Journal of Intelligent & Fuzzy Systems - Volume 32, issue 5

Authors: Shi, Yanli | Nan, Jizhu

Article Type: Research Article

Abstract: Fuzzy c-means is one of the most popular partitional clustering. However, it has the shortcoming that it is sensitive to initial centers and noises. Density-based clustering algorithm overcomes this shortcoming, but cannot obtain the better clustering results when the density of data space has uneven distribution. Grid-based method is advantageous to save computational time, but the clustering performance was unsatisfied. Based on the above analysis, the improved FCM algorithm based on initial center optimization method is proposed. First, the initial center optimization method based on density and grid is presented to avoid the sensitivity of FCM to initial centers. Then, …improved FCM algorithm based on initial center optimization method is proposed. Finally, the performance and effectiveness of the proposed clustering algorithm is evaluated by 4 San Francisco taxi GPS cab mobility traces data sets, and the experimental results show that the proposed algorithm has better clustering results. Show more

Keywords: Fuzzy clustering, fuzzy c-means, density-based clustering, grid-based method

DOI: 10.3233/JIFS-169286

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3487-3494, 2017

Authors: Linqin, Cai | Shuangjie, Cui | Min, Xiang | Jimin, Yu | Jianrong, Zhang

Article Type: Research Article

Abstract: Hand gesture recognition is widely used in human-computer interaction (HCI) and has attracted substantial researching attentions. This paper aims to develop low-complexity and real-time solutions of dynamic hand gestures recognition using RGB-D depth sensor for natural human-computer interaction applications. We combine Euclidean distance between hand joints and shoulder center joint with the modulus ratios of skeleton features to generate a unifying feature descriptor for each dynamic hand gesture. And then, an improved dynamic time warping (IDTW) algorithm is proposed to obtain the final recognition results, which applies the weighted distance and a restricted search path to avoid the huge computation …in conventional DTW and improves the recognition performance. Experimental results show that the proposed algorithm of dynamic hand gesture recognition not only achieves higher average recognition rate of 96.5% and better performance in response time, but also is robust to uncontrolled environments. Finally, according to our hand gesture recognition solutions, we develop one real-life HCI applications to control a virtual coalmine environment, which operates accurately and efficiently. Show more

Keywords: Dynamic gesture, red green blue-depth (RGB-D), human-computer interaction (HCI), dynamic time warping (DTW), virtual environment

DOI: 10.3233/JIFS-169287

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3495-3507, 2017

Authors: Hu, Fengjun | Tu, Chun

Article Type: Research Article

Abstract: According to the defects of the standard particle filter algorithm in target tracking of mobile sensor networks, such as low accuracy, large network energy consumption and poor anti-noise ability, an optimization model is proposed for target tracking of mobile sensor network based on motion state prediction. First, centroid algorithm was adopted to construct the node localization model, and then the features of the position and the direction of the moving target in the mobile sensor network were as the measurements. The method of integral point assignment was adopted to self-adaptionly optimize the weights of the standard particle filter algorithm, and …the introduced modifying factor, the value assignment of integral point was for self-adaption correction, then the difference between the observed and predicted values of the system was provided news residual interest knowledge in the re-sampling phase, to self-adaption modify the sampling particles by measuring the news. And then improve the operation efficiency of the particle filter algorithm with asymmetric kernel function, and provide new residual interest knowledge with the difference between the system current time and forecast values in the re-sampling phase, self-adaptive adjusting of sampling population through measuring the new rates. The simulation experiments show that the proposed improved particle filter algorithm has the higher accuracy and better stability for target tracking, and has lower energy consumption of the network. Show more

Keywords: Emerging sensor networks, movement trend prediction, parallel optimisation, integral point assignment, self-adaption correction

