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1939 articles for “data” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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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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High-speed Data Converter Architectures: Latched Comparator Design & Performance Comparison
Abstract: This paper focuses on the design and optimization of latch comparators for high-speed data converter applications. The performance of different comparator architectures is compared in terms of speed, power consumption, and noise performance. The proposed latch comparator architecture uses a preamplifier to boost gain and sensitivity, and a latch to store the output signal. The latch comparator design is optimized for low power consumption and high speed, and is implemented …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 23–32 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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Evaluating the Performance of a Smart VCR System Using Python for Data Analysis Based on IoT
Abstract: Commercial buildings use a significant amount of electricity, with around 60% to 80% being attributed to the HVAC system. Implementing IoT and smart sensors can help reduce this consumption by 10% to 30%. To lower the electricity usage of air conditioners, a study has proposed an IoT-based smart VCR system with sensors, meters, gateway, and cloud computing modules. This system is designed to collect data and regulate the VCR system …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 2, 2024 · pp. 7–23 Read article
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Performance of Artificial Neural Network for Tree Species Identification using Sentinel-2 Data
Abstract: Accurate land cover mapping, especially concerning vegetation, is crucial for effective land use policy planning and sustainable forest management. Hence, achieving accuracy in mapping requires a deep understanding of composition changes, vegetation conditions, and the spatial distribution of tree species. In the spatial context of tree species, it holds significant potential for applications including invasive species monitoring, delineating contaminated areas, and biodiversity conservation. However, traditional methods for tree species identification …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 2, 2024 · pp. 12–21 Read article
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Real-Time Ocean Monitoring and Early Warning Systems with IoT Technology
Abstract: The increasing frequency of extreme weather events, rising sea levels, and threats to marine biodiversity This paper explores the application of IoT in enhancing real-time ocean monitoring and early warning systems, focusing on the deployment of smart sensors, connected buoys, and data analytics to collect key parameters such as temperature, salinity, pH, and wave activity. To preserve and responsibly utilise the seas, oceans, and marine resources in support of sustainable …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 13–24 Read article
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Brain Tumor Detection Through CNN: Techniques, Dataset Insights, and Methodology
Abstract: Computer technologies are playing huge roles in some areas of the medical domain like surgery and therapy of different diseases. Researchers are doing studies and trying to experiment to detect different diseases like cancer, virus infections, and leprosy. There are many different medical imaging datasets that are publicly available for medical research purposes of diseases like cancer, virus infections, and leprosy, etc. where we can be able to access large …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 30–40 Read article
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Design and Implementation of an IoT-based Traffic and Parking Management System Integrated with GIS for Urban Environments
Abstract: As urbanization accelerates, managing traffic flow and parking availability has become increasingly challenging. This article presents the design and implementation of an internet of things (IoT)-based traffic and parking management system integrated with geographic information systems (GIS) to address these challenges in urban environments. The proposed system utilizes a network of IoT sensors to monitor traffic flow, congestion levels, and parking space availability in real time. The data collected by …
Published in Trends in Transport Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 23–32 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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MIRDcalc & OLINDA/EXM Dosimetry Software Analysis by SPECT/CT Scan Data of Lu-177 DOTATATE Radionuclide Therapy of NET Patients
Abstract: Accurate dosimetry is essential in nuclear medicine for optimizing radionuclide therapies and ensuring patient safety. In Radiopharmaceutical dosimetry the Medical Internal Radiation Dosimetry (MIRD)Society is the pioneer in organ-level dosimetry providing the fundamental basis for commonly used clinical and research dosimetry software like MIRDOSE and OLINDA/EXM. Recently, in MIRD Pamphlet No. 28, Part 1, the MIRD committee of the Society of Nuclear Medicine and Medical Imaging presented a new Software …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 48–63 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 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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Study of an Improved Quantum Particle Swarm Optimization-Based Framework for Neural Network Optimization in Modelling of Polymer Data
Abstract: The accurate forecasting of polymer viscosity at various physicochemical conditions has been quite critical due to the nonlinear interactions and interrelations between the variables. This paper suggests a better hybrid modelling framework, which involves the use of Artificial Neural Networks (ANN) and more advanced versions of Quantum Particle Swarm Optimization (QPSO) to better predict polymer viscosity. The input parameters taken are, namely, log (shear rate), polymer concentration, NaCl concentration, Ca …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 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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Privacy-preserving Multi-keyword Search in Multi-owner Setting Using Blockchain
Abstract: Searchable encryption (SE) has become an essential cryptographic technique, allowing users to securely search through encrypted data. However, most existing SE schemes rely on a single intermediary, such as a cloud server, leading to potential single-point failures, privacy breaches, and untrustworthy results. Many blockchain-based SE schemes have been proposed to address these issues. However, they frequently encounter difficulties such as supporting a multi-keyword, multi-owner model, ensuring query privacy, and maintaining …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 2, 2024 · pp. 12–18 Read article
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Geospatial Measurement of Shrinking Lake Mead Using Multi-Temporal Datasets From 1987 to 2020 and Its Relationship with the Climate Change
Abstract: The study provides an overview of the relation between climate change and its harsh consequences, and thereby revealing evidence of extremes conditions such as drought. Lake Mead of USA is one such example which is a readily contracting lake. The reason is fast temperature increment, human exploitation, etc. therefore leading to jeopardized and devastating effects on life structure. GIS and Remote Sensing has emerged as an extraordinary key instrument for …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 18–27 Read article