International Journal of Wireless and Mobile Computing (32 papers in press)
Expected-mode augmentation method for group targets tracking using the random matrices
by Yun Wang, Guoping Hu, Hao Zhou
Abstract: In order to improve the estimation performance of interactive multiple models (IMM) tracking algorithm for group targets, a new EMA-VSIMM tracking algorithm is proposed in this paper. Firstly, by using the expected-mode augmentation (EMA) method, a more proper expected mode set has been chosen from the basic model set of group targets, which can make the selected tracking models match up to the unknown true mode availably. Secondly, in the filtering process of variable-structure interactive multiple model (VSIMM) approach, the fusion estimation of kinematic state and extension state have been implemented by using classical weighting method and scalar coefficients weighting method, respectively. We use the trace of the corresponding covariance matrix of extension state to calculate the weight coefficient. We calculate the prediction value of the extension state parameter by using a fuzzy reasoning approach to improve the estimation accuracy of the covariance matrix, which takes the elliptical area of extension and its change ratio as the input of the fuzzy controller. The performance of the proposed EMA-VSIMM algorithms is evaluated via simulation of a generic group targets manoeuvring tracking problem.
Keywords: interactive multiple models; expected-mode augmentation; group targets; maneuvering tracking.
Group maintenance strategy for stochastic selective maintenance
by Jianchao Zeng, Jing Zhao
Abstract: Selective maintenance is often applied to many industrial environments in which the maintenance actions are performed between sequence missions. When the length of maintenance or work mission time is stochastic and there are multiple maintenance workers with different capacities, previous works that determine maintenance and mission time are unsuitable. Assuming that the time of work mission is random and maintenance time is determined, to maximise system reliability of the next work mission, this paper proposes a stochastic model for a two-state system comprising several series-parallel components with multiple maintenance workers under the maintenance time limit. The optimal maintenance plan is obtained by hybrid intelligent optimisation algorithm. The validity and feasibility of the model are verified by the simulation.
Keywords: stochastic model; stochastic selective maintenance; mission time; maintenance time; group maintenance.
A hybrid harmony search algorithm for node localisation in wireless sensor networks
by Zhaolu Guo, Shenwen Wang, Baoyong Yin, Songhua Liu, Xiaosheng Liu
Abstract: Harmony search (HS) has been widely used in the field of wireless sensor networks. However, the search strategy of the basic HS has excellent exploration capability but weak exploitation capability. To enhance the search capability of HS, this paper presents a hybrid harmony search algorithm (HBHS) for node localisation in wireless sensor networks. The proposed HBHS employs the best solution to enhance the exploitation capability. Moreover, HBHS uses an adaptive search step-size scheme to further enhance the search capability. To verify the search performance, HBHS is compared with two HS algorithms on a suite of classical benchmark problems. The comparisons confirm that HBHS can achieve better performance than the compared HS algorithms on the most of the benchmark problems. Further, HBHS is applied for node localisation in wireless sensor networks.
Keywords: wireless sensor networks; localisation; harmony search; hybrid strategy.
Multi-strategy artificial bee colony based on multiple population for coverage optimisation
by Hui Sun, Haihua Xie
Abstract: In order to overcome the shortcomings of weak local search ability and slow convergence speed for the standard artificial bee colony algorithm, this paper proposes an improved multi-strategy artificial bee colony algorithm based on multiple populations (IMSABC). Firstly, the employed bees are randomly divided into three subgroups, corresponding to three evolutionary strategies. If the candidate solution obtained from searching is inferior to the current honey source, the bee is randomly assigned to other subgroups and the search strategy is changed. In this way, it not only facilitates the information exchange between populations, but also balances the global search and local development capabilities of the algorithm since the three search strategies have different characteristics. Secondly, by imitating the particle swarm algorithm, the search strategy of the following bees is improved by using the abundant information contained in the current global optimal honey source and random neighbour honey source. The simulation results of twelve benchmark test functions and 28 CEC2013 functions show that the performance of this algorithm has significant advantages compared with many similar improved algorithms. In order to improve the unreasonable distribution of sensor nodes and improve the network coverage, the above algorithm is applied to optimize the coverage of wireless sensor networks and achieve better optimisation effect.
