International Journal of Wireless and Mobile Computing (44 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.
Evaluation on multithreaded queue test data for multi-channel filter rod forming machine
by Jianhong Cao, Xu Kong, Qi Ji, Min Zhang
Abstract: This paper takes the real-time problems of cigarette industry multithreaded queue test data for multi-channel filter rod forming machine, under the existing evaluation system has not adapted the premise of the entire inspection business, through the information technology tools to assist in establishing business operational standards, and processes involved in the production and business management, based on dynamic statistics analysis the multi-threaded process for different queues to ensure the output results in real time. This method guarantees the DF10 double pole filter rod forming machine 1000 metres per minute production quality control, real-time visualisation of process quality, and fills the trade gap in this technically area.
Keywords: cigarette equipment; multithread; queue; testing data.
Cloud manufacturing service composition with service cooperation level evaluation
by Bin Xu, Yong Tang, Zhengshan Wang, Liang Shi, Jin Qi, Zhiyuan Hu
Abstract: Cloud manufacturing is a new type of modern manufacturing mode. The Cloud Manufacturing Service Composition (CMSC) is one of the key issues of cloud manufacturing. The quality and efficiency of cloud manufacturing services are influenced by the rationality of the optimisation model. Previous studies have rarely considered the impact of cooperation between services on the quality of the manufacturing service composition. In this paper, a Service Cooperation Level (SCL) evaluation mechanism and a corresponding update model are proposed to dynamically measure the level of cooperation between services. Furthermore, a novel Cloud Manufacturing Service Composition model with Service Cooperation Level Evaluation (CMSC-SCLE) is established by introducing the SCL evaluation value as a new objective. Finally, an Improved Strength Pareto Evolutionary Algorithm 2 (ISPEA2) is proposed to solve the CMSC-SCLE problem. The experimental results show that the CMSC-SCLE model is more practical than the CMSC model. In addition, compared with other four classical multi-objective optimisation algorithms, ISPEA2 achieves better performance when solving CMSC-SCLE problem.
Keywords: cloud manufacturing service composition; improved strength pareto evolutionary algorithm 2; multi-objective optimization; service cooperation level.
Numerical simulation on explosion overpressure features of methane-air premixed gas at different concentrations in utility tunnels
by Shangqun Xie, De-Ying Li, Le-Duan Chen, Rui Zhou
Abstract: According to the structural features of utility tunnels, the origin and development process of combustion and explosion of premixed natural gas with the volume fraction of 5%, 7%, 9%, 11%, 13% and 15% was simulated by fluid dynamics software ANSYS-Fluent. The results showed that the evolution rules of the overpressure and overtemperature produced by the flame front were basically the same within the critical concentration range of methane explosion. Local pressure and temperature jumps in the right of bottom edges were formed, appearing at the maximum overpressure, which was affected by the combustion front and pressure waves together with reflected wave pressure. The combustion process in utility tunnels can be divided into four stages: rapid growth of combustion, steady development of combustion, combustion jump, pressure and temperature oscillating retrenchment after burning. The simulated maximum overpressure is around 1.7 MPa and it is obtained under the conditions when the premixed gas concentration is 9% and 7%.
Keywords: numerical simulation; utility tunnels; explosion; overpressure.
An automatic detection model of pulmonary nodules based on deep belief network
by Zhiyong Zhang, Jialing Yang, Juanjuan Zhao
Abstract: The deep belief network (DBN) is a typical representative of deep learning, which has been widely used in speech recognition, image recognition and text information retrieval. Owing to a large number of CT images formed by the advanced spiral CT scanning technology, a pulmonary nodules detection model based on user-defined DBN with five layers (PndDBN-5) is proposed in this paper. The process of the method consists of three main stages: image preprocessing, training of PndDBN-5, testing of PndDBN-5. First, the segmentation of lung parenchyma is done. Segmented images are cut with minimum external rectangle and resized using the bilinear interpolation method. Then the model PndDBN-5 is built and trained with preprocessed training samples. Finally, testing PndDBN-5 with preprocessed testing samples is completed. The data used in this method are derived from The Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), which is the largest open lung nodule database in the world. The experimental results show that the correct rate of PndDBN-5 model for pulmonary nodule detection reached 97.5%, which is significantly higher than the traditional detection method.
