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550 articles for “data transformation”
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Revolutionizing Knee Osteoarthritis Diagnosis: Unleashing the Potential of Vision Transformers
Abstract: Osteoarthritis (OA) is the most common kind of arthritis. By analysing data from both sides of the knee joints, radiologists use the Kellgren–Lawrence (KL) grading system to determine the severity of osteoarthritis (OA). The need for knee arthroplasties has increased as a result of this. Recently, there have been proposals for computer-assisted techniques to improve the precision of OA diagnosis. Choosing between conservative and surgical treatment options for knee osteoarthritis …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 1, 2024 · pp. 24–31 Read article
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Evaluating the Efficiency of LLMs-SA (Sentiment Analysis) via Social Media Texts
Abstract: Sentiment analysis (SA) is becoming popular in business and scientific communities as the processing of natural language (NLP), computational linguistics, text analytics, image-based processing or video- based processing is used in extracting and mining subjective information in the web, social network, etc. It is able to detect positive, negative or neutral information and can be selected to absorb polarity, sentiments, urgency and goals of mount importance. The majority of the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Monitoring and Safety of Aircraft using Wireless Technology
Abstract: Traditional aircraft sensor networks, burdened by wire complexity and high-power demands, struggle with scalability and real-time data acquisition. This paper proposes Bluetooth Low Energy advertising as a transformative solution, leveraging its lightweight, energy-efficient, and secure nature within tree network architecture. Sensors broadcast data packets picked up by strategically placed gateways, enabling efficient data dissemination through multi-hop relaying. The approach boasts scalability due to minimal hardware and power requirements, leading to …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 2, 2023 · pp. 14–21 Read article
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Bridging the Gap and Unlocking Health Literacy: A Guide to Medical Report Clarity
Abstract: This research highlights the significant challenges faced by the general population in interpreting laboratory reports, medical charts, and other health-related documents. Studies show that approximately 9 out of 10 individuals struggle to understand such medical information, primarily due to low health literacy levels. This lack of understanding has become a hidden epidemic, affecting the way people engage with and respond to their own healthcare. While medical tests are essential for …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 31–36 Read article
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Real-Time Attendance System using Face Recognition Using OpenCV and Firebase Realtime Database
Abstract: The Facial Recognition Attendance System now a days revolutionizes traditional attendance tracking by seamlessly integrating cutting-edge image processing with the capabilities of Firebase Realtime Database. This user-friendly solution simplifies and transforms the attendance management experience. Imagine an intuitive interface utilizing facial recognition technology to effortlessly track attendance. Leveraging advanced face detection algorithms and the enchantment of computer vision, our system ensures accurate face recognition, making each individual unmistakably identifiable. Beyond …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 2, 2026 Read article
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Passive Digital Phenotyping for Longitudinal Burnout and Occupational Mental Health Surveillance: A Transformer-Based Explainable Deep Learning Approach Using Smartphone Behavioral Streams
Abstract: Occupational burnout constitutes a pervasive yet chronically under-surveilled public health threat, its insidious temporal evolution rendering episodic self-report instruments structurally inadequate for early detection. This paper introduces BurnoutSense, a passive digital phenotyping framework that continuously harvests eight heterogeneous smartphone behavioral data streams encompassing application usage ecology, communication metadata, geospatial mobility, screen interaction dynamics, inferred sleep rhythmicity, keystroke kinematics, ambient noise exposure, and battery/charging cadence to construct individualized multivariate behavioral signatures …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 44–53 Read article
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Significant Advances in Cloud Computing in Information and Communications Technology
Abstract: The critical advances in information and communications technology (ICT) over the last half-century have led to the increasingly common vision that computing will one day become the 5th utility. This computing utility will provide the essential level of computing service considered basic to meet the everyday needs of the general public. To convey this vision, a number of computing models have been proposed, with the most recent being cloud computing. …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 33–38 Read article
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IoT in Water Resource Management: Trends and Innovations in Water Level Monitoring Systems
Abstract: One of the major problems faced by most of the countries in the world is the issue of water scarcity, and wastage during transmission has been identified as a major culprit; this is one of the motivations for this research, to deploy computing technician creating a barrier to wastage in order to not only provide more financial gains and help the environment as well as the water cycle which in …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 39–45 Read article
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Secure Forge: Deepfake Image Detection Using Vision Transformers
Abstract: Deepfake technologies have become a major risk to the credibility and trustworthiness of digital visual information. Using powerful generative models like GANs and autoencoders, deepfakes can generate highly realistic fake videos and images, resulting in misinformation, identity theft, and public loss of trust in digital media. Classic Convolutional Neural Networks (CNNs) while being highly effective in initial-stage, deepfake detection tend to be limited by their local receptive fields and dependency …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 32–45 Read article