Keywords: artificial bee colony algorithm; multiple populations; random selection strategy.
The feature extraction of facial expression based on the point distribution model of improved Kinect
by Xiaofeng Cao, Shi Cheng
Abstract: In the facial expression recognition system, owing to the differences of faces, the complexity of the organ distribution and the influence of the outside factors, the facial features location becomes a challenging task. Using the Kinect point distribution, we present a facial extraction algorithm of expression feature, and carry out the related experiments. The experimental results show that the proposed methods have the significant advantage in the extracting features that are with unrelated deformation, non-sensitive to noise, or have a high degree of distinction.
Keywords: Kinect; feature extraction; facial expression; emotional computing.
Cloud outsourcing computing security protocol of matrix multiplication computation based on similarity transformation
by Shanshan Kong, Yongquan Cai, Fei Xue, Haiyang Yu, Ditta Allah
Abstract: With the emergence of the cloud computing paradigm in scientific and business applications, computation outsourcing to the cloud has become a popular application in the age of cloud computing. However, this computing paradigm brings in some new security concerns and challenges, such as input/output privacy and result verifiability. In this paper we use similar transformation of matrix design secure verifiable and practical outsourcing protocol for matrix multiplication calculation. Compared with those existing outsourcing protocols, our protocol has obvious improvements concerning both efficiency and security. In order to check the correctness of the result returned from the cloud, an efficient verification algorithm is employed. Computational complexity analysis shows that our protocol is highly efficient.
Keywords: cloud computing; outsourcing computation; secure outsourcing; multiplication calculation; verification.
A fuzzy priority-based congestion control scheme in wireless body area networks
by Faezeh Pasandideh, Abbas Ali Rezaee
Abstract: Wireless sensor network (WSN) is a technology that has many applications. In healthcare, wireless body area network (WBAN) applications, especially sensors placed on parts of the patient's body, are able to detect the patient's vital signs and transmit them to a medical centre. However, when several sensors begin to simultaneously send the data, congestion might happen. The probability of the congestion to happen is directly related to the number of sensors that constantly send data packets. This can lead to a rise in the packet loss ratio and thus a decline in the efficiency as well as the overall performance of the system, so congestion control is one of the major challenges. Congestion detection and control are essential to such systems. This study proposes a technique similar to the random early detection (RED) active queue management (AQM) to indicate congestion. A two-input-single-output fuzzy logic system is used to dynamically adjust the maximum drop probability (maxp) parameter of the RED algorithm, then two adaptive values, the minimum threshold (minth) and the maximum threshold (maxth), are used to estimate the congestion level of each sensor node. We adjust the send rate of the parent node with a fuzzy logical controller (FLC) based on the child node traffic load, considering the different amounts of data being transmitted. The simulation results show that proposed protocol achieves high performance compared with PCCP and PHTCCP, in terms of packet loss, end-to-end delay and energy.
Keywords: wireless sensor network; healthcare application; congestion control; fuzzy logic controller; active queue management.
Optimisation of the high order problems in evolutionary algorithms: an application of transfer learning
by Guosheng Hao, Gai-Ge Wang, Zhao-Jun Zhang, De-Xuan Zou
Abstract: Evolutionary Algorithms (EAs) have been applied to many optimisation problems, among which those with high order are difficult for EAs. The higher the order, the steeper the curve around the optimum is, therefore the more difficult it is. This paper introduces Transfer Learning (TL) aided EAs to conquer the high order problems more efficiently and effectively by optimum transfer from the low order problem (as source domain) to high order problem (as the target domain). The experiments validated this method by comparison of the average numbers of the convergence generation and an impressive feature was observed: this method is robust against the difficulties of the problems. This method is not only significant for high order problems, but also useful for other difficult problems by borrow optimum from other feature-similar easy problems.
Keywords: optimum; difficult problem; transfer learning; high order.
