Search
203 articles for “Enhanced Sensitivity”
-
Climate-Driven Shifts in Vector-Borne Disease Ecology Across South Asia
Abstract: Climate change remains one of the most important phenomena affecting the geographical distribution and movement patterns of vector-borne diseases. In South Asia – characterized by high population density, rich biodiversity, and sharp climatic differences – there is growing evidence of the relationship between increasing temperatures and erratic precipitation, along with the behavior of insect vectors. This research aims to evaluate the effects of climate environmental changes on the distribution and …
Published in International Journal of Insects · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
-
Differential Privacy-Aware Data Sanitization for Multi-Level Security
Abstract: Multi-level security (MLS) models are fundamental for enforcing mandatory access control in high-security environments such as government, military, healthcare, and finance. However, traditional MLS frameworks, including the Bell-LaPadula and Biba models, often create rigid data silos, preventing efficient data utilization. Differential privacy (DP) presents a novel solution by enabling controlled information leakage while preserving confidentiality. By injecting statistical noise into query results, DP allows lower-clearance users to access sanitized versions …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 1, 2025 · pp. 42–52 Read article
-
Understanding the Impact: Adult BCG Vaccination in the Fight Against Tuberculosis
Abstract: Tuberculosis (TB) remains a big global health challenge, with significant mortality rates, especially in developing nations. India holds most TB cases throughout the globe. As HIV rates, multidrug-resistant tuberculosis (MDR-TB), and extensively drug-resistant tuberculosis (XDR-TB) continue to increase, the situation is deteriorating. These all come in the way of the End TB epidemic campaign by the World Health Organization (WHO) by 2030. Immunology and vaccinology represent critical fronts in TB …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 1–6 Read article
-
Nanotechnology-Enhanced Wearable Biosensors for Liver Disease Detection: Integration with AI for Predictive Analytics
Abstract: The worldwide health burden of liver diseases is substantial, and effective treatment and management depend heavily on early detection. This study investigates the integration of nanotechnology-enhanced wearable biosensors with artificial intelligence (AI) techniques for predictive analytics in liver disease detection. The construction of extremely selective and sensitive biosensors that can identify a variety of biomarkers linked to liver illnesses has been made possible via nanotechnology. These nanotechnology-based biosensors can be …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 1, 2024 · pp. 22–36 Read article
-
A Brief Review on Herbal Excipients
Abstract: Natural or herbal excipients are significantly more advantageous than their synthetic equivalents because they are readily available, non-toxic, and less expensive. The pharmaceutical industries are becoming more interested in using these herbal excipients – mainly polymers of natural origin – in formulation development because of growing knowledge of them. The purpose of this study is to provide light on the possibility of using natural excipients, which are biocompatible and able …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 12, Issue 2, 2025 · pp. 5–14 Read article
-
Real Time Alcohol Detection with Accident Prevention System Using Arduino
Abstract: The aim of our research work is to present a project designed to make human driving safer and to significantly reduce road accidents caused by drunk driving. This project integrates an MQ3 alcohol sensor with an Arduino-based system using the ATmega328 processor, which offers enhanced functionality compared to conventional microcontrollers. The MQ3 sensor is capable of detecting alcohol content in a person’s breath and has a sensitivity range of approximately …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 19–26 Read article
-
Integration of Biosensors in Robotic Systems for Enhanced Environmental Monitoring
Abstract: Biosensors are analytical devices that use biological components, such as enzymes, antibodies, or nucleic acids, to detect specific chemical or biological substances. They have shown great potential in various fields, particularly in environmental monitoring, due to their sensitivity, specificity, and ability to provide real-time data. Integrating biosensors with robotic systems combines the strengths of both technologies, allowing for efficient data collection in remote, hard-to-reach, or hazardous environments. This integration enables …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 38–49 Read article
-
Industry 4.0 and Smart Supply Chains: Transforming Supply Chain Processes for Enhanced Efficiency and Sustainability
Abstract: The fourth industrial revolution, or Industry 4.0, is an important transformation in how industries function via the use of cutting-edge digital technology. Supply chain management is being substantially altered by integrating technologies like blockchain, big data, automated processes, artificial intelligence, and the internet of things into typical operations of the supply chain. With the help of these technologies, corporations can design intelligent supply chains that are more effective, flexible, and …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 1, 2025 · pp. 36–41 Read article
-
Limits to Knowledge-Sharing by Computers
Abstract: The rapid advancement of artificial intelligence (AI) and machine learning (ML) has significantly enhanced the capabilities of computers in processing, analyzing, and disseminating knowledge. However, despite these advancements, there are inherent limits to the extent that knowledge-sharing can be fully realized through computer systems. This study explores the various barriers that hinder the effective sharing and transfer of knowledge through machines, including technological limitations, ethical concerns, and the complexities of …
