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98 articles for “Data Heterogeneity”
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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ICU Health Monitoring System in IoT with Machine Learning
Abstract: The Internet of Things (IoT) allows humans to push to a higher level of automation by developing systems using various sensors, interconnected smart devices, and the Internet. In ICU, patient checking is basic and most vital activity as little deferral in choice related to patients’ treatment may cause lasting permanent disability or maybe death. Most ICU devices are equipped with various sensors to live health parameters but to watch it …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 1, 2021 · pp. 25–34 Read article
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A Knowledge Graph Approach for Breast Cancer Diagnosis and Data Sharing Platform Implementation in the Context of Human Papillomavirus Infection
Abstract: Background: Breast cancer remains among the most prevalent malignancies in women worldwide, and effective diagnosis and data integration continue to challenge clinical practice. Diagnostic reports from mammography and ultrasound contain rich clinical information that is often under-utilised due to heterogeneous formats and limited data-sharing infrastructure. In the context of human papillomavirus (HPV) infection, which may influence oncogenic pathways and data complexity, advanced computational methods offer new solutions to this problem. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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DATABASE-DRIVEN ENERGY MANAGEMENT IN ELECTRIC VEHICLES
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
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Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article
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Computational Intelligence and Neuro-Fuzzy Modelling of Polymer Composites: A Critical Review of Performance Prediction and Optimization
Abstract: The increased variety in polymer matrices, reinforcements, fillers, and processing parameters has led to the need to better understand the structure-property, process-property relationships in order to accurately predict and optimize the performance of polymer composites. This paper reviews the applications of computational intelligence methods in polymer composites, with special focus on artificial neural networks, adaptive neuro-fuzzy inference systems, machine learning techniques, and hybrid optimization. The literature is analyzed based on …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Internet of Things: Threats and Security
Abstract: Security is the most important in today’s world as we have personal and confidential data which we do not want to share with anyone, but somehow attackers attack on our data and steal our identity. Same happens in IoT, attackers somehow attack on devices or communication channels and steal the data. This study reviews all the threats and security issues in IoT. Nowadays, devices are made in such a way …
Published in Current Trends in Information Technology · Vol. 12, Issue 2, 2022 · pp. 7–11 Read article
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Enabling Intelligent Interoperability: Advancing Sensor Networks Through the Semantic Sensor Web (SSW)
Abstract: The Semantic Sensor Web (SSW) is an evolution of the traditional Sensor Web, integrating semantic web technologies to enhance the discovery, interpretation, and integration of heterogeneous sensor data. By embedding semantic annotations into sensor observations and metadata, SSW enables automated reasoning, improved interoperability, and more sophisticated querying capabilities across diverse sensor networks. This approach addresses key challenges in handling large-scale, distributed, and dynamic sensor data, particularly in domains such as …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 2, 2025 · pp. 21–37 Read article
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Green Fabrication of Glutaraldehyde-Crosslinked Chitosan/PVA Biocomposite for Heavy Metal Removal from Wastewater
Abstract: Chitosan (CS) and Polyvinyl alcohol (PVA) are polymers that possess biodegradable, biocompatible, and non-toxic properties, making them suitable for wastewater treatment applications. The primary objective of this research is to chemically modify chitosan in a novel manner to enhance its ability to remove hexavalent chromium Cr(VI) from aqueous solutions. In this study, a composite material was synthesized by crosslinking PVA and CS with glutaraldehyde (GA), resulting in the formation of …
Published in Journal of Water Pollution & Purification Research · Vol. 12, Issue 3, 2025 · pp. 59–83 Read article
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Harnessing NLP for Automation and Intelligence Across Sectors
Abstract: Natural Language Processing or NLP is a vital subset of Artificial Intelligence or AI which enables machines to interpret, understand, and communicate using human language in a remarkable way. From the traditional rule-based approaches to the modern advanced deep learning techniques such as transformers, neural networks, and hybrid models, NLP has been evolving year by year. This study reflects on various applications of NLP, including sentiment analysis, machine translation, analysis …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 23–32 Read article
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Record Linkage in Knowledge Discovery Process Using Angle Based Machine Learning
