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906 articles for “Learning Effect”
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Use of Intelligent Control Systems to Manage Traffic Effectively and Productively
Abstract: Intelligent control system is the advanced technology in which the collected data is provided to A.I. and with the help ofvarious methods like machine learning, neural networks, Bayesian probability, fuzzy logic the solution to a particularproblem is found.In a country’s growth the traffic management plays a great role as the maximum industries depends on the highways orroads and when it is well planned it can reduce the commute time and …
Published in Trends in Mechanical Engineering & Technology · Vol. 13, Issue 1, 2023 · pp. 22–27 Read article
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Synopsis of Plant Disease Detection Methodologies and their effect on Environment
Abstract: Agriculture is the primary occupation in India. It accounts for 18% GDP and provides employment to 50% of country’s labour’s. However, due to climate change, yield of crops is reducing and affecting Indian economy. One of the reason behind this is increase in number of plant diseases. So, disease detection becomes vital. But it needs huge personnel, additional processing time, extensive knowledge on plants and their diseases. Hence, machine learning …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 10, Issue 3, 2020 · pp. 16–21 Read article
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Fitness and Aesthetics Hostel Gym Management
Abstract: Fitness & Aesthetics’ mission is to help people achieve their fitness objectives by offering training regimens and healthy living plans, as well as assistance with managing a club. By automating the current manual method with the use of digitized equipment and comprehensive computer software, it will provide the information of the Trainer, Gym, Facility, Workout Routines, and Time Slot and proceed into the administrative position, satisfying their requirements, in order …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 1, 2023 · pp. 21–27 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article
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Traffic Density Estimation Using Image Frames in Python
Abstract: Traffic congestion is a critical challenge in modern urban environments, leading to significant delays, environmental pollution, and increased accident rates. With the rapid growth of vehicle populations in metropolitan areas worldwide, the need for intelligent and automated traffic monitoring systems has become increasingly urgent. Traditional monitoring approaches, such as inductive loop detectors and manual surveillance, are limited in scalability, deployment cost, and adaptability to dynamic traffic scenarios. This paper presents …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 38–45 Read article
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Data Breaches and Malware Detection in Healthcare System
Abstract: The healthcare sector is undergoing a chaotic digital transformation, but the incorporation of new technologies is not typically the cause of health information-related data breaches. According to published industry studies, there are still many recorded data breaches as a result of equipment theft, hacking, ransomware attacks, and misuse, as well as a lack of basic security precautions. When compared to any other field, protecting health information is given the highest …
Published in Journal of Advanced Database Management & Systems · Vol. 9, Issue 3, 2022 · pp. 15–24 Read article
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Harnessing the Role of Chatbot in Enhancing Educational Accessibility and Engagement
Abstract: Chatbots in education offer a valuable means to enhance accessibility and provide immediate, 24/7 support, assisting students and educators in accessing information and solving queries efficiently. They also contribute to personalized learning experiences, engaging students in interactive and informative interactions, ultimately fostering a more dynamic and effective educational environment. This research work delves into the creation and deployment of a chatbot, with a specific emphasis on its use within the …
Published in Journal of Advancements in Robotics · Vol. 10, Issue 2, 2023 · pp. 21–30 Read article
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Virtual Reality Based Decentralized Educational Art Gallery
Abstract: One can experience the forefront of education by engaging with our virtual reality (VR) powered decentralized educational art gallery. This groundbreaking platform seamlessly integrates VR technology with decentralized networks, crafting an unmatched learning journey. Curated collections of art from diverse cultures and eras can be explored, accompanied by interactive educational modules that deepen one’s understanding of each piece. One can engage with fellow learners in real time, fostering collaboration and …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 31–37 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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Machine Learning Approaches for Intelligent Network Traffic Management in 6G
Abstract: The increasing adoption of smart devices, Internet of Things (IoT) technologies, cloud-based services, autonomous applications, and multimedia platforms has greatly enhanced the demands and complexity of modern wireless communication networks. To meet these evolving requirements, upcoming sixth-generation (6G) communication systems are anticipated to deliver extremely high data transmission speeds, support a vast number of connected devices, ensure minimal communication delays, enable intelligent network management, and provide seamless real-time connectivity for …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 2, 2026 · pp. 19–32 Read article
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Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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A Study to Assess the Effectiveness of Video-assisted Teaching Programme on Knowledge Regarding Good Touch and Bad Touch among School Children at Selected School, Vadalur
Abstract: Background: Good touch and bad touch are gradually learnt through a child's day activities. We can increase this learnt behavior by making effort to teach a child about the difference between good touch and bad touch in early age. Child protective services in 2010, reported that among child maltreatment cases, 17% suffered physical abuse, 9% sexual abuse, 63% neglect and 7% emotional abuse. Objectives: 1: To assess the pre-test knowledge …
Published in Journal of Nursing Science & Practice · Vol. 10, Issue 1, 2020 · pp. 21–25 Read article
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Bearing Fault Diagnosis Using ANN and SVM with the Help of Wavelet Transform Based Features
Abstract: Many researchers use vibration signals as fault characteristics of any rotating bearing for fault detection and use various optimization techniques available for fault of bearing classification. The method of fault classification uses few neural network (NN) geometry and parameters necessary for the formulation. There is no derived formulation which can be used to select the optimal values for the network parameters. The parameters which are required to be calculated, impacts …
Published in Recent Trends in Electronics Communication Systems · Vol. 4, Issue 2, 2017 · pp. 26–34 Read article
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Comparative Performance Analysis of Swarm and Intelligent Evolutionary Techniques for Optimal Design of Distribution Transformer
Abstract: This paper addresses the method of optimal design of a three phase distribution transformer using Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Teaching-Learning-Based-Optimization Algorithm (TLBO). The design and analysis programs have been developed for constrained optimal design with cost as the objective function. The active part cost of the transformer has been minimized keeping in view BEE (Bureau of Energy Efficiency) standards and constraints. A design example on a …
Published in Trends in Electrical Engineering · Vol. 5, Issue 3, 2015 · pp. 46–58 Read article
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Comparison of K-nearest Neighbor and Artificial Neural Network Classifiers for the Detection of Breast Cancer
Abstract: Breast cancer is the most common type of cancer seen in women in the present day, which is also considered a life-threatening disease. If this cancer can be detected in its early stage it can be a lifesaver for many people around the world. Machine Learning techniques have become one of the hotspots for predicting the early diagnosis of breast cancer. This research work experiments with the two most popularly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 78–83 Read article
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Hybrid Approach for Community Detection Using Deep Learning Techniques
Abstract: Community detection in complex networks is a fundamental problem with applications across diverse domains, ranging from social networks to biological systems and beyond. Traditional methods based on graph theory have been widely used for identifying communities within networks. However, the intricate and evolving nature of modern networks demands more sophisticated approaches. This research work proposes a hybrid approach that combines the strengths of deep learning techniques with traditional community detection …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 18–26 Read article
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Human-Centered AI in Museums: Enhancing Accessibility and Visitor Engagement
Abstract: Artificial intelligence (AI) is being used extensively in museums, which are cultural and learning spaces, to improve accessibility, optimize environmental conditions, and improve visitor experiences. Traditional museum designs are evolving to accommodate the demands of contemporary visitors, as they frequently fall short in properly engaging various audiences. AI-powered tools like augmented reality, machine learning, and smart sensors allow museums to design customized, adaptable spaces. Based on real-time visitor data, these …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 27–33 Read article
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Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 Read article
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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article