Keywords: deep belief network; contrastive divergence; pulmonary nodules; detection.
Multi-threads computation for aggregation of time-series data
by Wang Jie, Lu Jingyi
Abstract: Applications involving time-series data have become popular with the rapid improvement of smart terminals and wireless networks. For example, in the case of mobile sensing, a sensing user will get a private input in each time period. And during the same period, the aggregator wants to calculate the aggregation statistics from the private inputs of sensing users. The privacy issue becomes much more challenging in the case of an untrusted aggregator. We are trying to increase the computation efficiency of the untrusted aggregator. Multi-cores architecture based CPU has been widely applied for not only personal computers but also servers. It has been an indispensible field in our everyday life. In this paper, we take advantages of multi-threads computation to a scalable basic aggregation protocol, and improve the computation efficiency of the trusted aggregator. We conduct some experiments to compare it with the basic protocol. The conducted experiments show the computation efficiency of our proposed protocol.
Keywords: cryptography; privacy; time-series data; multi-threads.
Low financial cost with ant colony optimisation in intelligent agriculture
by Xu Gaofeng
Abstract: With the development of wireless sensor networks, industrial automation and other computer and information related high technologies, a lot of practical IoT applications have greatly increased the productivity. Currently, more and more capital is being invested in IoT, especially intelligent agriculture as many countries begin to pay more attention to basic and intelligent agriculture. For large intelligent agriculture systems, it will cost a lot of time and energy (which further will cost investors' money) for the mobile sink to collect all the data of the sensing system with the help of cluster head node. In this paper, we try to solve this issue that minimizes the data collection path of the mobile sink, with the help of the ant colony optimisation algorithm. We implement the algorithm in Python and conduct two experiments that show that we can get the best path of the given example and show how the efficiency changes when the numbers of ants and loops increase. The better the optimal path becomes, the less financial cost we can achieve.
Keywords: financial cost; wireless sensor network; ant colony optimisation; intelligent agriculture.
Gray-information-based robustness of interdependent networks under attack on edges
by Dan Cui, Jianguo Chen
Abstract: The researches on robustness of interconnected networks have received more and more attention. However, previous studies of robustness are based on two extreme attack strategies, i.e. random attack and targeted attack. In the real world, the attack information is usually ambiguous. In this paper, the gray-information-based attack model is adopted to evaluate the robustness of the interdependent networks against the attack on edges. Through extensive simulation, we find that the robustness of the interdependent networks under gray-information-based attack gets stronger with the increase of redundancy parameter. We also get the conclusion that the robustness of the interdependent networks in the scenarios of gray-information-based attack is stronger than that of targeted attack and weaker than that of random attack. Finally, by comparison of three types of coupled networks, NW-NW and WS-WS coupled networks are found to be the most robust types under gray-information attack. Between the different type coupled network and same type coupled network, neither is guaranteed to be more robust than the other.
Keywords: gray information; interdependent network; robustness; cascading failures.
A hybrid training method of convolution neural networks using adaptive cooperative particle swarm optimisation
by Genfu Xiao, Huan Liu, Weian Guo, Lei Wang
Abstract: In order to deal with the problem of easily falling into local minimum in convolution neural networks (CNN) training, a hybrid training algorithm based on heuristic algorithm is proposed. Firstly, an adaptive cooperative particle swarm optimisation (ACPSO) is proposed, which uses a learning automaton to adaptively divide the subpopulation of the cooperative particle swarm optimisation (CPSO) and lets the decision variables with strong coupling relationship enter the same subpopulation. The adaptive strategy improves the ability of the CPSO algorithm to solve the high dimensional problem. Then, the connection weights of CNN are considered as elements in particles, and the ACPSO algorithm is used to train the CNN. The output of the ACPSO algorithm is applied as the initial weight of the BP algorithm for the purpose of speeding up the training speed of the CNN. The experimental results show that the ACPSO-BP algorithm has achieved good results, and the recognition rate of the CNN is improved. Thus it has the potential to be applied to other deep learning fields.