Design and optimisation of narrow dual bandpass filter using bell-shaped structure for RF receiver system
by Azman Ahmad, Abdul Rani Othman
Abstract: A novel approach for designing a narrow dual bandpass filter (BPF) using a microstrip coupled line resonator (CLR) is presented in this paper. The proposed CLR consists of butterfly radial stub and 45
Keywords: dual BPF; bell-shaped structure; microstrip coupled-line; butterfly radial stub; mitered bend.
An investigation on wireless sensor networks pipeline monitoring system
by Maroua Abdelhafidh, Mohamed Fourati, Lamia Chaari Fourati, Amor Laabidi
Abstract: Pipeline Monitoring Systems (PMS) have appeared as an interesting research area that should be deeply studied. Accordingly, the several uses of pipelines in industrial and critical domains require to be permanently supervised to guarantee their continuous functionality and to offer a comprehensive fluid distribution system. Wireless Sensor Network (WSN) technology is the most suitable technique to detect and to localise anomalies in pipelines. This is enabled by the intelligent sensors that establish efficient pipeline data collection and streaming, and the real time system reaction in case of failure detection. In this survey, we give a holistic view of WSN-PMS based on the recent state-of-the art. We present the taxonomy for WSN-PMS in which we detail their specifications and address their challenges to enhance their real deployment. We review the different WSN-based pipeline leak detection methods and discuss their accuracy and effectiveness level to give depth knowledge on WSN-PMS.
Keywords: fluid; pipeline; wireless sensor network; pipeline monitoring system; leak detection; detection method; hybrid technique; real time monitoring.
Research on financial advertisement personalised recommendation method based on customer segmentation
by Liming Wang, Yanni Liu, Jicheng Wu
Abstract: In the context of mobile internet, financial companies have encountered some obstacles in the development of marketing. The traditional recommendation system based on association rules regards all customers as a whole to carry out the correlation analysis without considering the individual differences, which greatly reduces the effectiveness of personalised recommendation in the rule mining stage. Given these shortcomings, this paper proposes a financial product advertising marketing system based on customer segmentation. Through the segmentation of financial customer groups, the method could be representative of different consumption habits and consumer characteristics of the customer groups. Then we carry out the association rules mining in various customer groups, and establish the customer base to provide a targeted customer personalised service.
Keywords: customer segmentation; data mining; customer segmentation; personalized recommendation.
Wireless ad hoc networks: detection of malicious nodes by using a neighbour-based authentication approach
by Khurram Gulzar Rana, Cai Yangquan, Muhammad Azeem, Allah Ditta, Haiyang Yu, Sijjad Ali Khuhro
Abstract: Ad hoc networks are vulnerable to routing attacks owing to their wireless insecure communication, dynamic topology and resource-constrained capabilities. Ad hoc networks undergo a variety of routing attacks. Ad hoc on-demand distance vector (AODV) routing protocol exhibits gutless defence against black hole attacks that disrupt its normal functionality and compromise data transmission. In the current research, a novel solution AODV black hole detection and removal (AODV-BDR) is proposed. AODV-BDR detects and removes black hole attack by using a neighbour-based authentication technique. According to suggested solution, every intermediate node that claims that it upholds a fresh route to destination sends its Next Hop Node (NHN) address to source in route reply packet. Source sends validation packet to NHN. On receiving the validation packet, NHN generates a validation reply having information about Previous Hop Node (PHN) and sends it to the source. On receiving validation reply, source declares malicious or normal behaviour of PHN. Results revealed that projected scheme detects malicious nodes with great accuracy. Moreover, AODV-BDR is very useful because it carries no overhead of encryption and hashing.
Keywords: ad hoc networks; black hole attack; AODV-BDR; validation packet; previous hop node; next hop node; neighbour list; gratuitous route reply.
