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365 articles for “Data reduction”
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Bug Triage with Bug Data Reduction
Abstract: The process of fixing bug is bug triage, which aims to correctly assign a developer to a new bug. Software companies spend most of their cost in dealing with these bugs. To reduce time and cost of bug triaging, we present an automatic approach to predict a developer with relevant experience to solve the new coming report. In proposed approach we are doing data reduction on bug data set which …
Published in Journal of Advanced Database Management & Systems · Vol. 2, Issue 3, 2015 · pp. 1–4 Read article
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Big Data Dimensionality Reduction Technique with Deep Autoencoder
Abstract: Dimensionality reduction refers to the act of narrowing the focus from an abundance of potential variables to a more manageable set. Google created the open-source Flutter framework for creating mobile apps. The issue of high-dimensional data hindered the system's effectiveness in terms of providing correct findings (the quantity of false-positive, negative, true-positive, and negative outcomes). The process of solving a classification problem, carrying out a precise visualization, and transmitting vast …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 2, 2023 · pp. 1–13 Read article
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Experimental Exploration of Crack and Damage Dynamics of Hybrid FRP Nano Composites
Abstract: Fiber-reinforced polymer (FRP) composites have become essential materials in modern engineering structures because of their excellent strength-to-weight ratio, corrosion resistance, and adaptability in design. Among different fracture modes, Mode I interlaminar fracture where cracks propagate under tensile opening stresses is one of the most critical forms of damage in layered composites. Since delamination occurs within the matrix-rich regions between plies, improving the matrix properties plays a key role in enhancing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 220–232 Read article
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Class Imbalance Reduction and Training Data Selection for Cross Project Defect Prediction
Abstract: The research aims to predict errors in a targeted project using data from other projects. This project is named as the Cross-Project Defect Prediction (CPDP). There are a number of ways available to improve the predictable performance of CPDP models. However, there is no comparison of modern methods. Predictability facilitates the rational distribution of testing resources by detecting software modules that may be problematic before releasing products. If a project …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 9, Issue 3, 2022 · pp. 12–20 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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Challenges and Opportunities in Spatio Temporal Data Analysis
Abstract: Spatiotemporal data analytics is a dynamic field that seeks to extract valuable information from data that integrates both spatial and temporal dimensions. This article explores the importance of this emerging field and its applications in a variety of fields, including environmental science, public health, and urban planning. Spatiotemporal data analysis addresses important research questions, such as determining event probabilities, understanding change patterns, identifying associations between events, and predicting events Future. …
Published in Journal of Remote Sensing & GIS · Vol. 14, Issue 2, 2023 · pp. 1–11 Read article
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Hierarchical Methodology Approach to SOC Design: A Comprehensive Look
Abstract: The design scale of a chip has increased many folds in the last few years and shows a continuous exponential trend. This is made possible by the reduction in transistor size and an evolving process technology. As a result, it is possible to move to SoC technology (System on Chip-A single die consisting of multiple subsystems) rather than a traditional ASIC. This has obviously resulted in an increase in the …
Published in Journal of VLSI Design Tools and Technology · Vol. 10, Issue 3, 2020 · pp. 35–42 Read article
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A PCA Based K-Means Clustering Algorithm for Wireless Sensor Nodes
Abstract: This paper presents a novel and improved approach for K-Means Clustering of wireless sensor networks, by using Principal Component Analysis for data reduction on the raw data. A wireless sensor network consisting of 100 nodes is classified into three different clusters using PCA based K-Means Algorithm. Davies-Bouldin Index is used as a parameter to check the effectiveness of the clustering algorithm. Experimental results demonstrate that the PCA based K-Means Algorithm …
Published in Journal of Web Engineering & Technology · Vol. 2, Issue 2, 2015 · pp. 6–10 Read article
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Recent Strategies for Bug Triaging Techniques
Abstract: Nowadays, there are many emerging software companies. As they develop software, they have to deal with large number of software bugs. It is well expensive and unavoidable too so these bugs are needed to be fixed. The bug triaging process is nothing but to assign effective and proper developer for bug fixing. There are various techniques are used for this process earlier. Human triaging was not a time worth process …
Published in Journal of Advanced Database Management & Systems · Vol. 7, Issue 1, 2020 · pp. 23–26 Read article
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Optimization of Production Processes to Minimize Waste and Improve Efficiency in Automobile Servicing Plant Using Lean Six Sigma
Abstract: This study focuses on optimizing production processes within an automobile servicing plant to minimize waste and enhance efficiency through the application of lean six sigma (LSS) methodologies. Utilizing a case study approach, the research addresses real-time challenges related to productivity and waste reduction. Data collection involves assessing machine functionality metrics, material and labor flow at various stages of the servicing process. The optimization strategy integrates lean tools including value stream …
Published in International Journal of Manufacturing and Production Engineering · Vol. 2, Issue 2, 2024 · pp. 47–63 Read article
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The Role of Surface Treatments on Mechanical and Interfacial Shear Strength of Pineapple Leaf Fibers
Abstract: Natural fibers are seen as having potential application as reinforcing agents in polymer composite materials due to their main advantages, which include moderate strength and stiffness, low cost, and being an environmentally beneficial, degradable, and renewable material. They are susceptible to absorbing moisture because of their innate hydrophilicity, which can weaken or plasticize the adherence of the fibers to the surrounding matrix and impact the performance of composite materials employed …
Published in Journal of Materials & Metallurgical Engineering · Vol. 12, Issue 3, 2022 · pp. 18–28 Read article
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An Improved Power Line Interference Reduction Approach Based on Combination of Mirror Extension and IIR filtering Through a Data Driven Mechanism
Abstract: Electrocardiogram (ECG) is a clinical sign monitoring measurement of the cardiac abnormalities. Like other biomedical signals, the ECG signal is also contaminated by various kinds of noise and artifacts such as power line interference, base line wandering, muscle artifacts and electrode artifacts. The present paper proposes a scheme for power line interference (PLI) reduction from ECG signal. It makes use of the concept of mirror method, empirical mode decomposition (EMD) …
Published in Current Trends in Signal Processing · Vol. 7, Issue 2, 2017 · pp. 13–21 Read article
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Applications of AI: Does it Impact Emissions of Carbon?
