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1518 articles for “Computational Data”
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AI-Driven IoT-Based Decision-Making System for Brainwave Study: The KSK Approach
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain–computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 28–35 Read article
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Data Embedding Technique for Palette Scale Image using Derived Genetic Algorithm (DEP-DGA)
Abstract: Steganography method is used for exchanging the hidden information. It is defined as the study of hidden communication that deals with the existence of communicated messages. The existing methodology for minimizing additive distortion in steganography fails in measuring the level of distortion for the given source palette digital image. Perfect sphere shaped palette digital images are not suitable for selection, as cover models because the hidden data might be easily …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 2, 2014 · pp. 1–10 Read article
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Sentiment Analysis of X (Formerly Twitter) Using Machine Learning
Abstract: Sentiment analysis is a methodology to determine the nature and behavior of each and every user for the content posted on the social media platform in the form of post and feed. Consumers of the online platform are encouraged to post reviews of the product that they purchase. Little attempt is created by Amazon to confine or limit the content of these reviews. The number of reviews for various merchandise …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 2, 2024 · pp. 28–37 Read article
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Concurrent PTSD Psychotherapy Through Multi-Personnel Virtual Reality Framework
Abstract: Networked Virtual Environments (NEV) are sets of disjointed virtual worlds which are topographically set apart from the users yet connected through the communication network to give them the illusion of being in the same virtual location. NVEs are increasingly receiving consideration from business and research point of view. Contrasted with various sorts of possible applications, NVEs require a high responsiveness to ensure continuous streaming of live data for full immersion. …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 7, Issue 1, 2017 · pp. 22–26 Read article
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Facial Emotion Recognition Using CNN and OpenCV: A Review
Abstract: Emotion Recognition Using a Facial Feature Recognition is a prominent area of study in the world of Human Computer Interaction (HCI). Humans may express a wide range of emotions and moods through facial movements and body language. In this project, in order to detect the live emotions from the human facial gesture, we will be using an algorithm that allows the computer to automatically detect the facial recognition of human …
Published in Journal of Open Source Developments · Vol. 10, Issue 1, 2023 · pp. 1–9 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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A Review of Attacks and Challenges in Mobile Cloud Computing
Abstract: In MANET, all mobility terminals are a self-directed nodal, that may function as both a router and a host. Some applications of mobile ad hoc network are described in this paper. Securing wireless ad hoc networks is an incredibly complicated issue. A special system may be vulnerable to unauthorized data manipulation because the system does not confirm a customer’s individuality prior to agree to data access. In mobile cloud computing, …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 1, 2017 · pp. 35–43 Read article
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IoT-Based Anti-Theft GPS Tracking System for Real-Time Vehicle Monitoring
Abstract: For the last six decades, advances in global positioning systems (GPS) technology for tracking vehicles have greatly enhanced their ability to secure, monitor, and track vehicles. However, many conventional methods using GPS to track vehicles have been limited by the scope of their/its operational communication range. This has reduced their effectiveness in terms of being able to track those vehicles once they are out of the limits of the original …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 1, 2026 · pp. 22–28 Read article
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Real-Time IR Intensity Measurement and Computation for Systems
Abstract: In contemporary defense mechanisms, infrared (IR) sensing has become a fundamental technology for identifying and neutralizing heat-seeking threats, especially concerning aircraft protection. Conventional IR detection systems, such as single-channel radiometers and basic thermal sensors, frequently face restrictions due to low spatial resolution, sluggish data processing, and inadequate user engagement. These constraints can impede the prompt identification of dangers like missile launches or flare activations, potentially endangering mission safety. Additionally, numerous …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 8–13 Read article
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Data Mining Methods for Terrorist Activity
Abstract: ABSTRACTIdentification of outliers is an important component of data mining since such observations can have a profound influence and distort the analysis. In the recent years, detection of outlier has been broadly applied in the field of data mining. It is an important method for many research applications such as credit card fraud, computer intrusion detection, and criminal activities in electronic commerce, medical diagnosis and anti-terrorism, image processing, etc. Detection …
