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76 articles for “feature representation”
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A Supervised Learning Approach for Toxic Comment Detection on Social Media Platforms
Abstract: Nowadays everyone uses social media platforms like X (formerly Twitter), Instagram, Facebook, etc. for various purposes. With the help of this, we share our opinions, ideas, and feelings. Generally, the datasets obtained from the internet are constructive; however, there is a significant proportion of toxic ones. The datasets are filtered to remove noise, and noise is removed in post-processing. The study initiates with the upload and preprocessing of a toxic …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 7–14 Read article
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Modulation of Receptor Proteins: A Recent Paradigm in Drug Discovery and Target
Abstract: The main aim in drug discovery is to design different ligands those work on specific drug targets. However, various effective drugs work through the modulation of many proteins than single target. Advancement in system biology are establishing a phenotypic strength and a network structure, which suggests that, the excellent selective compounds may be performed less than desired clinical efficacy in comparison to multi-target drugs. In this new appreciation of the …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 5, Issue 1, 2018 · pp. 14–24 Read article
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Satark India Application
Abstract: AbstractWe face many problems and see a lot of issues happening in our surroundings but we ignore those because of the tedious path of government to follow up and investigate the issue. Mobiles play a major role in delivering solutions to our everyday problems. We have designed the android phone application “Satark India Application” that focuses on delivering a clean society. This app gives people the platform where the issue …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 8, Issue 1, 2021 · pp. 23–32 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Ranking of Image Search by Click-Based Uniformity and Typicality
Abstract: AbstractAccording to the image search re-ranking, apart from the semantic gap and intent gap, which is the gap between the representation of user’s query and the real objective of the users, is forming a major issue in restricting the evolution of image retrieval. In order to reduce human effects, the method use image click-through data, which can be viewed as the implicative feedback from users, to help overcome the intention …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 39–46 Read article
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Creative Collaboration on a Digital Canvas
Abstract: A Collaborative whiteboard is presented where users at multiple locations can communicate with each other. The system features a virtual environment with vivid avatars, stroke compression and streaming technology to effectively deliver stroke data across meeting participants, friendly human interaction and navigation, virtual and physical whiteboard. The whiteboard is both a physical platform for our input/output interfaces and a virtual screen for sharing common multimedia. It is this whiteboard correspondence …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 29–36 Read article
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Deep Learning Approach to Produce Artificial Speech (Text-To-Audio)
Abstract: This program utilizes key features of the .NET framework to facilitate smooth text-to-speech conversion and audio playback. Upon execution, users are prompted to input text via a graphical user interface (GUI), which the program converts into speech using the ‘SpeechSynthesizer’ class from the ‘System. Speech.Synthesis’ namespace. The audio that has been synthesized is handled and stored as a WAV file called ‘output.wav’ by utilizing the ‘FileStream’ class, allowing for future …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 28–33 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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Topology and Geometry in Data Science: Persistent Homology and Beyond
Abstract: In recent years, the interplay between topology, geometry, and data science has gained substantial momentum, offering powerful frameworks to analyze and interpret complex datasets. Traditional statistical and machine learning methods often rely on linear or metric- based assumptions, which may fail to capture the intrinsic structure of high-dimensional or nonlinear data. In contrast, topological and geometric methods provide shape-oriented, scale- invariant tools that focus on the continuity, connectivity, and global …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 21–27 Read article
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A Novel Binary Arithmetic Computational Method
Abstract: The proposed algorithm for arithmetic operations presents an innovative and intriguing approach, primarily centered around the use of counters and the manipulation of '1's in binary representations. This algorithm promises to introduce significant advancements in computational efficiency and accuracy, making it a potential game-changer in the field of arithmetic calculations. At the core of this method lies the reliance on the number of '1's in each location within a binary …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 10, Issue 1, 2023 · pp. 21–25 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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Online Examination: Methods & Analysis
Abstract: This article proposes an online examination method. There are few characteristic features over the existing system which is discussed in brief. This system enables the data security, safe informative collection at a large scale. The users involving in conducting the online exams & also the students applying for exam can directly communicate by this model of conducting exam. We offer strategies that are relevant to the aspects of the assessment …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 8, Issue 3, 2021 · pp. 37–42 Read article
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Recovering the History of Filtered JPEG Images for Forensic Detection
Abstract: The image editing software available today are apt for creating visually compelling and sophisticated fake images, which cause major issues to the reliability of digital contents as a right representation of reality. Authenticity is the main problem in most digital image communications. Various forensic techniques have been developed for the verification of image integrity, authentication, and tampering detection. Digital image forensics aims at finding the authenticity of images by recovering …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 3, Issue 2, 2016 · pp. 1–6 Read article
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Microstructural Investigation on Strength of New Age Mortar Synthesis with Thermosetting Polymer, GGBS, Fly Ash and Quarry Dust
Abstract: AbstractThermo setting polymer mortars containing Resin, hardener, fly ash, Quarry dust and GGBS (Ground Granulated Blast furnace slag). Merging representation of bio phenol-A-Di-glycidyl ether-based polymer with fly ash, Quarry dust and GGBS results are presented here for this present study. An innovative process is used to prepare the specimen in mild condition with commercial thermo setting polymer-based resin and hardener, fly ash, GGBS, along with quarry-dust-based paste. Following this procedure, …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 63–71 Read article
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A Comprehensive Study of Natural Language Processing Systems Using Modern Programming Languages: Techniques, Architectures, Experimental Evaluation and Applications
Abstract: Natural language processing is a key field of study within artificial intelligence that focuses on enabling machines to understand and work with human language. This is because there is much digital text data everywhere. Natural Language Processing is what this study is about. It looks at new ways of doing Natural Language Processing. The old ways are like machine learning, and the new ways are like learning. This study compares …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 · pp. 12–23 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article