Machine learning
17 articles · search the full text for this term
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Smart Wastewater Treatment Plant Modeling Using ANN And ASM1 MATLAB Simulation
Abstract: Wastewater Treatment Plants (WWTPs) are necessary infrastructure for protecting the environment and public health, but modeling and predicting performance has been an ongoing challenge for engineers working within a WWTP and regulators of the environment. For many years the Activated Sludge Model No. 1 (ASM1) has been the standard for simulating biological treatment processes, but the conventional implementations in MATLAB do not provide the user-friendly interface, the predictive intelligence, or …
Published in International Journal of Chemical Engineering and Processing · Vol. 12, Issue 2, 2026 · pp. 44–62 Read article
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A Study on Machine-Learning-Driven Insight into theThermal Behavior of Polymers and Composite Materials
Abstract: The thermal performance of polymeric and composite systems underpins their suitability for aerospace, electronics, and energy‑storage applications, yet reliable prediction of temperature‑dependent properties remains a formidable challenge. In this work we present a data‑driven framework that harnesses modern machine‑learning (ML) techniques to forecast key thermal metrics – glass‑transition temperature (Tg), melting point (Tm), thermal conductivity (k), and decomposition onset (Td) – from a chemically informed descriptor space. A curated database …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 1–11 Read article
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The Role of Artificial Intelligence in Mental Health: New Approaches for Diagnosis and Treatment
Abstract: Artificial intelligence (AI) is increasingly reshaping mental health care by supporting early identification of mental health conditions, improving diagnostic accuracy, and enabling personalized intervention strategies for disorders such as depression, anxiety, and post-traumatic stress disorder. Advanced AI technologies, including machine learning algorithms and natural language processing techniques, allow analysis of large-scale behavioral, textual, and speech-based data to identify patterns related to emotional and cognitive health. These tools help clinicians make …
Published in International Journal of Software Computing and Testing · Vol. 12, Issue 1, 2026 · pp. 22–26 Read article
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Climate Change Modeling Using Machine Learning and Big Data
Abstract: Climate change is now one of the biggest issues that affect the world today and studying its impacts for it is very significant in enabling the formulation of social policies. This paper also discusses how climate sciences, machine learning, and big data analytics can greatly help in the improvement of the current capacities in climate modeling. Explaining the methods of climate modeling, we look at how the big data offers …
Published in International Journal of Software Computing and Testing · Vol. 11, Issue 1, 2025 · pp. 6–11 Read article
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Advances in Machine Learning and Data Analytics: A Multidisciplinary Synthesis
Abstract: Machine learning has emerged as a key driver of innovation across a wide range of fields. Its transformative potential is evident in natural language processing, computer vision, and real-time automation, where it addresses intricate challenges with remarkable efficiency. This paper delves into recent developments in machine learning, spotlighting techniques, such as semi-supervised learning frameworks, stable diffusion models for generative tasks, and advanced lightweight architecture for real-time defection detection. By integrating …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 1, 2025 · pp. 12–17 Read article
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Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
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Comparative Analysis of Air Quality Indices Across Five Eastern States of India Using ML Models and Pollutant Based Insights
Abstract: This paper presents a comparative study of Air Quality Index (AQI) levels in five eastern Indian states–Arunachal Pradesh, Assam, Meghalaya, Nagaland, and Tripura. Using historical data, the study explores the concentration of key pollutants, including PM2.5, PM10, NO2, SO2, CO, and Ozone, highlighting regional variations in air quality. Assam, with its higher levels of urbanization and industrial activity, shows elevated AQI levels, especially for pollutants like PM10 and NO2. In …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 1, 2025 · pp. 31–42 Read article
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Predictive Analytics in E-Learning: Enhancing Student Performance Through Machine Learning Models
Abstract: With the explosion of electronic devices and internet technologies in today’s world, the amount of data we store has grown massively. Data is simply information that has been organized in a way that makes it easy to share or work with. A potent technology that enables computers to learn from data without direct programming is machine learning, which we employ in our research. The focus of this study is on …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
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Face and Speech Emotion Recognition
Abstract: The study “faces and speech recognition” underscores the critical role of speech emotion recognition (SER) and its diverse applications across various fields, such as medicine, human-computer interaction, and customer service. SER has gained significant importance in cognitive psychology due to its potential to enhance user experience, improve patient care, and optimize the interaction between users and products. The process involves the identification and extraction of essential features from speech signals, …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 35–43 Read article
