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76 articles for “feature representation”
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Geomatic Based Morphometric Analysis of Kadalibadi Micro-Watershed of Ansupa Lake Catchment, Cuttack District, Odisha
Abstract: In the present study, an attempt has been made to evaluate morphometric parameters derived from SRTM data and also land use/land cover, geomorphology, soil and also drainage map are prepared from SOI toposheet, LISS IV and Cartosat II satellite images. The study is about the Kadalibadi micro-watershed of Ansupa catchment and the micro-watershed, covering five nos. of villages (Kadalibadi, Podapada, Radhadarsanpur, Mahidharpur and Baidehipur). Remote sensing (RS) along with geographical …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 5, Issue 1, 2016 · pp. 10–21 Read article
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Data Representation and Abstraction in Computer Systems: An Interactive Study
Abstract: Data abstraction simplifies data, while data representation stores or encodes it. Data abstraction in programming involves constructing a data type that hides data representation. This lets consumers concentrate on the data’s primary features rather than its implementation. Data abstraction is common in object-oriented programming and database administration. Computers store data in binary format. The smallest binary unit is a bit, or “binary digit”. Bytes typically have eight bits. Data abstraction …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 22–31 Read article
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Tweets Classification using Different Classifiers for Sentiment Analysis
Abstract: Twitter is a famous platform for social networking where people share and engage with "tweets" comments. It is a way of expressing people's opinions or emotions on various topics. Different parties, like producers and consumers, have carried out a sentiment analysis on tweets to gain insights into goods or to analyze the sector. Also, the accuracy of our sentiment analysis forecasts will increase with the recent advances in machine learning …
Published in Research & Reviews : Journal of Statistics · Vol. 10, Issue 3, 2021 · pp. 34–43 Read article
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Predictive Modeling of Polymer Elasticity and Mechanical Strength Using Deep Learning for Functional Polymer Material Characterization and Performance Assessment
Abstract: Knowing the polymers elasticity and mechanical strength is essential in the characterization of functional polymer materials, for rapid characterization and to avoid extensive experiments. Traditional polymer characterization methods are often time consuming and resource intensive and the mechanical response of polymers can be nonlinear, thus complicating the prediction of the properties. These limitations can be overcome by introducing a Variational Temporal Fusion Transformer (VaTFT) for the deep learning prediction of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Automatic Chest X-ray Report Generation Using Machine Learning
Abstract: In this study, a deep neural network is suggested for the automatic creation of precise radiologist reports from chest X-ray pictures. The proposed network responds to the need for medical image captioning by learning to extract key features from the image and creating tag embeddings for each patient's X-ray images. Medical image captioning demands coherence and high accuracy in identifying abnormalities and extracting information. For a finer representation, the network …
Published in Journal of Instrumentation Technology & Innovations · Vol. 13, Issue 1, 2023 · pp. 29–39 Read article
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A Comparative Study Between GSM and CNN to Develop Gesture Detection Based Alert System for Women Safety
Abstract: Women’s safety is a pressing issue in today’s world, and technology can play a crucial role in addressing it. This project introduces a facial expression recognition device that uses Convolution Neural Network (CNN) technology and develop it’s comparison with an expression system with use of GSM is done. Unlike traditional methods relying on manual activation or dedicated devices, this system reacts instantly to threatening situations by recognizing predefined gestures, ensuring …
Published in International Journal of Electrical Power and Machine Systems · Vol. 2, Issue 1, 2024 · pp. 24–30 Read article
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LBP-HOG-Statistical-Wavelet Transform Feature Based MCA Classifier
Abstract: Face recognition systems use computer algorithms choose specific, recognizable features on a person’s face. With a mathematical representation, the information is compared to data on other faces acquired in a face recognition database. The distance between the eyes or the shape of the chin are two examples of these characteristics. The job of matching several facial modes, such as visible and near infrared images, is known as heterogeneous face recognition. …
Published in Trends in Opto-electro & Optical Communication · Vol. 12, Issue 2, 2022 · pp. 19–30 Read article
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Real-time Malicious URL Detection Using Machine Learning
Abstract: In malicious URLs (universal resource locators)discovery, antiquated classifiers are tested because of the information volume is enormous, designs are dynamical over the long haul, and furthermore the relationships among choices are modern. Feature engineering plays a crucial role in addressing these issues. To raised representation, the underlying the drawback and improve the performances of classifiers in characteristic malicious URLs.This paper proposes a mixture of linear and non-linear house transformation strategies. …
Published in Journal of Web Engineering & Technology · Vol. 8, Issue 1, 2021 · pp. 8–13 Read article
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A Review Paper on The Mathematical Foundations of Artificial Intelligence
