Huanyu Zhao, Guoqiang Wang, Shuai Wang, Ruipeng Yang, He Tian, Qiushi Bi

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 581-592, 2018, DOI:10.31209/2018.100000025

Abstract Articulated tracked vehicles have high mobility and steering performance. The unique structure of articulated tracked vehicles can avoid the subsidence of tracks caused by high traction from instantaneous braking and steering. In order to improve the accuracy of the steady-state steering of the articulated tracked vehicle, the velocity of both sides of the track and the deflection angle of the articulated point need to match better to achieve the purpose of steering accurately and reduce energy consumption and wear of components. In this study, a virtual prototype model of the articulated tracked vehicle is established based on the multi-body dynamic… More >

Yuhua Peng^a, Dingyue Chen^a, Lihao Chen^b, Jiayu Yu^b, Mengjie Bao^a

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 531-539, 2018, DOI:10.31209/2018.100000020

Abstract For the study of the effect of deicing with carbon fiber heating wire in the bridge pavement structure, through built-in carbon fiber heating wire in the bridge pavement structure, experimental studies were carried out indoor on the effects of thermal conductivity in different embedding positions, layout spacing and the installs power of carbon fiber heating wire. With indoor laboratory test data as the basic parameters, using ABAQUS finite element software simulation, an analysis was carried out of the degree that the surface temperature of the heating wire, the thermal physical parameters of asphalt concrete, and environmental conditions have influence on… More >

Zheng Xu, Zhiguo Yan

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 517-518, 2018, DOI:10.31209/2018.100000018

Abstract This article has no abstract. More >

Leo Raju^a, R. S. Milton^b, Senthilkumaran Mahadevan^a

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 483-491, 2018, DOI:10.1080/10798587.2017.1305647

Abstract The objective of this paper is to monitor and control a micro-grid model developed in MATLABSimulink through Multi Agent System (MAS) for autonomous and distributed energy management. Since MATLAB/Simulink is not compatible with parallel operations of MAS, MAS operating in Java Agent Development Environment (JADE) is linked with MATLAB/Simulink through Multi Agent Control using Simulink with Jade extension (MACSimJX). This allows the micro-grid system designed with Simulink to be controlled by MAS for realizing the advantages of MAS in distributed and decentralized microgrid systems. JADE agents receive environmental information through Simulink and they coordinate to take best possible action, which… More >

Li-Hong Juang^a, Ming-Ni Wu^b, Shin-An Lin^b

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 249-256, 2018, DOI:10.1080/10798587.2016.1272777

Abstract Detecting human gender from complex background, illumination variations and objects under computer vision system is very difficult but important for an adaptive information service. In this paper, a preliminary design and some experimental results of gender recognition will be presented from the walking movement that utilizes the gait-energy image (GEI) with denoised energy image (DEI) pre-processing as a machine learning support vector machine (SVM) classifier to train and extract its characteristics. The results show that the proposed method can adopt some characteristic values and the accuracy can reach up to 100% gender recognition rate under combining the horizontal added vertical… More >

Yue Li¹, Guangquan Xu^2,3, Hequn Xian^1,*, Longlong Rao³, Jiangang Shi^4,*

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 637-647, 2019, DOI:10.31209/2019.100000118

Abstract In order to prevent the spread of Android malware and protect privacy information from being compromised, this study proposes a novel multidimensional hybrid features extraction and analysis method for Android malware detection. This method is based primarily on a multidimensional hybrid features vector by extracting the information of permission requests, API calls, and runtime behaviors. The innovation of this study is to extract greater amounts of static and dynamic features information and combine them, that renders the features vector for training completer and more comprehensive. In addition, the feature selection algorithm is used to further optimize the extracted information to… More >

Tongmao Ma^1,2, Shanchen Pang¹, Weiguang Zhang¹, Shaohua Hao¹

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 605-613, 2019, DOI:10.31209/2019.100000115

Abstract In cloud computing, task scheduling is a challenging problem in cloud data center, and there are many different kinds of task scheduling strategies. A good scheduling strategy can bring good effectiveness, where plenty of parameters should be regulated to achieve acceptable performance of cloud computing platform. In this work, combined elitist strategy, three parameters values oriented genetic algorithms are proposed. Specifically, a model built by Generalized Stochastic Petri Nets (GSPN) is introduced to describe the process of scheduling in cloud datacenter, and then the workflow of the algorithms is showed. After that, the effectiveness of the algorithms is found to… More >

Nan Pan^1*, Dilin Pan², Yi Liu², Gang Li³

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 367-373, 2019, DOI:10.31209/2019.100000098

Abstract A set of laser detection system for shearing tools is developed, By holding breakage of the cable, firstly, using single-point laser displacement sensors to pick up surface features signal of line trace, then wavelet decomposition is used to reduce the noise, and the signal after noise reduction is obtained. After that, the threshold based sequence comparison method is used to achieve matches of similar coincidence for trace features, and then using a gradient descent method to getting the minimum cost of cost function value through continuous iterative, and finally realizing the fast traceability of corresponding shearing tool. More >

Nan Pan¹, Yi Liu², Dilin Pan², Junbing Qian¹, Gang Li³

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 359-366, 2019, DOI:10.31209/2019.100000097

Abstract It will face a lot of problems when using existing image-processing and 3D scanning methods to do the similarity analysis of the line traces, therefore, an effective comparison algorithm is put forward for the purpose of making effective trace analysis and infer the criminal tools. The proposed algorithm applies wavelet decomposition to the line trace 1-D detection signals to partially reduce background noises. After that, the sequence comparison strategy based on wavelet domain DTW is employed to do trace feature similarity matching. Finally, using linear regression machine learning algorithm based on gradient descent method to do constant iteration. The experiment… More >

Belayat Hossain^a, Takatoshi Morooka^b, Makiko Okuno^b, Manabu Nii^a, Shinichi Yoshiya^b, Syoji Kobashi^a

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 105-115, 2019, DOI:10.31209/2018.100000034

Abstract This work aimed to predict postoperative knee functions of a new patient prior to total knee arthroplasty (TKA) surgery using machine learning, because such prediction is essential for surgical planning and for patients to better understand the TKA outcome. However, the main difficulty is to determine the relationships among individual varieties of preoperative and postoperative knee kinematics. The problem was solved by constructing predictive models from the knee kinematics data of 35 osteoarthritis patients, operated by posterior stabilized implant, based on generalized linear regression (GLR) analysis. Two prediction methods (without and with principal component analysis followed by GLR) along with… More >