DOI: 10.3233/JIFS-169288

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3509-3524, 2017

Authors: Singh, Shailendra Pratap | Kumar, Anoj

Article Type: Research Article

Abstract: The differential evolution, one of the most powerful nature inspired algorithm is used to solve the real world problems. This algorithm takes minimum number of function evaluations to reach near to global optimum solution. Although its performance is very good, yet it suffers from the problem of stagnation. In this paper, some new mutation strategies are proposed to improve the performance of differential evolution (DE). The proposed method adds one more vector named as Homeostasis mutation vector in the existing mutation vectors to provide more bandwidth for selecting effective mutant solutions. The proposed approach provides more promising solutions to guide …the evolution and helps DE escaping the situation of stagnation. Performance of proposed algorithm is compared with other state-of-the-art algorithms on COCO (Comparing Continuous Optimizers) framework. The result verifies that our proposed Homeostasis mutation strategy outperform most of the state-of-the-art DE variants and other state-of-the-art population based optimization algorithms. Show more

Keywords: Adaptation, optimization, evolutionary algorithm

DOI: 10.3233/JIFS-169289

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3525-3537, 2017

Authors: Zong, Liang | Bai, Yong | Huang, Tongcheng | Zhou, Shihao

Article Type: Research Article

Abstract: The satellite network has the advantages of wide coverage, convenient access, and the influence of the natural environment. Wireless multi-hop network is suitable for the occasion that cannot be easily or inconvenient to lay network facilities and the occasion of the need for rapid automatic networking. Multi-hop network and the satellite network may combine a heterogeneous network that can provide an effective and convenient way to access the network in the ocean or in remote areas. This paper, firstly, builds a heterogeneous network with satellite network and multi-hop network, and discusses the bandwidth delay product (BDP) of heterogeneous network, then …proposes a new end-to-end congestion control algorithm. The proposed scheme at the outset increases the dynamic time interval for the initial transmission data that can reduce the backlog of burst data at the access point, and then increases the amount of data transmission in the slow start that can improve high bandwidth delay product of satellite network. In the congestion avoidance, it adjusts the congestion window size by monitoring the random packet loss and congestion packet loss. This algorithm can effectively solve the long delay in heterogeneous networks, and improve the accuracy of the high packet loss rate monitoring in multi hop networks and satellite networks. The proposed algorithm can effectively solve the influence of the long delay in the heterogeneous network, at the same time it can distinguish the different packet loss. Show more

Keywords: Congestion control, multi-hop network, satellite network, heterogeneous networks

DOI: 10.3233/JIFS-169290

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3539-3550, 2017

Authors: Chen, Xue Gang

Article Type: Research Article

Abstract: Network reliability is an important index in measuring the reliability of large-sized network, but network reliability calculation is a NP-hard problem, and simulation is a feasible approach to estimating network reliability. Aiming at the problem of reliability evaluation in a complex network, develop a general scheme that combines Crude Monte Carlo and event-driven, and a novel reliability assessment method based on event-driven is put forward. The unbiased and the accurate estimation of the proposed method are analyzed from a theoretical point of view. Experimental results demonstrate that the proposed method is more efficient than other algorithms, such as high simulation …efficiency, fine estimation accuracy and greatly reducing the algorithm complexity. Show more

Keywords: Network reliability, failure events, Monte-Carlo, event-driven, connectivity

DOI: 10.3233/JIFS-169291

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3551-3560, 2017

Authors: Bagga, Sachin | Girdhar, Akshay | Trivedi, Munesh Chandra

Article Type: Research Article

Abstract: Thread based programs are very much efficient in terms of increasing application response, improving structure of the program, combining with the remote procedure call(RPC) and complete utilization of the computation available. A shared-memory system along with the multithreading, can result in developing a parallel system on which different threads can run in parallel on different processor cores. Even when there are more number of threads than the processor cores, scheduling along with context switching can be done to ensure start of execution of all the threads. Keeping these benefits in mind, present research formulates that in certain cases, the results …of multithreading based programming on a single system can be more convincing than making use of the cluster based distributed programming. Proposed work tests all these claims, by decomposing an image having salt and pepper noise into number of small images and then applying median filtering parallely on all these subimages using multithreading approach. Various performance measurement metrics like % Idle Time, % Processor Time, % Maximum Frequency, % Processor Utility, total execution time are used to validate the results generated by the proposed approach. Remote method invocation (RMI) based cluster for distributed programming has also been deployed to perform the same operation on a cluster based architecture with number of nodes working together, to compare the results of both the architectures. Show more

Keywords: SPMD, time sharing, median filter, Java, RMI, threads, processor frequency, processor utility

DOI: 10.3233/JIFS-169292

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3561-3573, 2017

Authors: Gupta, Tanvi | Gandhi, Tapan K. | Panigrahi, B.K.

