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62 articles for “Data Recovery”
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Green and Edge-Aware Computing: Rethinking Cloud Infrastructure for Sustainability
Abstract: Cloud computing has transformed the way organizations access and manage information technology resources, providing flexible, scalable, and cost-efficient services that support today’s data-driven world. Despite these advantages, the rapid expansion of large-scale cloud infrastructures has resulted in rising energy consumption, significant heat generation, and a growing environmental footprint. This research focuses on advancing green cloud computing by examining methods that reduce power usage while maintaining high performance. Key strategies include …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 17–24 Read article
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Diffusion-Based Enhancement of Low-SNR Time- Frequency Signals
Abstract: Traditional enhancing techniques are useless in low signal-to-noise ratio (LSNR) situations because noise drastically interferes with communication signals. Based on an enhanced DiffBIR model, this paper suggests a dual-stage signal improvement approach that combines diffusion with deep learning. By combining the Inception module for multi-scale feature extraction with the Pixel Fusion Attention (PFA) module for significant region highlighting, the model improves signal recovery in the time- frequency domain. Experiments show …
Published in Current Trends in Signal Processing · Vol. 17, Issue 2, 2026 Read article
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A Study on Clinical Characteristics and The Impact Of Covid-19 In Hemodialysis Patients
Abstract: Background: The Corona Viruses Disease-19 pandemic has severely impacted Hemodialysis patients, who are vulnerable due to compromised immune systems and underlying comorbidities. Frequent Dialysis center visits increase their exposure risk to severe acute respiratory syndrome- Coronavirus Disease, and chronic inflammation, uremia, and immunosenescence may impair their immune response. Methods: This retrospective study included 60 Hemodialysis patients diagnosed with COVID-19 between January -July 2024. Data on demographics, clinical characteristics, laboratory results …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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Thermodynamic Optimization and Exergy-Based Performance Analysis of Hybrid Thermal Management Systems for Electric Vehicles
Abstract: The transition toward sustainable transportation has brought electric vehicles (EVs) to the forefront of modern engineering innovation. Despite their environmental benefits and improved energy efficiency, EVs face major thermal challenges that affect performance, safety, and durability. Efficient thermal management of batteries, power electronics, and electric drive systems is vital to ensure reliability under diverse operating conditions. This study presents a detailed thermodynamic optimization and exergy-based performance analysis of hybrid thermal …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 19–23 Read article
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Development Of Ai-Driven Systems for Real-Time Joint Movement Detection and Correction in Frozen Shoulder Therapy Using Sensor-Based Shoulder Rehabilitation Devices
Abstract: Frozen shoulder, or adhesive capsulitis, is a common musculoskeletal disorder characterized by progressive pain, stiffness, and restricted range of motion that significantly impairs functional ability and quality of life. Recent advancements in artificial intelligence and sensor-based technologies have enabled the development of intelligent rehabilitation systems capable of real-time joint movement detection and correction. Wearable sensors such as inertial measurement units, electromyography sensors, and flexible strain sensors capture continuous biomechanical data …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Myco-Engineering Systems: Harnessing Fungal Networks for Carbon Sequestration and Sustainable Ecosystem Restoration
Abstract: Fungal organisms play a foundational role in global ecosystem stability, particularly through their contributions to nutrient cycling, soil regeneration, and carbon sequestration. Recent scientific advances have highlighted the potential of fungal mycelial networks as natural bioengineered systems capable of supporting sustainable environmental restoration. This paper introduces the concept of Myco-Engineering Systems, an interdisciplinary framework that integrates fungal biology, environmental science, and artificial intelligence (AI) to enhance carbon capture and ecosystem …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 2, 2026 Read article
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A Overview of Free Space Optical Communication (FSO)
Abstract: Free Space Optical communication (FSO) is a wireless communication system that employs light propagation across free space to transport data between two sites without the usage of fibre optic cables. It uses either lasers or light emitting diodes (LEDs) for high speed data transmission with enormous bandwidth, which makes it a desirable solution for modern communication systems. The FSO provides many advantages such as minimal installation cost, excellent security, licence …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 31–35 Read article
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Post Covid-Sequela: Novel-Inception of DM: A Review
Abstract: As patients recovers from COVID 19 pandemic, a subset of the covid patients experienced a post covid condition with long term symptoms, few weeks after their discharge or recovery from the (SARS-CoV-2) infection. Hence, we tried to prove the hypothesis whether diabetes mellites is an afresh possible sequala of covid infection by systematically evaluating the consistently changing glucose level of the post covid patients. The databases PubMed and Google Scholar …
Published in Research and Reviews : A Journal of Immunology · Vol. 16, Issue 2, 2026 Read article
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Predictive Factors of Long-Term Sobriety: A Post-Discharge Outcome Study in Mangalore, Goa, and Vasai (2019–2023)
Abstract: Relapse following discharge remains a major challenge in addiction recovery, even with structured treatment protocols in rehabilitation centers. This study examines post-discharge outcomes from Kripa Foundation’s rehabilitation centers in Mangalore, Goa, and Vasai over a five-year period (2019–2023). A total of 100 patients were categorized into four behavioural outcome groups: Clean (Sober), Relapsed, R.I.P. (Deceased), and Unknown. The study aimed to identify demographic and behavioural predictors of sustained sobriety post-discharge. …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 29–44 Read article
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Utilizing Machine Learning to Evaluate the Connection between Poisson's Ratio and the Petrophysical Properties of Reservoir Rocks
Abstract: The Poisson's ratio is a crucial cornerstone, illuminating our understanding of geomechanical behaviour in wells during the dynamic drilling process and the inspiring recovery journey. This research rigorously employs machine learning methods to analyse the significant impact of geophysical parameters on the Poisson ratio in hydrocarbon reservoirs found in oil fields. The analysis utilized data from multiple oil and gas fields, highlighting the crucial relationships between the Poisson ratio, the …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 33–43 Read article
