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1115 articles for “Evaluation”
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Caregiver Burden Among Informal Caregivers of Terminally Ill Older Adult Patients in Rural Kerala, India
Abstract: Background: The increasing prevalence of chronic and terminal illnesses among the aging population has elevated the role of family members as primary caregivers for seriously ill patients, particularly in rural settings. This shift places significant burdens on caregivers, encompassing financial, emotional, and physical challenges, thereby impacting their own quality of life and well-being.Objective: This study aimed to explore the factors associated with informal caregiver burden in rural patients with critical …
Published in International Journal of Geriatric Nursing · Vol. 9, Issue 1, 2026 · pp. 48–58 Read article
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Classification of Fetal ECG Arrhythmia by Using Advance Hybrid Deep Learning Technique CNN-LSTM
Abstract: Fetal heart abnormalities, particularly fetal heart arrhythmias, are becoming an increasing concern in maternal healthcare. Early and accurate detection remains challenging due to limitations in conventional diagnostic techniques and inadequate signal processing methods. Existing studies have applied various machine learning and deep learning approaches; however, capturing the complex characteristics of fetal electrocardiogram (ECG) signals remains a significant gap. This study proposes an advanced deep learning-based approach for detecting fetal heart …
Published in International Journal of Cardiovascular Nursing · Vol. 12, Issue 1, 2026 · pp. 27–36 Read article
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Assessment of Awareness and Treatment Adherence Among Patients with Hypertension and Elevated Blood Sugar
Abstract: Hypertension and elevated blood sugar are two major chronic conditions that frequently coexist and significantly increase the risk of cardiovascular complications and other long-term health issues. Effective management of these conditions requires not only medical treatment but also adequate patient awareness and consistent adherence to prescribed therapies and lifestyle modifications. This study aims to assess the level of awareness and treatment adherence among patients diagnosed with hypertension and elevated blood …
Published in International Journal of Cardiovascular Nursing · Vol. 12, Issue 1, 2026 · pp. 1–5 Read article
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Photo-Catalytic Degradation of Dyes Using Graphene Oxide–Dithizone Composite
Abstract: Graphene oxide–dithizone (GO–DTZ) composite was successfully synthesized through the copolymerization of graphene oxide and dithizone to develop an efficient photocatalytic material for wastewater treatment. The dithizone polymer was prepared using a 1:2 molar ratio, while graphene oxide was synthesized via the modified Hummers’ method to obtain highly oxidized graphene sheets with abundant oxygen-containing functional groups. The GO–DTZ nanocomposite was fabricated by ultrasonically dispersing graphene oxide with the synthesized dithizone polymer …
Published in International Journal of Analytical and Applied Chemistry · Vol. 12, Issue 2, 2026 · pp. 46–53 Read article
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A Study to Assess the Effectiveness of Structured Teaching Program on Knowledge Regarding Prevention of Varicose Veins Among Staff Nurses at Selected Hospital in Kanpur
Abstract: Varicose veins are a common occupational health problem associated with prolonged standing and impaired venous circulation, particularly among healthcare professionals such as staff nurses. If preventive measures are not adopted in a timely manner, varicose veins can progress to serious complications affecting quality of life and work efficiency. Nurses working in hospital settings are at increased risk due to long working hours, extended periods of standing, and high physical demands. …
Published in International Journal of Medical Surgical Nursing · Vol. 9, Issue 1, 2026 · pp. 34–59 Read article
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A Descriptive Study on Current Trends in the Diagnosis and Management of Diabetic Foot
Abstract: Diabetic foot is a major and frequently occurring complication of diabetes mellitus, significantly contributing to patient morbidity, increased hospital admissions, and a higher risk of lower limb amputations. Timely identification and proper management are crucial to halt disease progression and enhance patient outcomes. This descriptive study focuses on examining current practices and advancements in the diagnosis and management of diabetic foot within clinical settings. The study highlights modern methods used …
Published in International Journal of Medical Surgical Nursing · Vol. 9, Issue 1, 2026 · pp. 23–33 Read article
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Knowledge Enhancement on Scrub Typhus Through Planned Teaching: A Study Among UrbanAdults in Puducherry
