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147 articles for “Logistics”
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Machine Learning Approaches Towards Resume Classification
Abstract: Finding the right person for an open position can be an unnerving task, especially when there are many applicants, and if the recruiter or the Human Resources department must sort and further categorize all those resumes then it will be a labor-intensive, time-consuming, and tiresome task. Additionally, human assessment of resumes may be biased and prone to mistakes. Manually screening the proper candidate's resume from the pool is not practicable; …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 1–7 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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Marine Fleet And Container Transportation In Marine Terminals And Its Effect On Increasing Products
Abstract: The advancement of technology has made sea container terminals become complex infrastructures to manage, so this should be studied and investigated by analysts and transportation experts through improving the efficiency and performance of the container terminal. However, the large number and variety of logistical activities gathered together is a major obstacle to effective decision-making processes. In most cases, logistic processes in this field are considered as NP-hard problems. In addition, …
Published in Journal of Materials & Metallurgical Engineering · Vol. 14, Issue 2, 2024 · pp. 21–27 Read article
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The Futuristic Outlook of E-Commerce in India
Abstract: In the past ten years, India has witnessed extraordinary growth in e-commerce, which can be attributed to the proliferation of smartphones, the growing middle class, and the increasing number of people who have access to the internet. The retail scene has been revolutionized by major firms such as Amazon and Flipkart, as well as growing local platforms, which offer a diverse range of items and services. A further acceleration of …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 3, 2024 · pp. 1–10 Read article
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Comparative Analysis of Heart Disease Prediction System
Abstract: In the present world, where heart illnesses are on the rise, it is crucial to forecast these diseases. Performing the task on heart disease is a bit difficult and it must be finished precisely and successfully. Heart disease identification relies heavily on Machine Learning (ML) and data mining approaches. The primary focus of the review paper is that patients are easily prone to cardiac diseases depending on medical traits. Using …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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Optimization of Robotic Path Planning Algorithms for Autonomous Material Handling Systems
Abstract: For autonomous systems for handling materials (AMHS) to operate as efficiently as possible in industrial and logistical settings, robotic route planning is essential. This study examines many robotic route planning algorithms, emphasizing their use, ways of optimization, and difficulties in material handling systems. To improve the effectiveness, precision, and computational viability of these algorithms, the study also examines a number of optimization strategies, including machine learning, parallelization, heuristic search, and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 15–20 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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Comparative Study of Machine Learning Algorithms for Detection of Breast Cancer
Abstract: Breast cancer continues to be the most commonly diagnosed cancer among women, with more than 2.3 million new cases diagnosed yearly worldwide. It is stated as the leading cause of cancer-related deaths. Therefore, this emphasizes the dire necessity for early diagnosis with a view to improving survival. Early diagnosis elevates the effectiveness of prediction and treatment. This research carries out a structured and analytical evaluation of various machine learning algorithms, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 113–129 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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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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NutriHeart with Chatbot
Abstract: Heart disease stands as one of the world's principal reasons for human deaths since it causes major preventable fatalities each year. Healthcare institutions currently explore machine learning (ML) integration for establishing new approaches toward predicting, and acting ahead of healthcare developments. NutriHeart presents an AI-based platform that accomplishes cardiovascular risk detection early and extends heart wellness by delivering customized nutritional and lifestyle recommendations. Using Support Vector Machines (SVM) along with …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 22–34 Read article
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A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Determinants of the Adoption of chemical Fertilizer in Kaffa, Bench Sheko and Sheka zones of Southwest Ethiopia
Abstract: Agriculture is the backbone of the Ethiopian economy, but the production system was backward, and the adoption of agricultural technology was low. This study aims to identify and determine factors affecting smallholder farmers' adoption of chemical fertilizer. Bita, Chena, Andiracha, and Sheyi Bench district of the southwest Ethiopia region was selected for this study. Household individual survey interview, key informant interview, and focus group discussion were the primary data collection …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 1–12 Read article
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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
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Sustainable Waste Management through Polymer Recycling: A Review of Business Model and Managerial Innovation
Abstract: Plastic and other polymeric materials have transformed modern life by providing durability, versatility, and cost-effective solutions across industries such as packaging, healthcare, construction, and transportation. However, their extensive use and improper disposal have created significant environmental concerns, including plastic pollution, landfill accumulation, and marine ecosystem degradation. This review synthesizes existing literature on polymer recycling with a focus on business-model innovation and managerial practices that can support sustainable waste management at …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 155–166 Read article
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Explainable Machine Learning Integrated with Polymer-Based Diagnostic Technologies for Liver Health Classification
Abstract: Early and reliable assessment of liver health is essential for timely treatment, yet most machine-learning approaches face limitations such as class imbalance and low clinical interpretability. This study proposes a polymer-integrated, explainable machine-learning framework that combines SMOTE-based data balancing, Logistic Regression, and XAI techniques (SHAP and LIME) for transparent liver-health classification. In addition to ML modelling, the study emphasizes the emerging role of polymer-based biosensors, microfluidic polymer chips, polymer nanomaterials, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 631–643 Read article
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Drona-Chariot: A Medical Equipment Carrier Drone
Abstract: Caring for trauma victims in harsh environments poses numerous difficulties, especially when a rescue effort is delayed. Human-containable medical equipment may also be consumed by a single victim, making replenishment impossible prior to evacuation, especially in long-term on-site supply scenarios. This project aims to build an unmanned autonomous aerial vehicle that successfully delivers remote places with life-sustaining medical supplies where it is impossible or impractical for vehicles or pedestrians to …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 1, 2023 · pp. 7–14 Read article
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Heart Attack Prediction Using Machine Learning
Abstract: Heart attacks have become a prevalent and serious condition in recent years due to a variety of causes. Numerous variables, including age, sex, fat, and others, can be used to predict it. In the current study, it was found that a data set with 13 parameters and 302 distinct data values, collected from a Kaggle dataset to assess patient condition, was covered. This article delves into the application of machine …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Credit Card Fraud Detection Using Machine Learning Techniques
Abstract: Credit card fraud has become a significant concern in today's digital economy, with billions of dollars being lost annually to fraudulent transactions. Conventional rule-based approaches frequently prove inadequate in addressing the constantly changing strategies employed by fraudsters. Machine learning methods have emerged as robust solutions for detecting credit card fraud, presenting the capability to accurately identify fraudulent transactions promptly. In this study, we investigate the efficiency of three widely used …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 1–7 Read article
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Regulatory Requirements for Pharmaceutical Product Registration in Zambia
Abstract: There is a significant burden of diseases in Zambia and its neighboring countries, such as malaria, HIV/AIDS, and other ailments. These health challenges necessitate a high consumption of pharmaceutical products. Currently, the majority of essential health drugs in Zambia are imported from outside of Africa. This reliance on external sources presents an opportunity for new investments in the local manufacturing of pharmaceutical products. Although Zambia may not be the largest …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 2, 2024 · pp. 33–41 Read article