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104 articles for “machine learning algorithms”
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Smart Agro-Advisory Systems: AI-Based Platforms for Real-Time Farmer Decision Support
Abstract: Agriculture is a vital sector for food security and economic growth, particularly in the developing world. Farmers, however, often face unpredictability of weather conditions, insect attacks, wasteful use of resources, and uncertainties of the market. Farmers' practices are mostly based on experience and intuition, which might not always be the best to apply. Smart Agro-Advisory Systems (SAAS) based on Artificial Intelligence (AI) offer real-time decision support to farmers, enabling them …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 8–14 Read article
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Impact of Exhaust Gas Recirculation on NOx Emissions and Efficiency in Diesel Engines
Abstract: Abstract Exhaust gas recirculation (EGR) has emerged as a pivotal strategy to reduce nitrogen oxide (NOx) emissions from diesel engines, which significantly contribute to air pollution and environmental degradation. NOx emissions pose serious concerns due to their role in forming smog, acid rain, and adverse health impacts. By recirculating a portion of the exhaust back into the intake manifold, EGR reduces these emissions by restricting the manufacturing of NOx and …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
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A Review of AI and Machine Learning Techniques in Dew Point Pressure Prediction for Gas Condensate Systems
Abstract: Condensate gas reservoirs pose considerable management challenges due to their intricate phase behavior and the critical need for accurate predictions of dew point pressure (PDew). A precise determination of PDew is vital for optimizing production strategies, estimating reserves, and planning enhanced oil recovery operations. Traditional methods for PDew determination often involve experimental analyses that can be both costly and time-consuming, highlighting the necessity for alternative predictive models. This review consolidates …
Published in International Journal of Chemical Engineering and Processing · Vol. 11, Issue 1, 2025 Read article
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Effect of Segmentation of White matter, grey matter and CSF in the prediction of Neurological disorders
Abstract: The segmentation of white matter, grey matter, and cerebrospinal fluid (CSF) plays a crucial role in predicting and diagnosing neuro disorders. This study investigates the impact of precise segmentation techniques on identifying biomarkers and structural changes associated with various neurological conditions, including Alzheimer's disease, multiple sclerosis, and schizophrenia. By leveraging advanced imaging technologies and machine learning algorithms, we aim to enhance the accuracy of neuro disorder predictions through detailed analysis …
Published in International Journal of Neurological Nursing · Vol. 10, Issue 2, 2024 · pp. 9–14 Read article
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Personalized Movie Recommendations: Leveraging Machine Learning to Enhance Viewer Experience
Abstract: The film industry has experienced a tremendous surge in content creation over the past few decades, leading to an overwhelming array of movies across various genres and languages. As a result, movie enthusiasts often find it challenging to discover films that align with their unique preferences and tastes. To address this issue, the application of machine learning techniques for movie recommendation has gained prominence. An introduction to the idea and …
Published in International Journal of Digital Communication and Analog Signals · Vol. 10, Issue 2, 2024 · pp. 1–6 Read article
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Ethereum Price Prediction Using Extra Trees and Random Forest Regressors
Abstract: The Ethereum market is famous for its unpredictability and the possibility of significant profits, presenting both opportunities and obstacles for investors and stakeholders. Given the dynamic nature of this ecosystem, accurate prediction of Ethereum’s price movements is essential for informed decision-making. In this project, we propose an innovative approach that leverages ensemble learning techniques, specifically extra trees and random forest regressors, for Ethereum price prediction. By harnessing a diverse dataset …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 2, 2024 · pp. 9–25 Read article
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Design and Optimization of Heterogeneous Catalysts for Green Chemistry Processes
Abstract: The design and optimization of heterogeneous catalysts are critical for advancing green chemistry processes, aiming to minimize environmental impact while maximizing efficiency. This study explores innovative strategies for the development of heterogeneous catalysts that facilitate environmentally benign reactions. By integrating principles of catalyst design, surface science, and reaction engineering, we aim to enhance catalytic performance, selectivity, and stability. Catalyst composition and structure, investigating novel materials, including metal-organic frameworks (MOFs), zeolites, …
Published in International Journal of Chemical Synthesis and Chemical Reactions · Vol. 10, Issue 1, 2025 · pp. 42–48 Read article
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Novel Approaches to Thermodynamic Optimization in Industrial Processes
Abstract: Thermodynamic optimization in industrial processes stands as a pivotal pursuit in enhancing efficiency, sustainability, and economic viability. Traditional methodologies have primarily focused on established principles, yet the escalating demands for resource conservation and emissions reduction necessitate innovative strategies. This abstract presents a compendium of novel approaches aimed at revolutionizing thermodynamic optimization in industrial settings. Firstly, the incorporation of advanced machine learning algorithms unveils unprecedented opportunities for predictive modeling and real-time …
Published in International journal of Thermodynamics and Chemical Kinetics · Vol. 9, Issue 2, 2023 · pp. 20–25 Read article
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A Realtime Coronavirus Notifier
Abstract: Fresh corona virus deadly disease has not clinically confirmed vaccine or medicines. Its tolerant are improving through the help of antibiotic drug, anti-viral treatments, over and above vitamin C supplementation. It is currently apparent that the world necessities an expedient and speedier answer for contain and tackle the further spread of COVID-19 across the world with the guide of non-clinical advance for instance data mining schemes, improved aptitude furthermore extra …
Published in International Journal of Distributed Computing and Technology · Vol. 7, Issue 1, 2021 · pp. 22–25 Read article
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A Review on Crypto coin price prediction
Abstract: Due to its advantages over the established banking system, cryptocurrencies have experienced a sharp increase in price inrecent years, which has had a positive impact on the economy. As cryptocurrencies are organized by blockchain technology, itinherits its properties such as Decentralization, Transparency, Immutability. In recent years, investors and stakeholdershave become increasingly interested in machine learning and AI-assisted trading. The effectiveness of machine learningtechniques in predicting the stock market leads one …
