Pranamita Nanda^1,*, N. Duraipandian²

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1099-1110, 2022, DOI:10.32604/csse.2022.024695 - 09 May 2022

Abstract In severe cases, diabetic retinopathy can lead to blindness. For decades, automatic classification of diabetic retinopathy images has been a challenge. Medical image processing has benefited from advances in deep learning systems. To enhance the accuracy of image classification driven by Convolutional Neural Network (CNN), balanced dataset is generated by data augmentation method followed by an optimized algorithm. Deep neural networks (DNN) are frequently optimized using gradient (GD) based techniques. Vanishing gradient is the main drawback of GD algorithms. In this paper, we suggest an innovative algorithm, to solve the above problem, Hypergradient Descent learning… More >

Srinivasan Ananthanarayanan Bragadeesh, Arumugam Umamakeswari^*

Computer Systems Science and Engineering, Vol.41, No.1, pp. 1-18, 2022, DOI:10.32604/csse.2022.019842 - 08 October 2021

Abstract Life Cycle Tracking (LCT) involves continuous monitoring and analysis of various activities associated with a vehicle. The crucial factor in the LCT is to ensure the validity of gathered data as numerous supply chain phases are involved and the data is assessed by multiple stakeholders. Frauds and swindling activities can be prevented if the history of the vehicles is made available to the interested parties. Blockchain provides a way of enforcing trustworthiness to the supply chain participants and the data associated with the various actions performed. Machine learning techniques when combined decentralized nature of blockchains… More >

Muhammad Shoukat Aslam¹, Taher M. Ghazal^2,3, Areej Fatima⁴, Raed A. Said⁵, Sagheer Abbas¹, Muhammad Adnan Khan^6,7,*, Shahan Yamin Siddiqui^1,8, Munir Ahmad¹

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 881-888, 2021, DOI:10.32604/iasc.2021.017920 - 20 August 2021

Abstract The real-time management and control of heating-system networks in residential buildings has tremendous energy-saving potential, and accurate load prediction is the basis for system monitoring. In this regard, selecting the appropriate input parameters is the key to accurate heating-load forecasting. In existing models for forecasting heating loads and selecting input parameters, with an increase in the length of the prediction cycle, the heating-load rate gradually decreases, and the influence of the outside temperature gradually increases. In view of different types of solutions for improving buildings’ energy efficiency, this study proposed a Energy-efficiency model for residential More >

V. Sudha^1,*, T. R. Ganeshbabu²

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 827-842, 2021, DOI:10.32604/cmc.2020.012008 - 30 October 2020

Abstract Diabetic Retinopathy (DR) is a type of disease in eyes as a result of a diabetic condition that ends up damaging the retina, leading to blindness or loss of vision. Morphological and physiological retinal variations involving slowdown of blood flow in the retina, elevation of leukocyte cohesion, basement membrane dystrophy, and decline of pericyte cells, develop. As DR in its initial stage has no symptoms, early detection and automated diagnosis can prevent further visual damage. In this research, using a Deep Neural Network (DNN), segmentation methods are proposed to detect the retinal defects such as… More >

Ru Jin^*, Xinlian Zhou, Yue Wang

Journal of Information Hiding and Privacy Protection, Vol.2, No.3, pp. 115-123, 2020, DOI:10.32604/jihpp.2020.010180 - 18 December 2020

Abstract In a wireless sensor network [1], the operation of a node depends on the battery power it carries. Because of the environmental reasons, the node cannot replace the battery. In order to improve the life cycle of the network, energy becomes one of the key problems in the design of the wireless sensor network (WSN) routing protocol [2]. This paper proposes a routing protocol ERGD based on the method of gradient descent that can minimizes the consumption of energy. Within the communication radius of the current node, the distance between the current node and the More >

Yasir Nawaz¹, Muhammad Shoaib Arif ¹, Mairaj Bibi^{2, *}, Javeria Nawaz Abbasi², Umer Javed³, Amna Nazeer²

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 657-677, 2020, DOI:10.32604/cmc.2020.08584

Abstract Present contribution is concerned with the construction and application of a numerical method for the fluid flow problem over a linearly stretching surface with the modification of standard Gradient descent Algorithm to solve the resulted difference equation. The flow problem is constructed using continuity, and Navier Stoke equations and these PDEs are further converted into boundary value problem by applying suitable similarity transformations. A central finite difference method is proposed that gives third-order accuracy using three grid points. The stability conditions of the present proposed method using a Gauss-Seidel iterative procedure is found using VonNeumann… More >

Chung Wen Hung, Wei Lung Mao, Han Yi Huang

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 329-341, 2019, DOI:10.31209/2019.100000093

Abstract Nonlinear system modeling and identification is the one of the most important areas in engineering problem. The paper presents the recurrent fuzzy neural network (RFNN) trained by modified particle swarm optimization (MPSO) methods for identifying the dynamic systems and chaotic observation prediction. The proposed MPSO algorithms mainly modify the calculation formulas of inertia weights. Two MPSOs, namely linear decreasing particle swarm optimization (LDPSO) and adaptive particle swarm optimization (APSO) are developed to enhance the convergence behavior in learning process. The RFNN uses MPSO based method to tune the parameters of the membership functions, and it More >