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127 articles for “ANOM”
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Deep Learning based Solution for Leaf disease Detection in Crops and Fertilizer Recommendation
Abstract: The field of agriculture faces significant threats, including diseases that attack plant leaves. To address this issue, our system assists farmers in promptly detecting plant diseases using advanced technology. The user, typically a farmer, only needs to capture an image of the affected leaf and input it into our system. Our system then analyzes the uploaded image to accurately identify the specific disease afflicting the leaf. This analytical process is …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 31–40 Read article
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Multimodal Generative AI for Vehicular Applications at Edge
Abstract: This paper explores how the rapid advancements in vehicular technology, including autonomous driving and intelligent transportation systems, have driven the need for real-time data processing and decision-making. Multimodal generative AI, when deployed at the edge, offers a powerful solution for vehicular applications by leveraging diverse data sources such as video, audio, sensor inputs, and environmental data. This paper explores the integration of multimodal generative AI with edge computing in vehicular …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 27–34 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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A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks
Abstract: The Internet of Things (IoT) refers to the integration of physical objects with the Internet, allowing for connectivity and monitoring. This idea has garnered immense attention from researchers and users alike, driven by the widespread accessibility of the Internet. It spans a wide range of devices, including smart versions of conventional appliances, innovative tools tailored for Internet-enabled ecosystems, and sensors that leverage connectivity to revolutionize industries such as manufacturing, healthcare, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 1–11 Read article
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Statistical Methods in Law: Analysing Trends and Patterns in Judicial Outcomes
Abstract: The research paper explores the integration of statistical techniques within the domain of legal science, emphasizing their role in assessing and interpreting ongoing trends. By employing methods such as descriptive statistics, inferential statistics, and multivariate analysis, the study highlights how empirical data can effectively uncover disparities in areas like sentencing practices, risk assessments, and the evaluation of policy outcomes. These statistical tools enable researchers and legal professionals to identify patterns, …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 32–36 Read article
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Voltage Vigilance: Ensuring Balance and curbing Theft in Power Distribution Networks
Abstract: This project proposes a system for detecting electrical overload and earth faults using an Arduino Uno controller. The system uses a current sensor to identify overloads and a voltage sensor to detect earth faults. An ESP8266 module allows users to switch between the two fault detection modes. When an overload is detected, the Arduino turns off AC bulbs using a relay and sends an alert message via a GSM module. …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 15–21 Read article
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Progression in multi-omics and immunological research on host-parasite interactions: Transcriptomics, proteomics, genomics, metabolomics, and immune responses
Abstract: The interaction occuring between hosts and parasites is a quick and multi step-complex biological process that tries to influence disease outcomes. In recent years, multi-omics approaches, such as transcriptomics, proteomics, genomics, metabolomics, and immunological studies, have gathered substantial eye in dissecting these interactions at a microscopic level. These techniques enable a vast understanding of the molecular structures involved in parasitic infections and host defense mechanisms. This article reviews the advancements …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 1, 2025 Read article
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Fake Cryptocurrency Detection Using Python
Abstract: This study investigates the use of Python-based techniques for detecting fraudulent cryptocurrencies, addressing a growing concern in the digital financial ecosystem. The research methodology integrates various data science approaches, including web scraping, API integration, and advanced data analysis using Pandas and NLTK. Machine learning models, particularly classification algorithms such as Random Forest, are employed to analyze key features extracted from cryptocurrency whitepapers, social media discussions, and transactional data. By training …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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TensorFlow-Based Big Data Analytics for IoT Networks: A Study
Abstract: Internet of Things (IoT) has exploded in recent years, connecting billions of devices generating massive amounts of data. This deluge presents both a significant opportunity and a considerable challenge. While the potential insights hidden within this data are transformative, customary data processing techniques frequently fall short when handled with the velocity, volume, and variety of IoT-generated data. This is where Big Data technologies step in, offering the tools and infrastructure …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 31–38 Read article
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Investigation of the Hall and Nernst-Ettingshausen Effects in Diluted Magnetic Semiconductors
Abstract: This review explores the Hall and Nernst-Ettingshausen effects in various magnetic systems, including diluted magnetic semiconductors (DMS), topological insulators, superconductors, and novel composite materials. In DMS, the interplay of ferromagnetism and magnetic impurities introduces unique transport behaviors, particularly influencing the anomalous Hall effect (AHE) and thermomagnetic phenomena. We also examine the Nernst-Ettingshausen effect (NE) in topological insulators and superconductors, revealing the influence of band topology and vortex-like excitations. Special attention …
Published in Research & Reviews : Journal of Physics · Vol. 13, Issue 3, 2024 · pp. 1–5 Read article
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 Read article
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Enhancing Credit Card Fraud Detection Using Device Fingerprinting and Behavioral Biometrics
Abstract: Credit card fraud is a growing global concern, with financial losses projected to reach $ 43.47 billion by 2028. Credit card fraud poses a major challenge in the financial industry, resulting in substantial financial losses and security risks. This research introduces a Machine Learning-based Credit Card Fraud Detection System designed to improve the accuracy of fraud identification. Due to the imbalanced nature of fraud datasets, SMOTE (Synthetic Minority Over-sampling Technique) …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 40–50 Read article
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Integrated Dam Automation: Real-Time Monitoring and Controlling Using IoT
Abstract: Dam automation is a critical area in water resource management, especially given the rising demand for sustainable and safe water control systems. An integrated approach to dam automation involves implementing advanced sensors and monitoring systems to improve structural safety, water quality, and resource management. This paper presents a comprehensive automation model that combines crack detection, convolutional neural networks (CNNs), water level monitoring, turbidity sensing, and rainfall data to ensure real-time …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 31–38 Read article
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Artificial Intelligence and Machine Learning Applications in Optimizing Air Conditioning Systems
Abstract: The growing demand for air conditioning systems, especially in the wake of climate change and increasing global temperatures, has led to a significant increase in energy consumption. This, in turn, contributes to the growing concerns of environmental sustainability and operational costs. As a result, there is a pressing need for innovative solutions to optimize the performance and energy efficiency of air conditioning (AC) systems. Artificial Intelligence (AI) and Machine Learning …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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Enhancing Campus Security Using IOT Sensors
Abstract: Security within university campuses continues to be of paramount importance to learning institutions, with conventional CCTV systems tending to be slow and prone to operator errors. The project discusses an IoT system with Flutter, ESP32-CAM, flame and noise sensors, and buzzer for an efficient real-time surveillance and timely emergency response. The system can detect abnormal conditions like loud noises and fire risks, sending alarms and enabling live video streaming over …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 26–31 Read article
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Advanced Digital Twin and AI Integration for Real-Time Optimization in Polymer Production
Abstract: The integration of Internet of Things (IoT) with Artificial Intelligence (AI) technologies opens up considerable avenues for reshaping polymer manufacturing by improving operational effectiveness, securing exceptional product standards, and advancing sustainability in the environment. This academic manuscript delineates an advanced framework that integrates IoT and AI with synergistic technologies, including blockchain, edge computing, and digital twin methodologies, to revolutionize polymer manufacturing processes. The proposed architecture utilizes IoT sensors for the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 81–89 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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IoT Based Electricity Theft Detection System
Abstract: The proliferation of smart grids and advanced metering infrastructure has paved the way for innovative solutions to tackle the longstanding issue of electricity theft. This study presents an IoT-based electricity theft detection system that leverages real-time data analytics and machine learning algorithms to identify potential theft cases. The proposed system utilizes smart meters to collect electricity consumption data, which is then transmitted to a central server for analysis. The system …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 18–22 Read article
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A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 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