Journals / IASC / Vol.27, No.1

  • ARTICLE

    Tyre Inspection through Multi-State Convolutional Neural Networks

    C. Sivamani1, M. Rajeswari2, E. Golden Julie3, Y. Harold Robinson4, Vimal Shanmuganathan5, Seifedine Kadry6, Yunyoung Nam7,*
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 1-13, 2021, DOI:10.32604/iasc.2021.013705
    (This article belongs to this Special Issue: Recent Trends in Artificial Intelligence for Automated Complex Industrial Systems)
    Abstract Road accident is a potential risk to the lives of both drivers and passers-by. Many road accidents occur due to the improper condition of the vehicle tyres after long term usage. Thus, tyres need to be inspected and analyzed while manufacturing to avoid serious road problems. However, tyre wear is a multifaceted happening. It normally needs the non-linearly on many limitations, like tyre formation and plan, vehicle category, conditions of the road. Yet, tyre wear has numerous profitable and environmental inferences particularly due to maintenance costs and traffic safety implications. Thus, the risk to calculate tyre wear is therefore of… More >

  • ARTICLE

    Investigating Crucial Factors of Agile Software Development through Composite Approach

    AbdulHafeez Muhammad1, Ansar Siddique2,*, Quadri Noorulhasan Naveed3, Usman Saleem1, Mohd Abul Hasan4, Basit Shahzad5
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 15-34, 2021, DOI:10.32604/iasc.2021.014427
    (This article belongs to this Special Issue: Soft Computing Methods for Innovative Software Practices)
    Abstract The major emphasis of Software Engineering (SE) discipline is to produce successful software systems. The success of software projects is estimated through quadruple measures including budget, cost, scope, and quality. To meet this aim of SE, several software development processes are presented in the literature. Such processes are categorized into two different methodologies which are known as traditional and agile software development methodologies. The issue with traditional software development methodologies is that they had not shown any remarkable progress towards the fundamental goal of SE. Consequently, software development organizations have started to adopt agile methodologies in the pursuit of successful… More >

  • ARTICLE

    Hybrid Multimodal Biometric Template Protection

    Naima Bousnina1, Sanaa Ghouzali2,*, Mounia Mikram1,3, Maryam Lafkih1, Ohoud Nafea4, Muna Al-Razgan2, Wadood Abdul4
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 35-51, 2021, DOI:10.32604/iasc.2021.014694
    (This article belongs to this Special Issue: Soft Computing in Intrusion Detection)
    Abstract Biometric template disclosure starts gaining an important concern in deploying practical biometric authentication systems, where an assailant compromises the database for illegitimate access. To protect biometric templates from disclosure attacks, biometric authentication systems should meet these four requirements: security, diversity, revocability, and performance. Different methods have been suggested in the literature such as feature transformation techniques and biometric cryptosystems. However, no single method could satisfy the four requirements, giving rise to the deployment of hybrid mechanisms. In this context, the current paper proposes a hybrid system for multimodal biometric template protection to provide robustness against template database attacks. Herein, a… More >

  • ARTICLE

    Building Graduate Salary Grading Prediction Model Based on Deep Learning

    Jong-Yih Kuo*, Hui-Chi Lin, Chien-Hung Liu
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 53-68, 2021, DOI:10.32604/iasc.2021.014437
    Abstract Predicting salary trends of students after employment is vital for helping students to develop their career plans. Particularly, salary is not only considered employment information for students to pursue jobs, but also serves as an important indicator for measuring employability and competitiveness of graduates. This paper considers salary prediction as an ordinal regression problem and uses deep learning techniques to build a salary prediction model for determining the relative ordering between different salary grades. Specifically, to solve this problem, the model uses students’ personal information, grades, and family data as input features and employs a multi-output deep neural network to… More >

  • ARTICLE

    Image Steganography in Spatial Domain: Current Status, Techniques, and Trends

    Adeeb M. Alhomoud*
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 69-88, 2021, DOI:10.32604/iasc.2021.014773
    Abstract This research article provides an up-to-date review of spatial-domain steganography. Maintaining the communication as secure as possible when transmitting secret data through any available communication channels is the target of steganography. Currently, image steganography is the most developed field, with several techniques are provided for different image formats. Therefore, the general image steganography including the fundamental concepts, the terminology, and the applications are highlighted in this paper. Further, the paper depicts the essential characteristics between information hiding and cryptography systems. In addition, recent well-known techniques in the spatial-domain steganography, such as LSB and pixel value differencing, are discussed in detail… More >

