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533 articles for “AI Machine Learning”
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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FLUTTERCHAT: A Real-time Firebase Chat Application with AI-based Chatbot
Abstract: Recently, the development and deployment of chatbots have gathered significant attention from both developers and researchers. Chatbots represent AI-driven conversational systems capable of understanding and responding to human language using advanced techniques like Natural Language Processing (NLP) and Neural Networks (NN). A cutting-edge real-time chat application has been crafted using Flutter and OpenAI, seamlessly integrating an AI-powered chatbot with an innovative image generator to enrich user interaction and engagement. The …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 42–51 Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Automated Healthcare Support System with AI
Abstract: The Automated Healthcare Support System with Artificial Intelligence (AI) presents a smart and scalable digital solution aimed at improving the accessibility and efficiency of healthcare services. The system is designed to provide preliminary medical guidance, perform symptom-based analysis, and deliver health-related insights through an intuitive user interface. By enabling early identification of potential health conditions, it assists users in determining the necessity of professional medical consultation. The proposed platform utilizes …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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AI Hindi Poem Generator
Abstract: The Hindi Poetry Generator project represents a pioneering initiative in the domain of computational creativity, blending machine learning algorithms and natural language processing methodologies to craft poetic expressions in the Hindi language. Rooted in the vast landscape of Hindi literature, this project harnesses the power of deep learning models to generate evocative and culturally significant poetry. At its core, the system relies on neural networks and sophisticated language modeling techniques …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 10–16 Read article
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Electronic Resources of University Libraries: AI-Driven Management and Optimization
Abstract: In order to maximize accessibility, utilization, and efficiency, university libraries’ growing reliance on electronic resources (ER) has prompted the creation of sophisticated management techniques. The difficulty of handling enormous volumes of data has increased as educational institutions move from conventional physical collections to massive digital repositories. A key instrument in revolutionizing library operations, artificial intelligence (AI) offers creative ways to improve retrieval methods, manage digital resources more effectively, and customize …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 8–15 Read article
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Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article
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A Review on the Impact of Artificial Intelligence on Cybersecurity
Abstract: When it comes to protecting against cyber threats, the use of AI is changing everything. Thanks to AI-powered technologies, organizations can now better foresee and handle potential intrusions. These solutions provide exceptional capabilities in identifying threats, monitoring in real time, and delivering predictive insights. But, with these innovations come significant hazards and difficulties, necessitating thoughtful deliberation and preventative measures. Artificial intelligence's impact on cybersecurity is explored in this article, looking …
Published in Journal of Artificial Intelligence Research & Advances Read article
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Overview AI-Driven Antenna Technologies and Privacy- Preserving Methods for Next-Generation 6G Wireless Systems
Abstract: The next generation of wireless communications, 6G, will be built on the convergence of artificial intelligence (AI) and advanced antenna systems. AI-driven antennas are poised to address the unprecedented requirements for data rate, reliability, adaptability, and ubiquity in future networks. An overview of current advancements in AI-enabled antenna systems for 6G networks is provided in this study. From traditional base station deployments to distributed, cell-free, and user-centric frameworks, it examines …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 28–34 Read article
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Data Recovery Using Brute Force Algorithm: A Review
Abstract: This article delves into the intriguing field of data recovery, with a particular emphasis on the brute force approach, a powerful yet frequently underappreciated method. We begin by exploring the evolution of data recovery techniques since the 1970s and 1980s, examining traditional methods used to retrieve lost or corrupted data. Following this historical perspective, the article provides a brief overview of various methodologies employed in data recovery, including techniques that …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 10–16 Read article
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CampusX: Empowering College Selection with 3D insights using machine Learning approach.