Published in International Journal of Distributed Computing and Technology · Vol. 8, Issue 1, 2022 · pp. 37–42 Read article
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Water Quality Monitoring System
Abstract: For water resources to be used in a safe and sustainable manner, water quality monitoring is crucial. In this article, we present a comprehensive system for tracking a variety of metrics, such as pH, temperature, conductivity, total dissolved solids, and others, in water quality. Sensors and other analytical instruments are used in the system to gather data, which is then wirelessly transmitted to a central database for analysis and storage. …
Published in International Journal of Analog Integrated Circuits · Vol. 8, Issue 2, 2022 · pp. 28–33 Read article
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Semantic Segmentation for Object Detection in Videos using Mask RCNN
Abstract: The segmentation of object instances is an essential step in real-time video detection. Object detection is the problem of detecting the information of all types of items in an image by designating their location with a rectangular box. Using its remarkable feature-learning capabilities, deep learning promotes object detection research. Numerous researchers have utilised various machine learning algorithms for object detection and have focused on enhancing the accuracy of feature extraction. …
Published in International Journal of Digital Communication and Analog Signals · Vol. 8, Issue 2, 2022 · pp. 7–15 Read article
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Predicting the Team Based on Player Performance and Formation in Sports Match by Machine Learning Approach
Abstract: In the field of sports evaluation of player performance and predicting the weight of the player for the formation of a well efficient team is very important. The main aim is to pick the best squad from all the available players. This will help to decide which team of players is the best to play against a particular opponent, perform prediction of the performance of the players in future matches …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 6, Issue 2, 2020 · pp. 1–5 Read article
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Depression Detection System
Abstract: Traditionally, depression was identified through in-depth clinical interviews, during which the psychologist would analyze the subject’s responses to ascertain his or her mental condition. With the prevalence of depression increasing, some automated and trustworthy methods of depression recognition are needed. Our Objective it to design a model that can extract relevant features automatically as an input using efficient machine learning algorithms and further detect the depressive state of the user …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 1, 2023 · pp. 28–37 Read article
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Advancements in Predictive Maintenance: A Review of Data-Driven Approaches, Machine Learning, and AI in Diverse Industrial Landscapes
Abstract: The Internet of Things (IoT), the use of machine learning (ML), and artificial intelligence (AI)-driven advances in predictive maintenance are the key topics of this study. With the goal of offering a thorough grasp of existing approaches and potential future developments, it analyzes applications in predictive maintenance in many sectors. Predictive maintenance approaches are the major topic of discussion, with an emphasis on their advantages, disadvantages, difficulties, and prospects. Additionally, …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 2, 2024 · pp. 19–32 Read article
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A Study of 3D Printing Technology and M.L. Algorithms for Enhanced Production
Abstract: Abstract The realm of 3D printing technology, also referred to as additive manufacturing, has garnered increasing interest in recent times due to its capacity to construct intricate geometric structures. Fused deposition modeling (FDM) stands out among the various techniques and has gained widespread adoption. However, achieving optimal outcomes with FDM poses a challenge, necessitating meticulous selection of process parameters. Presently, many methodologies rely on Machine Learning (ML) algorithms akin to …
Published in International Journal of Computer Aided Manufacturing · Vol. 11, Issue 1, 2025 · pp. 6–15 Read article
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Impact of AI in HRM Practicing Job Satisfaction in Any other Hospital
Abstract: Artificial Intelligence (AI) is becoming more prevalent in organizations, presenting both opportunities and challenges for Human Resource Management (HRM). The integration of AI in HRM reflects the dual potential for advancement and complexities within organizational dynamics. Striking a balance in leveraging AI's benefits while addressing its challenges is crucial for effective HRM. In the medical field, Artificial Intelligence (AI) in hospitals involves the application of advanced computational algorithms and machine …
Published in International Journal of Broadband Cellular Communication · Vol. 9, Issue 2, 2023 · pp. 18–26 Read article
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A Review on Property Price Tracking Using ML Model
Abstract: The very common reason for an investment is to get benefits in future. Different legal and illegal utilization leads to cost fluctuation. It is therefore important to well manage the [exploitative] of the property, and an application like price predictor is well equipped with optimal solution. However, such price prediction methods require an appropriate knowledge and experience regarding this domain. By utilising machine learning techniques and algorithms, the price of …
Published in International Journal of Analog Integrated Circuits · Vol. 8, Issue 2, 2022 · pp. 11–20 Read article
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Criminal Face Identification Using Deep Learning and Machine Learning
Abstract: Criminal face identification is a crucial task for law enforcement agencies to prevent and solve crimes. The traditional methods for identifying criminals using human expertise and eyewitness testimonies have several limitations, such as subjectivity, inaccuracy, and unreliability. Machine learning and deep learning techniques have yielded promising gains in facial recognition and identification applications in recent years. In this study, we propose a criminal face identification system that combines machine learning …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 9, Issue 1, 2023 · pp. 28–34 Read article
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AI-Artificial Intelligence
Abstract: — In this paper, we pursue to offer an introduction to AI to policymakers and other stakeholders in the wider Internet ecosystem. The paper describes the basics of the technology behind AI, recognizes the key considerations and challenges surrounding the technology, and offers several high-level principles and recommendations to follow when dealing with the technology. Keyword: AI, Machine Learning, Key Consideration, Algorithms.
Published in International Journal of Software Computing and Testing · Vol. 3, Issue 2, 2017 · pp. 21–31 Read article