Fostering Collaboration and Stakeholders’ Engagement at the Bayugan Central District Elementary Schools
Gladys L. Lagura and Eva P. Noynay
Abstract: This study explored the collaboration among stakeholders in Bayugan Central District Elementary Schools Agusan del Sur, focusing on the extent of collaborations and community benefits of their partnership through engagement, activities, projects, donations, and training programs. Using a descriptive correlational design and structured questionnaires, the research assessed these collaborations benefits to resource access
Ecological Determinants of Lumpy Skin Disease Virus Transmission in Wild and Domestic Cattle Populations
Sakshi Jaina, Deepika Yadava
Abstract: Lumpy Skin Disease Virus (LSDV) is an emerging transboundary pathogen of bovid that poses significant threats to livestock health and rural economies. While clinical manifestations of LSD are well documented, the ecological determinants that shape transmission across landscapes remain less systematically integrated into control frameworks.
Forest Governance related to Wildlife/CITES in Ethiopia-Implementation
Ali Seid Demeke, Fantaye Negash and Aweke Shitaye
Abstract: This paper aims at analyzing a review of policies in relation to wildlife conservation and management in Ethiopia. The paper will give information on wildlife policy, legal matters, challenges towards implementing existing wildlife laws, as well as perform gap analysis.
Workforce Structure and Economic Systems in Madagascar: Labor Markets, Institutions, and Contemporary Development Constraints
Raherisambatra Michael Josephson
Abstract: Madagascar’s workforce and economic system are characterized by a persistent dual structure in which a small formal sector coexists with a dominant informal and subsistence economy. Despite moderate economic growth in recent years, the country continues to face structural labor market challenges, including high levels of vulnerable employment, low labor productivity, and widespread working poverty.
Inflation Dynamics and the Cost of Living in Madagascar: Price Trends, Structural Drivers, and Welfare Implications in a Low-Income Economy
Raherisambatra Michael Josephson
Abstract: Inflation has emerged as one of the most persistent macroeconomic and social challenges facing Madagascar over the past decade. In a low-income economy characterized by widespread poverty, high informality, and strong dependence on food and fuel imports, price increases directly translate into welfare losses for households and heightened vulnerability for firms.
Autonomous Privacy Observability - An AI Agentic Framework for Real-Time Detection of CCPA and GPC Non-Compliance in Dynamic Web Frontends
Poorna Chander Kola
Abstract: The proliferation of dynamic web frontends, often leveraging Single Page Application (SPA) architectures and complex client-side interactions, has made the continuous monitoring and enforcement of data privacy regulations increasingly challenging. Traditional, static auditing methods and manual checks struggle to keep pace with rapid deployment cycles and the nuanced ways user data is collected and shared in real-time.
Enhancing industry collaboration for skills acquisition improvement among business education students in Cross River State Universities
Akeke, M.N.G., Atah, C.A., & Ateb. T. A.
Abstract: The study looked at ways to strengthen industry collaboration to improve skills acquisition among business education students in Cross River State universities. The study was conducted in Cross River State, Nigeria using data from three universities.
Enhancing Inclusivity in Fundamental Skills Development at Basic Education in Nigeria
AKEKE, M. N. G.
Abstract: All students, regardless of aptitude or disability, ought to be provided with basic education, which is the foundational level of formal education Globally, inclusive education aims to provide all pupils with regardless of the variety present in the system or society, an equitable and easily accessible high-quality education.
AI approach towards Quality Control Systems for Zero Defect Manufacturing
Dr. Dipali Brijpalsingh Tawar, Mr. Vinayak Sambhaji More
Abstract: Artificial intelligence (AI) has been included into quality control systems as a result of the drive for zero defect manufacturing, which has completely changed industrial processes. The application of AI-driven quality control systems in manufacturing settings is examined in this paper, with a focus on the systems' real-time fault detection, prediction, and preventive capabilities.
