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30 articles for “X tree”
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A Proposed Hybrid Spatial Indexing: QX Tree
Abstract: Out of different spatial indexing structures available for accessing spatial data, none of them is suitable for high dimensions. This is because the performance of the spatial indexing structures become poorer with the increase in dimension. Thus there is a need for a better spatial indexing structure for the same. Here we have proposed a hybrid indexing structure by combining the Quad Tree and X Tree. We have considered the …
Published in Recent Trends in Programming languages · Vol. 2, Issue 1, 2015 · pp. 23–27 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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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 10–20 Read article
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Detection of Phishing Website URLs and Email/SMS Using Random Forest and Multinomial Naive Bayes
Abstract: Currently, phishing attacks via SMS/email and URL have become significant threat to cybersecurity, posing risks to both individuals and organizations alike. Phishing attacks typically involve the creation of fraudulent websites or the dissemination of deceptive emails and SMS messages to trick users into disclosing sensitive information such as passwords, credit card numbers or personal details. To respond to these attacks, we develop a robust system for the detection of phishing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 22–30 Read article
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Tweets Classification using Different Classifiers for Sentiment Analysis
Abstract: Twitter is a famous platform for social networking where people share and engage with "tweets" comments. It is a way of expressing people's opinions or emotions on various topics. Different parties, like producers and consumers, have carried out a sentiment analysis on tweets to gain insights into goods or to analyze the sector. Also, the accuracy of our sentiment analysis forecasts will increase with the recent advances in machine learning …
Published in Research & Reviews : Journal of Statistics · Vol. 10, Issue 3, 2021 · pp. 34–43 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Early Autism Diagnosis: Machine Learning Models and Their Effectiveness
Abstract: Diagnosis is of utmost importance for timely intervention and support. However, traditional diagnosis methods, which are based on subjective assessment, are delayed. This project explores the role that machine learning techniques might play in enhancing the accuracy and effectiveness of ASD detection. Several state-of-the-art classification algorithms were benchmarked using a dataset from Kaggle. Logistic Regression, XG Boost, Random Forest, Decision Tree, and Gradient Boosting were taken into consideration. Other performance …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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Effect of Slope on Estimating Tree Biomass using Satellite Data in Belasitsa Mountain Forest, Bulgaria
Abstract: 800x600 Remote sensing of above ground tree biomass (AGTB) in rugged and mountainous forest sites incurs uncertainties in accuracy due to the influences of various bio-physical and topographic factors. Particularly slope is an important factor affecting the accuracy of remote sensing AGTB. This study investigates how slope affects the estimation of above ground tree biomass using vegetation indices (VIs) calculated from an ASTER image in the Belasitsa Mountain forest in …
Published in Journal of Remote Sensing & GIS · Vol. 5, Issue 3, 2014 · pp. 17–30 Read article
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Cyber-Security Evaluation for a Hypothetical Nuclear Power Plant using the Attack Tree Method
Abstract: The widespread introduction of digital network systems in nuclear power plants has increased such infrastructures vulnerability to cyber-attacks. The attack tree approach to evaluate and analyze cyber-attacks quantitatively, in a nuclear power plants' network system is presented in this work. Information on a hypothetical nuclear power plants' network system was used to build attack trees that show different attack paths that external adversaries can use to compromise the network system. …
Published in Journal of Nuclear Engineering & Technology · Vol. 4, Issue 3, 2014 · pp. 1–14 Read article
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Optimizing Heart Disease Prediction: Comparative Analysis of Machine Learning Algorithm for Early Detection
Abstract: The expanding realm of data analysis holds considerable importance in healthcare, particularly in the medical sector where forecasting heart disease is considered a complex endeavor. Early prediction of serious health conditions can be the determining factor between survival and fatality, with heart disease being one such critical health issue. Over the past decade, the main reason for death has been heart disease. Heart disorders come in many different forms, and …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Effect of Image Band Number and Band Multicollinearity on Mapping Accuracy of Tree Diversity and Evenness
