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281 articles for “neural systems”
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Charting the Path Forward: An In-Depth Analysis of Breakthroughs and Hurdles in Artificial Intelligence
Abstract: Recent years have witnessed tremendous progress in artificial intelligence (AI), fueled by exponential increases in processing power and data accessibility. These developments have made it possible for AI to be widely used in a variety of industries, such as healthcare, finance, autonomous driving, and more. Significant difficulties are presented by the "black-box" nature of many AI systems, which lack transparency and the capacity to explain. By encouraging algorithms that can …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 13–23 Read article
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Enhancing IoT Network Security with Hybrid Deep Learning Classifiers for DDoS Attack Detection
Abstract: The security and operational dependability of Internet of Things (IoT) networks are seriously threatened by the growing susceptibility to Distributed Denial of Service (DDoS) assaults brought about by their rapid expansion. The intricacy and dynamic character of these advanced attacks can provide a challenge to conventional intrusion detection systems. This study presents a novel method for strengthening IoT network security by combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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Image Processing and Deep CNN-based Automatic Liver Cancer Detection
Abstract: Liver cancer ranks among the leading causes of mortality for people worldwide. In the current situation, manually identifying the cancer tissue is a challenging and timeconsuming task. Treatment planning, response monitoring, tumor load assessment, and prediction are all made possible by the segmentation of liver lesions in CT scans. To address the current problem of liver cancer, the Hybridized Fully Convolutional Neural Network (HFCNN), which has been theoretically modeled, has …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 39–41 Read article
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A Gamified Digital Platform for Sustainable Farming Practices: Simulation, Statistical Analysis, and Water Resource Management Implications
Abstract: Sustainable farming practices play a critical role in enhancing agricultural water use efficiency, conserving limited water resources, and ensuring long-term food security under increasing environmental and climatic pressures. Despite their importance, farmer participation in conventional agricultural extension and training programs remains limited due to low engagement and a lack of sustained motivation. To address this challenge, this study proposes a gamified digital decision-support platform aimed at promoting sustainable agricultural and …
Published in Journal of Water Resource Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 13–24 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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Detection and Classification of Brain Tumor from MRI And CT Images using Harmony Search Optimization and Deep Learning
Abstract: Primary brain tumor detection and classification are critical factors in ensuring effective treatment and, ultimately, improving patient well-being. This paper describes a novel method for detecting and classifying brain tumors with the help of magnetic resonance imaging (MRI) and computed tomography (CT) images. The suggested method combines harmony search optimization (HSO) and Convolution Neural Networks (CNN) based on deep learning techniques, yielding an impressive accuracy rate of 99.13% for both …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 31–49 Read article
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Artificial Intelligence in Cybersecurity: Emerging Trends, Technological Advancements, and Future Directions for Cyber Defense
Abstract: Artificial Intelligence (AI) is revolutionizing the field of cybersecurity by automating complex security tasks, improving threat detection capabilities, and enhancing the precision of threat response mechanisms. With the rapid evolution of cyber threats such as malware, ransomware, phishing, and data breaches, conventional security systems are often insufficient to provide timely and accurate protection. AI, powered by machine learning algorithms and neural networks, enables the analysis of vast datasets to detect …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 103–112 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
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Tank Water Quality Analysis Using Machine Learning
Abstract: Tank Water quality is a critical factor for public health, agriculture, as well as industry. Continuous monitoring of tank water quality: temperature, humidity, water level, CO2 concentration, and pH, is vital for safe usage. Using machine learning, real-time data analysis can detect anomalies, predict issues, and optimize water management, ensuring timely responses and improved safety. This intelligent approach enhances decision-making and maintains water quality effectively in various environments.We develop an …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 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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Revolutionizing Agriculture with Advanced Computer Vision Technologies
Abstract: The integration of computer vision technology in smart agriculture has marked a significant advancement in the way farming operations are conducted, leading to enhanced productivity and efficiency. This paper explores the multifaceted applications of computer vision, which include crop monitoring, disease detection, automatic harvesting, and quality inspection. By utilizing high-resolution imaging and advanced algorithms, farmers can achieve real-time insights into crop health and growth stages, enabling them to make informed …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 2, 2025 · pp. 24–30 Read article
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AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science
Abstract: This study presents the development and real-world deployment of an intelligent system for flood monitoring and automated dam gate control using artificial intelligence (AI) and internet of things (IoT) sensors. Supervised machine learning models are developed to predict floods up to 48 h in advance. An automated dam gate operation system is designed to leverage the flood forecasts and real-time stream water levels for emergency control. The complete end-to-end infrastructure …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 9–17 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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Advanced Deep Learning Techniques for Sickle Cell Anaemia Detection
Abstract: Sickle Cell Anemia (SCA) is a prevalent genetic blood disorder characterized by the presence of abnormal hemoglobin, resulting in the distinctive sickle shape of red blood cells. Timely and accurate identification of Sickle Cell Anemia (SCA) is essential for effective management and treatment. This study presents a new method that utilizes Convolutional Neural Networks (CNNs), a deep learning model particularly effective for image analysis. The process involves using microscopic images …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 9–15 Read article
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Integral Sliding Mode Control: A Review of Applications
Abstract: Integral Sliding Mode Control (ISMC) has emerged as a robust and efficient method for handling nonlinear systems with uncertainty, turbulence and external disturbances. This study provides a detailed review of ISMC and its design foundations, design methods, practical application aspects and recent developments are included. ISMC design methodology is explored, to be extended with various design methods with different design methods. Recent advances in research, chatter reduction techniques, applications in …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 1, 2024 · pp. 25–35 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article