Ultrasound-Based Methods for Thyroid Nodule Detection and Classification: A Review
Shilpa Suhas Pawale, Dr. Sonali Kedar Powar
Abstract: Thyroid cancer, one of the most common endocrine malignancies, requires early and accurate diagnosis to improve patient outcomes. Recent advances in ultrasound-based techniques, including imaging protocols and computer-aided diagnostics, have significantly enhanced the detection and classification of thyroid nodules.
Impact of Artificial Intelligence on Industrial Sustainability
Dr. Divya Chitre, Ms. Bhakti Govind Shinde
Abstract: The increasing usage of Artificial Intelligence in the industrial setting has brought about a transformation in the industrial process chain, asset management, and decision-making mechanisms. Though AI-enabled systems are increasingly being regarded as facilitators of industrial sustainability, research evidence regarding the extent to which AI can contribute to industrial sustainability is still limited. This research aims to explore the role of AI in industrial sustainability using both conceptual analysis approaches and insights from existing industrial applications.
Green AI for Wireless Networks
Ms. Priyanka N. Bikkad, Dr. Manisha M. Patil
Abstract: The integration of Artificial Intelligence (AI) into wireless networks revolutionizes communication efficiency, but it also introduces significant energy demands
Data pre-processing in machine learning: A Research Perspective
Mrs. Namita Nitin Amrutkar, Dr. S. S. Kulkarni, Mrs. Sakina Sajjad Abaji
Abstract: Data pre-processing is a critical step in the development of machine learning (ML) systems, as the quality of input data directly affects model accuracy, reliability, and generalization
Reimagining HRM: The Role of Human-Centric AI in Employee Commitment and Development
Mrs. Shubhangi S. Chavan
Abstract: In today’s ever-changing digital work environment, incorporating Artificial Intelligence (AI) into Human Resource Management (HRM) is not a choice but a necessity.
Visualization-Driven Approaches in Mathematics Education: A Conceptual and Pedagogical Analysis
Supriya Deshmukh, Sumit Sasane
Abstract: Mathematics learning at the undergraduate level often reveals a disconnect between students’ ability to apply procedures and their understanding of underlying concepts.
Machine Learning-Based Sentiment Analysis of Customer Reviews: A Comparative Evaluation of Supervised Algorithms
Dr.Tejashri Sharad Phalle, Dr. Janardan Pawar
Abstract: Sentiment analysis is a vital use of Natural Language Processing (NLP) and machine learning, with broad applications in business intelligence, customer feedback systems, and social media monitoring. In this paper, for sentiment analysis of customer reviews supervised machine-learning algorithms are going to be compare.
Web Mining Applications in the Education Industry: A CRM Perspective
Ms. Swapna Tekale
Abstract: The World Wide Web has evolved into an enormous and continuously expanding digital ecosystem characterized by complexity and diversity. Its rapid growth has created significant opportunities for applying analytical approaches derived from data mining, collectively known as web mining.
The Quantum AI Revolution: A Review of Quantum Machine Learning
Mrs. Anchal Satpute, Dr. Madhavi Avhankar
Abstract: Quantum Machine Learning (QML) has become one of the leading interdisciplinary applications in terms of computational sciences.
Statistical Stability Analysis of Large Language Model Embeddings Across Prompt Variations and Model Architectures
Pawar Abhijit, Thakare Sarika, Ajagekar Pournima
Abstract: Large language models (LLMs) create numerical representations of text, called embeddings. These are key to applications like search and recommendations.
Adaptive Soil Nutrient Intelligence for Smart Agriculture Using IoT-Enabled real time NPK Sensing and Machine Learning
Jyoti N. Shrote
Abstract: Soil fertility is a critical factor influencing crop productivity, input efficiency, and long-term agricultural sustainability. Conventional laboratory-based soil testing methods are accurate but expensive, time-consuming, and unsuitable for continuous field-level monitoring.
