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198 articles for “Novel algorithm”
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A Multimodal Image Fusion based on NonSubsampled Contourlet Transform and Sparse Representation
Abstract: Detection of tumors in the brain is vital in diagnosis of brain cancer. Doctors suggest numerous scans like CT, MRI, PET, and SPECT for estimating the type of cancer, size and location of the tumor and the aging or spread of cancer. A single imaging technique is not sufficient for correct diagnosis of the disease. In case the scans are ambiguous, it can lead doctors to incorrect diagnosis, which can …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 2, 2018 · pp. 12–21 Read article
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Rainwater Measuring Algorithm in O(1) Time Complexity
Abstract: The Rain Terraces Time Complexity Data Structure Algorithm (RTTCDSA) introduces a novel method for managing temporal data efficiently, inspired by the natural flow of rainwater on terraced landscapes. This study presents the conceptual framework and implementation details of RTTCDSA, which leverages principles of temporal dynamics and landscape morphology to organize and query temporal data with optimal time complexity. RTTCDSA employs a hierarchical structure akin to terraced landscapes, facilitating rapid traversal …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 26–32 Read article
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A Novel Binary Arithmetic Computational Method
Abstract: The proposed algorithm for arithmetic operations presents an innovative and intriguing approach, primarily centered around the use of counters and the manipulation of '1's in binary representations. This algorithm promises to introduce significant advancements in computational efficiency and accuracy, making it a potential game-changer in the field of arithmetic calculations. At the core of this method lies the reliance on the number of '1's in each location within a binary …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 10, Issue 1, 2023 · pp. 21–25 Read article
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Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
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An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
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A PCA Based K-Means Clustering Algorithm for Wireless Sensor Nodes
Abstract: This paper presents a novel and improved approach for K-Means Clustering of wireless sensor networks, by using Principal Component Analysis for data reduction on the raw data. A wireless sensor network consisting of 100 nodes is classified into three different clusters using PCA based K-Means Algorithm. Davies-Bouldin Index is used as a parameter to check the effectiveness of the clustering algorithm. Experimental results demonstrate that the PCA based K-Means Algorithm …
Published in Journal of Web Engineering & Technology · Vol. 2, Issue 2, 2015 · pp. 6–10 Read article
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A Novel Optimized Shunt Active Power Filter using GA and ANN in Constant Frequency Aircraft System
Abstract: Constant instantaneous power control strategy for extracting reference currents for shunt filters have been changed with the use of Artificial Neural Network and Genetic Algorithm primarily based controller and their performances were compared. The acute evaluation of comparison of the repayment capability mostly based on THD and velocity could be carried out, and guidelines might be given for the selection of the technique for use. The simulated effects the use …
Published in Journal of Aerospace Engineering & Technology · Vol. 8, Issue 1, 2018 · pp. 36–43 Read article
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Application of Image Denoising through Comorbid Pixel Regularization Algorithm based on Neuro-Fuzzy Rule
Abstract: This study presents a novel approach of image denoising for medical images. Since, for medical diagnosis, action of object extraction plays a vital role but such jobs are limited with the visual observation and there is no denying from the fact that the medical images are subjected to noise which makes it difficult for the medical practitioner to extract features from such noisy images. Therefore, for accurate decisions it is …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 2, Issue 2, 2014 · pp. 7–11 Read article
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Advancements in Machine Learning: A Comprehensive Review of Algorithms, Applications, and Future Directions
Abstract: Gaining knowledge of Machine learning (ML)-guided format algorithms leverage predictive models to generate novel devices with optimized properties across several domains, which include drug discovery, fabric synthesis, and biomolecular engineering. Selecting an effective format set of policies consists of identifying appropriate hyperparameters, predictive models, and generative mechanisms to maximize format fulfilment. This study introduces an established method for set of policies requirements, ensuring that generated designs meet predefined fulfilment criteria, …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 17–33 Read article
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Enhancement of Digital Mammograms Using Intuitionistic Fuzzy Entropy Function
Abstract: A novel intuitionistic fuzzy entropy-based algorithm is developed for increasing the contrast of digital mammograms. The contrast enhancement helps in the early detection of masses and microcalcification in tissues thus paving the way for the auxiliary diagnosis of breast cancer. The current techniques for the enhancement of digital mammograms do not consider the uncertainty in pixel intensities of mammograms. The proposed technique aims at enhancing the mammograms using intuitionistic fuzzy …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 2, 2023 · pp. 10–26 Read article
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Solution of Optimal Reactive Power Dispatch Problem Using a Novel Meta-heuristic Technique
Abstract: This paper presents the use of a recently developed algorithm inspired by the hunting mechanism of grey wolfs in nature, called grey wolf optimizer (GWO) algorithm for solving optimal reactive power dispatch (ORPD) problem. The ORPD is formulated as a complex optimization problem with nonlinear characteristic. The GWO is used to find the set of optimal control variables of ORPD problem, such as generators’ terminal voltage, position of tap changers …