Published in Current Trends in Information Technology · Vol. 15, Issue 2, 2025 · pp. 01–05 Read article
-
Innovative Biosensor Applications in Petroleum Industry for Enhanced Monitoring and Safety Measures
Abstract: The petroleum industry is fundamental to the global economy, providing the energy and raw materials that drive modern society. However, this industry faces a myriad of challenges, including ensuring the safety of operations, monitoring critical processes effectively, and minimizing environmental impacts. Traditional monitoring techniques, while valuable, often fall short in delivering real-time data and comprehensive insights into operational parameters. These limitations can result in delayed responses to potential hazards and …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 1–13 Read article
-
Challenges and Promoting Factors for Tribal Girls in Vocational Education
Abstract: This research paper purely focused on the importance of vocational education and training programs specifically for tribal girls in India with a particular objective of its role in enhancing economic independence and promoting self- sufficiency in woman. It also highlighted multiple barriers like social, cultural, administrative, and economical in accessing the vocational education which affects the participation, retention. At the same time the study positions vocational education as a transformative …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 1, 2026 Read article
-
Advancements in Nanotechnology and Biosensor Integration for Detection and Treatment of Alice in Wonderland Syndrome
Abstract: Alice in Wonderland Syndrome (AIWS) is an uncommon neurological condition characterized by profound distortions in perception. Individuals with AIWS experience altered body image and spatial awareness, often perceiving objects, surroundings, or even their own body as being unusually large, small, or distorted. The condition presents a unique challenge for both diagnosis and management due to its elusive and varied symptoms. This paper explores how advancements in nanotechnology and biosensor integration …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 3, 2024 · pp. 1–12 Read article
-
Investigations On Use of Poly(3,4-Ethylenedioxythiophene): Poly (Styrene Sulfonic Acid) (PEDOT: PSS) Conductive Polymers for Design of Improved EEG Based Brain Computer Interface for Seizure Control and Analysis
Abstract: This research explores the application of Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) conductive polymers in the design of an enhanced Electroencephalography (EEG)-based Brain-Computer Interface (BCI) for seizure control and analysis. PEDOT: PSS, known for its high conductivity, flexibility, and biocompatibility, is employed to improve the efficiency and sensitivity of EEG electrodes, addressing challenges such as signal noise, skin-electrode impedance, and user comfort. The study evaluates the material’s properties, including its electrical conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 223–241 Read article
-
Parallel Privacy-Preserving Adaptive Federated Learning on GPU-Enabled Multi-Core Architectures
Abstract: The increasing deployment of parallel and distributed intelligent systems has intensified the need for privacy-preserving learning frameworks that can exploit multi-core and GPU-based architectures without centralizing sensitive data. This work proposes a parallel Adaptive Federated Learning (AFL) framework that integrates Differential Privacy and Secure Aggregation over heterogeneous multi-core and GPU platforms to enhance both data confidentiality and convergence efficiency. The framework dynamically adjusts client participation, learning rates, and aggregation weights …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
-
64 Bit ALU DESIGN USING VEDIC MATHEMATHICS
Abstract: High-speed arithmetic operations are crucial for better performance in contemporary digital systems. Particularly for high bit-width operations, conventional arithmetic logic units (ALUs) frequently experience increased latency and complexity. This work presents the design and implementation of a 64-bit Arithmetic Logic Unit (ALU) using notions from Vedic mathematics. The suggested design makes use of a Kogge-Stone Adder for effective addition and the Urdhva Tiryagbhyam sutra for quick multiplication. Among other mathematical …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
-
Optimizing Fin Parameters to Enhance Passive Heat Dissipation in Photovoltaic Panels
Abstract: This study explores passive cooling techniques to enhance the thermal management of photovoltaic (PV) modules, which is crucial for maintaining efficiency. A computational fluid dynamics (CFD) model, using ANSYS Fluent, was developed to evaluate three fin shapes: rectangular, trapezoidal, and triangular, attached to the back of PV modules. The study varied parameters such as fin count, thickness, and length to determine optimal configurations for cooling. Among the designs, triangular fins …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 25–35 Read article
-
Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
-
Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 Read article
-
A Review of XML Technologies for Enhancing Security in Advanced Database Management Systems
Abstract: The integration of Extensible Markup Language (XML) technologies into advanced database management systems (DBMS) has revolutionized data storage, retrieval, and security paradigms. This comprehensive review examines the critical role of XML-based security mechanisms in protecting sensitive data within contemporary database environments. The study explores various XML security technologies, including XML encryption, XML digital signatures, XML access control models, and XML firewalls, analyzing their implementation strategies and effectiveness in mitigating database …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
-
Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article