Abstract: Background: Scrub typhus is a re‑emerging zoonotic infection in India, often misdiagnosed due to nonspecific symptoms. Awareness among adults is crucial for early detection and prevention. Objective: To assess baseline knowledge of scrub typhus among adults, evaluate the effectiveness of a planned teaching programme, and examine associations with demographic variables. Methods: A one‑group pre‑test and post‑test design was used. Fifty adults from Muthialpet, Puducherry were selected by convenience sampling. Knowledge …
Published in International Journal of Immunological Nursing · Vol. 12, Issue 1, 2026 · pp. 27–30 Read article
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Effectiveness of an Educational Intervention in Improving Knowledge on the Prevention of Iron Deficiency Anaemia Among School Students
Abstract: Iron deficiency anaemia is recognized as one of the most prevalent nutritional health problems among school-going children and adolescents across the world. Factors, such as insufficient intake of iron-rich foods, unhealthy dietary habits, and inadequate awareness about preventive strategies, play a major role in increasing its occurrence. The current study was undertaken to evaluate the effectiveness of an educational intervention in improving knowledge regarding the prevention of iron deficiency anaemia …
Published in International Journal of Immunological Nursing · Vol. 12, Issue 1, 2026 · pp. 12–16 Read article
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Effectiveness of Structured-Teaching Program on Knowledge, Attitude, and Practice on Oral Hygiene Among School-Going Children Aged Between 10–13 Years Old at Selected School,Kuppam, Andhra Pradesh
Abstract: Background: Dental health is crucial to school health because untreated dental decay can hinder kids’ development and learning, exacerbate behavioral issues, and lower their self-esteem. Oral hygiene refers to the maintenance of cleanliness of the teeth and mouth to prevent dental problems such as dental caries, gingivitis, and bad breath. Effective oral hygiene focuses on controlling and preventing the buildup of dental plaque. This study was conducted to assess the …
Published in International journal of Nursing Science Practice and Research · Vol. 12, Issue 1, 2026 · pp. 12–18 Read article
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Hybrid Organic–Inorganic Metal Halide Perovskite Solar Cells: A Comprehensive Review of Materials, Device Architectures, Stability, Hysteresis, and Commercialization Challenges
Abstract: Hybrid organic–inorganic metal halide perovskite solar cells (PSCs) have emerged as a major focus of photovoltaic research due to their remarkable increase in power conversion efficiency, reaching 28% within a short period. Perovskite materials exhibit several attractive properties, including long charge-carrier diffusion lengths, tunable band gaps, and excellent light absorption capability. In addition, their low-cost fabrication processes combined with high efficiency make PSCs strong competitors to conventional silicon-based solar cells. …
Published in International Journal of Renewable Energy and its Commercialization · Vol. 12, Issue 2, 2026 · pp. 47–60 Read article
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Brain-Inspired Computing: The Rise of Neuromorphic AI
Abstract: Neuromorphic computing is an emerging computing paradigm that draws inspiration from the structure and operational principles of the human brain. By integrating ideas from neuroscience, computer design, and materials science, neuromorphic systems aim to deliver high-performance, low-power computation that is suitable for smart data processing. Unlike traditional von Neumann architectures, neuromorphic hardware uses massively parallel processing, event driven computation, and adaptive learning. This paper provides an overview of neuromorphic principles, …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 12, Issue 2, 2026 Read article
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RIS-Assisted 6G Wireless Communication: BER, Security Gain and Multi-Metric Performance Analysis
Abstract: Reconfigurable Intelligent Surfaces (RISs) provide programmable control over wireless signal propagation and are emerging as a promising technology for enhancing the reliability, energy efficiency, coverage, and physical-layer security of sixth generation (6G) wireless networks. This paper presents a unified simulation-based performance evaluation of conventional SISO, 4G SIMO, and 6G multi-antenna communication systems, followed by an RIS-assisted reliability and security analysis under Rayleigh fading conditions. The simulation results demonstrate that antenna …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 Read article
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Integrating Machine Learning with Edge Computing for Real Time Data Analytics
Abstract: Smart devices such as mobile phones, sensors, cameras, etc., are producing a huge amount of data every second. This data is normally sent to cloud servers for processing. This approach is normally slow and expensive, and it also raises a lot of privacy issues as data is sent over the internet, which takes a lot of time to return with results. This study aims to address the issue through the …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 2, 2026 Read article