Published in Journal Of Network security · Vol. 5, Issue 3, 2017 · pp. 17–22 Read article
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3D Printing for Polymer Science Visualization
Abstract: The burgeoning field of 3D printing offers exciting possibilities for various scientific disciplines. This paper explores the potential integration of 3D printing technology within the realm of polymer analysis. While the core focus of memory forensics investigations lies in digital forensics, the concept of 3D printing complex data structures presents intriguing possibilities for the visualization and communication of findings in polymer science. Here, we propose a future research avenue where …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 96–101 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Representative Feature Selection for Efficient Clustering
Abstract: AbstractClustering is one of the widely used data mining techniques. In machine learning, it is an unsupervised learning method that needs training data to be used. The problem with clustering is that it is computationally expensive and takes more time for grouping high-dimensional data. Therefore it is necessary to reduce number of features in the high-dimensional data in order to make the search space reduced. Many techniques came into existance …
Published in Journal Of Network security · Vol. 5, Issue 2, 2017 · pp. 19–27 Read article
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Low-Power Reconfigurable Digital Filter Design Using FPGA for IoT Edge Devices
Abstract: The rapid evolution of the Internet of Things (IoT) has led to an exponential increase in the deployment of edge devices that continuously process real-time sensor data under strict power, latency, and computational constraints. Digital filtering remains a critical operation in these devices, supporting tasks such as noise removal, data conditioning, and feature extraction for intelligent decision-making. However, conventional filter implementations on microcontrollers or fixed digital signal processors often struggle …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
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Quantitative Analysis of Static Load Balancing Algorithms in Cloud Computing Environment
Abstract: Cloud computing is an emerging internet-based technology emphasizing commercial computing. Cloud is a platform providing dynamic pool of resources and virtualization. It is based on pay-as-u-go model. The reliability of clouds depends on the way it handle loads, to overcome such problems clouds must be featured with the load balancing mechanism. Load balancing is required as we do not want one centralized server's performance to be degraded. Load balancing is …
Published in Current Trends in Information Technology · Vol. 5, Issue 1, 2015 · pp. 6–13 Read article
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Python: Empowering Data Science Applications and Research
Abstract: It was in 1991 that the first mention of Python came to light. Since it is one of the best programming languages, it is widely used in the data analytics industry. It is speedy, easy to use, and can smoothly alter data with no hiccups. It aids in the processes of data analytics generally, such as data collection, analysis, modelling, and visualization. Python stands out from other languages because it …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 1, 2023 · pp. 27–33 Read article
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Privacy Preserving of Vertically Partitioned Data Using Elliptical Curve Cryptography
Abstract: Data mining's privacy problems have become a big problem as a result of financial considerations. This work investigates the topic regarding the issue of privacy-preserving global association rule analysis over several parties in vertically partitioned data to efficiently prevent hidden trends and perform computations across the parties while respecting the privacy of their data. After that, it suggests using Shamir's method of secret sharing to support distributed mining of association …
Published in Journal of Advanced Database Management & Systems · Vol. 9, Issue 3, 2022 · pp. 31–38 Read article
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Anomaly Based Intrusion Detection Using Machine Learning Techniques
Abstract: Detection of Cyberattacks/anomalies in a network to build an efficient Intrusion Detection System (IDS) is very important. A system called an intrusion detection system (IDS) monitors network traffic in order to find suspicious activity and sends out signals when it is noticed. Monitoring and data analysis are designed with the objective of finding any network or system intrusions. Machine learning methods can anticipate both known and unidentified attacks. This project …
Published in Journal Of Network security · Vol. 10, Issue 2, 2022 · pp. 1–8 Read article
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Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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A Parallel Online Learning Algorithm for Anisotropic Digital Image Restoration
Abstract: Previously, in the computational scenarios where the training data has already been made available for the learning algorithm, the kernel based algorithm such as support vector machines have made significant advances in the machine learning field. Though there has been little advancement made in learning scenario at online settings to facilitate the various real-time applications at the user end. In this study we discussed the issues with the online learning …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 1, 2015 · pp. 21–26 Read article