Abstract: Several countries, including India, have vowed to achieve net-zero emissions by the middle of the century, in line with the Paris Agreement's goals. India, as one of the world's largest and fastest-growing economies and the third-largest carbon emitter, has set lofty goals in its climate change plan. By 2030, India intends to attain carbon peaking, which represents the top of its carbon emissions before beginning a slow drop. Furthermore, the …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 27–31 Read article
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Implementing and Analyzing Network Commands in Cloud and Edge Computing Environments with Cisco Simulators
Abstract: The present review examines edge and cloud topologies and compares them according to latency. Instead of using distant data centers like cloud computing platforms, edge computing designs process data physically close to the source. Increased demand for Internet of Things (IoT) devices, which are growing more concerned with real-time data processing and analysis, has fueled the expansion of edge computing and cloud computing. In essence, each of these designs offers …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 62–69 Read article
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Enhancing Cybercrime Detection Through Big Data Analytics: A Conceptual Framework
Abstract: The growing complexity of cybercrime reduction and prevention difficulties necessitates a different approach to dealing with the massive amounts of data involved. The issues of reducing and preventing cybercrime are becoming more complex as cybercrime becomes ingrained in our daily lives. When it comes to showcasing the original division of criminal activities, traditional police operations typically fall short, which means they contribute less to the right deployment of police resources. …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 1–11 Read article
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Knowledge discovery in software defect datasets using learning algorithms
Abstract: In this paper, the learning impact on various classification models were studied which were built using binary class-imbalanced data. Before the learning process, some preprocessing techniques were applied to training datasets for removing the redundancy. Nowadays feature selection and sampling techniques become an essential tool for many data mining task because learning algorithms do not perform well with defective datasets, dimensionality reduction problem arises. Sampling technique is also used to …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 2, 2018 · pp. 18–26 Read article
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Dimensionality Reduction: A Brief Survey on Its Myriad Techniques
Abstract: This paper is a short survey and analysis on different techniques and methods using which efficiency of existing techniques can be improved which are used for data exploration, or search for those features which has deeper relationship amongst the variable, which relies on greater extent on visual methods. However, for multidimensional data set with real time data collected captured using sensors or real time applications, redundant and unused or wanted …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 6, Issue 2, 2017 · pp. 46–51 Read article
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Analysis of The Performance of A PV/PCM System in Variable Solar Radiation Conditions
Abstract: This paper studies the performance of a PV/PCM system operating at variable solar radiation conditions. The system has been tested for six different solar radiation levels, from 250 W/m2 to 950 W/m2 determining the steady-state temperature for every case. An algorithm has been developed to predict the steady-state temperature. This prediction has produced values within 97% accuracy of experimental data. A reduction of temperature up to 18.9ºC has been achieved. …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 12, Issue 1, 2021 · pp. 1–20 Read article
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Matrix Factorization and Tensor Decomposition at Scale: Mathematical Foundations and Computational Approaches
Abstract: Matrix factorization and tensor decomposition techniques have emerged as fundamental tools in machine learning and data science for handling high dimensional data efficiently. This paper presents a comprehensive analysis of scalable matrix factorization and tensor decomposition methods, focusing on their mathematical foundations, computational complexity, and practical applications. We examine key algorithms including Singular Value Decomposition (SVD), Non-negative Matrix Factorization (NMF), CP decomposition, and Tucker decomposition, with particular emphasis on their …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 56–59 Read article
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An Investigation on Influence of Gamma-Irradiation and Doping on Chemical Structures and Optical Properties of Conducting Polypyrrole
Abstract: In this study, the authors report on effect of gamma-irradiation and doping (bromine, iodine and sulfate ion) on chemical structure and optical, electronic properties of polypyrrole. Optical absorption spectrum of PPY shown absorption bands centered around 36.2.5 nm (peak 1), 450 nm (peak 2) and 525 nm (peak 3) positions. Gamma irradiation resulted in broadening of peak A together with a band shift of 45–525 nm and disappearance peaks 2 …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 · pp. 48–57 Read article