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Rheological Studies of a Cross-Linked Polymer Gel System
Abstract: The petroleum accumulations are found associated with water and it is rarely obtained without accompanying water production. Water production is a major technical, environmental, and economic challenge associated with oil and gas extraction. Rheological findings are of fundamental importance for the development, manufacture and processing of innumerable products. Polymeric gels exhibit a wide range of rheological properties and they are stable both mechanically and thermally in most cases thus are …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 13–26 Read article
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Innovations in Mineral Science and Engineering for Sustainable Resource Development
Abstract: The growing global demand for mineral resources, coupled with increasing environmental and social concerns, has intensified the need for sustainable approaches in mineral science and engineering. Traditional mining and mineral processing practices, while essential for industrial development, are often associated with high energy consumption, resource depletion, and environmental degradation. In response, recent innovations in mineral science and engineering have focused on improving resource efficiency, minimizing environmental impact, and ensuring long-term …
Published in International Journal of Minerals · Vol. 3, Issue 1, 2026 · pp. 31–36 Read article
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Innovative Waste Management Solutions for Building Sustainable Cities and Enhancing Community Resilience
Abstract: The swift growth of urban areas presents considerable difficulties in waste management, as conventional disposal techniques lead to environmental harm. This study explores innovative green technologies designed to transform urban waste into valuable biomaterials and biofuels, fostering a circular economy and environmental conservation. The focus is on real-time monitoring systems, RFID-enabled waste tracking, and IoT-based platforms, which optimize waste collection and segregation, enabling efficient recovery of materials for biofuel production. …
Published in International Journal of Environmental Planning and Development Architecture · Vol. 3, Issue 1, 2025 · pp. 25–32 Read article
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AI-Driven Robotics for Sustainable Solutions in Disaster Management
Abstract: Disasters, whether natural or man-made, present significant challenges to societies worldwide. Efficient response, recovery, and mitigation strategies are crucial to minimizing human suffering, loss of life, and economic damage. Traditional disaster management strategies, while effective to some degree, often face limitations related to human resources, response time, accessibility, and safety. The integration of artificial intelligence (AI) and robotics into disaster management offers transformative potential for overcoming these challenges. This paper …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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Smart City Solutions for Waste Management and Pollution Control
Abstract: Recent trends in the role of artificial intelligence, IoT, and other smart technologies have a critical role toward addressing urban environmental challenges related to air quality and waste management in the context of a smart city. This changes the scope of managing air quality as, with the integration of IoT sensors, big data, and AI, they are able to predict pollution levels through real time monitoring and analysis. These technologies …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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Viscoelastic Behavior and Wrinkle Formation in Cotton- Polyester Garments: A Data-Driven Approach for Textile Care
Abstract: This study investigates the wrinkle behavior of cotton-polyester blended fabrics by analyzing data from over 1,200 store-handled garments. Integrating concepts from polymer chemistry and computer vision, it aims to establish a smart textile care framework based on fiber-specific wrinkle characteristics. The research identifies how cotton’s hydrophilic and non-elastic structure results in increased wrinkling, while polyester’s thermoplastic and crystalline properties enhance wrinkle resistance. Elastomeric fibers like Lycra contribute to wrinkle recovery …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 50–60 Read article
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Raspberry Pi-Based Real-Time Object Recognition for Smart Item Recovery
Abstract: In today’s fast-paced world, individuals often lose valuable time searching for misplaced items such as keys, phones, and remote controls—an estimated 2.5 days per year. This paper introduces a cost-effective, computer vision-based system that helps users efficiently locate everyday objects. The system utilizes a 1080p camera and the YOLO (You Only Look Once) object detection algorithm to enable accurate, real-time object recognition. Designed for practical usability, it stores detected object …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 28–36 Read article
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Digital and Sustainable Innovations for Zero-Waste Manufacturing
Abstract: The integration of digital technologies and sustainable practices in manufacturing is crucial for addressing global issues like resource depletion, pollution, and waste. Zero-waste manufacturing has emerged as a transformative approach to minimize environmental impact and boost production efficiency. This paper explores how digital and sustainable innovations support this goal. Industry 4.0 technologies— such as IoT, AI, Big Data, and robotics—enable real-time monitoring, predictive maintenance, and optimized resource use. Sensors and …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 3, 2025 · pp. 34–42 Read article
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Influence of Remote Therapeutic Monitoring on Efficiency and Effectiveness of PT in Home Health Settings
Abstract: The delivery of physical therapy (PT) services in a home health setting presents unique challenges and opportunities, particularly as the demand for personalized, patient-centric care continues to grow. Remote therapeutic monitoring (RTM) has emerged as a transformative tool, enabling therapists to monitor patients’ progress, adherence, and outcomes beyond the traditional in-person visits. Leveraging technologies, such as wearable devices, mobile applications, and telecommunication platforms, RTM bridges the gap between sessions, fostering …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 1, 2024 · pp. 35–40 Read article
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Mathematical Modeling of Epidemics Using Stochastic Differential Equations: A Review
Abstract: The accurate modeling of infectious disease dynamics is crucial for predicting outbreaks and informing public health interventions. While deterministic models such as the SIR (Susceptible-Infected-Recovered) framework have traditionally been used to understand disease transmission, they often fail to account for the randomness inherent in real-world scenarios. Disease spread is influenced by numerous uncertain factors, including individual behavioral changes, environmental fluctuations, and imperfect data reporting. These uncertainties can significantly impact model …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article