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Encoding-Decoding Algorithm Using the Catalan Transform of Weighted Tribonacci Sequence
Abstract: In order to improve information security, this paper presents a unique algorithm for encoding and decoding messages utilizing the Catalan Transform of a Weighted Tribonacci Sequence. Utilizing the Catalan and Tribonacci sequences, the methodology combines the concepts of number theory and combinatorics to create an effective encryption and decryption process. First, an array is created by mapping each character in the plaintext message to its corresponding ASCII value. The ASCII-weighted …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 12–16 Read article
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Farmer Producer Organizations as Catalysts of Rural Transformation: A Multidimensional Framework from Punjab, India
Abstract: Farmer Producer Organizations (FPOs) have evolved as an important institutional mechanism for resolving the socio-economic challenges of small and marginal farmers by fostering collective action, expanding market access, and boosting bargaining power. In the broader context of sustainable rural development, FPOs are increasingly acknowledged as catalysts of rural transformation by contributing to numerous dimensions of farmer well-being. However, current study has generally analyzed FPOs through economic and operational indicators, with …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 3, 2026 Read article
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Algebraic Foundations of Generalized Signal Processing: A Unified Approach Across Domains
Abstract: Using the techniques of algebra, notably polynomial algebras and modules, algebraic signal processing (ASP) is a contemporary, abstract framework that generalizes conventional signal processing— including Fourier analysis, filtering, and convolution. The notion is to use algebraic structures to explain signals, systems, and transformations such that ideas may be understood and generalized across many domains, including time, space, graph, or group. A unifying theoretical framework called ASP generalizes classical signal processing …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 33–44 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 Read article
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Synthesis, Production, and Mass Balance Analysis of Ten High-Volume Herbicides
Abstract: Herbicides play a crucial role in modern agriculture, enabling effective weed management and safeguarding crop yields amid rising global food demands and growing weed resistance, which can reduce productivity by up to 40%. This study provides a detailed examination of synthesis pathways, production methodologies, and mass balance dynamics for ten high-volume herbicides: Aclonifen, Ametryn, Amidosulfuron, Aminocyclopyrachlor, Aminopyralid, Atrazine, Azimsulfuron, Beflubutamid, Bensulfuron Methyl, and Bentazone, used to control broadleaf weeds, grasses, …
Published in Emerging Trends in Chemical Engineering · Vol. 12, Issue 3, 2025 · pp. 30–44 Read article
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The Role of Artificial Intelligence in Automating Incident Response in Cloud-Based Cybersecurity
Abstract: As cloud computing continues to gain traction across industries, the complexity and scale of cloud environments present significant challenges to traditional cybersecurity practices. The dynamic and distributed nature of cloud infrastructures necessitates agile and effective incident response mechanisms to detect, analyze, and mitigate threats in real-time. However, conventional incident response methods often fall short due to the growing sophistication of cyber threats and the vast amounts of data generated in …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 15–24 Read article
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Continuous Learning in Language Models: A Survey of Streaming Data Processing Techniques
Abstract: The integration of continual learning with Large Language Models (LLMs) and Natural Language Processing (NLP) represents a transformative step toward creating adaptive, intelligent systems capable of functioning effectively in ever-changing environments. Traditional LLMs are typically trained on large, pre-collected datasets, which limits their ability to evolve as new information emerges. Continual learning, in contrast, enables models to acquire new knowledge incrementally without the need for complete retraining, thereby supporting long-term …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 23–34 Read article
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Advancing UAV Video Transmission: A Full-Duplex System with RF and Signal Processing for Reliable, Long-Range HD Communication
Abstract: Unmanned aerial vehicles (UAVs) have transformed industries by enabling advanced aerial imaging and data collection. However, transmitting high-definition (HD) video from UAVs to ground stations poses challenges such as limited range, bandwidth constraints, and interference. This paper presents the development of an HD, full-duplex video transmission system using cutting-edge electronic technologies, including advanced radio frequency (RF) systems and signal processing. These electronic systems are designed to ensure fast, reliable, and …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 2, 2024 · pp. 38–45 Read article
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Report Pulse: Using Machine Learning
Abstract: This study presents the development of a novel medical report analyzer, specifically designed to streamline the interpretation of complex health data. The Report Pulse project represents a significant advancement in healthcare innovation, aiming to facilitate deeper insights into medical reports and foster personalized health management strategies. At its core, the Report Pulse project introduces a sophisticated blood report analyzer, which transcends conventional data analysis by providing actionable insights tailored to …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 28–33 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article