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98 articles for “Data Heterogeneity”
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Role of Organizational Culture in Mediating AI-Induced Social Alienation: A Meta-Analysis
Abstract: The fast adoption of artificial intelligence (AI) in the workplace has raised worries about its influence on employee well-being, particularly social alienation. Social alienation is characterised by feelings of detachment and estrangement at work. It can harm job satisfaction, staff engagement, and organisational performance. Existing literature suggests that organizational culture is crucial in shaping employee experiences with AI technologies. This meta-analysis investigates how organizational culture mediates the relationship between AI …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 28–33 Read article
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LBP-HOG-Statistical-Wavelet Transform Feature Based MCA Classifier
Abstract: Face recognition systems use computer algorithms choose specific, recognizable features on a person’s face. With a mathematical representation, the information is compared to data on other faces acquired in a face recognition database. The distance between the eyes or the shape of the chin are two examples of these characteristics. The job of matching several facial modes, such as visible and near infrared images, is known as heterogeneous face recognition. …
Published in Trends in Opto-electro & Optical Communication · Vol. 12, Issue 2, 2022 · pp. 19–30 Read article
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A Case-control Study on the Impact of Obesity on the Physical and Mental Health of Children
Abstract: The primary objective of the research is to determine prevalence of metabolic comorbidities in obese children. Specifically, we aim to assess the occurrence of hypertension, type 2 diabetes, stress and depression in this population. This study is conducted upon children and adolescents aged 2-19 years. A total of 2874 studies was searched and collected from electronic databases like PubMed, PubMed Central and Google Scholar by the use of keywords. Upon …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 13, Issue 3, 2023 · pp. 10–18 Read article
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A SEIR-Informed Stacked Fusion of Prophet, XGBoost, and LSTM for Ward-Level Epidemic Forecasting in Amravati Municipal Corporation
Abstract: Municipal epidemic preparedness depends on accurate short-horizon forecasts at fine spatial granularity. Ward-level incidence series are typically nonstationary due to changing contact patterns, interventions, reporting delays, and heterogeneous demographic and environmental factors. This paper presents a mathematically formulated hybrid forecasting architecture designed for Amravati Municipal Corporation (AMC). The method decomposes observed incidence into (i) a mechanistic SEIR baseline that enforces epidemiological structure and (ii) a data-driven residual learned using Prophet …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 17–23 Read article
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Emerging Paradigms in Parallel Computing: Trends and Innovations
Abstract: Parallel computing is at an inflection point with revolutionary new paradigms and technologies. The goal of this paper is to survey the recent trend in parallel computing from architecture, programming model and applications. Mahajan cites a litany of architectural developments such as heterogeneous computing systems with integrated graphics processing unit/central processing unit ; the emerging promise from quantum and neuromorphic architectures (please see later); advances in packing transistors using novel …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 39–43 Read article
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STRUCTURAL–EPIGENOMIC ATLAS: CNV/SV- DRIVEN PROGNOSTIC REFINEMENT ACROSS CANCERS
Abstract: Structural genomic alterations, including copy number variations (CNVs) and structural variants (SVs), play a central role in cancer initiation and progression. These alterations extend beyond gene dosage effects and interact dynamically with epigenomic mechanisms such as DNA methylation, histone modifications, and three-dimensional chromatin organization. Recent pan-cancer studies have demonstrated that CNV burden and SV signatures reflect key oncogenic processes including chromothripsis, homologous recombination deficiency, enhancer hijacking, and extrachromosomal DNA (ecDNA) …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
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A Study on AI-Driven Multi-Layered Defense in 6G Ecosystems
Abstract: The 6G networks bring about new degrees of possible functions related to connectivity, latency, data throughput, and integration with artificial intelligence (AI). This enables advances within healthcare, autonomous systems, and smart cities. The positive impact of rapid advancements must also be balanced with heightened risks due to the sheer volume of gaps that can be exploited, and the complex nature of the alignments and breaches. This results in the breaches …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Effect of Local Application of Phenytoin on Wound Healing in Surgical Wounds: A Scientific Review
Abstract: Surgical wound healing is a dynamic biological process influenced by local tissue response, vascularity, infection control, and systemic patient factors. Delayed wound healing contributes significantly to postoperative morbidity and healthcare costs. Phenytoin, a hydantoin derivative traditionally used as an antiepileptic agent, has demonstrated unexpected wound-healing properties when applied topically. This review critically evaluates experimental and clinical evidence regarding the role of locally applied phenytoin in enhancing wound healing in surgical …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 1, 2026 · pp. 15–19 Read article
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Physicochemical Transitions and Polymerization Dynamics in Multi-Generational Dentin Adhesives: A Critical Review of the Resin-Dentin Composite Interface
