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198 articles for “Novel algorithm”
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AI-Enabled Feedback Management for Enhancing Education
Abstract: Institutions are becoming more aware of the importance of student input in improving learning experiences in the current educational environment. However, the intricate and complex patterns found in this feedback are frequently missed by conventional techniques like manual reviews and simple statistics. Our proposal suggests a novel method for analyzing student input and more accurately predicting sentiment by utilizing Long Short-Term Memory (LSTM) algorithms. We can learn more about student …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 21–27 Read article
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AI Application in the Creation of Medications for COPD
Abstract: The crippling lung condition known as chronic obstructive pulmonary disease (COPD) is typified by a continuous restriction of airflow, which results in increased respiratory dysfunction and a reduced quality of life. The rising incidence of COPD worldwide emphasizes the pressing need for innovative pharmaceutical approaches to address the illness. Even though COPD care has advanced significantly, most current medications concentrate on symptom relief rather than disease change. This gap in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 01–05 Read article
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Summarizer: A Single Document text summarization using Hybrid Approach
Abstract: Summarization task is a process of diminishing the size of the input text, without altering its overall meaning, by selecting only the significant parts of the input text as an output. Summary of a text can be obtained either by an abstractive approach or an extractive approach. Our system is a hybrid system (that is the combination of abstractive and extractive approach). The first stage of this system is to …
Published in Journal of Advancements in Robotics · Vol. 5, Issue 2, 2018 · pp. 15–25 Read article
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Novel Perspectives in Imitation Learning: Trends, Challenges, Future Directions
Abstract: Imitation learning refers to a machine learning approach where an algorithm learns to accomplish a task by emulating the actions and behaviours of a proficient expert. The main aim of imitation learning is to extract knowledge from an expert and train the datasets using the existing knowledge. During training, the algorithm is presented with a large dataset of expert demonstrations and learns to map the input to the correct output …
Published in Journal of Open Source Developments · Vol. 10, Issue 1, 2023 · pp. 26–35 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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A Novel Analysis of Artificial Intelligence in Mechanical Engineering Application
Abstract: In this study, we have tried to explain the crucial role of Artificial Intelligence (AI) in the running of mechanical industry. The technology used these days in the machines is to aid the solution towards the real-world problems and complex situations. Many AI algorithms have been able to provide the solution to many engineering approaches. The importance of the artificial intelligence has automatized the mechanical engineering with smart machines and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 35–38 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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Advancing EEG Technology for Affordable and Effective Epilepsy Detection
Abstract: For a proper diagnosis and prompt treatment, epilepsy, a neurological condition marked by recurring seizures, needs to be continuously monitored. Manual interpretation is frequently used in traditional approaches for identifying epileptic seizures from electroencephalogram (EEG) signals, which can be laborious and error-prone. In this research, a novel method for automatically detecting epilepsy from EEG data using deep learning algorithms is presented. According to centers for disease control and prevention (CDC) …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 11–18 Read article
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Dimensionality Reduction using Eigenfaces and Fisherfaces for Face Recognition Applications using Kernel LMS Algorithm
Abstract: AbstractFace recognition is an intricate numerical technology in computer systems that can support recognition of human faces using methods such as principal component analysis (PCA), linear discriminant analysis (LDA), etc. by comparing the given facial uniqueness with the already available face database. PCA and LDA are classical feature extraction and data representation techniques used in face recognition algorithm involving unsupervised statistical methods. The 2-D facial image can be transformed into …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 29–55 Read article
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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
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Revolutionizing Urban Traffic Management: An AI and Multi-Agent System Approach Leveraging IoT Technology
Abstract: Our study addresses the challenging issue of traffic congestion in modern urban areas and the limitations of traditional solutions like road expansion and network indicators. To effectively tackle traffic congestion, the study explores various strategies that analyze traffic elements, falling into the Macroscopic and Microscopic Models. However, conventional traffic modeling faces significant challenges in dealing with complex traffic systems.Artificial Intelligence (AI) techniques, including fuzzy logic, evolutionary algorithms, neural networks, and …
