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334 articles for “feature based model”
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Call Quality Measurement and Application in Telecommunication Network
Abstract: The measurement of call quality from end-users’ perspective is emerging area of research on speech quality in telecommunication networks. The research is focused on deriving the call quality parameters from end-users’ perspective; and visualize and escalate the critical call quality. Also proses the method of redemption of call charges based on call quality parameters perceived. The research proposed and developed measures, for certain call parameters during the call and provide …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 3, Issue 1, 2016 · pp. 8–19 Read article
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AI Chatbot for Expressing Visual Content
Abstract: Recently, the artificial intelligence (AI) chatbot for expressing visual content has shown remarkable multi-modal capabilities. It can recognize funny features in photos and create webpages straight from handwritten text. These characteristics are uncommon in earlier vision language models. We think the use of a more sophisticated large language model (LLM) is the main factor behind vision verbalizer's superior multi-modal generating capabilities. We introduce vision verbalizer, which employs a single projection …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 11–19 Read article
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The Customized ZigBee Stack: Mathematical Modelling
Abstract: Abstract There are different protocols for realising WPAN. ZigBee protocol supports high node density, long range and robust communication and hence chosen for experimenting in WPAN. ZigBee protocol may not be adequate to bring all the consumer electronic devices under WPAN and control them as the devices may use different protocols. ZigBee stack is taken as base, it is modified to incorporate the features of common communication protocol so as …
Published in Recent Trends in Electronics Communication Systems · Vol. 3, Issue 3, 2016 · pp. 7–14 Read article
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Vehicle Insurance Fraud Detection Using Supervised Neural Network Model
Abstract: Vehicle insurance fraud is a serious problem that causes huge financial losses to insurance companies. In recent years, developing fraud detection models using machine-learning techniques has been of great interest. This study proposes a novel approach for vehicle insurance fraud detection using Supervised Neural network model on the Kaggle Vehicle Insurance Fraud Detection dataset. The initial step in this study involves performing data pre-processing and feature extraction on the dataset, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 10, Issue 1, 2023 · pp. 32–39 Read article
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QSAR Analysis on a Series of Triazole Based Tubulin Polymerization Inhibitors
Abstract: AbstractThe polymerization progression of microtubules is vital to their natural capacities. Polymerization flow allows microtubules to embrace spatial courses of action that can change quickly because of cell needs and, at times, to perform mechanical work. Compounds that interfere with the microtubule-tubulin equilibria in cells are helpful in the treatment of human diseases. A few triazoles mimics of combretastatin-benzothiazole (CAB) hybrids had good activity as inhibitors both of tubulin polymerization …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 4, Issue 2, 2017 · pp. 5–20 Read article
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An Approach for Similarity Matching and Comparison in Content Based Image Retrieval System
Abstract: Today, in the age of images and digitization relevant retrieval is quite a topic of research. With every new day thousands of pictures are getting added into the database making it a high dimensional data set. Therefore, from a high dimensional dataset to get a set of relevant images is quite a cumbersome task. In this paper, experiment has been performed on the trademark images. Trademark is a very important …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 3, 2015 · pp. 57–63 Read article
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Virtual Assistant: JarvisAI Using Natural Language Processing
Abstract: This research presents the development of a voice-interactive virtual assistant built upon the JarvisAI framework, integrating advanced technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Speech Recognition. The goal is to enable seamless and intuitive human-computer interaction by allowing users to communicate through natural spoken and written language. The assistant is designed to understand, interpret, and respond to various user commands, aiding in tasks such as information …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 26–39 Read article
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Comparative Analysis of Supervised Learning Algorithms for the Traffic Accident Prediction Under Rural and Urban Areas
Abstract: The features of different mechanisms for safety to traffic accidents are the biggest challenge for the automobile manufacturing industry in rural and urban areas. The objective of this work is to address the challenge of safety in traffic accidents by developing an accurate prediction model for identifying patterns in the different scenarios for preventing traffic accidents using accurate prediction. The machine learning algorithm is used to easily predict the traffic …
Published in Journal of Advancements in Robotics · Vol. 10, Issue 3, 2023 · pp. 20–27 Read article
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The Transient Performance of Power Line Towers
Abstract: This paper presents a refined approach to the transient analysis of power line towers. Each section of the tower’s steel structure is accurately modeled as a non-uniform transmission line. Among other features, an efficient representation of the towers’ cross-arms as open-ended non-uniform lines and their subsequent approximation by lumped capacitors will be explored. Furthermore, the error introduced by neglecting the presence of the cross-arms, as well as the effect of …
Published in Trends in Electrical Engineering · Vol. 3, Issue 2, 2013 · pp. 20–28 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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The Quicklift: Redefining Car Jack Dynamics & Design
