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  • Open Access

    ARTICLE

    Artificial Intelligence in Internet of Things System for Predicting Water Quality in Aquaculture Fishponds

    Po-Yuan Yang1,*, Yu-Cheng Liao2, Fu-I Chou2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2861-2880, 2023, DOI:10.32604/csse.2023.036810 - 03 April 2023

    Abstract Aquaculture has long been a critical economic sector in Taiwan. Since a key factor in aquaculture production efficiency is water quality, an effective means of monitoring the dissolved oxygen content (DOC) of aquaculture water is essential. This study developed an internet of things system for monitoring DOC by collecting essential data related to water quality. Artificial intelligence technology was used to construct a water quality prediction model for use in a complete system for managing water quality. Since aquaculture water quality depends on a continuous interaction among multiple factors, and the current state is correlated… More >

  • Open Access

    ARTICLE

    MNIST Handwritten Digit Classification Based on Convolutional Neural Network with Hyperparameter Optimization

    Haijian Shao1, Edwin Ma2, Ming Zhu1, Xing Deng3, Shengjie Zhai1,*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3595-3606, 2023, DOI:10.32604/iasc.2023.036323 - 15 March 2023

    Abstract Accurate handwriting recognition has been a challenging computer vision problem, because static feature analysis of the text pictures is often inadequate to account for high variance in handwriting styles across people and poor image quality of the handwritten text. Recently, by introducing machine learning, especially convolutional neural networks (CNNs), the recognition accuracy of various handwriting patterns is steadily improved. In this paper, a deep CNN model is developed to further improve the recognition rate of the MNIST handwritten digit dataset with a fast-converging rate in training. The proposed model comes with a multi-layer deep arrange More >

  • Open Access

    ARTICLE

    Analysis of Additional Damping Control Strategy and Parameter Optimization for Improving Small Signal Stability of VSC-HVDC System

    Hui Fang1, Jingsen Zhou1, Hanjie Liu2,*, Yanxu Wang2, Hongji Xiang1, Yechun Xin2

    Energy Engineering, Vol.120, No.4, pp. 931-948, 2023, DOI:10.32604/ee.2023.025163 - 13 February 2023

    Abstract The voltage source converter based high voltage direct current (VSC-HVDC) system is based on voltage source converter, and its control system is more complex. Also affected by the fast control of power electronics, oscillation phenomenon in wide frequency domain may occur. To address the problem of small signal stability of the VSC-HVDC system, a converter control strategy is designed to improve its small signal stability, and the risk of system oscillation is reduced by attaching a damping controller and optimizing the control parameters. Based on the modeling of the VSC-HVDC system, the general architecture of… More >

  • Open Access

    ARTICLE

    Earthworm Optimization with Improved SqueezeNet Enabled Facial Expression Recognition Model

    N. Sharmili1, Saud Yonbawi2, Sultan Alahmari3, E. Laxmi Lydia4, Mohamad Khairi Ishak5, Hend Khalid Alkahtani6,*, Ayman Aljarbouh7, Samih M. Mostafa8

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2247-2262, 2023, DOI:10.32604/csse.2023.036377 - 09 February 2023

    Abstract Facial expression recognition (FER) remains a hot research area among computer vision researchers and still becomes a challenge because of high intra-class variations. Conventional techniques for this problem depend on hand-crafted features, namely, LBP, SIFT, and HOG, along with that a classifier trained on a database of videos or images. Many execute perform well on image datasets captured in a controlled condition; however not perform well in the more challenging dataset, which has partial faces and image variation. Recently, many studies presented an endwise structure for facial expression recognition by utilizing DL methods. Therefore, this… More >

  • Open Access

    ARTICLE

    Intelligent Modulation Recognition of Communication Signal for Next-Generation 6G Networks

    Mrim M. Alnfiai*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5723-5740, 2023, DOI:10.32604/cmc.2023.033408 - 28 December 2022

    Abstract In recent years, the need for a fast, efficient and a reliable wireless network has increased dramatically. Numerous 5G networks have already been tested while a few are in the early stages of deployment. In non-cooperative communication scenarios, the recognition of digital signal modulations assists people in identifying the communication targets and ensures an effective management over them. The recent advancements in both Machine Learning (ML) and Deep Learning (DL) models demand the development of effective modulation recognition models with self-learning capability. In this background, the current research article designs a Deep Learning enabled Intelligent… More >