Published in Trends in Transport Engineering and Applications · Vol. 10, Issue 3, 2023 · pp. 1–8 Read article
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A Novel Approach of Gait Recognition Using LDA, PAL and Neural Network Technique
Abstract: Gait recognition is one type of biometric technology that can be used to the monitor person without their any cooperation. Controlled atmospheres for example; military installations, banks and even airports required to be able to rapidly detect threats and give differing stages of access to various customer groups. Gait presents a specific way or moving manner on the foot and gait recognition is the recognizing procedure an individual through the …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 3, 2015 · pp. 27–35 Read article
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Virtual Method to Predict Dental Disease
Abstract: The integration of technology and medicine in the healthcare domain has led to the emergence of inventive strategies to improve patient care and diagnostics. One such groundbreaking methodology is the utilization of Convolutional Neural Networks (CNNs) within the domain of deep learning, particularly for image recognition and processing tasks. In this paper, we propose a novel approach to image recognition that employs state-of-the-art deep learning algorithms to create a user-friendly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 8–15 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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A Novel Approach to Reduce Image Retrieval Problem Using Gabor Transform, Wavelet Transform and Euclidean Distance Measure
Abstract: In the processing of image, pattern recognition and computer vision, the image retrieval is a most famous research area. Our paper presents a new method in CBIR through merging the low level feature i.e. texture, color and shape features. At first, we transform the color space from RGB model to HSV model, and then extract color histogram to form color feature vector. CBIR is the process where search of image …
Published in E-Commerce for Future & Trends · Vol. 3, Issue 1, 2016 · pp. 10–15 Read article
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An Algorithm to Test Feasibility Predicate for Robotic Assemblies
Abstract: Selection of a feasible assembly sequence is an essential element to achieve cost effective manufacturing process. Test for feasibility predicate is a key segment in assembly sequence planning, which is generally carried by a skilled industrial engineer. The feasibility predicate test is involved in checking possibility of disassembling a component from the assembled product through a collision free path. To attain economic assembly process, the feasibility predicate test must also …
Published in Journal of Mechatronics and Automation · Vol. 1, Issue 2, 2014 · pp. 11–16 Read article
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An Algorithm to Test Feasibility Predicate for Robotic Assemblies
Abstract: Selection of a feasible assembly sequence is an essential element to achieve cost effective manufacturing process. Test for feasibility predicate is a key segment in assembly sequence planning, which is generally carried by a skilled industrial engineer. The feasibility predicate test is involved in checking possibility of disassembling a component from the assembled product through a collision free path. To attain economic assembly process, the feasibility predicate test must also …
Published in Trends in Mechanical Engineering & Technology · Vol. 4, Issue 2, 2014 · pp. 11–16 Read article
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A Novel Approach to Edge Detection and Performance Measurebased on the Theory of “Range” and “Bowley’s Measure ofSkewness” in a Noisy Environment
Abstract: We proposed a new edge detection algorithm in a salt and pepper noisy environment without any pre-processing. The algorithm is a simple, unique mathematical expression. It is the product of three terms: median, range and some edge image enhancement constant. The algorithm assumes that the edge exists in an image at non-zero skewness. We also proposed a performance measure technique by using “Bowley's measure of Skewness”. The coefficient of Skewness …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 8, Issue 1, 2021 · pp. 31–38 Read article
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Technology with a Human Face: Reimagining Progress through Universal Ethical Principles
Abstract: Technological progression is mostly considered as a tool of human evolution. In this digital era, however, quick novelty has revealed complex ethical gaps in the modelling and implement of technology. Technologies namely artificial intelligence, algorithmic systems, and digital surveillance progressively effect social life, economic activity, and political decision-making. While these technologies provide proficiency and progress, they also advance moral concerns connected to discretion, disparity, liability, and human dignity. The technique …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 30–36 Read article
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Novel Approach for Automated Diagnosis of Diabetic Retinopathy
Abstract: Automated and early diagnosis of diabetic retinopathy is a crucial need. Diabetic retinopathy (DR) is the major cause of blindness among people. DR is a progressive disease classified according to the presence of various clinical abnormalities. It doesn’t have any visible symptoms till the disease is at late stage. Therefore, it necessary to detect DR at early stage and to ensure proper treatment. For early detection of DR, different automated …
Published in Journal of Electronic Design Technology · Vol. 7, Issue 1, 2016 · pp. 9–13 Read article