Abstract: Artificial Intelligence (AI) is deeply rooted in various branches of mathematics, which provide the theoretical foundation and practical tools for developing intelligent systems. This paper explores the crucial role of mathematics in AI, focusing on key areas such as Linear Algebra, Probability and Statistics, Optimization Techniques, Calculus, Graph Theory, and Fourier and Wavelet Transforms. Linear Algebra is fundamental for representing and manipulating data, with applications in dimensionality reduction and neural …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 7–14 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 15–27 Read article
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PSSM Amino-Acid Composition Based Gene Identification Using Support Vector Machines
Abstract: AbstractThe main characteristic of identifying the molecular mechanism of the cell is to understand the significance or function of each protein encoded in the genome. For that purpose, genome annotation proves to be very supportive. One of the most obligatory phases of genome annotation is the prediction of the genes. Several methods or techniques have been developed in order to locate or predict the patterns of genes in genome sequence. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 1, 2019 · pp. 50–58 Read article
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Slope Stability Analysis by Swedish Slip Circle Method Using C-Programming
Abstract: The side slopes of an earthen dam should be safe against shear failure. Out of the various methods of stabilityanalysis of slopes, “Swedish Slip Circle Method” is commonly used in practice. Here in the Swedish circlemethod, potential failure surface is assumed to be cylindrical in shape (i.e., circular in cross section). Afterdetermining the actuating and resisting forces for assumed failure surface, the factor of safety is calculated. Theslope is considered …
Published in Recent Trends in Civil Engineering & Technology · Vol. 1, Issue 1-3, 2011 · pp. 47–68 Read article
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Enhancing Explainability in Machine Learning Based Spam Email Detection Using LIME and SHAP
Abstract: Spam emails represent a continual and irritating cybersecurity issue due to the fast expansion of cyberspace communication. These messages are unwanted and, in some cases, dangerous, such as phishing schemes, identity theft, and the propagation of malware. They cause severe financial and data security threats to individuals and organizations. Conventional spam detection techniques, such as rule-based spamming, blacklisting, and keyword classification, are techniques that find it difficult to match adaptive …
Published in Journal Of Network security · Vol. 14, Issue 2, 2026 · pp. 35–48 Read article
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Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 1–9 Read article
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Emerging Trends in Data Structures for Modern Machine Learning Applications
Abstract: In the realm of machine learning, data structures play a pivotal role in facilitating efficient data manipulation, storage, and retrieval, thereby significantly impacting the performance and scalability of machine learning algorithms. In recent years, the field of machine learning has witnessed the emergence of novel data structures tailored to address scalability and efficiency challenges inherent in handling large-scale and high-dimensional data. This study provides a look at the data preprocessing, …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 1–7 Read article
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Bias Detection and Accuracy Enhancement in Voice-based Banking Authentication Using Deep Learning
Abstract: Biometric systems have become an integral part of how many people access banking services today, and voice verification systems can be a secure and easy-to-use source of banking authentication that does not require any physical contact with the bank or any other person. From the security perspective, these systems would normally provide an effective means of identifying an individual but frequently exhibit bias with respect to demographics such as the …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article
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Representation of Knowledge Involving Soft Fuzzy Numbers and Its Application in Decision Making Problems
Abstract: In this study, we introduce the concept of a soft fuzzy number and study its arithmetic operations, a fuzzy number valued measure and an aggregation operator on the collection of soft fuzzy numbers. In real life situations, the perception of characteristic feature of an entity or a collection of entities is expressed by us as soft fuzzy number valued information system, so that the loss of information in understanding the …
Published in Recent Trends in Parallel Computing · Vol. 6, Issue 1, 2019 · pp. 38–47 Read article
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Cloud Services Models and its Security Features
Abstract: Cloud Computing plays a vital role in the time of internet. The goal of cloud computing is to transport the services and security. It provides setup and easy way of handling a vast data necessary to run organization positively. Cloud storage technology gets more expansion to attract multiple users. Storage capacity of cloud depends on the users. However, in storage representation, users’ data is all put in cloud servers. In …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 6, Issue 3, 2018 · pp. 13–17 Read article
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Unleashing the Power of Mathematics in Natural Language Processing: Sentiment Analysis Perspectives
Abstract: Sentiment analysis (SA), which utilizes natural language processing (NLP), computational linguistics, text analysis, image processing, and video processing to extract and analyze subjective information from the internet, social media, and other sources, is becoming increasingly popular in both the business world and the scientific community. It is even possible to model it so that it focuses on polarity, sentiments and emotions, urgency, and even goals. It is able to distinguish …
Published in Recent Trends in Programming languages · Vol. 10, Issue 2, 2023 · pp. 1–9 Read article