Search
30 articles for “Semantic processing”
-
Behavioral and Electrophysiological Correlates of Semantic Processing in Kannada
Abstract: Semantics is one of the fundamentals of language components, encoding of which helps in understanding the meaning of the spoken or written language. The processing pattern of semantics has been studied extensively in different languages using either the conventional psycholinguistic experiments or advanced neuroimaging techniques. Previous studies have documented the behavioral and electrophysiological correlates of semantic processing in different languages. However, the correlation between these measures has not been well …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 9, Issue 2, 2019 · pp. 1–9 Read article
-
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
-
Importance of Thesaurus in Natural Language Processing for Scholarly Data Extraction
Abstract: The exponential growth of scholarly literature needs advanced methods for efficient data extraction and knowledge discovery. Natural Language Processing (NLP) has emerged as a crucial technology in automating the analysis and organization of academic texts. Among various linguistic resources, thesauri serve as important tool for enhancing semantic understanding by providing structured vocabularies, synonyms, and hierarchical relationships between terms. This paper examines the importance of thesauri in enhancing NLP-based scholarly data …
Published in Emerging Trends in Languages · Vol. 3, Issue 1, 2026 · pp. 19–24 Read article
-
Optimizing Sentiment Analysis with Naïve Bayes and Random Forest Techniques: A Result-based Approach
Abstract: In the increased digitalization, the sentiment analysis and classification have evolved as an eminent area to determine the polarity of positive, negative, and neutral reviews of the customers and users on products. It is an integral application field that employs supervised learning, Machine Learning, and Natural Language Processing concepts. The proposed Semantic Analysis and Classification using Naive Bayes and Random Forest system accomplishes the sentiment polarity by classifying the user …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 46–57 Read article
-
Analysis of Various Tools of Natural Language Processing Based on Developers Perspective
Abstract: The subject of natural language method has visible mind-blowing development in current years, with neural network community substitution numerous of the traditional structures. A subset of artificial intelligence known as “natural language processing”, or NLP, analyses, comprehends, and generates natural human languages so that computers can reuse written and spoken human language without resorting to computer-generated language. Semantics and syntax are used in natural language processing, which is sometimes referred …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 2, 2022 · pp. 1–5 Read article
-
Enhancing Interview Preparedness: Development of A Comprehensive AI-Driven Mock Interview System
Abstract: In the contemporary era of virtual interviews, the need for a comprehensive system to prepare users for online interviews is imperative. Mock interviews serve as invaluable tools for enhancing confidence and communication skills, ultimately improving performance. This paper introduces a groundbreaking AI-Driven Mock Interview System (MIS) fortified with cutting-edge Natural Language Processing (NLP) methodologies, specifically targeting syntax and semantic analysis. The MIS integrates a robust JSON-based question- answer repository spanning …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 2, 2024 · pp. 19–25 Read article
-
Object Detection Using Deep Learning Algorithm
Abstract: Object detection is a computer technology related to computer vision and image processing that deals with detecting images of semantic objects of a certain class (for example cars, buildings, etc.) in digital images and videos. To detect objects, there are many algorithms available, in this paper YOLO algorithm is explored for detection of objects on real-time data. You Only Look Once (YOLO) is a state-of-the-art real time object detection system …
Published in Journal of Control & Instrumentation · Vol. 12, Issue 2, 2021 · pp. 1–13 Read article
-
Enhancing MRO Documentation Through Automated Translation of Non-Standard English to Simplified Technical English Using Offline LLMS
Abstract: Maintenance, Repair, and Overhaul (MRO) operations rely heavily on accurate and consistent documentation to ensure operational safety and compliance. However, the presence of non-standard English in technical documents often leads to ambiguity, misinterpretation, and inefficiencies in maintenance processes. This study presents an innovative solution that leverages an offline Large Language Model (LLM) to automatically translate non-standard English in MRO documents into standardized and technically precise language. By integrating predefined linguistic …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 9–15 Read article
-
Automated Evaluation of Descriptive Answers
Abstract: This paper offers a smarter system of automatic evaluation of descriptive responses in educational tests. The time-consuming aspect of testing with traditional manual marking, the subjectivity of that process, and the impossibility of scaling it makes it inapplicable, particularly to large academic environments. To resolve the issues, the proposed solution combines the methods of Natural Language Processing (NLP) and hybrid image-text processing on the responses of handwriting and typed answers. …
Published in Emerging Trends in Languages · Vol. 3, Issue 2, 2026 · pp. 1–9 Read article
-
Sentiment Analysis on Financial News Using Deep Learning Algorithm
Abstract: Sentiment analysis is the technique of computationally figuring out and categorizing reviews or comments expressed in a bit of textual content, especially a good way to decide whether or not the writer's mind-set in the direction and also very helpful to identify the customer’s opinion about the particular product or content. It is one of the active and wanted research areas in natural language processing. In existing work, machine learning …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 24–27 Read article