Abstract: Adhesive dentistry has undergone a transformative refinement over the past three decades, transitioning from technique-sensitive, multi-step etch-and-rinse protocols to streamlined universal formulations. This narrative review critically synthesizes evidence from thirty peer-reviewed investigations to evaluate the evolution of dentin bonding agents from the fourth through the eighth generations. The analysis places particular emphasis on the physicochemical dynamics of the resin-dentin interface, including interfacial bond strength metrics, marginal integrity, and microleakage behavior. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 209–228 Read article
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Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article
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Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article
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Swarm-Enabled AI for Smart Mobility and Sustainable Transport
Abstract: The significant issues facing the modern urban infrastructure are the management of road traffic problems, such as severe traffic congestion, the detection of unsafe driving behavior, and road safety. The traditional ground-based surveillance systems will be helpful, but they will reach their limits in large and dynamic environments. It is because of predetermined perspectives, blindness, and the inability to scale. To designate these problems, the present study proposes a traffic …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 33–38 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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Advancing Asthma Management: The Synergy of Systems Biology, Artificial Intelligence, and Next-Generation Therapeutics
Abstract: Asthma is an inflammatory disorder of the respiratory tract that is chronic and heterogeneous in nature and has various effects on millions of people. Being a chronic inflammatory disease, asthma remains incurable and the major conventional treatments offer limited success due to the mask nature of its pathophysiology. Systems biology/(AI), and next-generation has greatly enhanced knowledge and the management of asthma. The approaches based on gene, transcript, protein, and metabolite …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–12 Read article
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Personalized Therapy Using Drug Delivery Devices
Abstract: The persistent challenge in modern medicine lies in inter-patient heterogeneity, rendering standardized drug dosing protocols suboptimal for many chronic conditions. Traditional pharmacokinetics fail to account for real-time biological fluctuations, leading to cycles of ineffective treatment or dose-limiting toxicity. This paper explores the critical intersection of advanced drug delivery devices (DDDs) and personalized medicine, positioning these technologies as the vital link translating genomic and biological data into tangible, patient- specific interventions. …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 53–62 Read article
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Scope of ITS in Exaggerating Existing Traffic Systems in India
Abstract: AbstractIndia is the largest democracy of world. Its current population is 1.3 billion and the land area of 3.1 million square km. Increasing population and urbanization in India increases the demand of vehicles, which leads to a critical burden on our existing traffic management system. One of the key issues for smart cities is to apply more sustainable and eco-friendly solutions to overcome the existing traffic congestion and environmental pollution …
Published in Recent Trends in Sensor Research & Technology · Vol. 4, Issue 2, 2017 · pp. 14–18 Read article
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Securing the Internet of Things: Challenges and Solutions in the Era of IIoT
Abstract: The manufacturing, healthcare, and transportation sectors have undergone revolutionary changes due to the swift growth of the Internet of Things (IoT) and its industrial cousin, the Industrial Internet of Things (IoT). However, this technological advancement comes with significant security challenges. The heterogeneity of devices, ranging from simple sensors to complex machinery, creates a diverse attack surface. Additionally, many IoT devices lack robust security features, often due to cost constraints or …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 34–44 Read article
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Securing The Internet of Things: Threats, Safeguards, and Future Directions
Abstract: The Internet of Things (IoT) brings immense value while also presenting cybersecurity challenges due to its scale, distribution, and heterogeneity. This study conducts an in-depth analysis of IoT security issues, threats, vulnerabilities, and mitigation strategies through an extensive review of scholarly literature and real-world case studies. A multilayered security approach is proposed, encompassing device hardening, network monitoring, encryption, access controls, governance frameworks, and emerging technologies. The analysis underscores systemic IoT …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 26–31 Read article
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Role of Quantum Chemistry in Catalysis: A Comprehensive Review
Abstract: Catalysis plays a crucial role in modern chemical manufacturing, energy conversion, and environmental protection by enabling chemical reactions to occur more rapidly, selectively, and with reduced energy consumption. A fundamental understanding of catalytic processes at the atomic and electronic levels is essential for the rational design and optimization of catalysts. Quantum chemistry has emerged as a powerful theoretical and computational framework that enables detailed investigation of electronic structure, reaction energetics, …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 1, 2026 · pp. 01–16 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 15–24 Read article