Keywords: convolution neural networks; cooperative particle swarm optimization; learning automata; BP algorithm.
Research on improved H control system of MEMS mirror FTS under MBSE framework
by Huipeng Chen, Youping Gong, Zhangming Peng
Abstract: In this paper, we present the development method of MEMS micro mirror FTS system based on MBSE, and improve the classical H∞ control algorithm, which is applied to the MEMS Micro Mirror FTS system. For tilting of MEMS micro mirror motion, the MBSE-based V-development framework is used to build a unified model for the whole process of development, testing and verification, which makes the development process efficient and fast. The improved H∞ control algorithm is used for control and compared with the uncontrolled system. The results show that, the FTS yields a clean spectrum with a full width at half maximum (FWHM) spectral linewidth of 102 cm-1 under the H∞ robust control. Moreover, the FTS system can maintain good stability and robustness under various driving conditions.
Keywords: model-based systems engineering; H∞ control; MEMS micro mirror; Fourier transform spectrometer.
Research on robust reduction control method of steering-by-wire based on MBSE
by Huipeng Chen, Chen Yue, Guojin Chen, Chang Chen
Abstract: Based on the theory and method of MBSE, a model of a Steering-By-Wire (SBW) system with mechanical and electrical integration is established. Based on the model, a robust control strategy with H∞ mixed sensitivity is used, and a robust controller is designed. The high order robust controller is poor in real-time and has a high cost. Routh, Hankel norm and ISE index reduction method are used to reduce the controller. Through time domain and frequency domain analysis, the effects of various reduction methods on the controller are discussed. Simulation results show that the ISE index reduction method has better reduction effect and has good robust performance and robust stability.
Keywords: MBSE; steering-by-wire; sensitivity; robust control; model reduction.
Spectrum access queuing-based scheme for prioritized cognitive radio networks
by Saad Elsayed, Ibrahim Tarrad, Abdelhady Ammar
Abstract: Cognitive Radio Networks (CRNs) have been recognised as an effective approach for overcoming the problem of spectrum scarcity caused by development of wireless applications. This paper proposes a channel access model for prioritised cognitive radio networks using an iterative method of queuing theory. This model is applicable for multi-channels and multi-priority classes of secondary users. The proposed model formulates an accurate closed form of an expected waiting time in the queue, an expected number of users in the queue, an expected waiting time in the system (waiting time in queue and service time), and an expected number of users in the system. The results show that the waiting time in the queue and the waiting time in the system compared to the basic model without priority will be improved by 58.3% and 20.8% respectively for class one secondary users. The results also show that the waiting time in the queue and the waiting time in the system will be improved by 16.7% and 5.8% respectively for class two secondary users. The proposed model investigates the desirable schedules of primary and secondary users.
Keywords: cognitive radio; spectrum access; non-preemptive priority; queuing theory.
Trajectory optimisation design of robot based on artificial intelligence algorithm
by Li Huang, Kai Zhang, Wei Hu, Chengcheng Li
Abstract: Artificial intelligence has attracted more and more attention and has been widely used in all walks of life, especially in the education industry, where it has gradually become the core. Aiming at the problem of robot trajectory planning in artificial intelligence, this paper applies the project teaching method to the course of artificial intelligence, regards trajectory planning as a project, analyses and studies it, and uses ant colony algorithm to find the optimal planning path. Through the teaching of the project, the students will understand the ant colony algorithm more deeply. The algorithm is programmed independently to achieve the final trajectory optimisation. Students become the main body of the classroom, give full play to the initiative and enthusiasm of the students, through the operation of the project to train the students' innovative ability and cooperation ability, and improve the overall quality of the college students.
