Yang Zhou, Chunjiao Fu, Yuting Zhai, Jian Li, Ziqi Jin, Yanlei Xu^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4501-4517, 2023, DOI:10.32604/cmc.2023.038446

Abstract Accurate identification of rice diseases is crucial for controlling diseases and improving rice yield. To improve the classification accuracy of rice diseases, this paper proposed a classification and identification method based on an improved ShuffleNet V2 (GE-ShuffleNet) model. Firstly, the Ghost module is used to replace the convolution in the two basic unit modules of ShuffleNet V2, and the unimportant convolution is deleted from the two basic unit modules of ShuffleNet V2. The Hardswish activation function is applied to replace the ReLU activation function to improve the identification accuracy of the model. Secondly, an effective channel attention (ECA) module is… More >

Tusongjiang. Kari¹, Lin Du¹, Aisikaer. Rouzi², Xiaojing Ma^1,*, Zhichao Liu¹, Bo Li¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4573-4592, 2023, DOI:10.32604/cmc.2023.037954

Abstract The imbalance of dissolved gas analysis (DGA) data will lead to over-fitting, weak generalization and poor recognition performance for fault diagnosis models based on deep learning. To handle this problem, a novel transformer fault diagnosis method based on improved auxiliary classifier generative adversarial network (ACGAN) under imbalanced data is proposed in this paper, which meets both the requirements of balancing DGA data and supplying accurate diagnosis results. The generator combines one-dimensional convolutional neural networks (1D-CNN) and long short-term memories (LSTM), which can deeply extract the features from DGA samples and be greatly beneficial to ACGAN’s data balancing and fault diagnosis.… More >

Chaoyang Li, Hongxue Shen, Xiayang Shi, Hui Liang^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3941-3956, 2023, DOI:10.32604/cmc.2023.037796

Abstract Data security and user privacy are two main security concerns in the cold-chain logistics system (CCLS). Many security issues exist in traditional CCLS, destroying data security and user privacy. The digital signature can provide data verification and identity authentication based on the mathematical difficulty problem for logistics data sharing in CCLS. This paper first established a blockchain-enabled cold-chain logistics system (BCCLS) based on union blockchain technology, which can provide secure data sharing among different logistics nodes and guarantee logistics data security with the untampered blockchain ledger. Meanwhile, a lattice-based undeniable signature scheme is designed to strengthen the security of logistics… More >

Yingmei Li, Peng Han, Wei He^*, Guangling Zhang, Hongwei Wei, Boying Zhao

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3761-3780, 2023, DOI:10.32604/cmc.2023.037686

Abstract Prediction systems are an important aspect of intelligent decisions. In engineering practice, the complex system structure and the external environment cause many uncertain factors in the model, which influence the modeling accuracy of the model. The belief rule base (BRB) can implement nonlinear modeling and express a variety of uncertain information, including fuzziness, ignorance, randomness, etc. However, the BRB system also has two main problems: Firstly, modeling methods based on expert knowledge make it difficult to guarantee the model’s accuracy. Secondly, interpretability is not considered in the optimization process of current research, resulting in the destruction of the interpretability of… More >

Chunzhi Wang, Weidong Cao^*, Yalin Hu, Jinhang Liu

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4377-4393, 2023, DOI:10.32604/cmc.2023.037625

Abstract According to Cisco’s Internet Report 2020 white paper, there will be 29.3 billion connected devices worldwide by 2023, up from 18.4 billion in 2018. 5G connections will generate nearly three times more traffic than 4G connections. While bringing a boom to the network, it also presents unprecedented challenges in terms of flow forwarding decisions. The path assignment mechanism used in traditional traffic scheduling methods tends to cause local network congestion caused by the concentration of elephant flows, resulting in unbalanced network load and degraded quality of service. Using the centralized control of software-defined networks, this study proposes a data center… More >

Zixiong Wang, Qiuying Chen, Sang-Joon Lee^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2443-2459, 2023, DOI:10.32604/cmc.2023.037553

Abstract The rapid expansion of the non-fungible token (NFT) market has attracted many investors. However, studies on the NFT price fluctuations have been relatively limited. To date, the machine learning approach has not been used to demonstrate a specific error in NFT sale price fluctuation prediction. The aim of this study was to develop a prediction model for NFT price fluctuations using the NFT trading information obtained from OpenSea, the world’s largest NFT marketplace. We used Python programs to collect data and summarized them as: NFT information, collection information, and related account information. AdaBoost and Random Forest (RF) algorithms were employed… More >

Xinyi Qing^1,3, Baopeng Ye², Yuanquan Shi^1,3, Tao Li^4,*, Yuling Chen⁴, Lei Liu¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3607-3624, 2023, DOI:10.32604/cmc.2023.037532

Abstract Due to its decentralized, tamper-proof, and trust-free characteristics, blockchain is used in the Internet of Things (IoT) to guarantee the reliability of data. However, some technical flaws in blockchain itself prevent the development of these applications, such as the issue with linearly growing storage capacity of blockchain systems. On the other hand, there is a lack of storage resources for sensor devices in IoT, and numerous sensor devices will generate massive data at ultra-high speed, which makes the storage problem of the IoT enabled by blockchain more prominent. There are various solutions to reduce the storage burden by modifying the… More >

Amjad Hussain Zahid¹, Muhammad Junaid Arshad², Musheer Ahmad^3,*, Naglaa F. Soliman⁴, Walid El-Shafai^5,6

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3011-3026, 2023, DOI:10.32604/cmc.2023.037516

Abstract A substitution box (S-Box) is a crucial component of contemporary cryptosystems that provide data protection in block ciphers. At the moment, chaotic maps are being created and extensively used to generate these S-Boxes as a chaotic map assists in providing disorder and resistance to combat cryptanalytical attempts. In this paper, the construction of a dynamic S-Box using a cipher key is proposed using a novel chaotic map and an innovative tweaking approach. The projected chaotic map and the proposed tweak approach are presented for the first time and the use of parameters in their working makes both of these dynamic… More >

Baraa Wasfi Salim¹, Bzar Khidir Hussan², Zainab Salih Ageed³, Subhi R. M. Zeebaree^4,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4593-4609, 2023, DOI:10.32604/cmc.2023.037514

Abstract Recently, human healthcare from body sensor data has gained considerable interest from a wide variety of human-computer communication and pattern analysis research owing to their real-time applications namely smart healthcare systems. Even though there are various forms of utilizing distributed sensors to monitor the behavior of people and vital signs, physical human action recognition (HAR) through body sensors gives useful information about the lifestyle and functionality of an individual. This article concentrates on the design of an Improved Transient Search Optimization with Machine Learning based Behavior Recognition (ITSOML-BR) technique using body sensor data. The presented ITSOML-BR technique collects data from… More >

Jirasak Ji, Warut Pannakkong^*, Jirachai Buddhakulsomsiri

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3643-3656, 2023, DOI:10.32604/cmc.2023.037507

Abstract Inventory counting is crucial to manufacturing industries in terms of inventory management, production, and procurement planning. Many companies currently require workers to manually count and track the status of materials, which are repetitive and non-value-added activities but incur significant costs to the companies as well as mental fatigue to the employees. This research aims to develop a computer vision system that can automate the material counting activity without applying any marker on the material. The type of material of interest is metal sheet, whose shape is simple, a large rectangular shape, yet difficult to detect. The use of computer vision… More >