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  • Open Access

    ARTICLE

    A Fog Covered Object Recognition Algorithm Based On Space And Frequency Network

    Ying Cui1, Shi Qiu2,*, Tong Li3

    Intelligent Automation & Soft Computing, Vol.28, No.2, pp. 417-428, 2021, DOI:10.32604/iasc.2021.016802

    Abstract It is difficult to recognize a target object from foggy images. Aiming at solving this problem, a new algorithm is thereby proposed. Fog concentration estimation is the prerequisite for image defogging. Due to the uncertainty of fog distribution, a fog concentration estimation model is accordingly proposed. Establish the brightness and gradient model in the spatial domain, and establish the FFT model in the frequency domain. Also, a multiple branch network framework is established to realize the qualitative estimation of the fog concentration in images based on comprehensive analysis from spatial and frequency domain levels. In the aspect of foggy image… More >

  • Open Access

    ARTICLE

    CAMNet: DeepGait Feature Extraction via Maximum Activated Channel Localization

    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 >

  • Open Access

    ARTICLE

    Earth Fault Management for Smart Grids Interconnecting Sustainable Wind Generation

    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 >

  • Open Access

    ARTICLE

    HPMC: A Multi-target Tracking Algorithm for the IoT

    Xinyue Lv1, Xiaofeng Lian2,*, 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 >

  • Open Access

    ARTICLE

    Tomato Leaf Disease Identification and Detection Based on Deep Convolutional Neural Network

    Yang Wu1, Lihong Xu1,*, 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 >

  • Open Access

    ARTICLE

    Secure Image Authentication Using Watermarking and Blockchain

    Alsehli Abrar1, Wadood Abdul1,*, 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 >

  • Open Access

    ARTICLE

    Leverage External Knowledge and Self-attention for Chinese Semantic Dependency Graph Parsing

    Dianqing Liu1,2, Lanqiu Zhang1,2, Yanqiu Shao1,2,*, 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 >

  • Open Access

    ARTICLE

    Designing an Online Appointment System for Semiliterate Users

    Sarah Chaudhry1, Fakhra Batool1, Abdul Hafeez Muhammad1, Ansar Siddique2,*

    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 >

  • Open Access

    ARTICLE

    AI/ML in Security Orchestration, Automation and Response: Future Research Directions

    Johnson Kinyua1, Lawrence Awuah2,*

    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 >

  • Open Access

    ARTICLE

    Exact Analysis of Second Grade Fluid with Generalized Boundary Conditions

    Syed Tauseef Saeed1, Muhammad Bilal Riaz2,3, Dumitru Baleanu4,5,7,*, 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 >

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