Keywords: trajectory planning; project teaching method; artificial intelligence; ant colony algorithm.
Power consumption prediction with K-nearest-neighbours and XGBoost algorithm
by Zheng Liu, Qingsheng Kong, Lirong Yang
Abstract: Power consumption problem is an important part of economic development. Nowadays, power consumption of companies is rocketing. Power consumption prediction is an essential problem for power companies before supplying power. In this paper, we solve a power consumption prediction problem in Yangzhong High Tech Zone with K-nearest-neighbours and XGBoost algorithm. More importantly, we research on useful features for power consumption problems and it can guide power companies to supply appropriate amount of power. It will play an important role in regional construction in future.
Keywords: energy consumption prediction; time analysis; KNN; XGBoost.
Intelligent evaluation and computation of food packaging culture in Shanghai
by Zhen Wei, Wei Zhang, Chunhong Sun
Abstract: Presently, the priority for design in Shanghai is to quantitatively evaluate food packaging culture connotation with intelligence. This paper introduces analytic hierarchy process (AHP) to establish a Shanghai food packaging culture evaluation system and determine its index factors with ample computation. By selecting 50 sets of sample data, using artificial intelligence (AI) and back propagation (BP) neural network, the paper builds up Shanghai food packaging intelligent evaluation system, and provides a theoretical basis for the scientific computation on Shanghai food packaging culture connotation.
Keywords: Shanghai; food packaging; intelligence; evaluation; computation.
An efficient access control scheme based on CP-ABE with supporting attribute change in cloud storage systems
by Tao Ye, Yongquan Cai, Xu Zhao, Yongli Yang, Wei Wang, Yi Zhu
Abstract: The CP-ABE-based access control scheme, which can better realise the access control of many-to-multi-ciphertext shared in the cloud storage architecture, is still faced with the problems that the system cost is too large and the policy attribute revocation or restoration is not flexible. This paper proposes an efficient access control scheme based on CP-ABE with supporting attribute change in cloud storage system. The fine-grained access control can be achieved by re-encryption mechanism which takes the minimum shared re-encryption key for policy attribute set. Then the access structure tree is expanded by creating a corresponding virtual attribute for each leaf node attribute. The analysis results of the scheme indicate that not only are the efficiency and flexibility of the attribute change improved, but also the system cost is reduced.
Keywords: access control; policies attribute change; cloud storage; ciphertext-policy ABE.
Analysis and design of TENT map interleaver for interleave division multiple access scheme
by Aasheesh Shukla, Vinay Deolia
Abstract: Interleavers are the main component of almost all multiple access systems such as CDMA, IDMA etc. In Interleave Division Multiple Access (IDMA) systems, interleavers are crucially important for user separation that consequently also contributes maximising the system throughput. This paper develops an efficient TENT map based design of interleaver (TMI henceforth) generation which has less computational complexity and is more efficient in bandwidth compared with the existing prevailing algorithms in the domain. The proposed scheme is based on chaos theory and the simulation results show that TMI-based IDMA can achieve good BER performance without the need for extra memory resources.
Keywords: IDMA; chaos theory; tent map based interleaver; logistic interleaver.
Managing customary land conflicts and demarcations using mobile applications tools: a case study in Zambia
by Annie Mporokoso, Jackson Phiri
Abstract: Zambia has witnessed domestic and international customary land boundary conflicts due to improper land demarcation mechanism and partial documentation of customary land parcels. In this study we recommend the use and integration of Information Communication Technology (ICT) tools such as the Participatory Geographical Information System (PGIS) and the mobile application to be used in the implementation of the customary land management system. This will enable families and community groups to properly demarcate customary land boundaries thereby reducing land conflicts and providing security of tenure for customary land.
Keywords: land demarcations; PGIS; ICT; mobile application; land allocation; boundary conflicts and customary land; Zambia.