-
Role of Machine Vision in Autonomous Vehicles: A Review
Abstract: The integration of machine vision in autonomous vehicles (AVs) is a critical advancement in the field of intelligent transportation systems. Machine vision systems enable AVs to perceive their environment, understand road conditions, detect obstacles, and make real-time decisions necessary for safe navigation. These systems rely heavily on image processing techniques, which have evolved significantly over the past decade, leading to improved performance in complex driving scenarios. These developments are largely …
Published in Trends in Machine design · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
-
Retrieval of nouns and verbs in Persons with Aphasia
Abstract: A grammatically correct sentence is comprised of two parts, a subject (noun or pronoun) and a predicate (verb). The noun represents the names of a particular person, place or thing. The verb, on the other hand, represents actions, states, processes or relations. Nouns and verbs, differ in the linguistic dimensions, such as word frequency, imageabilty, and lexical semantic variables. These varying dimensions have been explored in individuals with Aphasia and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 9, Issue 1, 2019 · pp. 24–28 Read article
-
Face Aging Using Generative Adversarial Network
Abstract: This project addresses the challenge of predicting how a person may look in the future or how they appeared in the past using a single photograph. While existing methods mainly focus on altering texture, they often neglect changes in head shape that naturally occur during the aging process, limiting their effectiveness, especially when applied to images of children. To tackle this issue, a novel approach is introduced that employs a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 41–52 Read article
-
Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
-
Semantic Similarity Framework for Automatic Hallucination Detection in Large Language Models
Abstract: Large Language Models can generate fluent, contextually appropriate text across a range of NLP tasks, but they frequently produce outputs that are factually wrong while sounding confident and plausible. This problem, referred to as hallucination, poses serious risks in domains where accuracy matters. We propose a post-processing framework that detects hallucinated responses by comparing them against verified reference text using sentence embeddings. The system computes cosine similarity between the response …
Published in Emerging Trends in Languages · Vol. 3, Issue 2, 2026 · pp. 16–22 Read article
-
Continuous Learning in Language Models: A Survey of Streaming Data Processing Techniques
Abstract: The integration of continual learning with Large Language Models (LLMs) and Natural Language Processing (NLP) represents a transformative step toward creating adaptive, intelligent systems capable of functioning effectively in ever-changing environments. Traditional LLMs are typically trained on large, pre-collected datasets, which limits their ability to evolve as new information emerges. Continual learning, in contrast, enables models to acquire new knowledge incrementally without the need for complete retraining, thereby supporting long-term …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 23–34 Read article
-
Developing a RAG-PDF Reader Using Instructor XL and Falcon 7B
Abstract: This study outlines the development of a Retrieval-Augmented Generation (RAG) application, designed to efficiently extract, retrieve, and synthesize insightful responses from complex PDF documents. Leveraging advanced models like Instructor XL for generating high-quality semantic embeddings and Falcon 7B for sophisticated language generation, this system provides a robust solution for document comprehension in academic, research, and professional environments. By implementing efficient PDF text processing, embedding storage with FAISS for rapid similarity-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 45–49 Read article
-
Record Linkage in Knowledge Discovery Process Using Angle Based Machine Learning
Abstract: Record linkage is a critical data cleansing step in the knowledge discovery process, aimed at identifying and resolving inconsistencies across datasets. This study proposes an enhanced record linkage framework tailored for uncertain and large-scale data using a combination of distance measurement, probabilistic modeling, and semantic reasoning. A novel angle-based distance measurement technique is introduced to optimize matching between candidate records. To further boost match accuracy, a Finite Mixture Model (FMM) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1170 Read article
-
Investigating the Role of Ontologies to Develop Augmented Intelligence Applications
Abstract: This paper presents about knowledge representation utilizing ontologies to empower augmented intelligence (AUI) for Systems Engineering. Innovation patterns show new strategies and apparatuses for advanced designing will fuse AUI. Machine learning (ML) methods uphold arrangement, bunching, and affiliation distinguishing proof, yet battle to explain the reasoning for dynamic knowledge entities and their crucial representation. Knowledge representation assumes a critical part in applying this kind of Artificial Intelligence (AI). Ontologies equip …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 2, 2022 · pp. 11–16 Read article
-
Semantics Analysis of Expected Goals in Soccer Data Using Machine Learning
Abstract: In recent years, the increasing availability of soccer data has greatly enhanced the accuracy and depth of player performance evaluation. Soccer, being one of the most popular sports worldwide, attracts millions of fans due to its simple rules, minimal equipment requirements, and high entertainment value. However, analyzing an entire match manually can be time-consuming, leading to a growing demand for automated methods that can summarize and interpret game data efficiently. …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 31–47 Read article