An improved cluster-based routing algorithm for energy optimisation in wireless sensor networks
by Santar Pal Singh, S.C. Sharma
Abstract: Wireless sensor networks (WSNs) comprise huge numbers of tiny devices with restricted energy sources. Once installed, these nodes are generally unapproachable, thus an auxiliary energy supply is not possible. Therefore, energy proficiency is a crucial design issue in WSNs, and the energy efficiency must be improved to extend the network lifetime. So as to decrease the energy usage of nodes and prolong the lifetime of the network, a cluster-based routing algorithm with particle swarm optimisation (PSO) is proposed in this paper. This proposed algorithm improves the cluster head (CH) election method as it deals with the residual energy of nodes and distance to sink node. It optimises CH selection by PSO. The conventional clustering schemes, such as LEACH and the centralised version of it (LEACH-C), achieve better results in preserving the energy consumption. Thus, we compare our proposed algorithm with LEACH and LEACH-C. Simulation results confirm that the proposed algorithm outperforms LEACH and LEACH-C.
Keywords: WSN; energy; clustering; cluster head; LEACH; PSO.
Many-to-one D2D for content delivery in cellular networks
by Xiaoyan Zhao, Lilin Fan, Zhan'ao Xue, Peiyan Yuan
Abstract: The widespread expansion of mobile multimedia traffic results in a tremendous slowdown, or even breakdown, in cellular networks. Cache-enabled Device-to-Device (D2D) communication can be employed as a potential solution against the performance degradation. In this paper, we propose a many-to-one D2D communication model to carry on content delivery, which takes full advantage of storage redundancy in a dense network scenario. We study the minimisation problem of transmission delay and introduce the queuing mechanism of multi-server to derive the queue length for the number of D2D requesting users. Considering the cumulative interference caused by multi-pair D2D communications in the uplink period，restricted zone of D2D communication is defined to guarantee the quality of main link communication. Furthermore, the non-outage probability is deduced to analyse the system performance. Numerical simulations show that our system yields significantly throughput by one or two orders-of-magnitude in realistic settings, while transferring traffic load of the base station reasonably.
Keywords: device-to-device communication; transmission delay; many-to-one; non-outage probability.
Global minimisation of fuzzy level set for image segmentation
by Guoqi Liu, Chenjing Li, Ming Deng
Abstract: Level set is an important method in image segmentation, and some models based
on level set method have obtained great success, such as Chan and Vese (C-V) and its convex formulation, local binary fitting (LBF) model. However, these models have two drawbacks to be simultaneously solved. One is the non-convexity of energy function; the other difficulty is segmenting objects in the background of inhomogeneous intensity. In order to simultaneously cope with these shortcomings, a fuzzy level set energy function is proposed. In order to robustly deal with intensity inhomogeneity, a fuzzy factor is introduced in the original LBF model to describe the intensity inhomogeneity. Besides, the edge information is also integrated into the proposed model to improve the robustness of extracting objects. Finally, a regularisation optimisation method is introduced to obtain the global minimisation of the proposed model. Experimental results with quantitative evaluation confirm that the proposed method could segment objects in images with inhomogeneous intensity, and they also show that the proposed method is robust to initialisation because of the convexity of the proposed energy function.
Keywords: image segmentation; fuzzy level set; global minimisation; intensity inhomogeneity.
Investigation framework of web application vulnerabilities, attacks and protection techniques in structured query language injection attacks
by Nabeel Salih Ali
Abstract: Web security has become a great challenge in the recent years. Structured Query Language Injection Attack (SQLIA) is a prevalent and dominant class of the serious web application attacks. A crafter can easily get illegal access to the underlying database in the web application thereby gaining full control of the system and causing millions of dollars loss for corporations. In this paper, provides a comprehensive study of web applications and investigation their vulnerabilities, attacks, and protection techniques against Structured Query Language Injection Attacks (SQLIAs). The study includes presenting a taxonomy of the SQLIAs investigation framework, conducts a detailed review of the various SQLI attacks previous protection techniques. As well, summary and analysis of a critical review (strengths and weaknesses) of the detection and prevention techniques that have been done to address such attacks. Finally, highlights and focus on the critical and important directions or protection approaches that require more studies by future researchers.