Abstract: Record linkage is a critical data cleansing step in the knowledge discovery process, aimed at identifying and resolving inconsistencies across datasets. This study proposes an enhanced record linkage framework tailored for uncertain and large-scale data using a combination of distance measurement, probabilistic modeling, and semantic reasoning. A novel angle-based distance measurement technique is introduced to optimize matching between candidate records. To further boost match accuracy, a Finite Mixture Model (FMM) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1170 Read article
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An Interoperability on the Internet of Things (IoT): A Review
Abstract: With technological advancement growing at a rapid rate, we are presented with numerous ways of connecting ourselves to the rest of the world. The Internet of Things, or IoT, is now a reality, even at the minuscule level. With ubiquitous computing, we can stay in constant communication with the outside world. As such there are several types of devices capable of monitoring, measuring, and sending data back and forth from …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 40–53 Read article
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A Critical Review of the Limitations of the Arithmetic Mean and the Robustness of the Median in Statistical Analysis
Abstract: Arithmetic mean is an extremely popular measure of central tendency used in statistical analyses, primarily because it is so easy to calculate and has many positive mathematical characteristics. However, when there are outliers, skewed distributions or heterogeneous spread of data, the reliability of the arithmetic mean diminishes greatly. This paper includes a critical review of the limitations of the arithmetic mean and an assessment of the robustness of the median …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 2, 2026 · pp. 21–29 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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Implementation of Weighted Round Robin Algorithm in Shared Bus Architectures
Abstract: AbstractThe application domain of System-On-Chips (SoC) includes mobile devices, end terminals, multimedia terminals, automotive, set-top-boxes, games, processors etc. The SoC design paradigm relies heavily on reuse of intellectual property cores, enabling designers to focus on functionality and performance of the overall system. This is possible if IP cores are equipped with highly optimized interface for plug and play insertion into communication architecture. To this purpose the virtual Socket Interface Alliance …
Published in Journal of Electronic Design Technology · Vol. 8, Issue 2, 2017 · pp. 34–40 Read article
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Enhancing Road Safety: A System for Vehicular Accident Detection, Prevention, and Rescue Alerts
Abstract: The Vehicular Accident Detection, Prevention, and Rescue Alert System is a comprehensive solution aimed at bolstering road safety by integrating multiple advanced technologies. It merges drowsiness detection, alcohol level monitoring, and instant emergency alerts to mitigate accidents and expedite rescue efforts. Modern computer vision and machine learning techniques are used by the Drowsiness Detection Alarm to track driver conduct and spot drowsiness indicators. Upon detecting drowsiness, an immediate alarm is …
Published in International Journal of Solid State Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 7–11 Read article
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A Review on Life Cycle Assessment of Solar Photovoltaic Electricity Generation Systems
Abstract: A popular system for calculating the environmental effects of energy systems from conception to death is life cycle assessment, or LCA. As a low-carbon generation technology, solar photovoltaic (PV) systems have fast spread throughout the world. The various PV technologies (monocrystalline, polycrystalline, thin-film), system scales (residential, commercial, utility), industrial locations, balance of system (BOS) configurations, and end-of-life (EoL) scenarios are all covered in this review of published life cycle assessment …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 1–6 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Challenges in Parallel Computing for Big Data Analytics
Abstract: The integration of parallel computing into the realm of big data analytics promises accelerated processing speeds and enhanced scalability, but it is not without its formidable challenges. This study explores the multifaceted hurdles faced in the pursuit of efficient parallel processing for large-scale data analytics. The intricate task of distributing and partitioning massive datasets across multiple processing units demands adept strategies to ensure equitable workloads. Load balancing emerges as a …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 1, 2024 · pp. 1–6 Read article
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Triple Negative Breast Cancer—Pattern of Recurrence and Survival: A Single Institute Experience
Abstract: Triple negative breast cancer (TNBC) is a distinct biological entity and recent data shows it as a heterogeneous group with at least 6 subtypes with differences in clinical outcome.This study intends to analyze the prevalence, recurrence pattern and outcome of triple negative breast cancer in our patient cohort.We reviewed the outcomes of 244 consecutive triple negative non-metastatic breast cancer patients who were treated with a radical intent from Jan 2004 …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 6, Issue 3, 2017 · pp. 5–8 Read article