Abstract: CampusX redefines college selection with dynamic 3D insights, empowering students to navigate campuses virtually. Utilizing cutting-edge machine learning and visualization techniques, it transforms static data into interactive experiences. Personalized comparisons enable informed decision-making, while predictive analytics forecast future campus developments. With a user-centric interface and robust privacy protocols, CampusX ensures seamless exploration and data security. This innovative platform bridges the gap between prospective students and their ideal educational environments, revolutionizing …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 23–29 Read article
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Artificial Intelligence in Diagnostics: Advancements, Challenges, and Future Prospects
Abstract: AI is changing (and will change) healthcare as we know it, and diagnostics might be the specialty that feels the most discomfort. Artificial intelligence-based analytical systems are facilitating the detection, diagnosis, and treatment of a variety of diseases, with better accuracy, speed, and results. Now, this abstract investigates the role of AI in diagnostics, scouring its elements, landmark techniques, transformative impact and future overview. This article explains AI and discusses …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 8–17 Read article
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AI-Designed Functionally Graded Polymer Composites for Multifunctional Thin Films
Abstract: The design of multifunctional polymer composite thin films requires simultaneous optimization of mechanical, optical, barrier, and thermal properties—objectives often in conflict when using conventional homogeneous materials. This study presents an artificial intelligence-driven framework for designing functionally graded material (FGM) architectures in polymer nanocomposite thin films. We integrated machine learning with physics-based modeling to optimize compositional gradients across film thickness, achieving superior performance compared to homogeneous and discrete multilayer alternatives. A …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1026–1041 Read article
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AI-Driven Psychological Profiling on Social Media: Mechanisms, Ethical Breaches, and Regulatory Challenges in Data Inference
Abstract: This literature review examines AI-driven psychological profiling on social media, analyzing 21 academic studies that focus on machine learning techniques such as supervised learning, deep neural networks, sentiment analysis, and natural language processing. These methodologies infer mental health indicators—such as depression, anxiety, and stress—from users' digital footprints, encompassing linguistic patterns, engagement metrics, and temporal behaviors. While these tools offer potential for early detection of psychological distress, they also raise significant …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 1–7 Read article
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Employee Well-Being: Deep Learning Approaches to Stress Detection
Abstract: Stress has become a major concern for employee health, productivity, and overall well-being in today's fast-paced work environment. It is a growing global issue, affecting both individual employees and the productivity of organizations. Work-related stress occurs when the demands of a job surpass an individual's ability to manage, whether because of long hours, overwhelming responsibilities, or other pressures. Factors such as conflicts with coworkers or supervisors, constant changes, and job …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 52–58 Read article
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Multi-functional UAV for Disaster Response and Management
Abstract: Unmanned Aerial Vehicles (UAVs), commonly known as drones, have become integral across diverse fields such as agriculture, surveillance, and defense, with expanding roles in critical operations like search and rescue and post-disaster management. Despite their versatility, current UAVs encounter challenges in disaster response due to limitations in flight time, costs, and accuracy, particularly in dynamic weather conditions. The UAV is equipped with features essential for disaster site surveillance, human detection, …
Published in Journal of Aerospace Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 1–6 Read article
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AI-Enabled Linear Regression Model for Spectroscopic Milk Adulteration Analysis
Abstract: Milk adulteration poses a serious threat to public health and quality assurance in the dairy industry. This requiring rapid, reliable, and non-destructive detection techniques. This study presents a linear regression-based analytical model for identifying and quantifying milk adulteration using spectroscopic data. Spectral measurements of milk samples, including both pure and adulterated variants were acquired using spectroscopic techniques at relevant wavelengths.Blending of other components in pure milk , is specifically called …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 28–42 Read article
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Stock Market Prediction Using Machine Learning: Techniques, Challenges, and Future Directions
Abstract: The continuous advancement of machine learning (ML) technologies has significantly transformed the field of financial forecasting, particularly in the area of stock market prediction. The ability to accurately forecast stock price movements and market trends plays a crucial role in supporting informed investment strategies and effective risk management. This paper provides a comprehensive review of recent developments in the application of ML techniques for predicting stock market behavior. It classifies …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 10–16 Read article
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Cloud-driven Fraud Detection: Evaluating Decision Tree and Random Forest Classifiers for Credit Card Transaction Security
Abstract: With the alarming rise in global financial fraud, necessitating substantial annual losses, modern techniques for fraud detection are continuously evolving across various business domains. Fraud detection involves constant monitoring of user activities to estimate, perceive, or prevent undesirable behaviour. Cloud Computing emerges as a promising solution, accelerating application deployment, fostering creativity and innovation, reducing costs, and enhancing overall business acumen. This study introduces a cloud-driven approach to fraud detection, specifically …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 13–27 Read article