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Advancing Early Detection of Menkes Disease Through Image Analysis and Biosensor Integration
Abstract: Menkes disease, a rare X-linked recessive disorder of copper metabolism, poses significant challenges in early diagnosis due to its nonspecific initial symptoms. This paper presents a comprehensive approach to enhance the early detection of Menkes disease by leveraging image processing techniques, pattern recognition algorithms, and innovative biosensor technologies. A novel framework is proposed that combines analysis of hair microscopy images, facial feature recognition, and copper-sensitive biosensors to create a multi-modal …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 24–34 Read article
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Network Intrusion Detection Using Wireshark and Machine Learning
Abstract: The growth of networked devices has highlighted the desire for advanced intrusion detection (IDS) tools to protect digital systems from evolving cyber threats. Traditional IDS systems are often difficult to adapt to the threat environment because they rely on predefined signature lists. This study presents a new approach that combines Wireshark, a widely used network packet analysis tool, with advanced machine learning for intrusion detection. Our system leverages Wireshark's data …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 23–31 Read article
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Farm Management for Sustainable AI and IOT Based Agriculture
Abstract: The sector of agriculture has undergone a transformation thanks to the integration of synthetic Artificial intelligence (AI) and The Internet of Things. This has made it conceivable to move towards smart agriculture and promote the evolution of sustainable farming methods. In-depth study of the uses, approaches, difficulties, and potential applications IoT and AI in intelligent agriculture and sustainable farming is offered in this survey report. We examine the several AI …
Published in International Journal of Agrochemistry · Vol. 10, Issue 1, 2024 · pp. 1–7 Read article
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A Smart Recommendation System for Carrier Shipper Matching Using Multilabel Classification – A Survey
Abstract: Efficient matching between carriers and shippers is crucial in the logistics industry to optimize resource utilization and minimize costs. This paper puts forth a smart recommendation framework dependent on multilabel classification techniques to improve the carrier-shipper matching process. The method makes use of machine learning techniques to predict multiple relevant carrier options for a given shipment request. We present a comprehensive literature review on related works in carrier-shipper matching and …
Published in International Journal of Broadband Cellular Communication · Vol. 10, Issue 1, 2024 · pp. 1–7 Read article
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Maculopathy Detection and Recommendation using Machine Learning
Abstract: Maculopathies, a diverse group of eye diseases affecting the central portion of the retina, the macula, are a leading cause of vision loss globally. Early detection and accurate diagnosis are critical for timely intervention and preventing irreversible vision loss. However, traditional methods such as manually detecting the disease are time-consuming, tiring, and often lack sensitivity and specificity, hindering optimal patient care. Here we delve into the applications of machine learning …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 10–16 Read article
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A Role of Machine Learning for Students' Academic Success Prediction
Abstract: This research paper aims to identify early predictions of students’ academic success with the help of different indicators. One of the crucial parts of the study is identifying additional indicators that play an essential role in defining students' academic success. Early prediction of success will be helpful for various stakeholders such as students, parents, educators/teachers, institutions, universities, and the government. Machine Learning is a part of Artificial Intelligence (AI) and …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 1, 2024 · pp. 1–6 Read article
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The Implementation of Machine Learning in the Search to Fight Plant Disease
Abstract: The agriculture business loses money and time due to plant diseases. Diagnosing disease accurately takes skill and devotion. Infected plants may have spots or streaks of a different color on their leaves. Several fungal, bacterial, and viral species can also infect plants. Individual plant disease signs and indications are assessed. Neural network applications are growing. Recent research studies have determined how well machine learning reviews traditional plant disease diagnosis methods. …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 1, 2024 · pp. 25–34 Read article
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Identifying Fake News Using Big Data
Abstract: In today's world, where digital information spreads swiftly, the rise of fake news poses a threat to society. This research paper presents a method to address this issue by employing data analytics. To address the issues of misinformation, public manipulation, and threats to democracy we propose a framework. Our strategy incorporates advanced methodologies, including natural language processing, machine learning, and network analysis. Using these techniques, we examine various data sources …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 1, 2024 · pp. 7–14 Read article