Search
404 articles for “complex algorithms”
-
A Review on the Intelligent Schemes for Automatic Generation Control in Modern Power System
Abstract: AbstractAutomatic generation control (AGC) is one of the important control problems in the design and operation of interconnected power system, and is gaining popularity today due to the growing size, varying structure, upcoming renewable energy sources and new uncertainties, and complexity of power systems. AGC system requires increased intelligence and flexibility to guarantee balance between load and generation. The modern AGC systems surely must be intelligent, and should be capable …
Published in Journal of Advancements in Robotics · Vol. 4, Issue 3, 2017 · pp. 1–4 Read article
-
Performance Analysis of Routing and Protection Schemes for High Speed Networks
Abstract: AbstractManagement of high-speed networks becomes critical as traffic volume increases. Impact of failures is aggravated in networks carrying huge volume of data. Impact is more pronounced as level of multiplexing in high speed networks increase. It is important to deal with survivability of high speed networks in efficient manner in order to maintain high Quality of Service (QoS). In this paper, a performance analysis of routing and protection algorithms in …
Published in Journal of Web Engineering & Technology · Vol. 4, Issue 3, 2017 · pp. 11–18 Read article
-
Achieving Multi-objectives Using a Single Neural Network
Abstract: Achieving multi-objectives using a single neural network is a research area that aims to develop techniques to optimize multiple objectives simultaneously using a single neural network. This approach can be applied in various fields, such as image and speech recognition, robotics, and natural language processing, to achieve better performance and reduce the complexity of the models. The key challenge in this area is to balance the trade-off between different objectives …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 3, 2022 · pp. 1–15 Read article
-
Incremental Conductance Algorithm and Perturb and Observe Algorithm Reveals Key Insights into Their Comparative Analysis: A Review
Abstract: The maximum or more is a crucial aspect of PV systems to optimize energy harvesting from solar panels, which have been the focus of extensive research and implementation. This study presents a comprehensive comparative analysis of these two methods of evaluation to evaluate their performance and suitability for various operating conditions. The Perturb and Observe method, a simple and widely adopted MPPT algorithm, involves perturbing the operating point and observing …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 9–16 Read article
-
Modulation of Receptor Proteins: A Recent Paradigm in Drug Discovery and Target
Abstract: The main aim in drug discovery is to design different ligands those work on specific drug targets. However, various effective drugs work through the modulation of many proteins than single target. Advancement in system biology are establishing a phenotypic strength and a network structure, which suggests that, the excellent selective compounds may be performed less than desired clinical efficacy in comparison to multi-target drugs. In this new appreciation of the …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 5, Issue 1, 2018 · pp. 14–24 Read article
-
Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
-
Quantum Key Distribution Based on BB84 Protocol
Abstract: Classical cryptosystem, which is based on mathematical complexity and irrationally time-consuming to decode, is endangered with the inception of quantum computers empowered with unprecedented computational processing along with sophisticated quantum algorithms. Thus requiring quantum cryptography and Quantum Key Distribution (QDK) protocol for secured key distribution. This thesis work contributes to the field of cryptography. First of all, it shows unconditionally secured QKD which is bound by quantum mechanics laws. It …
Published in Journal of Semiconductor Devices and Circuits · Vol. 10, Issue 3, 2024 · pp. 26–32 Read article
-
Deep Learning based Solution for Leaf disease Detection in Crops and Fertilizer Recommendation
Abstract: The field of agriculture faces significant threats, including diseases that attack plant leaves. To address this issue, our system assists farmers in promptly detecting plant diseases using advanced technology. The user, typically a farmer, only needs to capture an image of the affected leaf and input it into our system. Our system then analyzes the uploaded image to accurately identify the specific disease afflicting the leaf. This analytical process is …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 31–40 Read article
-
Optimization of Robotic Path Planning Algorithms for Autonomous Material Handling Systems
Abstract: For autonomous systems for handling materials (AMHS) to operate as efficiently as possible in industrial and logistical settings, robotic route planning is essential. This study examines many robotic route planning algorithms, emphasizing their use, ways of optimization, and difficulties in material handling systems. To improve the effectiveness, precision, and computational viability of these algorithms, the study also examines a number of optimization strategies, including machine learning, parallelization, heuristic search, and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 15–20 Read article
-
Adaptive Tree Climbing Robot
Abstract: This paper is proposed to design a tree climbing robot which makes the robot to realize the environment and climb on tree autonomously. The proposed robot is inspired by locomotion of inchworms. By the use of limit switches, the algorithm reconstructs the shape of the tree which reveals how the environment can be realized with limited information. Since the shape of trees is irregular and complex, it is a challenging …
