Search
358 articles for “Interactive Learning”
-
Lip Reading: Transforming Speech to Text
Abstract: Lip reading, the ability to interpret spoken language by observing lip movements, is a valuable skill that can aid in various applications, particularly in enhancing speech recognition systems. This project explores the implementation of a deep learning-based lip-reading model to improve the accuracy and robustness of speech recognition in challenging environments, such as noisy or audio-limited settings. The proposed lip-reading system leverages Convolutional Neural Networks (CNNs) and Recurrent Neural Networks …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 23–33 Read article
-
Assistive Technology Advancements: Revolutionising Support for Individuals with Specific Learning Disabilities
Abstract: Assistive Technology (AT) has become an offer to revolutionise the provision of people with specific Learning Disabilities (SLD), making the learning process more inclusive and equal. In this paper, the current developments in AT will be discussed that cater to fundamental learning issues in reading, writing and mathematics. Text-to-speech and speech-to-text innovations, mind-mapping tools, and others are important innovations that improve reading comprehension and written expression, as well as strength …
Published in International Journal of Trends in Humanities · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
-
Using AIML to Enhance Demand Forecasting in Business
Abstract: Artificial intelligence machine learning (AIML) can play a significant role in enhancing demand forecasting in business. AIML is a programming language designed for creating chatbots and conversational agents, but its application extends beyond simple interactions. In the context of demand forecasting, AIML can be utilized to analyze historical data, customer interactions, and market trends. By implementing AIML algorithms, businesses can create intelligent models that learn from past demand patterns, customer …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 35–40 Read article
-
Yojana Access: All schemes on one click
Abstract: In a developing country like India, it becomes mandatory that every underprivileged member of the country is aware of the various schemes initiated by the government. Making use of the machine learning and web development, we propose an idea to develop an online portal that will serve as the direct link between the government and the citizens which is “Yojana Access”. This portal will reduce the paperwork and there will …
Published in Journal of Web Engineering & Technology · Vol. 7, Issue 2, 2020 · pp. 32–38 Read article
-
Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
-
A Review of Machine Learning Applications in Web Data Mining
Abstract: The rapid development of Internet technology has resulted in a rapidly changing and intricate digital environment that requires new methods for organizing and evaluating online data. This study examines the use of machine learning (ML) in web data mining, focusing on its ability to extract relevant insights from huge amounts of online data. Web data mining, which is divided into three categories: content mining, structure mining, and use mining, uses …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 39–47 Read article
-
Designing Intelligent Agents for Effective Collaboration with Human in Complex Environment
Abstract: An intelligent agent is a self-governing system that can take action to accomplish its goals based on how it perceives its surroundings. This paper introduces a newly designed humanoid robot that demonstrates significant advancements in performance, reliability, durability, energy efficiency, and environmental sustainability. The design emphasizes a bio-inspired musculoskeletal system, enabling natural and flexible motion while improving operational lifespan. A self-repair system is integrated to allow the robot to address …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 3, 2025 · pp. 1–7 Read article
-
A SEIR-Informed Stacked Fusion of Prophet, XGBoost, and LSTM for Ward-Level Epidemic Forecasting in Amravati Municipal Corporation
Abstract: Municipal epidemic preparedness depends on accurate short-horizon forecasts at fine spatial granularity. Ward-level incidence series are typically nonstationary due to changing contact patterns, interventions, reporting delays, and heterogeneous demographic and environmental factors. This paper presents a mathematically formulated hybrid forecasting architecture designed for Amravati Municipal Corporation (AMC). The method decomposes observed incidence into (i) a mechanistic SEIR baseline that enforces epidemiological structure and (ii) a data-driven residual learned using Prophet …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 17–23 Read article
-
Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
-
Some Recent Developments in Media Technology
Abstract: The creation, distribution, and consumption of material have all changed as a result of the media technology's quick development. The influence of 5G on streaming and interactive media, virtual and augmented reality (VR/AR), blockchain for media rights management, and artificial intelligence (AI) in content creation are some of the current developments in media technology that are examined in this article. The rapid advancement of digital technology in recent years has …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 1, 2025 · pp. 30–36 Read article
-
Effect of Multimedia Instruction on Learning: A Case Study
Abstract: Multimedia are increasingly one of the most popular information access devices; and what stands out from the study is the high use of interactive, multi-user functions which can at times be disruptive or beneficial during the study. The use of multimedia in education has proven its importance due to its positive impact on the teaching and learning process. So, the present study investigates comparative effectiveness of multimedia-aided teaching on students’ …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 2, 2018 · pp. 7–11 Read article
