Search
52 articles for “K-means algorithm”
-
Implementation of Data Mining Approach to Find the Adaptability of Students in Online Education during Covid-19 Pandemic
Abstract: The global Covid-19 pandemic has severely affected very aspects of human life, including education. The virus' stunning spread created havoc in the educational system, causing educational institutions to close. As an effect, students must quickly adopt to the change to synchronous online learning. This study identified the different aspects affecting the adaptability level of students in online class. It also identifies the student’s adaptability level in different circumstances in online …
Published in Journal of Artificial Intelligence Research & Advances Read article
-
Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 Read article
-
Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
-
CHROMAWEAR: An AI Assisted Personalized Fashion Design Recommender System for Diverse Skin Tones to Enhance Fashion Choices
Abstract: In the age of fashion, we receive the same question every day: What should I wear today to look nice? The fashion industry is always changing, welcoming inclusivity and diversity. Still, despite the advancements, there are difficulties meeting people's varied needs, especially with regard to skin tone. This research work presents a personalized fashion design recommender system with artificial intelligence support to improve the fashion choices of people with different …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 49–58 Read article
-
Monitoring of Unauthorized Identity and Access Behaviour for Outsourced Data in Cloud Environment
Abstract: The outsourcing of data is a significant challenge in the modern cloud computing ecosystem when it comes to tracking unauthorized identification and access behaviour. In order to overcome this issue, this research suggests a thorough method for reliable anomaly detection in cloud systems. Improving data security and offering a trustworthy monitoring system are the two main goals. The suggested approach proceeds methodically, gathering information from several sources such as user …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 9–19 Read article
-
Face And Spoofing Detection Via Genetic Algorithm-Based Feature Selection with MTCNN
Abstract: Face detection and liveness detection in various environments such as different lighting effects, occlusion, complex backgrounds, and different poses and angles play an important role in facial recognition or detection purposes. In this research paper, propose an improved algorithm for face detection and liveness, spoofing detection via genetic algorithm for feature selection, and mtcc detecting the edge of the facial image by Canny filter and spotting the face from the …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 1, 2025 · pp. 17–26 Read article
-
Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article
-
Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
-
The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments
Abstract: The novel approach that this work discusses is a DCD-based iterative learning filter approach improved with deep learning methodologies, designed to improve the efficiency of acoustic echo cancellation. The proposed system can really manage both linear and nonlinear echo scenarios, dynamically adapting to fluctuating acoustic environments. The above comparative evaluations with standard filter, the standard RLS filter, indicate that the mean square error, and the standard deviation of the correlation …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 9–24 Read article
-
Artificial Intelligence in Image Recognition: Context of Machine Vision
Abstract: The machine learning discipline is as old as decades, but some problems such as image recognition, location detection, image classification, image generation, speech recognition, and natural language processing cannot be solved. Image classification studies are another basic, most classic and essential line of research in deep learning. Computer intelligent recognition of the images technology has enabled a gradual reaction (updating) to foreign measurement trends, which promotes advancement of different areas …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 01–06 Read article
-
Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
-
Country Cluster Visualization Based on Agricultural Imports: Unsupervised Learning Approach
Abstract: The clustering algorithm used in this analysis makes it easier for policymakers to understand performance metrics. K-means clustering has been demonstrated to be a tool for analyzing countries' agricultural imports and a visualization tool for interpreting the results in this study. Authors have used agricultural imports from 190 nations from Knoema, a web-based open data platform. Cereals, meat, and coffee imports from 190 nations in 2016 are included in the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 1–7 Read article
-
From Oral to Virtual: The Evolution of Storytelling
Abstract: Storytelling, a timeless art of expressing ideas and emotions, has experienced a revolutionary transformation in the digital era. The emergence of digital platforms like social media, streaming services, podcasts, and interactive apps has completely transformed how stories are created, shared, and experienced. This modern age is marked by accessibility, interactivity, and multimedia convergence, allowing storytellers to reach world audiences in unprecedented fashion. With the advent of the digital era, stories …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
-
Exploring the Efficiency of Leading and Lagging Indicators in Algorithmic Trading
Abstract: This paper details a comparison of the overall performance of leading and lagging technical indicators used in algorithmic trading over an extended period. While much of the prior research focuses on index price forecasting and some on statistical arbitrage derived from these predictive techniques, there is a scarcity of studies that assess and evaluate trading strategies. The strategies considered for the study were tested on historical data of the 50 …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 8–18 Read article
-
Modelling and Performance Evaluation of a Multiport Converter for Active Balancing of Lithium- ion Battery Cells
Abstract: In this paper, a flexible multiport DC-DC converter-based active cell balancing technique for Li-ion battery packs is presented. Cell balancing plays an important role in terms of safety, capacity utilization, and battery lifespan. For Li-ion cells in series configuration, the difference in voltages and states of charge (SOCs) leads to imbalance issues which might negatively affect their performance and shorten their lifespan. To solve these problems, the proposed technique utilizes …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 2, 2026 Read article
-
Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
-
Baggage Detection and Recognition Using Local Tri-Directional Pattern
Abstract: Nowadays, pattern-based image retrieval algorithms are gaining popularity just because of their uniqueness. There are several issues in the previously proposed systems. The proposed system resolves issues highlighted in the literature. Our proposed system is tested on two image datasets ILIDS and PETS 2006. LTDP provides good results as compared to LBP in baggage detection on two classes that either bag is present or not in an image because LTDP …
Published in International Journal of Mobile Computing Technology · Vol. 1, Issue 1, 2023 · pp. 8–17 Read article
-
Enhancing Energy Storage and Optimization of Distributed Energy Resources Using a Hybrid SWOA-MSNN Approach
Abstract: The fast growth of Distributed Energy Resources (DERs) like solar photovoltaics, wind power, and energy storage devices requires enhanced optimization methods to manage energy efficiently and stabilize operations in contemporary smart grids. A significant challenge is the dynamic optimization of the energy storage systems (ESS) and the distribution of the energy among DERs in conditions of uncertainty of loads and generation. The conventional control and optimization methods generally find it …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
-
VHDL-Based Strategies for Protecting IoT Devices from Power and Electromagnetic Side-Channel Attacks: A Study
Abstract: The environment of the Internet of Things (IoT) is rapidly developing, linking billions of devices across a wide variety of disciplines. Furthermore, despite the fact that it provides an unprecedented level of convenience and efficiency, this interconnection also presents a fertile ground for security weaknesses. Side-channel attacks, also known as SCAs, are one of the dangers that pose a considerable risk. These attacks specifically target the cryptographic implementations that are …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 30–40 Read article
-
Investigative Study of Adaptive Fault Tolerance in Optical Networks
Abstract: Optical networks have become the backbone of modern telecommunications infrastructure, enabling high-speed data transmission across global networks. However, these networks face significant reliability challenges due to component failures, signal degradation, and environmental factors. This investigative study examines adaptive fault tolerance mechanisms in optical networks, focusing on emerging technologies and methodologies that enhance network resilience. The research analyzes various fault detection techniques, including machine learning-based approaches, self-healing protocols, and dynamic reconfiguration …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 2, 2025 · pp. 24–30 Read article