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118 articles for “clustering approach”
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Data-Driven Machine Learning Approach for Vehicle Fuel Economy Prediction and Performance Monitoring Using Real-World OBD Data
Abstract: Modern passenger vehicles generate large volumes of operational data through On-Board Diagnostics (OBD) systems, enabling continuous observation of vehicle performance under real-world driving conditions. However, much of the existing research mainly analyses previously recorded data and does not provide predictive mechanisms for monitoring vehicle performance under dynamically varying operating conditions. This study presents an AI and machine learning–based method for predicting and monitoring real-world vehicle performance and fuel economy using …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 47–66 Read article
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Studies of CRISPR/CAS 9 Gene Interactions in Streptococcus pyogenes
Abstract: Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/cas9/single guide RNA (sgRNA) system is a DNA editing system in mostly studied in prokaryotes. Studies of CRISPR/cas9 gene interactions in Streptococcus pyogenes has been conducted using in silico approaches in the present research. Proteins like DNA polymerase I (polA), NAD-dependent DNA ligase LigA (ligA), Translaldolase (tal), Thymidine kinase (tdk), Streptococcal exotoxin I (speI), Phage associated protein (SPy_0679) and Hypothetical proteins like SPy_1047, SPy_1048, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 7, Issue 3, 2018 · pp. 32–38 Read article
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Implementing FP-Growth Algorithm using Map Reduce for Mining Association Rules
Abstract: Abstract: In mining frequent itemsets, one of most important algorithms is FP-growth. FP-growth proposes an algorithm to compress information needed for mining frequent itemsets in FP-tree and recursively constructs FP-trees to find all frequent itemsets. Map Reduce is a distributed processing framework where the application is divided into many fragments of work, each of which may be executed on any node on a cluster. The main objective of this paper …
Published in Journal of Advanced Database Management & Systems · Vol. 6, Issue 2, 2019 · pp. 18–29 Read article
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The Sound System of Ezha, Ethio-Semitic
Abstract: This article is devoted to present a descriptive account of Ezha phonology. The various speech sounds of the language are approached from the perspective of their individual articulatory characteristics and from the perspective of the ways in which they pattern together. A total of thirty three consonant and seven vowel phonemes are attested. In terms of phoneme clustering, Ezha sounds can assume four different patterns: Sonorant-Obstruent, Obstruent-Sonorant, Sonorant-Sonorant, and Obstruent-Obstruent …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 7, Issue 1, 2017 · pp. 14–23 Read article
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Challenges and Opportunities in Spatio Temporal Data Analysis
Abstract: Spatiotemporal data analytics is a dynamic field that seeks to extract valuable information from data that integrates both spatial and temporal dimensions. This article explores the importance of this emerging field and its applications in a variety of fields, including environmental science, public health, and urban planning. Spatiotemporal data analysis addresses important research questions, such as determining event probabilities, understanding change patterns, identifying associations between events, and predicting events Future. …
Published in Journal of Remote Sensing & GIS · Vol. 14, Issue 2, 2023 · pp. 1–11 Read article
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Texture Segmentation Using Multichannel Filtering And Kohonen’s Self Organizing Map
Abstract: The texture is very important cue in region based segmentation of images. Texture features play a very important role in computer vision and pattern recognition. Texture segmentation can be broken down into two areas, feature extraction and clustering. In this paper, we implement two stage of feature extraction technique using multichannel filter and Self Organizing Map (SOM). Firstly, we go through channel filters, also known as 2-D Gabor functions. The …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 3, Issue 3, 2012 · pp. 17–30 Read article
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An Approach to Image Recognition on the Basis of Plant Diseases Ontology
Abstract: AbstractOntology engineering for the plant science is supposed to contribute on the basis of plants traits that determine phenotypic expression in a given environment. Plants play a very important role in the ecological balance and daily necessities in the life. Due to environmental or other causes many of the plants become damaged and hence the investigation of the plant recognition on the basis of diseases is a major research area …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 3, 2015 · pp. 1–9 Read article
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A Review on Various Approaches of Intrusion Detection System and Random Forest in Data Mining
Abstract: With the development in Information and Communication Technology (ICT), it have become a fundamental factor of human’s life. But this technology has brought lots of threats in cyber world. These threats increase the chances of network vulnerabilities to attack the structure in the network. DM based intrusion area techniques consistently fall into any of the two classes; anomaly detection and mistreat finding. In general course of DM alludes to extricating …
Published in Recent Trends in Programming languages · Vol. 5, Issue 1, 2018 · pp. 6–13 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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Classification of Mammogram Images by Machine Learning Algorithm Attacker Nodes
Abstract: Abstract— Breast cancer is basic in ladies' these days. In beginning when cells in the breast start to develop out of control. These cells generally structure a tumor that will frequently be seen on a x-beam or felt as a lump. Cells in almost any piece of the body can move toward becoming malignant growth and can spread to different regions of the body. There are very nearly 6 phases …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 2, 2019 · pp. 1–10 Read article
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Study Analysis of Geolocational Data with Statistics: A Review
Abstract: The biggest challenge while traveling is looking for a place to stay, and considering doing a complete, thorough analysis of real-world data. The objective of the present study is to refer, clean, fetch, analyze and run K Means clustering on geolocational data to suggest lodgings to the travelers and immigrants of a city; maximizing the likelihood of the distances between the target and the landmarks, given the observed delays, yields …