-
An Abnormal Expression Detection System (AEDS) Using Deep Learning Algorithms
Abstract: In the last decade, many deep learning algorithms have achieved remarkable success and gained popularity in various computer vision tasks, including object detection, image recognition, and segmentation. This AEDS (Abnormal Expression Detection System)leverages the power of deep learning algorithms to detect abnormal facial expressions in real-time automatically. AEDS proposed two important models; those are Deep CNN and RNN. CNN is responsible for learning discriminative features from facial images and capturing …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 72–79 Read article
-
FutureGen – Predicting Genetic Health
Abstract: FutureGen is an intelligent web-based system developed to help couples assess the risk of genetic disorders in their future child through data-driven analysis. The system brings together modern web technologies and machine learning to offer accurate and accessible predictions. The frontend, built with React, provides an intuitive interface for user interaction, while a Flask-based backend API handles model inference and manages communication with the Supabase database, which securely stores user …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 · pp. 23–35 Read article
-
Campus Connect: Intelligent Web Platform for Integrating Academic and Administrative Campus Activities
Abstract: Campus Connect is a full-stack web-based application designed to improve communication, collaboration, and community engagement within a college campus. It acts as a centralized platform where students, faculty, and staff can create profiles, connect with each other, and participate in academic and extracurricular activities. The system includes features such as a news feed for announcements and events, discussion forums for academic interaction, a resource-sharing section for study materials, and an …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 2, 2026 · pp. 9–14 Read article
-
PREDICTIVE LEARNING POWERED BY AI AND SOPHISTICATED STUDENT ENGAGEMENT TECHNIQUES
Abstract: The contemporary landscape of education has witnessed a paradigm shift in integrating advanced technologies that have revolutionized the learning experience. Innovative methodologies have emerged to address longstanding challenges, such as enhancing student engagement, accurately predicting academic performance, and personalizing the learning journey. However, despite the numerous benefits that technology brings to education, there remains a crucial hurdle - sustaining student motivation and engagement. Traditional teaching methodologies often struggle to generate …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 127–140 Read article
-
Gradient Boosted Regression Tree Approach to Predicting Toxic Interactions on X and YouTube
Abstract: In the digital age, social media platforms play a vital role in facilitating user engagement, encompassing both positive interactions and avenues for negative, often harmful behaviors. Recognizing and addressing toxic exchanges is paramount to nurturing healthy online communities and preserving users’ well-being. This study introduces a novel method for identifying toxic interactions by utilizing Gradient Boosting Regression Trees (GBRT) algorithm, a machine learning approach renowned for its exceptional accuracy and …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 7–14 Read article
-
DR. REVIVE: An AI-Powered Medical Recommendation System for Optimised Resources and Improved Patient Care
Abstract: Dr. Revive is an AI-powered medical recommendation system designed to enhance virtual healthcare interactions by connecting patients, doctors, and healthcare stakeholders. Leveraging advanced machine learning algorithms, it analyses user-reported symptoms to provide initial medical recommendations, serving as a reliable first point of guidance. With access to a comprehensive medical database, the platform delivers accurate and timely advice, empowering patients while supporting healthcare professionals with data-driven decision-making. By offering a complete …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
-
Measuring Microstructure, Wear Resistance, and Mechanical Reliability Enhancement in Polymer Nanocomposites via Data-Driven Analysis with Deep Learning
Abstract: Polymer nanocomposites have gained great attention owing to their superior mechanical performance, better wear resistance and customizable microstructural properties for aerospace, automotive, medicinal and industrial engineering applications. However, the correct evaluation of the link between the microstructure evolution and the material reliability is a huge issue due to the intricacy of nanoscale interactions and diverse material characteristics. In this study, we propose a data-driven approach that integrates deep learning and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
An Overview of Intelligent Operating Systems (iOS)
Abstract: The rapid convergence of artificial-intelligence techniques with core operating system services is ushering in a new class of platforms—intelligent operating systems (iOS)—that can anticipate, adapt, and optimize on behalf of both applications and users. This paper surveys the architectural shifts required to embed learning, reasoning, and self-healing capabilities into the kernel, scheduler, memory manager, and I/O subsystems. We present a prototype framework, NeuroKernel, that augments traditional OS primitives with three …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 · pp. 21–28 Read article
-
Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 15–24 Read article