  • ARTICLE

    SDN Controller Allocation and Assignment Based on Multicriterion Chaotic Salp Swarm Algorithm

    Suresh Krishnamoorthy1,*, Kumaratharan Narayanaswamy2
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 89-102, 2021, DOI:10.32604/iasc.2021.013643
    Abstract Increase in demand for multimedia and quality services requires 5G networks to resolve issues such as slicing, allocation, forwarding, and control using techniques such as software-defined networking (SDN) and network function virtualization. In this study, the optimum number of SDN multi-controllers are implemented based on a multi-criterion advanced genetic algorithm that takes into consideration three key parameters: Switch controller latency, hopcount, and link utilization. Preprocessing is the first step, in which delay, delay paths, hopcount, and hoppaths are computed as an information matrix (Infomat). Randomization is the second step, and consists of initially placing controllers randomly, followed by an analytical… More >

  • ARTICLE

    Improved Channel Allocation Scheme for Cognitive Radio Networks

    Shahzad Latif1, Suhail Akraam2, Arif Jamal Malik3, Aaqif Afzaal Abbasi3, Muhammad Habib3, Sangsoon Lim4,*
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 103-114, 2021, DOI:10.32604/iasc.2021.014388
    Abstract

    In recent years, wireless channel optimization technologies witnessed tremendous improvements. In this regard, research for developing wireless spectrum for accommodating a wider range of wireless devices increased. This also helped in resolving spectrum scarcity issues. Cognitive Radio (CR) is a type of wireless communication in which a transceiver can intelligently detect which communication channels are being used. To avoid interference, it instantly moves traffic into vacant channels by avoiding the occupied ones. Cognitive Radio (CR) technology showed the potential to deal with the spectrum shortage problem. The spectrum assignment is often considered as a key research challenge in Cognitive Radio… More >

  • ARTICLE

    An Improved Range Doppler Algorithm Based on Squint FMCW SAR Imaging

    Qi Chen, Wei Cui*, Jianqiu Sun, Xingguang Li, Xuyu Tian
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 115-126, 2021, DOI:10.32604/iasc.2021.011617
    Abstract The existing range-Doppler algorithms for SAR imaging are affected by a fast-time Doppler effect so they cannot be directly applied to FMCW SAR. Moreover, range migration is more evident in squint mode. To reveal the influence of the continuous motion of FMCW SAR in the squint mode on the echo signal and optimize the imaging process, an improved range-Doppler algorithm is based on squint FMCW SAR imaging is proposed in this paper. Firstly, the imaging geometry model and echo signal model of FMCW SAR are analyzed and deduced. The problem of Doppler center offset under squint mode is eliminated by… More >

  • ARTICLE

    Task-Oriented Battlefield Situation Information Hybrid Recommendation Model

    Chunhua Zhou*, Jianjing Shen, Xiaofeng Guo, Zhenyu Zhou
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 127-141, 2021, DOI:10.32604/iasc.2021.012532
    Abstract In the process of interaction between users and battlefield situation information, combat tasks are the key factors that affect users’ information selection. In order to solve the problems of battlefield situation information recommendation (BSIR) for combat tasks, we propose a task-oriented battlefield situation information hybrid recommendation model (TBSI-HRM) based on tensor factorization and deep learning. In the model, in order to achieve high-precision personalized recommendations, we use Tensor Factorization (TF) to extract correlation relations and features from historical interaction data, and use Deep Neural Network (DNN) to learn hidden feature vectors of users, battlefield situation information and combat tasks from… More >

  • ARTICLE

    Research into Visual Servo Based Haptic Feedback Teleoperation

    Tao Ni1, Lingtao Huang1,*, Huanfei Zheng2, Hongyan Zhang1
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 143-158, 2021, DOI:10.32604/iasc.2021.012268
    Abstract To overcome the problem that a teleoperation system loses robustness when the target moves outside the robot’s visual field or it is far away from the desired position, and to improve the operability and controllability of a master-slave teleoperation system, we present an image servo based haptic feedback (ISBHF) control method for teleoperating. The ISBHF control method involves extracting target feature points and constructing image servo based virtual force. First, the image characteristics of the environment and targets are identified and extracted by a 3D reconstruction method. A composite image Jacobian matrix is used to construct virtual guidance force based… More >