Abstract: A Jack is a tool that aids in raising the vehicles without considerable physical efforts and thereby reducing strain injuries. This paper is about designed model of Jack and performing the static analysis (viz:structural) with the help of Solid works software. The outcomes obtained demonstrates that jack can be used safely. Additional improvements to be made in the jack is by modifying the vertical cylindrical bar so that it can …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 86–92 Read article
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Comparison of AODV and DSR Routing Protocols by using Mobility Model in Vehicular Ad-Hoc Network
Abstract: AbstractVehicular ad hoc network is a type of network that provides the communications between vehicle and road side; vehicle and vehicle; and vehicle and infrastructure. VANET has new applications and features for travelers for providing vehicle related information for safety purpose that has never been possible in past. It is an application of MANET. In MANET the node is communicating with the base station. The present paper is mainly intended …
Published in Journal of Communication Engineering & Systems · Vol. 5, Issue 2, 2015 · pp. 24–29 Read article
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A Hybrid model of ResNet50 integrated U-Net for image Denoising for Polymer and Composite Microstructure Analysis
Abstract: In digital era a high-quality imaging plays a very important role in polymer and composite material characterization features such as fiber-matrix interfaces, voids, microcracks cause problems in mechanical and functional properties. Polymer imaging includes optical microscopy and scanning electron microscopy, due to sensor limitation, environmental conditions add noise to the image and reduce quality of image. The noise degrades image quality, and it leads to reduce reliability in material analysis. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 592–602 Read article
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AI-Driven Dairy Ledger: Enhancing Efficiency with Machine Learning
Abstract: The dairy business nevertheless has ongoing difficulties with financial management, record-keeping, and operational effectiveness, which frequently lead to resource mismanagement, human mistakes, and revenue losses. These problems are most noticeable on small- to medium-sized farms where manual labor is the primary method. This study introduces an AI-driven Dairy Ledger, a complete machine learning-powered system designed to automate and optimize key dairy functions, such as tracking cow feed orders, managing milk …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 36–46 Read article
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Automatic Text Summarization – A Review
Abstract: ABSTRACT We present Encoder/Decoder a unique methodology for summarization of text documents. The summarization of text is to be done in two forms one is abstractive and the other one is extractive. Summarization of text is a main job of natural language processing. With the help of new idea we make a unique amalgam model of abstractive-extractive to combine BERT(Bidirectional Encoder Representations from Transformers). Firstly we transform the summaries which …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 3, 2020 · pp. 22–27 Read article
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Detection of Breast Cancer with Python
Abstract: Global cancer data confirms more than 2 million women diagnosed with breast cancer each year reflecting majority of new cancer cases and related deaths, making it significant public health concern. But fortunately, it is also the curable cancer in its early stage. Early diagnosis of breast cancer with timely and effective treatment services improves the prognosis and survival of patients. During classifying tumors, there are significant chances of error and …
Published in Research & Reviews : Journal of Statistics · Vol. 9, Issue 3, 2020 · pp. 5–22 Read article
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Genomic Selection for Grain Yield in Wheat Using Machine Learning on DArT Molecular Markers: A Comparative Evaluation Across Multi-Environment Trials
Abstract: Genomic selection (GS) predicts complex quantitative traits directly from genome-wide molecular markers, bypassing the need for extensive phenotypic trials and accelerating plant breeding cycles. We conducted a comparative evaluation of seven regression approaches — ridge regression (the machine-learning equivalent of RR-BLUP), Lasso, Elastic Net, Partial Least Squares, linear Support Vector Regression, Random Forest, and Gradient Boosting — for predicting grain yield from 1,279 Diversity Array Technology (DArT) molecular markers genotyped …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Advanced Airline Operations Control System Using NodeJS
Abstract: This research paper presents the development of an Advanced Airline Operations Control System (AAOCS) using NodeJS, a lightweight and scalable JavaScript runtime environment. Leveraging NodeJS's event-driven architecture and non-blocking I/O model, the system facilitates efficient management of flight operations, crew scheduling, resource allocation, and real-time decision-making in the aviation industry. Key features include real-time decision support tools, a microservices-based architecture for scalability, integration with external data sources and APIs, and …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 1, 2024 · pp. 45–51 Read article
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Homology Modeling and in silico Characterization of a Hypothetical Protein of Arabidopsis lyrata ssp. Lyrata
Abstract: Arabidopsis lyrata, a plant belonging to brassicaceae, is a model organism for studying evolutionary and ecological genetics. Most of the proteins of this plant have remained uncharacterized and their functional roles are still to be elucidated. In this investigation, we have attempted to characterize one such hypothetical protein in terms of its physico-chemical properties, secondary and tertiary structure features by in silico study. The protein was classified under glycoside hydrolase …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 3, Issue 2, 2013 · pp. 1–5 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article