., [Pròleg, Xavier Novell Gomà, Bisbe de Solsona], [Bisbat de Solsona], Solsona 2018, 687 p., ilustraciones. [Recensión de Rafael Lazcano].
José Manuel ROMERO, Gesta misional de los Agustinos Recoletos en China, 1924-1955, prólogo Ángel Martínez Cuesta, [edita Agustinos Recoletos - Provincia de Nicolás de Tolentino], Madrid 2019, 542 p., ilustraciones. [Recensión de Rafael Lazcano].
STEM students prefer assessment practices known to reduce the impact of test anxiety
Authors: Costello R.A. , Hammarlund S.P. , Christiansen E.M. , Kiani M.K. , Glessmer M.S. , Cotner S. , Ballen C.J.
Published: February 2025

Undergraduate introductory STEM courses often rely on few, high-stakes exams to assess student learning. This assessment strategy engenders high test anxiety and negatively impacts academic performance. We know little about how students want to be assessed—particularly those who experience high test anxiety. Applying a humanist learning framework, we asked students at a university in Norway to envision their ideal assessment practice. Our analyses affirm that test anxious students performed worse in their STEM courses, and students with marginalized identities in STEM were more test anxious. Additionally, we found that students overwhelmingly want more assessments. We also found that first-generation students, a student group rarely studied in Norway, want different types of assessments to replace high-stakes exams. In sum, student preferences aligned with assessment practices known to reduce the impact of test anxiety. Our results support calls for creating STEM environments where student voices are valued.