  • ARTICLE

    Reconstruction and Optimization of Complex Network Community Structure under Deep Learning and Quantum Ant Colony Optimization Algorithm

    Peng Mei1, Gangyi Ding1, Qiankun Jin1, Fuquan Zhang2,*, Yeh-Cheng Chen3
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 159-171, 2021, DOI:10.32604/iasc.2021.012813
    Abstract Community structure is a key component in complex network systems. This paper aims to improve the effectiveness of community detection and community discovery in complex network systems by providing directions for the reconstruction and optimization of community structures to expand the application of intelligent optimization algorithms in community structures. First, deep learning algorithms and ant colony algorithms are used to elaborate the community detection and community discovery in complex networks. Next, we introduce the technology of transfer learning and propose an algorithm of deep self-encoder modeling based on transfer learning (DSEM-TL). The DSEM-TL algorithm’s indicators include normalized mutual information and… More >

  • ARTICLE

    Imperfect Premise Matching Controller Design for Interval Type-2 Fuzzy Systems under Network Environments

    Zejian Zhang1, Dawei Wang2,*, Xiao-Zhi Gao3
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 173-189, 2021, DOI:10.32604/iasc.2021.012805
    Abstract The interval type-2 fuzzy sets can describe nonlinear plants with uncertain parameters. It exists in nonlinearity. The parameter uncertainties extensively exist in the nonlinear practical Networked Control Systems (NCSs), and it is paramount to investigate the stabilization of the NCSs on account of the section type-2 fuzzy systems. Notice that most of the existing research work is only on account of the convention Parallel Distribution Compensation (PDC). For overcoming the weak point of the PDC and acquire certain guard stability conditions, the state tickling regulator under imperfect premise matching can be constructed to steady the NCSs using the section type-2… More >

  • ARTICLE

    A Negotiated Pricing Model for Innovation Services Based on the Multiobjective Genetic Algorithm

    Yan Zhou1,*, Yue Li1, Yunxing Zhang2
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 191-203, 2021, DOI:10.32604/iasc.2021.014142
    Abstract Service pricing is a bottleneck in the development of innovation services, as it is the issue of most concern to the suppliers and demanders. In this paper, a negotiated pricing model that is based on the multiobjective genetic algorithm is developed for innovation services. Regarding the process of service pricing as a multiobjective problem, the objective functions which include the service price, service efficiency, and service quality for the suppliers and the demanders are constructed. Because the solution of a multiobjective problem is typically a series of alternatives, an additional negotiation process is necessary in determining the final decision. A… More >

  • ARTICLE

    A Novel Semi-Supervised Multi-Label Twin Support Vector Machine

    Qing Ai1,2,*, Yude Kang1, Anna Wang2
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 205-220, 2021, DOI:10.32604/iasc.2021.013357
    Abstract Multi-label learning is a meaningful supervised learning task in which each sample may belong to multiple labels simultaneously. Due to this characteristic, multi-label learning is more complicated and more difficult than multi-class classification learning. The multi-label twin support vector machine (MLTSVM) [], which is an effective multi-label learning algorithm based on the twin support vector machine (TSVM), has been widely studied because of its good classification performance. To obtain good generalization performance, the MLTSVM often needs a large number of labelled samples. In practical engineering problems, it is very time consuming and difficult to obtain all labels of all samples… More >

  • ARTICLE

    Uplink SCMA Codebook Reuse Transmission and Reception Scheme

    Xiaohong Ji1, Junjun Du1, Guoqing Jia1,*, Weidong Fang2,3
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 221-231, 2021, DOI:10.32604/iasc.2021.013145
    Abstract Sparse code multiple access (SCMA) is a new non-orthogonal multiple access scheme suitable for 5G communication, which can effectively improve spectrum efficiency and support massive connections. Multiple users in the SCMA system realize the sharing of the same time-frequency resources by mapping data into codewords of a special code book (Code Book, CB). A typical SCMA system increases the spectrum utilization to 150%. In order to further improve the system spectrum utilization and increase the number of user connections, this paper proposes an uplink SCMA codebook reuse transmission and reception scheme (CB-Reuse-SCMA), which reuse a codebook to multiple users. The… More >