Abstract: 800x600 Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Satellite imageries are increasingly being used in the studies of plant diversity due to cost effective wider spatial coverage. Multispectral or hyperspectral imageries consist of different spectral bands where some bands might be multicollineared among them and deemed redundant to use in the classification/analysis. This study investigates how the accuracies of maps of tree diversity and evenness of an area …
Published in Journal of Remote Sensing & GIS · Vol. 4, Issue 2, 2013 · pp. 14–22 Read article
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Contra Harmonic Mean Labeling for Some Tree and Corona Related Graphs
Abstract: AbstractA graph G (V,E) is called a Contra Harmonic mean graph with p vertices and q edges, if it is possible to label the vertices xÎV with distinct element f(x) from 0, 1,…,q in such a way that when each edge e = uv is labeled with f(e=uv) = 16f(u)2+f(v)2f(u)+f(v)"> or 16f(u)2+f(v)2f(u)+f(v)"> with distinct edge labels. The mapping f is called Contra Harmonic mean labeling of G. Keywords: Graph, Contra …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 6, Issue 2, 2019 · pp. 24–29 Read article
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Applying the XML-based Technique to Support Keyword Search in Graph Data
Abstract: Graphs have been important and proper structures to represent data with complex relationships in the Web, and keyword search provides a convenient way to querying graphs. Some researchers considered to return r-cliques as answers for keyword search in graph databases. Such concepts can retrieve meaningful information effectively, but the existing approach is computationally expensive. In this paper, we propose to utilize the efficient technique originally designed for keyword search in …
Published in Journal of Advanced Database Management & Systems · Vol. 1, Issue 2, 2014 · pp. 25–32 Read article
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Measuring Tree Diversity of Sitaram Peth Village of Bhadravati Taluka of Chandrapur District by Applying Whittaker’s Additive Model
Abstract: Forest plays a major role for sustaining biodiversity and various ecological services. There are 12 tribal districts in the Maharashtra state, which holds about 60 percent of total forest cover of the state. And among these tribal districts, Chandrapur and Gadchiroli together shares about 46 percent of forest cover. For the better conservation and management practices, the tree diversity of these forest should be measured periodically. In the present study, …
Published in Research & Reviews : Journal of Ecology · Vol. 14, Issue 2, 2025 · pp. 49–54 Read article
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IoT-enhanced Extensible Messaging Presence Protocol: A Multiple Multicast Architecture for Diverse Applications
Abstract: Extensible Messaging Presence Protocol (XMPP) is a real-time information transmission specification protocol based on IP technology and XML supporting publish/subscribe messaging systems. Publishers use multicast to send data simultaneously to multiple subscribers. IoT devices benefit enormously by using XMPP Extension Protocols (XEPs) available in the literature that enables using XMPP for multicast. Publishers are considering Multiple Multicast (MMC) to address subscriber overlap while sending messages to multiple subscribers simultaneously. This …
Published in Journal of Advances in Shell Programming · Vol. 10, Issue 2, 2023 · pp. 1–13 Read article
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Comparison of Models of Machine Learning and Hyperparameter Optimization Methods on Various Datasets
Abstract: The most likely phase in achieving powerful and robust machine learning models is probably the hyperparameter tuning step. The traditional exhaustive methods of search (grid search and others) ensure that the search space is covered, but are computationally inexpensive; random search is less expensive and can still miss good regions; and lastly, the modern model-based and population-based methods (Bayesian optimization, tree-structured Parzen estimator (TPE), genetic algorithms) are thought to provide …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 · pp. 35–42 Read article
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A Comparison Between Two Association Rule Mining Techniques
Abstract: Normal 0 false false false EN-US X-NONE X-NONE Data mining requires associated items to be mined from given transactions. Association rule mining (ARM) has gained importance in view of trend-prediction and decision-making process. Mostly ARM is implemented using variants of FP tree growth techniques. This paper introduces an improved technique for ARM – Improved Relative Dotted Sequence Path (IRDSP)-based ARM. The logic justifying why this technique saves time in comparison …
Published in Current Trends in Information Technology · Vol. 1, Issue 2-3, 2011 · pp. 1–7 Read article