Sliding mode control with PI-based saturation for nano-positioning
by Liu Yang, Donghao Xu
Abstract: This paper proposes a modified sliding mode controller design with proportion-integral (PI)-based saturation (PISSMC) for nano-positioning of piezoelectric actuators (PEAs). Based on the sliding mode theory, the controller can consider hysteresis as the uncertainty of the system, and the nonlinearities of hysteresis and model imperfection can be processed to achieve precise positioning and tracking control. The PI term of this controller can decrease the steady-state error of the system and alleviate the chattering of the discontinuous part of the SMC controller. Further, as the only measurable information is the position, a high-gain observer is adopted to estimate the states. The designed controller employs a linear PEA system as parameters estimation of the model to estimate the control gain and compensate for the process nonlinearity. The robust stability of the PISSMC is proved through a Lyapunov stability analysis. Experimental results demonstrate that compared with the traditional SMC, the proposed controller can accomplish better control performance, such as more accurate resolution, less steady-state error and slighter chattering.
Keywords: sliding mode control; piezoelectric actuators; hysteresis; nano-positioning; nonlinear system.
Causal feature selection method based on extended Markov blanket
by Yinghan Hong, Zhifeng Hao, Guizhen Mai, Han Huang
Abstract: Feature selection is generally a key preprocess in artificial intelligence, machine learning and pattern recognition. Its purpose is to select a set of features that is most effective to predict the target. The existing features selection methods are generally a kind of features sorting methods according to the dependence between these features and the target variable. It is difficult for these methods to determine a certain number of features; moreover, in this study we show that some key feature is probably removed by these methods. To alleviate this problem, a causal feature selection method based on causal network is proposed. When the target variable and its candidate feature set form a causal network model, the proposed method can detect the causal features by conditional independence test based method according to extended Markov blanket. This method is able to cut out a certain number of features, simultaneously can avoid missing any key feature. Experimental results demonstrate that the proposal outperforms the counterparts when applies in support vector regression.
Keywords: causal feature selection; causal network; conditional independence test; Markov blanket.
Survey on different low complexity decoding algorithm for different orthogonal STBC MIMO wireless communication system under Rayleigh fading channel
by Priyanka Mishra, Chandra Kant Shukla
Abstract: This paper presents a survey based on the combination of spatial multiplexing and space-time coding techniques under Rayleigh fading channel constraint in MIMO wireless communication systems. The decoding algorithms, such as Maximum Likelihood, V-BLAST and Sphere Decoder are analysed and their performance is evaluated using different orthogonal space-time block coding techniques, such as quasi and rotated quasi-orthogonal space-time block codes. It has been observed that noise and interference get reduced by our proposed encoders with lower complexity at the receiver end. This improves the noise and interference performance by offering low complexity at the receiver. The paper also focuses on the performance of the combining effect of the demodulation algorithms with several other STBCs in the outcome.
Keywords: multiple input multiple output; orthogonal space-time block codes; rotated QOSTBC; Sphere Decoder; Maximal Likelihood; vertical Bell Laboratories layered space-time.
Detection of malicious domain names based on an improved hidden Markov model
by Tang Hengliang, Dong Chengang
Abstract: The ability to detect malicious domain names is critical for protection against internet security, data theft, and other dangers. Current methods for recognising malicious domain names have demonstrated poor detection accuracy in dealing with massive data. This paper proposes a novel malicious domain name detection method based on an improved Hidden Markov Model (HMM). First, by analysing various characteristics of good and evil domain names in DNS communication, we can use Spark fast extraction to distinguish their attributes; Then we can quickly classify unknown domain names accurately by using Baum-Welch algorithm and Viterbi algorithm in Hidden Markov Model (BVHMM) to achieve the effective detection of malicious domain names; Finally, to test our approach, we conducted a series of experiments, and the experimental results demonstrated that our model achieved good accuracy and recall rate compared with other detection models.
Keywords: malicious domain names; hidden Markov model; Baum-Welch algorithm; Viterbi algorithm; Spark.