Published in Journal of Advancements in Robotics · Vol. 1, Issue 3, 2014 · pp. 11–16 Read article
-
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
-
An Evolution of the Pixel Embedding Techniques in Image Based Adaptive Steganography
Abstract: The word “Steganography” was basically derived from the Greek words with the meaning “covered writing.” This paper presents some of the main adaptive image steganography approaches. Many algorithms have been presented; in almost all the algorithms the approach is to embed the secret data in the images. Here we are discussing about adaptive steganography which is based upon spatial domain and frequency domain with an additional layer of mathematical model. …
Published in Journal of Web Engineering & Technology · Vol. 1, Issue 1, 2014 · pp. 1–18 Read article
-
Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
-
Advancements, Hurdles, and Applications in Quantum Computing
Abstract: Using the ideas of quantum mechanics, quantum computing has become a paradigm shift in computing, enabling computations to be completed tenfold quicker than with traditional computers. This study investigates the current status of quantum computing, looking at the notable advancements, ongoing difficulties, and potential uses that could completely change a range of industries. By utilizing the principles of superposition and entanglement, quantum computers can potentially solve complex problems that classical …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 11–29 Read article
-
Diabetes Prediction Using ML Techniques
Abstract: Diabetes mellitus, commonly referred to as diabetes, denotes a cluster of prevalent endocrine disorders characterized by persistent elevated levels of blood sugar. Diabetes is classified into two main types: type 1 and type 2. Type 1 diabetes arises when the body is unable to produce insulin, while type 2 diabetes involves either insulin resistance or insufficient insulin production. Early detection and intervention are essential to reduce its harmful impacts. The …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
-
Assessing the Effectiveness of Machine Learning Algorithms in Simulating Malware Detection Processes
Abstract: On the information system comprehends, computer virus attacks play a very important role and, by undermining regionally and globally, are considered one of the most critical threats. The traditional malware detection methods, more varied, being based on signature, are incapable of providing sufficient coverage over malicious programs in a short time. This is due to the speed of evolution and growing complexity of malware variants. This situation, in turn, requires …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 3, 2023 · pp. 11–20 Read article
-
Role of Reinforcement Learning in Improvement of Semiconductor Doping
Abstract: The semiconductor industry faces increasing challenges in achieving optimal doping profiles as device dimensions shrink and performance requirements intensify. Traditional doping optimization methods, while effective, often struggle with the complex, multi-dimensional parameter spaces characteristic of modern semiconductor manufacturing. This study explores the transformative role of reinforcement learning (RL) in improving semiconductor doping processes, examining how RL algorithms can autonomously optimize doping parameters to enhance device performance, reduce manufacturing costs, and …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 23–34 Read article
-
AI Enhanced E-Voting System Securing Elections with Face Recognition and OTP Authentication in India
Abstract: The E-Voting domain seeks to leverage technology to address these issues, enabling citizens to vote securely and conveniently while maintaining the transparency of the electoral process. Machine learning algorithms like Haar cascade and CNN will enhance the system's security, accuracy, and efficiency by leveraging data- driven approaches. Conventional voting techniques frequently encounter obstacles including identity theft, convoluted processes, and hold-ups in the processing of results. This article suggests a complex …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 21–30 Read article
-
Artificial Machine Intelligence Language for Banking Chatbot
Abstract: The developed system introduces a banking chatbot utilizing Artificial Intelligence Markup Language (AIML) to enhance customer interactions within the banking sector. With the increasing demand for efficient customer service and the adoption of automated systems, chatbots have emerged as a pivotal solution for banks to streamline operations and improve user experience. The proposed banking chatbot leverages state-of-the-art natural language processing (NLP) algorithms powered by AIML to interpret user queries, provide …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 3, 2024 · pp. 8–13 Read article
-
Single Sensor Camera Image Denoising Using PCA and Demosaicking with LMMSE
Abstract: Single sensor cameras are used mostly for image acquisition in digital cameras with a colour filter array (CFA). These cameras save image in an unrefined format, since the complete process of image acquisition get lengthy and complex, so it introduces noise in the image and hence requires some efficient technique for denoising. Different techniques have been used to denoise the captured image but efficiency of the algorithms has not been …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 1–10 Read article