Salisu Muhammed^*, Erbuğ Çelebi

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 397-416, 2021, DOI:10.32604/iasc.2021.016574

Abstract As the models with fewer operations help realize the performance of intelligent computing systems, we propose a novel deep network for DeepGait feature extraction with less operation for video sensor-based gait representation without dimension decomposition. The DeepGait has been known to have outperformed the hand-crafted representations, such as the frequency-domain feature (FDF), gait energy image (GEI), and gait flow image (GFI), etc. More explicitly, the channel-activated mapping network (CAMNet) is composed of three progressive triplets of convolution, batch normalization, max-pooling layers, and an external max pooling to capture the Spatio-temporal information of multiple frames in one gait period. We conducted… More >

Nagy I. Elkalashy^*, Sattam Al Otaibi, Salah K. Elsayed, Yasser Ahmed, Essam Hendawi, Ayman Hoballah

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 477-491, 2021, DOI:10.32604/iasc.2021.016558

Abstract In this study, the active traveling-wave fault location function is incorporated into the management of earth faults for smart unearthed and compensated distribution networks associated with distributed renewable generation. Unearthed and compensated networks are implemented mainly to attain service continuity, specifically during earth faults. This advantage is valued for service continuity of grid-interconnected renewable resources. However, overcurrent-based fault indicators are not efficient in indicating the fault path in these distribution networks. Accordingly, in this study, the active traveling-wave fault location is complemented using distributed Rogowski coil-based fault passage indicators. Active traveling waves are injected by switching the neutral point of… More >

Xinyue Lv¹, Xiaofeng Lian^2,*, Li Tan¹, Yanyan Song¹, Chenyu Wang³

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 513-526, 2021, DOI:10.32604/iasc.2021.016450

Abstract With the rapid development of the Internet of Things and advanced sensors, vision-based monitoring and forecasting applications have been widely used. In the context of the Internet of Things, visual devices can be regarded as network perception nodes that perform complex tasks, such as real-time monitoring of road traffic flow, target detection, and multi-target tracking. We propose the High-Performance detection and Multi-Correlation measurement algorithm (HPMC) to address the problem of target occlusion and perform trajectory correlation matching for multi-target tracking. The algorithm consists of three modules: 1) For the detection module, we proposed the You Only Look Once(YOLO)v3_plus model, which… 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 >

Alsehli Abrar¹, Wadood Abdul^1,*, Sanaa Ghouzali²

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 577-591, 2021, DOI:10.32604/iasc.2021.016382

Abstract Image authentication is an important field that employs many different approaches and has several significant applications. In the proposed approach, we used a combination of two techniques to achieve authentication. Image watermarking is one of the techniques that has been used in many studies but the authentication field still needs to be studied. Blockchain technology is a relatively new technology that has significant research potential related to image authentication. The watermark is embedded into the third-level discrete wavelet transform (DWT) in the middle frequency regions to achieve security and imperceptibility goals. Peak signal-to-noise ratio PSNR, structural similarity matrix (SSIM), normalized… More >

Dianqing Liu^1,2, Lanqiu Zhang^1,2, Yanqiu Shao^1,2,*, Junzhao Sun³

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 447-458, 2021, DOI:10.32604/iasc.2021.016320

Abstract Chinese semantic dependency graph (CSDG) parsing aims to analyze the semantic relationship between words in a sentence. Since it is a deep semantic analysis task, the parser needs a lot of prior knowledge about the real world to distinguish different semantic roles and determine the range of the head nodes of each word. Existing CSDG parsers usually use part-of-speech (POS) and lexical features, which can only provide linguistic knowledge, but not semantic knowledge about the word. To solve this problem, we propose an entity recognition method based on distant supervision and entity classification to recognize entities in sentences, and then… More >

Sarah Chaudhry¹, Fakhra Batool¹, Abdul Hafeez Muhammad¹, Ansar Siddique^2,*

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 379-395, 2021, DOI:10.32604/iasc.2021.016263

Abstract Information and Communications Technology (ICT) has revolutionized the healthcare leading to provision of eHealth facilities remotely. During the peak time of COVID-19, as the long queues at health care facilities can result in spread of the virus. ICT can play an effective role especially for reducing the extended waiting time of patients to consult a medical practitioner which is considered as a source of hazard during the pandemic. However, in developing countries where majority population is semiliterate so find difficulty when come into contact with appointment systems which are not particularly designed keeping in consideration the requirements of semiliterate users.… More >

Johnson Kinyua¹, Lawrence Awuah^2,*

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 527-545, 2021, DOI:10.32604/iasc.2021.016240

Abstract Today’s cyber defense capabilities in many organizations consist of a diversity of tools, products, and solutions, which are very challenging for Security Operations Centre (SOC) teams to manage in current advanced and dynamic cyber threat environments. Security researchers and industry practitioners have proposed security orchestration, automation, and response (SOAR) solutions designed to integrate and automate the disparate security tasks, processes, and applications in response to security incidents to empower SOC teams. The next big step for cyber threat detection, mitigation, and prevention efforts is to leverage AI/ML in SOAR solutions. AI/ML will act as a force multiplier empowering SOC analysts… More >

Syed Tauseef Saeed¹, Muhammad Bilal Riaz^2,3, Dumitru Baleanu^4,5,7,*, Ali Akgül⁶, Syed Muhammad Husnine¹

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 547-559, 2021, DOI:10.32604/iasc.2021.015982

Abstract Convective flow is a self-sustained flow with the effect of the temperature gradient. The density is non-uniform due to the variation of temperature. The effect of the magnetic flux plays a major role in convective flow. The process of heat transfer is accompanied by mass transfer process; for instance condensation, evaporation and chemical process. Due to the applications of the heat and mass transfer combined effects in different field, the main aim of this paper is to do comprehensive analysis of heat and mass transfer of MHD unsteady second-grade fluid in the presence of time dependent generalized boundary conditions. The… More >

Amjed Basil Abdulkareem¹, Nor Samsiah Sani^1,*, Shahnorbanun Sahran¹, Zaid Abdi Alkareem Alyessari¹, Afzan Adam¹, Abdul Hadi Abd Rahman¹, Abdulkarem Basil Abdulkarem²

Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 305-320, 2021, DOI:10.32604/iasc.2021.015413

Abstract The coronavirus disease 2019 (COVID-19) has infected more than 50 million people in more than 100 countries, resulting in a major global impact. Many studies on the potential roles of environmental factors in the transmission of the novel COVID-19 have been published. However, the impact of environmental factors on COVID-19 remains controversial. Machine learning techniques have been used effectively in combating the COVID-19 epidemic. However, researches related to machine learning on weather conditions in spreading COVID-19 is generally lacking. Therefore, in this study, three machine learning models (Convolution Neural Network (CNN), ADtree Classifier and BayesNet) based on the confirmed cases… More >