A Review on Blockchain based secure communication for IoT Devices
Mrs. Minal S. Darekar, Dr. Madhavi Avhankar
Abstract: The Internet of Things (IoT) connects a massive number of heterogeneous devices that exchange sensitive data over open networks, making security, trust, and privacy critical challenges. Conventional centralized security models suffer from single points of failure, limited scalability, and vulnerability to cyberattacks such as data tampering, spoofing, and unauthorized access
Sustainable Green AI–Driven Cybersecurity Framework for Smart Cities: Energy-Efficient Edge-Based Intrusion Detection
Miss. Rutuja Deepak Mokashi, Mrs. Amruta Sakhare, Mr. Shubham Bende
Abstract: Smart cities run on digital networks think IoT devices, edge computing, and cloud tech. But as everything gets more connected, the risk of cyberattacks just keeps climbing. Traditional AI cybersecurity tools do a decent job spotting threats, but they’re power-hungry and need a lot of processing muscle. Not exactly ideal if you’re trying to keep things green and ready to grow.
Re-envisioning the Transportation Problem: Adaptive, Penalty-Free, and Decision-Oriented Approaches
Rajminar Navgire, Ramdas Bolage, Deepali Chaudhari
Abstract: The classical transportation problem is a model that helps us figure out how to transport things in the best way possible. It is mainly used to reduce the cost of transportation while making sure we have things to meet the demand. We already have some methods to solve this problem like the North-West Corner Rule, the Least Cost Method Vogel’s Approximation Method and MODI. However these methods are not perfect.
Security and Performance Evaluation of Edge Computing Frameworks in Smart Environments
Donna Parekh, Dr. Madhavi Avhankar
Abstract: This paper provides a comprehensive evaluation of the security and performance aspects of edge computing frameworks in intelligent environments, including smart cities, residences, and industrial IoT systems.
Predicting Student Dropout Rates Using Machine Learning Techniques
Neha Karade, Manisha Patil, Dhruvi Jariwala
Abstract: Student dropout has been a perennial phenomenon in the higher education landscape. Conventional methods of analysing performance alone are not very effective for the early warning indicators of disengagement. This paper examines the use of four machine learning models: Logistic Regression, Decision Trees, Random Forest, and Support Vector Machine, on a data set of 1,200 students pursuing their higher education to determine the efficiency of models to predict student dropout.
Comparative Effectiveness of Machine Learning Algorithms in Forecasting Employee Performance across Multiple Key Performance Indicators in Diverse Organizational Contexts
Sarita Byagar, Dr. Ranjit Patil
Abstract: One of the significant requirement for powerful Human Resource functioning is precisely predicting the performance of its employees. This study discusses a systematic comparative literature review of numerous machine learning algorithms for carrying out the prediction of performance of employees across various organizations.
Challenges in AI–Cloud Integration: A Comprehensive Review
Vividha Bahety, Dr. Dhanashri Kulkarni
Abstract: Artificial Intelligence (AI) has been broadly integrated with cloud computing. The integration of these technologies has involved a lot of attention as it can deliver scalable, smart, and economically feasible solutions in numerous fields. Despite this opportunity for scalability, intelligence and economic viability for various applications using AI and cloud computing combined, there are many challenges as well.
Blockchain Driven Solutions for Preventing Cyber Threats in Online Gaming
Deepali Chaudhari, Shweta Bhoyate, Rajminar Navgire
Abstract: Evolution of online gaming into complex digital ecosystems supported virtual economies involving real-money transactions, real-time multiplayer interactions, and competitive environments. These rapid growth in popularity of online gaming is resulted into significant cybersecurity challenges, like digital asset theft, account compromise, financial fraud and cheating. Centralized architectures followed by most gaming platforms may cause single points of failure, limited transparency.
A Literature Review Study on IoT-Enabled Distributed Learning Systems as an Emerging Trend in Information Technology for Sustainable Smart Education
Ms. Yogeshwari Yawalkar
Abstract: Emerging trends in Information Technology (IT) are transforming nearly every sector of society, with education being one of the most significantly impacted domains. Technologies such as the Internet of Things (IoT), cloud computing, artificial intelligence, edge computing, and big data analytics are converging to enable intelligent, flexible, and sustainable learning environments.