  • Open Access

    ARTICLE

    Optimal Structural Parameters for a Plastic Centrifugal Pump Inducer

    Wenbin Luo1,*, Lingfeng Tang1, Yuting Yan2, Yifang Shi1

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.4, pp. 869-899, 2023, DOI:10.32604/fdmp.2022.022280 - 02 November 2022

    Abstract The aim of the study is to determine the optimal structural parameters for a plastic centrifugal pump inducer within the framework of an orthogonal experimental method. For this purpose, a numerical study of the related flow field is performed using CFX. The shaft power and the head of the pump are taken as the evaluation indicators. Accordingly, the examined variables are the thickness (S), the blade cascade degree (t), the blade rim angle (β1), the blade hub angle (β2) and the hub length (L). The impact of each structural parameter on each evaluation index is More >

  • Open Access

    ARTICLE

    A Hyperparameter Optimization for Galaxy Classification

    Fatih Ahmet Şenel*

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4587-4600, 2023, DOI:10.32604/cmc.2023.033155 - 31 October 2022

    Abstract In this study, the morphological galaxy classification process was carried out with a hybrid approach. Since the Galaxy classification process may contain detailed information about the universe’s formation, it remains the current research topic. Researchers divided more than 100 billion galaxies into ten different classes. It is not always possible to understand which class the galaxy types belong. However, Artificial Intelligence (AI) can be used for successful classification. There are studies on the automatic classification of galaxies into a small number of classes. As the number of classes increases, the success of the used methods… More >

  • Open Access

    ARTICLE

    Optimal Deep Transfer Learning Based Colorectal Cancer Detection and Classification Model

    Mahmoud Ragab1,2,3,*, Maged Mostafa Mahmoud4,5,6, Amer H. Asseri2,7, Hani Choudhry2,7, Haitham A. Yacoub8

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3279-3295, 2023, DOI:10.32604/cmc.2023.031037 - 31 October 2022

    Abstract Colorectal carcinoma (CRC) is one such dispersed cancer globally and also prominent one in causing cancer-based death. Conventionally, pathologists execute CRC diagnosis through visible scrutinizing under the microscope the resected tissue samples, stained and fixed through Haematoxylin and Eosin (H&E). The advancement of graphical processing systems has resulted in high potentiality for deep learning (DL) techniques in interpretating visual anatomy from high resolution medical images. This study develops a slime mould algorithm with deep transfer learning enabled colorectal cancer detection and classification (SMADTL-CCDC) algorithm. The presented SMADTL-CCDC technique intends to appropriately recognize the occurrence of… More >

  • Open Access

    ARTICLE

    Effective Return Rate Prediction of Blockchain Financial Products Using Machine Learning

    K. Kalyani1, Velmurugan Subbiah Parvathy2, Hikmat A. M. Abdeljaber3, T. Satyanarayana Murthy4, Srijana Acharya5, Gyanendra Prasad Joshi6, Sung Won Kim7,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2303-2316, 2023, DOI:10.32604/cmc.2023.033162 - 22 September 2022

    Abstract In recent times, financial globalization has drastically increased in different ways to improve the quality of services with advanced resources. The successful applications of bitcoin Blockchain (BC) techniques enable the stockholders to worry about the return and risk of financial products. The stockholders focused on the prediction of return rate and risk rate of financial products. Therefore, an automatic return rate bitcoin prediction model becomes essential for BC financial products. The newly designed machine learning (ML) and deep learning (DL) approaches pave the way for return rate predictive method. This study introduces a novel Jellyfish… More >

  • Open Access

    ARTICLE

    Jellyfish Search Optimization with Deep Learning Driven Autism Spectrum Disorder Classification

    S. Rama Sree1, Inderjeet Kaur2, Alexey Tikhonov3, E. Laxmi Lydia4, Ahmed A. Thabit5, Zahraa H. Kareem6, Yousif Kerrar Yousif7, Ahmed Alkhayyat8,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2195-2209, 2023, DOI:10.32604/cmc.2023.032586 - 22 September 2022

    Abstract Autism spectrum disorder (ASD) is regarded as a neurological disorder well-defined by a specific set of problems associated with social skills, recurrent conduct, and communication. Identifying ASD as soon as possible is favourable due to prior identification of ASD permits prompt interferences in children with ASD. Recognition of ASD related to objective pathogenic mutation screening is the initial step against prior intervention and efficient treatment of children who were affected. Nowadays, healthcare and machine learning (ML) industries are combined for determining the existence of various diseases. This article devises a Jellyfish Search Optimization with Deep… More >

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