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Detailed survey on detection of Dirtiness of PV panels using different approaches
Abstract: The accumulation of dust, dirt, bird droppings, pollen, and other environmental contaminants on photovoltaic (PV) panels significantly reduces their power generation efficiency and increases operational and maintenance costs. Therefore, timely and accurate detection of the cleanliness condition of solar panels is essential for maintaining optimal energy production, improving system reliability, and extending the operational lifespan of PV installations. In recent years, considerable research interest has been directed toward automated soiling …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article
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Exploration of Explainable Artificial Intelligence (XAI) Techniques to Enhance Model Interpretability
Abstract: Explainable Artificial Intelligence (XAI) has become a major research field because of the rising application of complex machine learning and deep learning models in actual decision-making systems. Although such models are accurate, they are in many cases black boxes and therefore the users do not have much understanding of the way the decisions are generated. This absence of transparency brings up some serious concerns connected with trust, accountability, fairness, and …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article
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Autonomous Multi-Agent Sensor Network for Distributed Environmental Instrumentation
Abstract: Environmental monitoring requires intelligent, scalable, and autonomous instrumentation systems capable of continuously sensing, processing, and communicating heterogeneous data under dynamic conditions. This study proposes an Autonomous Multi-Agent Sensor Network for Distributed Environmental Instrumentation, integrating distributed sensor nodes, edge computing, multi-agent collaboration, adaptive data fusion, and intelligent decision-making to achieve reliable real-time monitoring of environmental parameters. Each sensor agent autonomously performs local sensing, anomaly detection, energy-aware communication, and cooperative information exchange …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Machine Learning-Based Channel Estimation for 5G NR Systems: A Comprehensive Review of TDL/CDL Channel Models and CNN Architectures
Abstract: Accurate channel estimation is a fundamental requirement for reliable communications in fifth-generation New Radio (5G NR) systems, where highly dynamic propagation environments impose severe challenges on conventional pilot-based methods. This study provides a thorough analysis of channel estimate methods for 5G NR, including everything from contemporary deep learning (DL) techniques based on Convolutional Neural Networks (CNNs) to traditional Least Squares (LS) and Minimum Mean Square Error (MMSE) estimators. Our analysis …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Classification of power quality disturbances using advanced deep learning algorithms for Accurate and efficient electrical signal analysis
Abstract: Power systems today have to deal with more and more power quality issues (PQDs) like voltage drops, rises, harmonics, and transients because more people are using renewable energy sources and electronic devices. These problems can hurt equipment, stop services, and lower the overall reliability of power. In real-time settings, traditional detection methods often don't work as quickly or accurately as they should. This paper looks at how deep learning models, …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 12, Issue 2, 2026 Read article
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Speech Emotion Recognition using Multi- Kernel CNN for Features extraction and Random Forest Classifier
Abstract: Identifying human emotional states from speech signals is the main goal of Speech Emotion Recognition (SER), which has grown to be a significant area of study in affective computing. However, class imbalance and efficient feature extraction from speech data pose problems for many of the current methods. This study suggests a hybrid framework that combines a Random Forest (RF) classifier with a multi-kernel Convolutional Neural Network (CNN) to address these …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 2, 2026 Read article
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Cost-Constrained Sensor Reduction for Deployment AwareIoT-Based Multiclass Water Quality Monitoring
Abstract: Large-scale Internet of Things deployment for water quality monitoring systems is bounded by the capital and several other costs associated with the multi-dimensional sensor. While prior research demonstrates strong predictive performance using multi- parameter physicochemical sensing, limited attention has been given to explicit sensing cost constraints and deployment feasibility. This work formulates multiclass water quality classification as a cost-constrained learning problem in which sensing dimensionality is minimized subject to bounded …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 2, 2026 Read article