Artificial Intelligence–Enabled Stress Detection and Mental Well-Being Interventions: A Comprehensive Review
Ms. Bhakti Govind Shinde, Dr. Divya Chitre
Abstract: Stress and mental health issues have emerged as a pressing problem on work-places, educational institutions and hospital systems globally.
AI-Based Decision Support Systems for Sustainable Development
Madhumita Sharma, Neha Karade
Abstract: Making sustainable development happen is one of the most important and hardest to tackle issues of the twenty-first century. It takes a choice of understanding to be made under uncertainty and in the midst of complicated situations. Conventional Decision Support Systems (DSSs) have been unable to meet sustainability challenges owing to their inability to handle large-scale, different types of data efficiently.
A Comparative Study of Cloud Computing Techniques in respect to Security Challenges and different approaches to protect cloud premise
Dr. Dhanashri S. Kulkarni, Badshaha Gulab Nadaf
Abstract: Cloud is nothing but accessing all the services available worldwide. Cloud is specifically used for storage different resources and worldwide databases and also have access to utmost all the software’s across the world.
Comparative Analysis of Stress Detection Techniques Using Machine Learning
Varsha Narayanrao Ikhe, Monali Chaudhari,Santosh Kakade
Abstract: It is quite common in the modern world to find human beings having the mild or moderate mental stress in diverse circumstances. Meditable degree of stress is healthy to an individual, but excess of stress impacts the mental health of the individual and is a guarantee of suicidal tendencies should the stress remain unattended in the long run. As more and more people experience stress, it becomes imperative to be in a position to recognize it at an early stage and make people understand and fix it before it becomes too late.
Performance of Database Execution Time for Enhancing Big Data Storage in e-Libraries
Monali Chaudhari, Snehalata Shirude, Varsha Narayanrao Ikhe
Abstract: Advanced library platforms use large amount of data, referred as Big Data, play a vital role in most transactions, which involve the delivery of data such as course materials and eBooks to students and staff, etc other academic users. The purpose of this paper is to propose an ArangoDB based cohesive model for digital library by evaluating of this multimodel with other data models using query execution time.
Evaluating the Impact of Agentic AI on Smart Technology in Autonomous Advanced Environment
Shital Pashankar, Dr. Jyoti Jadhav, Dr. Deven Mahajan
Abstract: Agentic AI is an artificial intelligence that can perform challenging tasks with little human help. Unlike older AI which has to face strict regulations and constant monitoring, agentic AI is capable of making its own advanced decisions, adapting to new situations, and acting freely in a dynamic environment
A Review of Artificial Intelligence Techniques for Cybersecurity Threat Detection
Shilpa Nawale, Sarika Shingate
Abstract: The effectiveness of earlier signature-based and rule-driven methods of detection was declining due to the increasing number and complexity of threats. Artificial intelligence (AI) is now a vital tool in cybersecurity, which enables the analysis of patterns of behaviour and the detection of unusual activity within complicated networks. This paper offers an in-depth examination and assessment of AI-driven threat detection methods
Adaptive Cybersecurity Mechanisms for Climate- Resilient Agricultural IoT Systems
Ms. Mansi Dilip Shriwastav, Dr. Madhavi Satish Avhankar
Abstract: The increasing deployment of Agricultural Internet of Things (Ag-IoT) systems is transforming food production and enabling climate-resilient farming practices. However, the growing reliance on interconnected sensing, automation, and cloud platforms significantly expands the attack surface, exposing agricultural operations to cyber threats that can disrupt critical processes, compromise data integrity, and undermine food security.
