Journal of Intelligent & Fuzzy Systems - Volume 38, issue 1

Authors: Song, Depeng | Li, Binbing | Qu, Yi | Chen, Yijun

Article Type: Research Article

Abstract: The frequency modulated continuous wave circular synthetic aperture radar (FMCW CSAR) is a high resolution imaging radar, which plays an important role in target recognition. However, the traditional wave number domain imaging algorithm has a low resolution for the target far from the scene center, which limits its wide applications in CSAR imaging. In this paper, when the targets are sparse or compressible, a circular convolution algorithm based on compressed sensing is proposed to improve the resolution. In the algorithm, the circular convolution and the Fourier transform is used to reduce computation cost. What’s more, the compressed sensing is applied …to improve the imaging resolution for the target far from the scene center, which can effectively avoid the complex calculation of the system kernel function in the traditional wave number domain algorithm. Some simulation results illustrate the effectiveness of the proposed method. Show more

Keywords: FMCW CSAR, compressed sensing, circular convolution, imaging

DOI: 10.3233/JIFS-179393

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 187-196, 2020

Authors: Wu, Peng | Li, Wei | Yan, Ming

Article Type: Research Article

Abstract: The traditional point cloud alignment method suffers from drawbacks such as a large extensive computation, low computing speed, and poor alignment accuracy. To overcome these problems, this paper proposes a fast and highly accurate algorithm based on fast point feature histograms (FPFH) algorithm and spatial constraints. The proposed algorithm first filters, denoises the point cloud dataset, and calculates the point cloud normal to obtain the FPFH eigenvalue. Then, the vertebral space is divided into three regions according to its location, and the feature points in each region are calculated. The Euclidean distance between a feature point and the boundary of …the adjacent region, and the weight coefficient corresponding to the feature point are given according to the calculated distance. The method overcomes the defect that the query feature point has a large workload in the traditional ICP algorithm and improves the registration precision of the point cloud. The experimental results show that the proposed method effectively solves the problems of the traditional point cloud registration algorithm, can effectively reduce the mismatch rate of point cloud registration, and can improve the registration accuracy and stability without reducing the registration of the elements. Show more

Keywords: Point cloud alignment, FPFH, ICP

DOI: 10.3233/JIFS-179394

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 197-206, 2020

Authors: Wu, Ling | Hu, Hao | Zhao, Weihua | Liu, Haoxue | Zhu, Tong

Article Type: Research Article

Abstract: Previous studies lack a comprehensive evaluation model that combined the subjective perception of the driver and the objective driving environment. This work investigates the characteristics of drivers’ behavior risk in highway extra-long tunnels. Real-vehicle tests were conducted in two typical extra-long tunnels and the speed of skilled and unskilled drivers were collected simultaneously. The quantified model of drivers’ behavior risk was proposed based on the safety speed difference. The variation characteristics of behavior risk both inside the tunnel and ordinary highway were analysed. Further, the NARX neural network was used to predict real-time speed with the heart rate regarded as …the input variable. Results showed that skilled drivers showed the highest behavior risk in the internal zone, while the highest value of unskilled drivers was at the exit zone in the tunnel section. Both two types of drivers presented the highest and the lowest behavior risk on the ordinary highway and the tunnel entrance zone respectively. The proposed NARX model could predict synchronous speed with high accuracy. These results of the present study concern the driver’s risk characteristics in Internet of Vehicles and how to establish the automated driver model in the simulation driving environment. Show more

Keywords: Time-series modelling, NARX neural network, driver, behavior risk characteristics, safety speed difference

DOI: 10.3233/JIFS-179395

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 207-217, 2020

Authors: Liu, Yan-Xiao | Yang, Ching-Nung | Sun, Qin-Dong | Chen, Yi-Cheng

Article Type: Research Article

Abstract: Traditional (k , n ) secret image sharing provides all-or-nothing decoding model and (k , n ) scalable secret image sharing provides progress decoding model during image reconstruction. Both these two decoding models are significance in various applications. However, the security level for real applications would change due to the dynamical environment, only one single decoding model cannot satisfy the changeable security requirement. In this work, we construct scalable secret image sharing schemes that provides both all-or-nothing and progress decoding models to satisfy the dynamical secure requirement. Each participant in our schemes only needs to keep one initial-shadow. During image …reconstruction, the dealer selects the decoding model according to current security requirement, if progress model is chosen, initial shadows can achieve image reconstruction in progress model without any modification; else if all-or-nothing model is chosen, the dealer does not need to resent new shadows to participants, the initial-shadows can be updated to satisfy all-or-nothing model efficiently. Show more