Keywords: investigation framework; SQL injection; protection techniques; detection and prevention; web attacks; web applications; web vulnerabilities.
Cellular automata-based model of formation of aerobic granular sludge
by Benzhai Hai, Jie Yang, HaiLei Wang, Zongbo Qiu
Abstract: In this paper, aerobic granules were developed in a sequencing batch reactor (SBR) using synthetic wastewater. A cellular automata (CA) model was established to simulate the formation of an aerobic granular sludge. The results indicate that the model not only visualised the complex formation process of aerobic granules, but also allowed qualitative and quantitative study of the aerobic granules. Thus, the CA model is suitable for simulation of the formation process of aerobic granules cultivated in a granular SBR.
Keywords: cellular automata; aerobic granular sludge; wastewater treatment.
A fault tolerance based route optimisation and data aggregation using artificial intelligence to enhance performance in wireless sensor networks
by Vinod Kumar Menaria, S.C. Jain, A. Nagaraju
Abstract: In the on-demand usage of wireless sensor networks (WSN) over the internet, fault tolerance is an exigent task to improve the overall performance of service computing. In the proposed research work, an attempt has been made to make use of an artificial bee colony approach to find data aggregation for providing fault tolerance in WSN and to make effective use of the existing resources over the internet. In this paper, it is tried to apply quadratic minimum spanning tree (Q-MST), which is an artificial intelligence technique to provide fault tolerance along with data aggregation in WSN. Q-MST is used to improve the fault tolerance in WSN to transmit data packets from the source node to sink node. Ant colony, PRIMS and Particle Swarm Optimisation (PSO) algorithms are used to generate the minimum spanning tree (MST), which can be used for data aggregation. The Q-MST is an improved version of the MST, where ordered pairs of distinct edges would be considered for implementing an alternative edge for the existing edge failure in MST.
Keywords: WSN; data aggregation; fault tolerance; PSO; MST; Q-MST; ABC.
Trajectory planning algorithm and simulation of 6-DOF manipulator
by Jiabing Hu, Ying Sun, Gongfa Li, Guozhang Jiang, Jianyi Kong, Hegen Xiong, Zujia Zheng, Du Jiang
Abstract: In order to solve the problem of joint acceleration mutation in the cubic polynomial trajectory planning algorithm, the algorithm of the quintic polynomial trajectory planning is studied. The results show that the calculation of the quintic polynomial trajectory planning algorithm is relatively heavy, and it can ensure the continuity of angular acceleration and stable operation of motor. Trajectory planning is carried out in Cartesian space by using the spatial line and the spatial arc interpolation algorithm. MATLAB robotics toolbox is used to model the motion system and simulate the motion, which verifies the correctness and feasibility of the linear interpolation and circular interpolation algorithm.
Keywords: manipulator; trajectory planning; Cartesian space; joint space; motion simulation.
Analytical analysis and effect of scrambling on inter-relay interference in a tri-sectored LTE-A network
by Mehboob Ul Amin, Javaid A. Sheikh, Shabir A. Parah, G.M. Bhat
Abstract: With exponential increase of traffic in LTE (Long Term Evolution), LTE operators face the problem of interference. The interference is considered to a threat to the technology of wireless networks and LTE advanced is no exception. Various techniques and methods have been proposed to mitigate the interference in 4G LTE advanced access networks. Mitigation and coverage extension are the major challenges associated with the design of 4G-LTE networks. The incorporation of Relay Nodes (RNs) in LTE networks for coverage and capacity enhancement generates some additional interference, known as inter-relay interference. To mitigate this interference in 4G-LTE-A standard, nodes need to be synchronised. In this paper, a new scrambling technique is used to synchronise the nodes in order to mitigate the effects of inter-relay interference. This makes the proposed technique unique, in the sense that intra-relay distance becomes immaterial, unlike the existing techniques where it is mandatory to maintain a specific distance between the RNs of the same sector. A new analytical model for tri-sectorised hexagonal cellular networks is presented. The expectation values for Signal-to-Interference Noise Ratio (SINR) and throughput capacity for all the positions of access links are derived. Simulations are carried out on Matlab software to validate the analytical analysis. The Cumulative Distribution Function (CDF) curves for both SINR and throughput capacity of each link depict the performance of the proposed model.