An Intelligent Framework for Energy-Efficient Resource Allocation in Cloud Data Centres Using Deep Reinforcement Learning
Dr. Ganesh Bhondve, Prof. Prashant Malwatkar, Prof. Prasad Shaha
Abstract: The exponential growth of data-intensive applications ranging from Generative AI to Big Data analytics has led to a surge in the energy consumption of cloud data centers. In 2026, data centers are projected to account for approximately 3.5% of global electricity usage, necessitating a shift toward "Green Cloud Computing." Traditional resource allocation methods often rely on static thresholds or manual scaling, which frequently lead to either over-provisioning (wasting energy) or under-provisioning (violating Service Level Agreements - SLAs).
Intelligent Cyber Defense: Leveraging Artificial Intelligence and Machine Learning for Next-Generation Cyber Security
Mr. Prajwal Bhalsing, Dr. Shivendu Bhushan, Dr. Vishal Verma
Abstract: The rapid expansion of digital technologies, cloud computing, and interconnected systems has significantly increased the complexity and frequency of cyber threats. Modern attacks such as ransomware, zero-day exploits, phishing campaigns, and advanced persistent threats (APTs) are becoming more sophisticated and difficult to detect using traditional security mechanisms. Conventional rule-based security tools are ineffective against evolving attack patterns and generate a high number of false positives [1].
Review Blockchain-Enabled Deep Learning Model for Supply Chain Optimization in Logistics
Akkamma Sakpal, Sonali Powar
Abstract: The swift digitalization of logistics and supply chain networks has exacerbated the necessity of safe, smart, and adaptable opti-mization frameworks with the ability to operationalize huge volumes and heterogeneous and real-time information. Here, block-chain technology used in conjunction with deep learning has become one of the promising paradigms to eliminate the unresolved issues regarding the integrity of data, their transparency, confidence, and the efficiency of decisions in logistics activities.
Blockchain based Innovations in FinTech: A Review
Dr. Suwarna Suresh Kedari
Abstract: Blockchain Technology leads to most revolutionary developments in the financial technology (FinTech) industry. This technology improves efficiency, security and transparency of financial services. Traditional financial systems deals with issues like high transaction cost, fraud, delays in international payments and a lack of trust.
Internet of Things (IoT) in Smart Agriculture: A Comprehensive Review of Technologies, Applications, and Challenges
Jyoti N. Shrote, Vijay More, Dr. Suwarna S. Kedari
Abstract: Agriculture is undergoing a significant transformation due to the rapid advancement of digital technologies, among which the Internet of Things (IoT) plays a crucial role. Smart agriculture, also known as precision agriculture, leverages IoT-enabled sensors, devices, and data analytics to enhance productivity, optimize resource utilization, and ensure sustainable farming practices.
Emergency Medical Services(EMS) Optimization Through Deep Learning–Based Traffic Prediction in Smart Cities
Ashish Dhoke, Dr. Shivendu Bhushan, Atish Shriniwar
Abstract: The most important measure of success of Emergency Medical Services (EMS) is rapid response time. Traffic jams are taking the form of an unpredictable variable as the urban setting is increasingly becoming dense and has a significant influence on the survival rate of patients. The dynamic, non-linear characteristics of real-time traffic conditions do not rely on traditional routing systems based on the use of either static distance measurements or past averages.
Developing an Effective Safety Culture A Leadership Approach
Faisal Saleh Al-Nezari
Abstract: This paper highlights the critical role that the leadership plays in this process and examines how the companies may create a strong safety culture. It contains the qualitative study that conducted through stakeholder interviews, evaluates the literature on safety culture, and provides a framework for the incorporating Job Safety Analysis into permit-to-work systems.
Future of AI is Multi-Agent with Sub-Agents in Software Testing and Automation
Him Raj Singh
Abstract: Modern AI is shifting from a single “all-knowing” agent to networks of collaborating agents. In software testing and automation, this means deploying specialized sub-agents – each focused on tasks like UI testing, API validation, or security checks – under a coordinating orchestrator.
