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441 articles for “dataset”
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Monitoring System for Students During Online Exams
Abstract: Remote learning has taken residence owing to the effect of COVID-19. Despite the details and many educational institutes were compulsory to close, students were able to complete their degrees using online platforms. Exams, on the other hand, remain unsolved. It’s been modified to a copy-and-paste assignment form for around, while others have just canceled them. If our current lifestyle is to become the new standard, there necessity to be a …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 22–29 Read article
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Artificial Intelligence in Drug Repurposing: A Short Impact Assessment
Abstract: Artificial intelligence (AI) in pharmaceutical repurposing has become a game-changing tool that opens new avenues for the application of new drugs that have already been approved. Traditional drug discovery is a lengthy and expensive process, whereas AI can rapidly analyze vast datasets of biological, chemical, and clinical information to predict drug-disease interactions. AI-driven techniques, such as machine learning, natural language processing, and deep learning, enable the identification of potential repurposing …
Published in Trends in Drug Delivery · Vol. 11, Issue 3, 2024 · pp. 42–45 Read article
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Cyberattack Detection and Prevention Using Empowering AI Tools
Abstract: With more organizations entering the digital transformation sphere, the opportunities and risks in cyberspace have increased and gone up in levels of sophistication and occurrence. Many of these developments are attributed to the limits of existing cyber security solutions where addressing new threats requires advanced detection technologies and techniques. Cyber threats gained a new meaning and dimension with artificial intelligence (AI) coming into play in ways that supplement security systems …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Algorithmic Strategies for Complex Data Handling: Optimizing Data Structures for Enhanced Computational Performance
Abstract: We live in an age of big data and processing very large often complicated datasets can be crucial to efficient algorithmic performance. This paper discusses different algorithmic techniques when working with difficult data and how to arrange your information structures correctly for better functionality in large-scale methods. It checks the impact of different algorithms like sorting, searching, and hashing in boosting its processing speed as well as memory use. This …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 1–10 Read article
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The Role of Bioinformatics in Nursing: Transforming Healthcare through Data-Driven Insights
Abstract: Bioinformatics, an interdisciplinary field combining biology, computer science, and information technology, is increasingly shaping the nursing profession. It offers powerful tools for improving patient care, advancing clinical research, and enabling personalized healthcare through data-driven decision-making. This article examines the integration of bioinformatics into nursing practice, tracing its historical roots from the Human Genome Project to its current applications in genomic medicine, precision healthcare, and population health. Nurses now play a …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 18–21 Read article
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Glitches in the Implementation of Bioinformatics in Medical Settings: A Comprehensive Review
Abstract: Bioinformatics is a dynamic field at the intersection of biology, computer science, and information technology, offering new possibilities in medicine by enabling a deeper understanding of genomics, molecular biology, and personalized treatment approaches. Its integration into healthcare could greatly enhance diagnostics, enable tailored treatments for individuals, and facilitate the analysis of large biological datasets. However, despite its potential, several barriers impede its successful implementation in clinical settings. These include technical …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–6 Read article
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The Analysis of Deep Learning-Based Methods for Identifying Diabetic Retinopathy
Abstract: Diabetic retinopathy (DR) is a degenerative eye condition resulting from diabetes mellitus, where high blood glucose levels lead to lesions on the retina. This condition is considered the leading cause of blindness among working-age diabetic patients, particularly in developing countries. As the disease is irreversible, the treatment aims to preserve the patient’s current vision. Early detection is crucial for effective management of DR to maintain vision. One of the main …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 15–31 Read article
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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 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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Exhaustive Search Meets DNA Sequencing: A Comprehensive Review of TSP-Based Approaches
Abstract: Exhaustive search is a highly computational complex algorithm that checks every possibility to obtain the best solution. We illustrate an exhaustive search by applying it to three important problems: the traveling salesman problem, the knapsack problem, and the assignment problem. In this paper, we took a traveling salesman problem to explain DNA Sequencing. Since traveling salesman problem is an algorithmic problem that finds the shortest route between a set of …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 2, 2024 · pp. 11–21 Read article
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Advances in Smart Cradle Design: Automation and Monitoring Systems for Infant Care
Abstract: With the hectic schedules of working parents currently, raising a baby has become difficult. The arduous juggling between career obligations and childcare responsibilities can strain the very limits of human capacity. The choices have historically been to entrust the child's care to either senior family members or hiring a dedicated infant carer in situations like these, where time's unrelenting passage leaves little time for a full 24-hour commitment to the …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 2, 2024 · pp. 34–43 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Size-biased Sujatha Distribution with Properties and Application to Model Flood Data
Abstract: In this study, a size-biased version of the Sujatha distribution was proposed to model flood data. The descriptive statistical properties based on moments and the reliability properties of the distribution are discussed in detail along with their derivation and graphical presentation. An interesting feature of the proposed distribution is that it is a member of the exponential family of distributions. A sequential probability ratio test was performed using the proposed …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 1, 2024 · pp. 31–46 Read article
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AI-Driven Innovation in Biomaterials: Predictive Modeling and Design for the Future
Abstract: The integration of artificial intelligence (AI) is revolutionizing the field of biomaterials, paving the way for innovative approaches in their development and production. This paper examines the connection between AI and biomaterials, emphasizing the substantial impact of predictive modeling on the evolution of the field. By examining recent research and cutting-edge uses, the document shows how AI-powered predictive modeling has revolutionized biomaterial design, marking a period of unparalleled precision and …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 25–35 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services
Abstract: The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 1–14 Read article
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Advanced Anomaly Detection in Cloud Infrastructures Using Deep Learning Algorithms
Abstract: It is critical to guarantee the stability and security of cloud environments as cloud computing is becoming the backbone of contemporary IT infrastructures. Neglecting to quickly identify and resolve anomalies, which might point to security breaches, performance problems, or system breakdowns, can lead to disastrous outcomes. The increasing size and complexity of cloud infrastructures are challenging the effectiveness of traditional anomaly detection methods. These approaches often depend on rule-based systems …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 1–11 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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The Intersection of Bioinformatics and Cellular Function in Disease Modeling
Abstract: The integration of bioinformatics and cellular biology has revolutionized our understanding of disease mechanisms, offering unprecedented opportunities to model complex biological systems. Bioinformatics is an interdisciplinary field that merges biology, computer science, and statistics, offering advanced tools to analyze vast biological datasets. Cellular functions, including gene expression, protein interactions, and metabolic pathways, form the foundation of physiological and pathological states. Disruptions in these processes can result in diseases like cancer, …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article