Keywords: interference mitigation; relay nodes; fourth generation–long term evolution-advanced; signal-to-interference noise ratio; throughput capacity.
Artificial bee colony algorithm for energy efficiency optimisation in massive MIMO system
by Fatma Bouchibane, Messaoyd Bensebti
Abstract: This paper deals with antenna selection for multi-user massive MIMO systems, with the aim of maximising energy efficiency. Massive MIMO technology, by employing a large number of antennas at a base station, provides huge improvements in throughput and energy efficiency. However, the increased number of antennas leads to additional energy consumption due to RF chains and signal processing circuit. The main purpose of the paper is to determine the optimal subset of antennas at the base station that should be activated to serve a given number of active user devices. This idea is implemented using an artificial bee colony algorithm, which has proven its efficiency by specifying the best control parameters.
Keywords: 5G; massive MIMO; energy efficiency; antenna selection; artificial bee colony.
A comparison of different transfer functions for binary version of grey wolf optimiser
by Shuqin Wang, Gang Hua, Guosheng Hao, Chunli Xie
Abstract: Grey Wolf Optimiser (GWO) is the recently proposed meta-heuristic algorithm inspired by grey wolves. The original version of GWO has been proposed to solve problems in continuous search spaces. However, there are many optimisation problems in discrete binary search spaces such as feature selection and dimensionality reduction. We applied eight transfer functions in our BGWO and compared their performance. The test functions whose minimum points are gotten at 0 are selected as bench functions but also those functions their minimum value are gotten at 1.
Keywords: grey wolf optimiser; binary optimisation; transfer function; test functions.
Reviews and challenges on applying status of the big data technology in the publishing industry
by Yeli Li, Xindong You, Likun Lu, Chuan Zhu
Abstract: The Big Data era is coming, which is making and will make a tremendous impact on the publishing industry, and many publishing industries have applied the Big Data technology on the different production links during publishing and gain its profit. We review current application status of Big Data technology in the different types of publishing industry in China and abroad. And we identify the different features of the different publishing industry types, and the different application emphasis on the different links. The possibility of using for references each other is also discussed. Reviews on the application status of the Big Data technology will clarify the process to employ the Big Data technology on transforming the procedures of the publishing industry, and provide the ideas and method to the publishing industry to utilise the advantages of the Big Data technology.
Keywords: big data; application status; publishing industry; publishing link; publishing procedure.
Distribution route multi-objective optimisation of dangerous goods considering the time reliability
by Ruichun He, Changxi Ma, Xiaoyan Jia, Qiang Xiao, Lei Qi
Abstract: In view of the increasingly prominent security issues of dangerous goods transportation, a distribution route optimisation model of dangerous goods is proposed. Firstly, the travel time reliability model and transportation risk model are established respectively. Besides, the multi-objective optimisation model of dangerous goods route is built based on the travel time reliability. Secondly, the genetic algorithm is designed to solve the optimisation model. Finally, a numerical case is used to verify the feasibility and effectiveness of the model and algorithm. Study result shows that the distribution route optimisation model of dangerous goods has an important theoretical value and practical significance of reducing the accident risk, increasing the time reliability and ensuring dangerous goods transportation safety.
Keywords: distribution route; optimisation; genetic algorithm; dangerous goods transportation.