Keywords: Secret image sharing, scalable, decoding model, all-or-nothing, progress

DOI: 10.3233/JIFS-179396

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 219-228, 2020

Authors: Li, Zhao | Song, Yi | Gong, Guoqiang | Zhou, Siwei | Lv, Ke

Article Type: Research Article

Abstract: Fault localization is the critical but most expensive step in testing manufacturing software, effectively locating faults has become an increasingly concerned study. The existing spectrum-based fault localization techniques utilize spectrum information and specific prioritization algorithm to generate the suspiciousness as well as the ranking of statements. However, the effectiveness of fault localization in manufacturing software would be dramatically reduced once the statement involving bug is assigned with the same suspiciousness as other non-faulty statements. A multi-technique fusion approach (FA) is proposed based on suspicious rankings, which merges various of randomly selected fault localization techniques to minimize the difference between the …numbers of statements that need to be examined (GAP) to find the bug respectively in the worst and best assumptions, further improve the effectiveness of fault localization. In addition, a novel metric for comparing fault localization techniques is developed. Experiments on Siemens Suite shows that our approach outperforms these selected techniques in the effectiveness. Show more

Keywords: Fault localization, manufacturing software, spectrum information, multi-technique fusion, GAP

DOI: 10.3233/JIFS-179397

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 229-238, 2020

Authors: Sun, Yang | Li, Jianrong | Fu, Xueliang | Wang, Haifang | Li, Honghui

Article Type: Research Article

Abstract: Task scheduling in the cloud environment is a hot issue in current research. Aiming at the task scheduling problem in cloud environment, this paper analyses the scheduling model of cloud tasks, proposed an improved genetic algorithm (PGA) based on phagocytosis, changed the crossover operation of standard genetic algorithm (GA), formed a sub-chromosome individual after phagocytosis of two mother chromosomes, another individual was generated randomly, and the new individual generated after phagocytosis is determined by the fitness function and the load-balancing standard deviation, so that the evolution process can ensure a high proportion of high-quality individuals in the population. Ensure the …diversity of the population. Then a multi-population hybrid coevolutionary genetic algorithm (MPHC_GA) is adopted, which uses the Min-Min algorithm to generate initial multiple sub-populations, and these sub-populations are evolved by standard genetic algorithm (GA) and improved genetic algorithm (PGA) based on phagocytosis. The simulation results show that the proposed algorithm is effective in cloud task scheduling. Show more

Keywords: Task scheduling, genetic algorithm, phagocytosis, multi-population hybrid coevolutionary

DOI: 10.3233/JIFS-179398

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 239-246, 2020

Authors: Li, Honghui | Lu, Hailiang | Fu, Xueliang

Article Type: Research Article

Abstract: With the rapid development of data center network, the traditional traffic scheduling method can easily cause problems such as link congestion and load imbalance. Therefore, this paper proposes a novel dynamic flow scheduling algorithm GA-ACO (Genetic Algorithm and Ant COlony algorithms). GA-ACO algorithm obtains the global perspective of the network under the SDN (Software defined network) architecture. It then calculates the global optimal path for the elephant flow on the congestion link, and reroutes it. Extensive experiments have been executed to evaluate the performance of the proposed GA-ACO algorithm. The simulation results show that, in comparison with ECMP and ACO-SDN …algorithm, GA-ACO can not only reduce the maximum link utilization, but also improve the bandwidth effectively. Show more

Keywords: Data center network, SDN, elephant flow scheduling, genetic algorithm, ant colony algorithm

DOI: 10.3233/JIFS-179399

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 247-255, 2020

Authors: Lei, Guoping | Luo, Xiuying | Cai, Li | Gao, Le | Dai, Nina | Xu, Qingshan | Tan, Zefu