Post COVID Determinants of Cardiovascular Recovery: Insights from a Multi Centric Observational Study in Haryana, India
Sundeep Guliaa, Anil Kumara
Abstract: Cardiovascular diseases (CVDs) remain the leading cause of global morbidity and mortality, and the COVID‑19 pandemic has introduced new complexities by precipitating acute cardiac injury and long-term sequelae
Determinants of Adherence and Recurrence of Malaria Among Women of Reproductive Age in a Mixed Effects Model Analysis
Eric Onyango, Joyce A. Otieno
Abstract: Background: The recommended treatment for uncomplicated malaria globally since 2001 has been artemisinin-based combination treatments, or ACTs. Patient adherence to ACT is critical for curing malaria and preventing drug resistance.
Security Based on Matrix of Keys in Header and Transpose for Physical Token Authentication Device
Binu C T, Rubini P
Abstract: The cipher is created by transpose and interchange of rows and columns based on keys. Key is generated based on transpose and interchange of matrix and square matrix also with empty value. header contain the size of matrix.
The Effectiveness of the Public Media as compared to the Private Media in Sensitizing People on Pollution by the Mines: A case study of ZNBC TV1 and Rise FM Radio in Chingola District, Zambia
JANE SIMALUMBA, ELIJAH MUTAMBANSHIKU MWEWA BWALYA
Abstract: The study sought to examine whether the public and private media contribute towards the sensitization of the public on pollution from the mines and to establish which media house is more effective between Zambia National Broadcasting Corporation (ZNBC) TV1 and RISE FM radio on public awareness campaign on pollution in Chingola District in Zambia.
Analysing The Scope of Community Participation In The Decentralised Constituency Development Fund: A Comparative Study of Mongu Central Constituency And Nalolo Constituency In Western Province, Zambia
IGNATIUS KALALUKA MWALA, ELIJAH MUTAMBANSHIKU MWEWA BWALYA
Abstract: This study analysed the scope of community participation in the decentralised Constituency Development Fund: A comparative study of Mongu Central Constituency and Nalolo Constituency in the Western Province of Zambia
The Effectiveness of Communication Strategies Used for Revenue Collection on The Informal Sector: A Case Study of The Zambia Revenue Authority
MARTIN MAGEZA CHANDA, ELIJAH MUTAMBANSHIKU MWEWA BWALYA
Abstract: This study assessed the effectiveness of communication strategies used for revenue collection on the informal sector by the Zambia Revenue Authority. The informal sector is Zambia’s largest employer. However, its contribution to domestic revenues has remained disproportionally low.
Sustaining Patient Care Quality in Tertiary Care Teaching Hospitals in Developing Countries: Challenges, Strategies, and Systemic Imperatives
Dr Shishir Basarkar
Abstract: Sustaining quality in tertiary care teaching hospitals in developing countries remains a persistent challenge due to increasing patient loads, limited resources, workforce constraints, and competing demands of service delivery, education, and research. While many institutions demonstrate short-term improvements during accreditation cycles, long-term sustenance of quality often remains elusive.
Machine Learning-Based Adaptive Restraint Algorithms Using Pre-Crash Sensor Data and Occupant State Estimation: A Comprehensive Review
Ganesh Shete, Sachin Ratnaparkhi, Rakshit Gummaraju
Abstract: This comprehensive review examines machine learning-based adaptive restraint algorithms using pre-crash sensor data and occupant state estimation, analyzing 15 peer-reviewed studies published between 2015 and 2025. The review systematically categorizes research into four thematic areas
Aluminium Sill Extrusions for Side-Pole Crashworthiness: A Review
Sachin Ratnaparkhi, Ganesh Shete, Rakshit Gummaraju
Abstract: Side impact protection remains a critical challenge in automotive crashworthiness, particularly for battery electric vehicles where intrusion must be minimized to protect high-voltage components.
INFLUENCE OF GOVERNANCE PRACTICES ON SUSTAINABLE DEVELOPMENT OF THE SUB-SAHARAN AFRICAN COUNTRIES
James C.N Mbugua, Ibrahim Tirimba, Fred Sporta
Abstract: The study sought to assess the influence of governance practices on sustainable development of the Sub-Saharan African countries.
