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647 articles for “data” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
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Counter Terrorism Prediction and Risk Evaluation (C-TRIP)
Abstract: The global landscape in the 21st century is marked by complex and evolving security challenges, none more pressing than the threat of terrorism. Acts of terror have left a profound impact on societies, economies, and governments worldwide, underscoring the critical importance of effective counter terrorism strategies. The “Counter Terrorism Prediction and Risk Evaluation (C-TRIP)” represents a significant stride in addressing this ever-pressing challenge. In a time marked by global security …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 14–24 Read article
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IP Transcendence: Unifying IPv6 Over IPv4 Network
Abstract: Dynamic routing also called adaptive routing like traditional glass optical fiber, POF uses a polymethyl methacrylate (PMMA) core with a fluorinated polymer cladding, resulting in a larger core diameter that simplifies alignment and splicing. POF's adaptability is one of its main benefits. Because of their fragility and stiffness, ordinary glass fibers would not be practicable in certain situations where POF can be put. POF is a great option for intricate …
Published in International Journal of Electrical Power and Machine Systems · Vol. 2, Issue 1, 2024 · pp. 36–42 Read article
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Efficient Malware Detection in Cybersecurity: Leveraging Advanced Data Structures for Enhanced Threat Identification
Abstract: The cybersecurity landscape is constantly changing with more advanced malware creating major challenges for detection systems. To address these challenges effectively, advanced data structures have become essential in optimizing how data is managed, processed, and analyzed for malware detection. This review paper delves into the role of several cutting-edge data structures—bloom filters, tries, hash tables, graphs, decision trees, and suffix trees—in enhancing the efficiency and accuracy of malware detection mechanisms. …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 32–40 Read article
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Collaborative Approaches in Using Satellite Data for Climate Action: A study
Abstract: As climate change continues to threaten coastal towns in many ways, satellite sensing has become an increasingly important tool for assessing and managing risk. This technology could help ecological scientists, legislators, and urban planners make better decisions, which could lead to safer and greater resilient coastal communities in the end. The use of satellite data in urban development and emergency preparedness programs has helped a lot in reducing the consequences …
Published in International Journal of Atmosphere · Vol. 2, Issue 2, 2025 · pp. 1–9 Read article
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Thermal Steganography: A New Way to Steal Data from Air-Gapped Computers Using Heat and Fan Noise
Abstract: Nowadays, high-security computers are "air-gapped," meaning they are not connected to the internet to prevent hacking. Cybercriminals are increasingly using direct, physical methods to access and take data instead of relying on internet-based attacks. This paper introduces a new cybersecurity threat called Thermal-Secret. Most existing heat-based attacks are very slow and fail if the room temperature changes. To solve this, we developed a Slope-Based method. Instead of looking at how …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 2, 2026 Read article
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The Dark Side of Technology: Addressing the Rise of Cybercrime and Data Breaches
Abstract: In the digital age, technological advancements have brought about remarkable improvements in communication, business, and daily life. However, these innovations have also given rise to a darker side of the tech world: an increase in cybercrime and data breaches. This article examines the growing threats posed by malicious actors, including hackers, cybercriminal syndicates, and state-sponsored entities, who exploit vulnerabilities in digital systems. It explores the wide-reaching impacts of cybercrime, from …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 06–15 Read article
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Time Series Forecasting Based on PyAF and fbProphet
Abstract: Time series forecasting is the technique of predicting future events using previous data. Time series data includes information that is collected and recorded at regular intervals, such as daily stock prices, monthly sales figures, or hourly temperature readings. The purpose of time series forecasting is to use previous data to create accurate forecasts about the future values of a given variable. This can be beneficial for a range of applications, …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 1, 2023 · pp. 32–36 Read article
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AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science
Abstract: This study presents the development and real-world deployment of an intelligent system for flood monitoring and automated dam gate control using artificial intelligence (AI) and internet of things (IoT) sensors. Supervised machine learning models are developed to predict floods up to 48 h in advance. An automated dam gate operation system is designed to leverage the flood forecasts and real-time stream water levels for emergency control. The complete end-to-end infrastructure …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 9–17 Read article
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Enhancing Attendance Recording: Python and Arduino Integration for RFID Data Transmission to MySQL
Abstract: The suggested attendance system is used to control attendance from a central unit in vast, branching factories or universities. It consists of terminal units and a central unit. A Raspberry Pi, a screen GUI, an RFID reader, a transponder card for each user (such as a student), and a GSM board make up each terminal unit. A PC, a GSM board, and an Arduino make up the main unit. Every …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 2, 2023 · pp. 23–28 Read article
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Trend Analysis of Long-Term Rainfall Data for Monsoon Season of Kharun Catchment
Abstract: This research paper investigates the trends in monsoon season rainfall over a 31-year period (1990–2021) using the non-parametric Mann–Kendall test. A range of statistical methods were utilized to analyze the rainfall data, providing valuable insights into its temporal patterns and trends. The correlation coefficient, measured by Kendall's Tau, exhibited a minimal positive correlation of 0.004 between years and their corresponding rainfall, quantities. This implies a slight tendency for increased rainfall …
Published in International Journal of Rural and Regional Development · Vol. 3, Issue 1, 2025 · pp. 12–17 Read article
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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
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Emotion Recognition from Electroencephalogram Signal and Eye Movement Based on Deep Learning
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems
Abstract: Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem. Existing victim selection heuristics, such as youngest, oldest, and lowest priority, apply static rules that overlook the dynamic runtime state of processes, leading to unnecessary computational loss. This paper reframes the inference-guided preemption (IGP) algorithm as a data-structure-centric solution, highlighting how resource allocation graphs, wait-for graphs, adjacency lists, min-heaps, and hash-based evidence stores interact to enable efficient …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
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Harnessing Bacteria for Next-Generation Data Storage Technologies – A Review
Abstract: The exponential increase in global digital information has created a pressing need for storage technologies that are more durable, compact, and sustainable than conventional electronic media. While hard drives, solid-state drives, and cloud-based systems have transformed information management, they face severe limitations related to storage density, energy consumption, maintenance costs, and long-term preservation. Researchers have, therefore, begun exploring biological systems as alternative information storage platforms. Among these, bacteria have emerged …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 2, 2026 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Progress and Uses of Satellite Remote Sensing
Abstract: Satellite remote sensing has become an important tool for watching, studying, and controlling both natural and man-made systems on Earth. Satellite sensors collect electromagnetic radiation that is reflected or transmitted from the Earth's surface. This data is needed for environmental monitoring, resource management, and hazard assessment. Recent improvements in sensor resolution, data processing techniques, and cloud-based platforms have made remote sensing applications much more accurate and easier to use. The …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 8–19 Read article
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Machine Learning for Finding Materials for Membranes
Abstract: Traditionally, finding and improving membrane materials has depended on trial-and-error experiments, which can take a long time, cost a lot of money, and only cover a small area. Recent improvements in machine learning (ML) have the potential to change the way membrane materials are designed by making it possible to make predictions about performance, selectivity, and stability based on data. ML algorithms can find hidden links between the structure, composition, …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Designing Digital Filters of Underwater Wireless Sensor Node
Abstract: Underwater Wireless Sensor Networks (UWSNs), an emerging area, integrate sensing, computing, and communication into a single compact device. The digital data is acquired using an FPGA (Field Programmable Gate Array), and the fusion of numerous sensor data is accomplished in the sensor node’s ARM (Advanced RISC Machine) CPU. The sensor interfacing circuit should connect the sensor to the sensor node’s data collecting system. The data from these sensors may be …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 1, Issue 1, 2023 · pp. 43–53 Read article