Rapid identification model of mine water inrush sources based on extreme learning machine
by Ya Wang, Mengran Zhou, Pengcheng Yan, Feng Hu, Wenhao Lai, Yong Yang, Yanxi Zhang
Abstract: In the process of disaster prevention of coal mine water inrush, it is necessary to quickly and accurately identify the types of water inrush sources. Based on the high sensitivity, rapid and accurate monitoring characteristics of laser induced fluorescence technology, the fluorescence spectra of water samples were collected on the experimental platform of water sample detection. After pre-processing spectra and extracting features, the multi-classification learning model is established by the extreme learning machine (ELM) algorithm. In this paper, it determines the sigmoid function as hidden layer activation function, and obtains the optimal number of hidden layer nodes by the method of cross-validation. ELM is compared with the conventional neural network classification model in different part, such as the average time and the average classification accuracy. The average classification accuracy of ELM combined with principal component analysis is about 98% and 93% in the training and testing set respectively. And the classification learning time is greatly improved. Therefore, the model is more suitable for rapid and accurate classification of water inrush sources.
Keywords: mine water inrush; water sources identification; laser induced fluorescence spectra; principal component analysis; extreme learning machine.
DRSO-EGSM: data replication strategy oriented to automatic energy gear-shifting mechanism
by Xindong You, Yeli Li, Zhenyang Zhu
Abstract: Recently, more and more attention has been paid on research of cloud storage system. However, with the rapid growth of data volume, the problem of high energy consumption and low efficiency has become the key factor for restricting its development. In order to provide better support for the energy gear-shifting mechanism, we designed an energy-effective data replicating strategy (DRSO-EGSM). Firstly, data is classified into two categories, based on which the number of replicas is determined. And then the replica placement strategy oriented to energy efficiency is designed. Corresponding performance model and energy consumption model are established for data partitioning strategy. Meanwhile, the energy effectiveness of the DSRO-EGSM is evaluated in GridSim simulator. Compared with current existing similar mechanisms TDCS and the default replication strategy of HDFS, substantive results obtained from simulation experiments show that DSRO-EGSM can have more advantages in reducing energy consumption while guaranteeing the system performance.
Keywords: data classification; data replication; energy efficiency; cloud storage system; energy management.
Quantum flower pollination algorithm for optimal multiple relay selection scheme
by Hongyuan Gao, Yanan Du, Shibo Zhang
Abstract: In order to obtain optimal selection scheme with multiple source-destination pairs and multiple potential relays in cooperative relay networks, an optimal relay selection scheme is designed in cooperative relay networks considering co-channel interference (CCI). It is an integer optimisation problem for selecting suitable relay nodes to obtain optimal system performance. To get the optimal estimation performance with low computing complexity, quantum flower pollination algorithm (QFPA) is proposed to resolve the difficulties of optimal relay selection, and the proposed optimal relay selection scheme is called as quantum flower pollination algorithm based optimal relay selection (QFPA-ORS). The proposed QFPA combines the advantages of quantum evolutionary theory and flower pollination algorithm (FPA). So QFPA has the capability to search the optimal solution. Simulation results show that QFPA based relay selection scheme has the ability to search global optimal solution compared with other relay selection schemes based on classical algorithm and performs better than three other previous intelligent algorithms.
Keywords: cooperative relay networks; multiple relay selection; quantum flower pollination algorithm; co-channel interference.
Adaptive fuzzy sliding mode control algorithm simulation for 2-DOF articulated robot
by Feng Du, Ying Sun, Gongfa Li, Guozhang Jiang, Jianyi Kong, Du Jiang, Zhe Li
Abstract: About articulated robot's control, chattering phenomenon existed in conventional sliding mode algorithm. Therefore a robotic adaptive fuzzy sliding mode control algorithm is also proposed. This kind of algorithm is designed as an adaptive single input and output fuzzy system to calculate the control gain. Meanwhile, the mathematical proof is carried out on system's stability and astringency by Lyapunov theory's adaptive law. The adaptive fuzzy sliding mode control is simulated in Simulink, the simulation results show that when the chattering becomes weaker, the function of the system is promoted. Fuzzy sliding mode controller can be changed and adjusted with the transformation of system's state. Steady-state convergence is constant, adaptive fuzzy sliding mode control algorithm still with a good robustness under the condition that articulated robot's parameters uncertain and external interference.
Keywords: adaptive fuzzy sliding mode control; articulated robot; chattering phenomena; position tracking.
