Kunkun Wang^1,2, Xianda Liu^2,3,4,*

Journal on Artificial Intelligence, Vol.3, No.1, pp. 9-19, 2021, DOI:10.32604/jai.2021.016706

Abstract With the development of Internet technology, the computing power of data has increased, and the development of machine learning has become faster and faster. In the industrial production of industrial control systems, quality inspection and safety production of process products have always been our concern. Aiming at the low accuracy of anomaly detection in process data in industrial control system, this paper proposes an anomaly detection method based on stacking integration using the machine learning algorithm. Data are collected from the industrial site and processed by feature engineering. Principal component analysis (PCA) and integrated rule tree method are adopted to… More >

Yang Wu¹, Lihong Xu^1,*, Erik D. Goodman²

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 561-576, 2021, DOI:10.32604/iasc.2021.016415

Abstract Deep convolutional neural network (DCNN) requires a lot of data for training, but there has always been data vacuum in agriculture, making it difficult to label all existing data accurately. Therefore, a lightweight tomato leaf disease identification network supported by Variational auto-Encoder (VAE) is proposed to improve the accuracy of crop leaf disease identification. In the lightweight network, multi-scale convolution can expand the network width, enrich the extracted features, and reduce model parameters such as deep separable convolution. VAE makes full use of a large amount of unlabeled data to achieve unsupervised learning, and then uses labeled data for supervised… More >

Sameer I. Ali Al-Janabi¹, Belal Al-Khateeb^2,*, Maha Mahmood², Begonya Garcia-Zapirain³

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 293-303, 2021, DOI:10.32604/iasc.2021.014419

Abstract The recent novel coronavirus (COVID-19, as the World Health Organization has called it) has proven to be a source of risk for global public health. The virus, which causes an acute respiratory disease in persons, spreads rapidly and is now threatening more than 150 countries around the world. One of the essential procedures that patients with COVID-19 need is an accurate and rapid screening process. In this research, utilizing the features of deep learning methods, we present a method for detecting COVID-19 and a screening model that uses pulmonary computed tomography images to differentiate COVID-19 pneumonia from healthy cases. In… More >

Xianqing Chen^1,2, Yan Yan^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 325-343, 2021, DOI:10.32604/cmes.2021.014489

Abstract Alcoholism is an unhealthy lifestyle associated with alcohol dependence. Not only does drinking for a long time leads to poor mental health and loss of self-control, but alcohol seeps into the bloodstream and shortens the lifespan of the body’s internal organs. Alcoholics often think of alcohol as an everyday drink and see it as a way to reduce stress in their lives because they cannot see the damage in their bodies and they believe it does not affect their physical health. As their drinking increases, they become dependent on alcohol and it affects their daily lives. Therefore, it is important… More >

Afiqah Halim¹, Wan Azani Mustafa^1,2,*, Wan Khairunizam Wan Ahmad¹, Hasliza A. Rahim², Hamzah Sakeran³

Oncologie, Vol.23, No.1, pp. 73-88, 2021, DOI:10.32604/Oncologie.2021.015154

Abstract Cervical cancer is a cell disease in the cervix that develops out of control in the female body. The cervix links the vagina (birth canal) with the upper section of the uterus, which can only be found in the female body. This is the second leading cause of death among women around the world. However, cervical cancer is currently one of the most preventable cancers if early detection is identified. The effect of unidentified cancer may increase the risk of death when the cell disease spreads to other parts of the female anatomy (metastasize). The Papanicolaou test is a cervical… More >

Qian Xu^1,*, Haitao Wang^1,2, Zhenhua Chen³, Zhigang Huang³, Pan Hu¹

Structural Durability & Health Monitoring, Vol.15, No.1, pp. 39-52, 2021, DOI:10.32604/sdhm.2021.014815

Abstract Crack detection in an aerospace turbine disk is essential for aircraft- quality detection. With the unique circular stepped structure and superalloy material properties of aerospace turbine disk, it is difficult for the traditional ultrasonic testing method to perform efficient and accurate testing. In this study, ultrasound phased array detection technology was applied to the non-destructive testing of aviation turbine disks: (i) A phased array ultrasonic c-scan device for detecting aerospace turbine disk cracks (PAUDA) was developed which consists of phased array ultrasonic, transducers, a computer, a displacement encoder, and a rotating scanner; (ii) The influence of the detection parameters include… More >

Dongyue Gao¹, Yunlong Ma², Zhanjun Wu^3,*, Yuebin Zheng³, Hongbo Lu¹

Structural Durability & Health Monitoring, Vol.15, No.1, pp. 23-37, 2021, DOI:10.32604/sdhm.2021.013737

Abstract Guided waves based damage detection methods using base signals offer the advantages of simplicity of signal generation and reception, sensitivity to damage, and large area coverage; however, applications of the technology are limited by the sensitivity to environmental temperature variations. In this paper, a Spearman Damage Index-based damage diagnosis method for structural health condition monitoring under varying temperatures is presented. First, a PZT sensor-based Guided wave propagation model is proposed and employed to analyze the temperature effect. The result of the analysis shows the wave speed of the Guided wave signal has higher temperature sensitivity than the signal fluctuation features.… More >

Bozhi Xu¹, Jiarui Liu¹, Jifan Liang¹, Wei Lu^1,*, Yue Zhang²

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1375-1388, 2021, DOI:10.32604/cmc.2021.016760

Abstract In recent years, with the rapid development of deep learning technologies, some neural network models have been applied to generate fake media. DeepFakes, a deep learning based forgery technology, can tamper with the face easily and generate fake videos that are difficult to be distinguished by human eyes. The spread of face manipulation videos is very easy to bring fake information. Therefore, it is important to develop effective detection methods to verify the authenticity of the videos. Due to that it is still challenging for current forgery technologies to generate all facial details and the blending operations are used in… More >

Jialin Wan¹, Muhammad Waqas^1,2, Shanshan Tu^1,*, Syed Mudassir Hussain³, Ahsan Shah², Sadaqat Ur Rehman⁴, Muhammad Hanif²

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 267-281, 2021, DOI:10.32604/cmc.2021.016260

Abstract Fog computing paradigm extends computing, communication, storage, and network resources to the network’s edge. As the fog layer is located between cloud and end-users, it can provide more convenience and timely services to end-users. However, in fog computing (FC), attackers can behave as real fog nodes or end-users to provide malicious services in the network. The attacker acts as an impersonator to impersonate other legitimate users. Therefore, in this work, we present a detection technique to secure the FC environment. First, we model a physical layer key generation based on wireless channel characteristics. To generate the secret keys between the… More >

Omar Almomani^*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 409-429, 2021, DOI:10.32604/cmc.2021.016113

Abstract Network Intrusion Detection System (IDS) aims to maintain computer network security by detecting several forms of attacks and unauthorized uses of applications which often can not be detected by firewalls. The features selection approach plays an important role in constructing effective network IDS. Various bio-inspired metaheuristic algorithms used to reduce features to classify network traffic as abnormal or normal traffic within a shorter duration and showing more accuracy. Therefore, this paper aims to propose a hybrid model for network IDS based on hybridization bio-inspired metaheuristic algorithms to detect the generic attack. The proposed model has two objectives; The first one… More >