  • ARTICLE

    Parallel Equilibrium Optimizer Algorithm and Its Application in Capacitated Vehicle Routing Problem

    Zonglin Fu1, Pei Hu1, Wei Li2, Jeng-Shyang Pan1,*, Shuchuan Chu1
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 233-247, 2021, DOI:10.32604/iasc.2021.014192
    (This article belongs to this Special Issue: Machine Learning and Deep Learning for Transportation)
    Abstract The Equilibrium Optimizer (EO) algorithm is a novel meta-heuristic algorithm based on the strength of physics. To achieve better global search capability, a Parallel Equilibrium Optimizer algorithm, named PEO, is proposed in this paper. PEO is inspired by the idea of parallelism and adopts two different communication strategies between groups to improve EO. The first strategy is used to speed up the convergence rate and the second strategy promotes the algorithm to search for a better solution. These two kinds of communication strategies are used in the early and later iterations of PEO respectively. To check the optimization effect of… More >

  • ARTICLE

    Research on Network Resource Optimal Allocation Algorithm Based on Game Theory

    Xiaojuan Yuan1,2,*
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 249-257, 2021, DOI:10.32604/iasc.2021.013637
    Abstract This paper briefly introduced the structure of heterogeneous cellular network and two algorithms which are used for optimizing the network resource allocation scheme: dynamic game algorithm based on spectrum allocation and the game allocation algorithm based on power allocation and alliance. After that, the two algorithms were simulated in MATLAB software and compared with another power iterative allocation algorithm based on non-cooperative game. The results showed that the system energy efficiency of the three algorithms decreased with the increase of the number of small base stations in the network; with the increase of the number of users in the network,… More >

  • ARTICLE

    DNS Service Model Based on Permissioned Blockchain

    Yantao Shen1,*, Yang Lu2, Zhili Wang1, Xin Xv3, Feng Qi1, Ningzhe Xing4, Ziyu Zhao5
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 259-268, 2021, DOI:10.32604/iasc.2021.013704
    Abstract With the continuous development of the Internet, the domain name system (DNS) as infrastructure is playing an increasingly important role. However, traditional DNS architecture is centralized, and there are some security problems such as the right concentration and power abuse. This paper combines blockchain technology with DNS technology and proposes a domain name service model based on the permissioned blockchain. At first, this paper designs a top-level domain chain (TLDChain) model to conduct consensus on block transactions and achieve decentralization of domain name service. Then, this paper introduces a data model to upload data. At the same time, to improve… More >

  • ARTICLE

    Identifying Cross Section Technology Application through Chinese Patent Analysis

    Ping-Yu Hsu1, Ming-Shien Cheng2,*, Chih-Hao Wen3, Yen-Huei Ko1
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 269-285, 2021, DOI:10.32604/iasc.2021.013404
    Abstract Cross-domain technology application is the application of technology from one field to another to create a wide range of application opportunities. To successfully identify emerging technological application cross sections of patent documents is vital to the competitive advantage of companies, and even nations. An automatic process is needed to save precious resources of human experts and exploit huge numbers of patent documents. Chinese patent documents are the source data of our experiment. In this study, an identification algorithm was developed on the basis of a cross-collection mixture model to identify cross section and emerging technology from patents written in Chinese.… More >

  • ARTICLE

    An Adaptive Link-Level Recovery Mechanism for Electric Power IoT Based on LoRaWAN

    Yuqi Wang1, Sujie Shao1,*, Shaoyong Guo1, Ruijun Chai1, Feng Qi1, Michel Kadoch2
    Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 287-298, 2021, DOI:10.32604/iasc.2021.013543
    Abstract Electric power Internet of Things (IoT) is a network system that can meet multiple requirements of the power grid, such as infrastructure, environment recognition, interconnection, perception and control. Long Range Radio Wide Area Network (LoRaWAN) with the advantages of ultra-long transmission and ultra-low power consumption, becomes the most widely used protocol in the electric power IoT. However, its extremely simple star topology also leads to several problems. When most of terminals depend on one or several gateways for communication, the gateways with heavier communication tasks have poorer communication quality. The load of each gateway is unbalanced, which is hardly conducive… More >

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