Article Type: Research Article

Abstract: Battery management system (BMS) is an important part of electric vehicle that can improve the efficiency of battery and ensure the safety during operating process. State of charge (SOC) estimation is one of kernel technology of BMS. High precision of SOC estimation can not only increase service life of battery, but also enhance energy utilization efficiency and cut down the operational cost. Based on fully understand working principle of battery, three-order RC equivalent circuit is chose to simulate the external characteristics. Introduce the working theory of that combination of extended Kalman filter (EKF) and open circuit voltage (OCV), and the …whole recursive algorithm of estimation SOC, using the OCV-SOC look-up table to solve the problem of initial value of SOC to a certain degree. The hardware circuit and software of BMS are designed. Hardware circuit consists of current measurement circuit, voltage measurement circuit, temperature measurement circuit and equalization circuit. The software is designed by C as the development language, the Microsoft Visual Studio 2008 as development environment and SQL Server 2008 as database management system. The experiments are carried out after the experimental platform of system hardware and software is constructed. The system realizes the real-time online monitoring of BMS, SOC estimation and etc. The result verifies the reliability and feasibility. The precision requirement of SOC estimation by using EKF algorithm and OCV-SOC look-up table meets the national standard for electric vehicle. Show more

Keywords: Electric vehicle, battery management system, smart EFK algorithm, extended kalman filter, state of charge

DOI: 10.3233/JIFS-179400

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 257-262, 2020

Authors: Bian, Qian | Zhang, Xuejun | Wang, Zhenduo | Liu, Mujun | Li, Bijiang | Wu, Dongbo | Liu, Gang

Article Type: Research Article

Abstract: Multi-phase computed tomography images are widely applied to doctors’ routine interpretation of organic lesions or before human abdominal surgery. However, because of the lack of intuitive and three-dimensional (3D) observations, human factors lead to 80% of the clinical errors. A primary malignant tumor resection system based on a virtual reality (VR) helmet and a force-feedback device combined with a 3D printing model is proposed in this paper. First, we used the thin-plate spline (TPS) deformation method to register the different phase images. In the case of a metastatic tumor, a spherical scoring filter (SSF) model was built for searching the …tumor pattern with edge detection and subtraction processing, from which the initial tumors were selected on the basis of the calculated score. For hepatocellular carcinoma cases, candidates were extracted as the areas without edges by using edge detection filters on the subtraction image between the equilibrium and arterial phase images. Finally, the false positive (FP) candidate was eliminated before obtaining the 3D shape of the liver tumor in the expansion process, thus providing an accurate volume of lesions for the surgical plan for the liver resection. The results showed that our virtual surgery system enabled the user to simulate the use of a scalpel for cutting and removing the organ labels; 3D display on a VR helmet with a deformable effect; and touching organs with a force-feedback device. Our virtual surgery tools could simulate all of the effects of the doctors’ operations and make clinical practice more efficient. Show more

Keywords: Virtual surgery system, hepatocellular carcinoma (HCC), metastatic tumor, multi-detector CT (MDCT), spherical scoring filter, force-feedback device

DOI: 10.3233/JIFS-179401

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 263-276, 2020

Authors: Zeng, Zhijun | Gao, Yong | Liu, Liyan | Yan, Xiaojun | Xu, Guoliang | Liu, Hongning | Ji, Yanhua

Article Type: Research Article

Abstract: Although it is very important to pay attention to the personalized medicine of tumour patients, there is quite lacking some methods to evaluate the synergistic effects of the top anti-cancer drugs in clinic. In the study, therefore, we used the network of pharmacogenetic and bioinformatics to discuss the complex interactions in the top anti-cancer drugs with the help of computer high performance operating power and network visualization. We got a total of 81 known targets from the top 10 anti-cancer drugs. The shared most targets were from the 5-fluorouracil, capecitabine and tegafur, occupying 4, 4 and 3 targets, respectively. Based …on complex network visual effect of the computer, gene set enrichment analysis displayed that the targets were mainly on five major categories. All the data showed that the two groups of drugs having some synergistic effects (5-fluorouracil, capecitabine, tegafur and tamoxifen, letrozole, respectively), which is suggests the top anti-cancer drugs’ synergic existing in combination drugs on clinic. Show more

Keywords: Computer, visualization, pharmacogenetics, caner, anti-cancer drugs

DOI: 10.3233/JIFS-179402

Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1, pp. 277-281, 2020