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198 articles for “Novel algorithm”
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A Novel Approach for Design and Optimization of Slot Antenna for WLAN Applications
Abstract: The simulation, and analysis of a micro-strip fed slot antenna array intended for operation in the 2.4 GHz ISM (Industrial, Scientific, and Medical) band, which is widely used for wireless technologies such as Wi-Fi and Bluetooth. A slot antenna is a type of antenna where a slot (cut or gap) is made on a metal surface, and it radiates electromagnetic waves. Utilizing ANSOFT HFSS software, the antenna's performance is optimized, …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
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Precision Medicine for Neurofibromatosis Type 1: Progress and Prospects in Drug Discovery
Abstract: Objective: The development of neurofibromas, café-au-lait spots, and other neurological problems are the hallmarks of neurofibromatosis type 1 (NF1), a hereditary disorder. The dearth of efficacious pharmaceutical therapies underscores the need for novel therapeutic approaches, even in the face of clinical variability. Through very accurate prediction of the binding affinity of possible therapeutic drugs with the target protein, the computational technique known as “molecular docking” has become a potent tool …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 01–15 Read article
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A Survey on Cryptography and Steganography
Abstract: The two most significant security aspects that deal with the transmitting knowledge or information over various medium for example Internet are steganography and also cryptography. Steganography deals with the hiding the presence of an information and cryptography deals with the hiding the data contents. Both of them are used to confirm security. But none of them can be easily complete the basic need of security, i.e., the services like as …
Published in Recent Trends in Programming languages · Vol. 2, Issue 3, 2015 · pp. 5–13 Read article
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The Future is Smelling: Exploring the Potential of e-Nose
Abstract: The human sense of smell, a complex and often underestimated faculty, allows us to perceive the world through volatile organic compounds (VOCs). This ability to detect and differentiate between aromas, flavors, and even potential hazards has inspired the development of the electronic nose, or e-nose. More than just a novelty, e-noses are rapidly becoming sophisticated analytical tools with applications that span across numerous industries. By mimicking the biological processes of …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 15–25 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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A Novel Deep CNN Model for COVID-19 Detection based on Lung CT Images
Abstract: In recent months, worldwide society has been destroyed by COVID-19 (Coronavirus Disease 2019), a catastrophic contagious illness that has ravaged the whole world. Deep learning (DL) approaches are the most widely used strategies for chest CT scan processing and illness prediction in the medical field. COVID-19 is infectious sickness that mostly influences the lungs also has the potential to be fatal if left untreated in its extreme form. It also …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 1, 2022 · pp. 1–14 Read article
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Designing a Novel Insider Threat Model for Enhanced Cybersecurity
Abstract: Designing a novel insider threat model is a critical imperative in the realm of cybersecurity. As organizations face an ever-expanding threat landscape, insider threats, whether deliberate or inadvertent, present a formidable challenge to the safeguarding of sensitive data and critical assets. This abstract encapsulates the significance, challenges, and innovations inherent in crafting an effective insider threat model for enhanced cybersecurity. The necessity for novel insider threat models arises from the …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 24–27 Read article
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Report Pulse: Using Machine Learning
Abstract: This study presents the development of a novel medical report analyzer, specifically designed to streamline the interpretation of complex health data. The Report Pulse project represents a significant advancement in healthcare innovation, aiming to facilitate deeper insights into medical reports and foster personalized health management strategies. At its core, the Report Pulse project introduces a sophisticated blood report analyzer, which transcends conventional data analysis by providing actionable insights tailored to …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 28–33 Read article
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Vehicle Insurance Fraud Detection Using Supervised Neural Network Model
Abstract: Vehicle insurance fraud is a serious problem that causes huge financial losses to insurance companies. In recent years, developing fraud detection models using machine-learning techniques has been of great interest. This study proposes a novel approach for vehicle insurance fraud detection using Supervised Neural network model on the Kaggle Vehicle Insurance Fraud Detection dataset. The initial step in this study involves performing data pre-processing and feature extraction on the dataset, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 10, Issue 1, 2023 · pp. 32–39 Read article
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A Study on Automatic Feedback Control by Image Processing for Mixing Solutions in a Microfluidic Device
Abstract: Precise and rapid mixing of chemical and biological reagents is a critical yet challenging aspect of microfluidic systems, often limited by laminar flow conditions and the need for manual or pre- programmed interventions. Existing mixing strategies frequently lack real-time adaptability and closed-loop control, hindering reproducibility and the execution of complex reaction protocols. This work presents an innovative automatic feedback control system utilizing the study on real- time image processing to …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 32–41 Read article
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Devanagari Script Recognition System using Combined Approach
Abstract: We envisioned serving simple technique with novel idea for the newcomers, working in the Devnagari Optical Character Recognition (DOCR) area. In this system, template matching technique and statistical technique is combinely used for the character recognition. Statistical information is considered as a feature of an image and here pixels values are considered as feature to achieve the recognition. The numbers of comparisons are drastically reduced compared to traditional template matching …
Published in Current Trends in Signal Processing · Vol. 4, Issue 1, 2014 · pp. 4–10 Read article
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Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
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Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 1–9 Read article
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Optimizing the Integration of Photovoltaic and Wind Energy Systems for Enhanced Efficiency
Abstract: This work provides a novel approach for integrating a large-capacity doubly excited induction generator (DFIG)-based wind energy system with solarphotovoltaic (PV). The suggested plan offers a practical PV-grid integration solution by utilising DFIG’s grid and rotor side power converters to pump PV power into the grid. This eliminates the requirement for a separate converter for PV power processing. Compared to a comparable rated inverter utilised in traditional PV-grid systems, the …
Published in Journal of Power Electronics and Power Systems · Vol. 13, Issue 2, 2023 · pp. 34–52 Read article
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YOLOv8 in Focus: A Review of its Application in Driver Monitoring Systems
Abstract: This research presents a novel Driver Monitoring System (DMS) that utilises Convolutional Neural Networks (CNNs) to achieve remarkable results. Specifically, the YOLOv8 (You Only Look Once version 8) detection technique is used. The main goal is to increase road safety by using cutting-edge computer vision techniques to analyse driver behaviour in real-time. The YOLOv8 detection method, a cutting-edge CNN model renowned for its precision and effectiveness in object recognition, is …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 3, 2023 · pp. 35–40 Read article
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments
Abstract: The novel approach that this work discusses is a DCD-based iterative learning filter approach improved with deep learning methodologies, designed to improve the efficiency of acoustic echo cancellation. The proposed system can really manage both linear and nonlinear echo scenarios, dynamically adapting to fluctuating acoustic environments. The above comparative evaluations with standard filter, the standard RLS filter, indicate that the mean square error, and the standard deviation of the correlation …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 9–24 Read article