Analysis on fast training speed of extreme learning machine and replacement policy
by Shi-Xin Zhao, Xi-Zhao Wang, Li-Ying Wang, Jun-Mei Hu, Wei-Ping Li
Abstract: Extreme learning machine is known for its fast learning speed while maintaining acceptable generalisation. Its learning process can be divided into two parts: (1) randomly assigns input weights and biases in hidden layer, and (2) analytically determines output weights by the use of Moore-Penrose generalised inverse. Through the analysis from theory and experiment aspects we point out that it is the random weights assignment rather than the analytical determination with generalised inverse that leads to its fast training speed. In fact, the calculation of generalised inverse of hidden layer output matrix based on singular value decomposition (SVD) has very low efficiency especially on large scale data, and even directly cannot work. Considering this high calculation complexity reduces the learning speed of ELM conjugate gradient is introduced as a replacement of Moore-Penrose generalised inverse and conjugate gradient based ELM (CG-ELM) is proposed. Numerical simulations show that, in most cases, CG-ELM achieved faster speed than ELM in the condition of maintaining similar generalisation. Even in the case that ELM cannot work because of the huge amount of data CG-ELM attains good performance, which illustrates that Moore-Penrose generalised inverse is not the contribution of fast learning speed of ELM from experiment view.
Keywords: extreme learning machine; generalised inverse; SVD; conjugate gradient method.
Video compression and compensation of moving target image based on redundant wavelet theory
by Gu Gong, Hua Zhu
Abstract: The redundant wavelet transform has the translation invariant property, and the motion estimation can achieve better results in the redundant wavelet domain. This paper proposes the redundant discrete wavelet transformation (RDWT) for motion estimation and compensation in video compression and compensation of moving target image, and a fast adaptive block matching motion estimation algorithm based on redundant wavelet transform. This paper also introduces the methods of image domain search, starting point prediction and motion estimation into the redundant wavelet transform, and the study method based on optical flow which can enhance the transmission robustness with low redundancy. The experimental results show that the algorithm can effectively reduce the time required for motion estimation and improve the efficiency of motion estimation, and the subjective quality of the motion estimation is very good. The research results can provide technical support for robot vision system.
Keywords: redundant wavelet; pattern recognition; image features; time-frequency spectrum.
Evaluation of environmental performance based on SBM-Tobit two-stage model
by Minmin Teng, Chuanfeng Han
Abstract: Governments are the main institutions of environmental governance, but the investment-output results of environmental governance differ across different governments. This paper uses the SBM model to measure the static performance of environmental governance in eastern China from 2008 to 2014, and then uses Tobit regression analysis to identify factors influencing environmental performance. The results show that the environmental performance of seven provinces has a relatively large variation, and the proportion of environmental governance investment in GDP has the greatest impact on environmental performance.
Keywords: environmental governance; performance evaluation; non-expected output; SBM-Tobit model; eastern China.
Research on productive efficiencies measurement of Chinese toll highway enterprises based on super-efficiency DEA and windows analysis
by Changbing Jiang, Shufang Li, Liang Li
Abstract: Super-efficiency DEA-CCR/BCC and Windows analysis models are firstly used to analyse the productive efficiencies of Chinese toll highway enterprises listed on the Shanghai and Shenzhen stock markets during 2004 and 2013. Through cross-sectional data and panel data analysis, the research indicated that (a) the large-scale toll highway enterprises have no significant advantage of productive efficiency over the middle and small-scale toll highway enterprises; (b) Chinese toll highway enterprises show decreasing returns to scale except for several enterprises which have scale efficiency at present; (c) the productive efficiencies productivity shows large annual differences; (d) there is great effect on productive efficiencies whether toll highway enterprises could reduce the cost of production to a certain extent; (e) the productive efficiencies of Chinese toll highways are low as a whole; (f) with increasing age of enterprise established, the productive efficiencies of Chinese toll highway enterprises show volatility and slowly rising overall trend.
Keywords: toll highway enterprises; productive efficiencies; data envelopment analysis.