Published in Journal of Advanced Database Management & Systems · Vol. 9, Issue 3, 2022 · pp. 25–30 Read article
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DNA Barcoding
Abstract: DNA barcoding system is a promising approach towards the diagnosis of biological diversity using DNA sequences as a primary key for retrieval of genetic information. It is emerging as a standardised method for mapping various species on the earth. DNA barcoding is a tool for identification of new species, conservation of endangered species and clustering of various species under a particular group. Many databases have been developed across the globe …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 3, Issue 1, 2016 · pp. 9–13 Read article
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Survey on Intrusion Detection Using Data Mining Methods
Abstract: The present emerging information growth has made numerous challenges in the data mining. Data mining is the procedure of removing valid, before known, and comprehensive data sets for the future decision making. With the better technology through WWW, the streaming information comes into the picture with its challenges. The data, which alters with time and updates its value, is known as streaming information. As most of the data is streaming …
Published in Journal of Advanced Database Management & Systems · Vol. 3, Issue 2, 2016 · pp. 33–43 Read article
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A Machine Learning Approach for Investigating Spatial Structures between Spectral line Sources: Formaldehyde Absorptions versus Methanol Masers
Abstract: In this paper the authors present fascinating ideas on using machine learning algorithms to study connections in spatial distributions between observed spectral line sources. The method has been illustrated using observations of 4.8 GHz formaldehyde absorptions and 6.7 GHz methanol masers in the Galaxy. Both spectral line features have been well-observed in close associations with galactic star-formation regions, and we initiate this study to understand spatial connections between them. We …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 2, Issue 2, 2013 · pp. 1–11 Read article
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Finding Risk Factors in Thyroid and Cardiovascular System Using Naive Bayesian (NB) Machine Learning Technique
Abstract: Thyroid malady could be a common condition. A TSH test is carried out to check for the capacities of your thyroid organ. Illnesses of thyroid can be caused by conditions which cause thyroid organ over or under function. The test can moreover assist you recognize thyroid conditions some time recently indications happen. It is either as well (hyperthyroidism) or under-active (hypothyroidism), you might know. In case untreated, thyroid clutter may …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 8, Issue 1, 2020 · pp. 1–5 Read article
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IoT-enhanced Extensible Messaging Presence Protocol: A Multiple Multicast Architecture for Diverse Applications
Abstract: Extensible Messaging Presence Protocol (XMPP) is a real-time information transmission specification protocol based on IP technology and XML supporting publish/subscribe messaging systems. Publishers use multicast to send data simultaneously to multiple subscribers. IoT devices benefit enormously by using XMPP Extension Protocols (XEPs) available in the literature that enables using XMPP for multicast. Publishers are considering Multiple Multicast (MMC) to address subscriber overlap while sending messages to multiple subscribers simultaneously. This …
Published in Journal of Advances in Shell Programming · Vol. 10, Issue 2, 2023 · pp. 1–13 Read article
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Smart Manufacturing with Advanced Polymer Composites: Enabling Industry 4.0 Readiness in Indian MSMEs
Abstract: Thanks to Industry 4.0, manufacturing is now undergoing major changes that highlight using technology, machines, and sustainable solutions. Yet, very few Indian MSMEs can use these technologies due to obstacles like a lack of resources and outdated systems. This research looks at how combining Smart Manufacturing with Advanced Polymer Composites can improve Indian MSMEs’ preparations for Industry 4.0. When APCs are combined with cyber-physical systems, IoT, machine learning, and additive …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 194–216 Read article
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Exploration of Employees Behaviour and Ethical Climate in IT Industry: Using Ethical Climate Questionnaire (ECQ)
Abstract: Objective: This paper accentuates the validation of the multidimensional measure of Employees Behaviour that links with current changes in organisational landscape and raised desires of responsibility for IT organisations. It likewise highlights the assessment and validation of Employees Behaviour (EM) based upon the revised version of Ethical Climate Questionnaire developed by Victor and Cullen. Analysis: This study proceeds in the following manner. It starts with a literature review in Employee …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 8, Issue 1, 2018 · pp. 8–12 Read article
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Exploration of Diverse Epoxy-Based Surface Coating Methods for Enhancing Anticorrosion Characteristics
Abstract: Epoxy-based polymers, commonly referred to as polyepoxides, constitute one of the most versatile and widely adopted categories of polymeric materials due to their exceptional structural, mechanical, and chemical characteristics. Their unique macromolecular framework enables strong interfacial bonding, high mechanical stability, and superior resistance to environmental and chemical degradation, positioning them as advanced alternatives to many traditional organic corrosion inhibitors that often fail under prolonged exposure to aggressive conditions When polyepoxides …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 167–177 Read article
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A Machine Learning-based Analysis of Climate Change
Abstract: Climatic variations are a pressing global challenge that demands immediate and comprehensive attention. A wealth of articles has been published on climate change mitigation and adaptation, yet there remains a need for innovative methods to explore the complexities of climatic variations and to devise more efficient and effective strategies for adjustment and alleviation. With technological advancements, machine learning (ML) and deep learning (DL) approaches have derived significant popularity across various …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 1–10 Read article