Published in Trends in Electrical Engineering · Vol. 7, Issue 3, 2017 · pp. 8–16 Read article
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An Offline Space Division Multiplexing Based Elastic Optical Network Model with Switching and Modulation Format Adaptation for Flexible Spectrum and Spatial Assignment
Abstract: Abstract: The Space Division Multiplexing (SDM) based Elastic Optical Networks (EONs) (SDM-bEONs) is the proposed solution to both, the required upgradation of the network’s capacity constrained by the non-linear Shannon’s limit and the provisioning needed for the future diverse Internet traffic’s required capacity. With SDM providing ‘space’ as an additional freedom degree, the assignment of resource (i.e., spectrum and space) in the SDM-b-EONs translates into the Routing, Modulation Format, Space, …
Published in Trends in Opto-electro & Optical Communication · Vol. 9, Issue 1, 2019 · pp. 1–23 Read article
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Optimized Design and Control of Oil Exploitation Strategies: An Assisted Approach
Abstract: Because there are so many factors and scenarios to consider, optimizing oil exploitation tactics requires complicated decision-making. Conventional approaches frequently concentrate on particular elements of the design infrastructure, which restricts their capacity to fully handle the process. In order to maximize a set of oil exploitation variables in a hierarchical fashion, this research proposes a novel assisted optimization technique that combines mathematical algorithms with engineering analysis. By grouping variables into …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 29–34 Read article
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Fractional Homotopy Analysis Transform Method for a Fin Having Temperature Dependent Internal Heat Generation
Abstract: Fractional Homotopy Analysis Transform Method (FHATM) is a new analytical tool for solving homogeneous and non-homogeneous fin equations. FHATM is a novel and innovative modification in Laplace Transform Algorithm (LTA) thus making analysis easier. Non-linear problems are solved by proposed technique without using Adomian and He’s polynomial which is a clear benefit of this new algorithm over decomposition and homotopy perturbation transform methods. This is an elementary technique which gives …
Published in Journal of Experimental & Applied Mechanics · Vol. 10, Issue 1, 2019 · pp. 23–34 Read article
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A Novel Technique Reduce Image Encryption And Decryption Time With Using Parallel Processing
Abstract: Electronic commerce commonly known as e-commerce, trade in products using the internet. Security at the e-commerce becomes more and more important. For example, if you pay through the internet you want to be sure, that nobody can get your payment information. To prevent the misuse of personal data in the field of online banking. Public key biometric identification is a sequence of bytes used to authenticate, biometric identifications are built …
Published in E-Commerce for Future & Trends · Vol. 2, Issue 3, 2015 · pp. 27–34 Read article
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A Secure Approach for Cross-chain Transactions Using Machine Learning Model
Abstract: The ability to conduct transactions or transfer assets between different blockchain networks is referred to as cross-chain transactions. It enables users to transfer assets from one blockchain network to another. In the Cryptocurrency ecosystem, the risk of fraudulent activities has become a significant concern. Due to these fraudulent activities, the cross-chain transactions have encountered challenges in terms of security and integrity. The need for robust fraud detection mechanisms becomes crucial …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 17–24 Read article
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Adaptive Huffman Algorithm for Data Compression Using Text Clustering and Multiple Character Modification
Abstract: Adaptive Huffman algorithm is a popular data compression technique that creates a variable-length binary code for each symbol in a message. However, the original algorithm may not be efficient in compressing text data, particularly when dealing with long sequences of repeated characters. In this study, we propose a novel approach to enhance the compression ratio of the Adaptive Huffman algorithm by utilizing text clustering and multiple character modification. The proposed …
Published in Recent Trends in Programming languages · Vol. 10, Issue 1, 2023 · pp. 30–40 Read article
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A Novel Approach for Confidence Estimation using Support Vector Machines for More Accurate Value Prediction
Abstract: Data dependencies create hurdles in exploiting instruction-level parallelism (ILP) among instructions. To overcome them, data value predictors are used which guess instructions’ result before it is actually executed. Thus, future instructions which depend on the outcome of that instruction executes sooner. But, since value prediction accuracy is very crucial in determining the amount of parallelism that can be exploited, confidence estimation is used along with it to lessen the value …
Published in Journal of Advancements in Robotics · Vol. 1, Issue 2, 2014 · pp. 18–29 Read article
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An Improved K-means Clustering Algorithm for Classification of Odor/Gas Sensor Data Using Normalized Cosine Distance Parameter
Abstract: This paper presents a novel approach of K-means Clustering for classification of odors/gases (E-nose) using cosine distance as a distance parameter. A sensor array constituting five sensors is exposed to four different types of gases to extract data. The problem of classifying the data into respective classes in considered as a K-means Clustering task. To quantify the amount of similitude between the data corresponding to same classes; usually euclidean distance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 56–60 Read article
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A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article