Article Type: Research Article

Abstract: Magnetic Resonance Imaging (MRI) is a diagnostic tool of remarkable potential in the area of neuroscience and clinical neuroimaging. The diagnostic accuracy can be limited by incompetence of the operating personnel, which can be supplemented by machine learning algorithms for classification of physiology and pathology. This paper uses effective information feature extraction, principal component analysis (PCA) for feature reduction and support vector machine (SVM) for classification of multi-sequence MR images of 7 patients. All axial slices of the brain are classified into normal and abnormal images. Various methods for feature extraction were tested among which effective information yielded the highest …accuracy of 80.8% in a set of 677 images used for training and testing. The sensitivity and specificity were 80% and 81.06%, respectively. Different grid sizes were tested, and the highest accuracy was reported for 2 × 2 which indicates that the feature extraction must be taken over a small grid to ensure detection of minor variation from normal. The image sequences tested considered in the study are T1 weighted, T2 weighted, Fluid-attenuated inversion recovery (FLAIR), and post contrast T1 weighted. T2 weighted images were best classified with the maximum accuracy of 95.97%. This method proved to be effective to classify the images of all four sequences with accuracy ranging from 92–96%. The method was also tested with out of sample data and the accuracy obtained was 72.4%. The novelty of this work lies in the classification of multi-sequential images using all the different slices of the patient which includes the top of the skull as well as the mandible. The slices differ significantly as the spread of the tumor varies with each slice. The slices are taken at 5mm gap and the tumor can have a thickness less or more than the slice gap considered for the scan. Show more

Keywords: Machine learning, MRI, SVM, T1 weighted, FLAIR

DOI: 10.3233/JIFS-169293

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3575-3583, 2017

Authors: Xiao, Ming-Ming | Luo, Yu-Ping

Article Type: Research Article

Abstract: For a thorough understanding of procedures in various network applications, and to automatically classify, recognize, trace, and control them, it is necessary that the state machine representing application sessions is obtained in advance. This article presents a novel approach to reversely infer a protocol state machine from collected data of the application layer. Protocol state machines are derived using a method of error-correcting grammatical inference, which is based on symbol sequences that appear in the application sessions. The techniques are implemented into a tool called PREUGI, which is conducted in a real network, containing a number of real applications with …several application layer protocols, to validate the proposed method. Show more

Keywords: Protocol reverse engineering, protocol state machine inference, protocol analysis, error-correcting grammatical inference

DOI: 10.3233/JIFS-169294

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3585-3594, 2017

Authors: Zhang, Jian | Fillatre, Lionel | Nikiforov, Igor

Article Type: Research Article

Abstract: The anomaly localization in distributed networks can be treated as a multiple hypothesis testing (MHT) problem and the Bayesian test with 0 - 1 loss function is a standard solution to this problem. However, For the anomaly localization application, the cost of different false localization varies, which cannot be reflected by the 0 - 1 loss function while the quadratic loss function is more appropriate. The main contribution of the paper is the design of a Bayesian test with a quadratic loss function and its performance analysis. The non-asymptotic bounds of the misclassification probabilities of the proposed test and the standard one with 0 - 1 …loss function are established and the relationship between their asymptotic equivalence with respect to signal-to-noise ratio and the geometry of the parameter space is analyzed. The effectiveness of the non-asymptotic bounds and the analysis on the asymptotic equivalence are verified by the simulation results. Show more

Keywords: Anomaly localization, multiple hypothesis testing, wireless sensor network, Bayesian test

DOI: 10.3233/JIFS-169295

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 5, pp. 3595-3608, 2017