Corrugated fractal monopole antenna with enhanced bandwidth for ultrawideband applications
by Rajeshkumar Venkatesan, Rajkumar Rengasamy
Abstract: A very compact coplanar waveguide (CPW) fed fractal monopole antenna with a modified ground plane is presented. The main objective is to obtain ultrawideband (UWB) characteristics from a simple microstrip monopole antenna. A wideband behaviour and good impedance matching are obtained by modifying the ground plane to semi-trapezoidal shape. Further, the self-similar fractal nature is introduced in the radiating element to enhance the bandwidth. The proposed antenna shows a wider impedance bandwidth from 3 GHz to 11.2 GHz for S11 ≤ 10 dB. A fractional bandwidth of about 115.5% (impedance bandwidth ratio 3.73:1) is achieved for the third fractal iteration. The total volume of the presented antenna is 18
Keywords: CPW; fractal antenna; self-similar; ultrawideband; wireless communication.
Mathematical modelling and analysis of hierarchical modulation in AWGN and Rayleigh channel.
by Kala K. Chandra, J. Jayakumari
Abstract: In digital video broadcasting, either multifrequency or single frequency network is used to transmit local and global broadcasting contents, respectively. Multifrequency network consumes large spectrum to transmit local information alone. Therefore an efficient technique is required to embed both local and global content in a single constellation. In this paper, hierarchical modulation or multilayered modulation is employed to satisfy this requirement in which the task is achieved by layered constellation. The base layer carries the high priority global contents and the low priority information by the enhancement layer. The performance of the system is highly determined by the detection rules and the coder chosen. The performance of hierarchical modulation system is analysed by framing decision rules for both high priority and low priority streams. In addition to derivation of probability of error of the system, the analysis of bit error rate of coded and uncoded system is done. Convolutional encoder with code rate 1/3, 1/2 and 2/3 is used in this paper.
Keywords: single frequency network; multifrequency network; QPSK; QAM hierarchical modulation; multilayer modulation; digital video broadcasting.
Application of Q-learning based on adaptive greedy considering negative rewards in football match system
by Xue Fei, Li Juntao, Yuan Ruiping, Liu Tao, Dong Tingting
Abstract: Aiming at the problem that the multi-robot task allocation method in a soccer system can easily fall into the problem of local optimal solution and real-time performance, a new multi-robot task allocation method is proposed. First, in order to improve the speed and efficiency of finding optimal actions and make better use of the disadvantages that traditional Q-learning cannot often propagate negative values, we propose a new way to propagate negative values, that is, Q-learning methods based on negative rewards. Next, in order to adapt to the dynamic external environment, an adaptive ε greedy method of which the mode of operation is judged by the ε value is proposed. This method is based on the classical ε-greedy. In the process of solving problems, ε can be adaptively changed as needed for a better balance of exploration and exploitation in reinforcement learning. Finally, we apply this method to the robot's football game system. It has been experimentally proven that dangerous actions can be avoided effectively by the Q-learning method which can spread negative rewards. The adaptive ε-greedy strategy can be used to adapt to the external environment better and faster so as to improve the speed of convergence.
Keywords: task assignment; Q-learning; negative reward; ε algorithm； adaptive technology.
Full-duplex relay selection analysis for decode and forward and amplify and forward relaying
by Fatima Ezzahra Airod, Houda Chafnaji, Ahmed Tamtaoui
Abstract: In this paper, we explore the cooperation over a modern wireless communication network, where we promote the communication between a pair of moving nodes, the source and the destination, to exchange information. We assume that fading constraints overrun this environment, so accordingly the direct link between the source and the destination nodes is not considered. Therefore, full-duplex (FD) relays cooperate with the source to send data packets to the destination. In this new generation of networks, the crucial issue for wireless devices is their limited battery capacity that impacts mainly, the network lifetime. Note that this constraint has as much as importance when devices forward data to other terminals. Thus, with the regard of keeping a good compromise between the power consumption and the system performance, this paper studies an optimal relay selection to select one best relay to forward data to the destination based on Decode-and-Forward (DF) and Amplify-and-Forward (AF) relaying techniques. We derive the DF and AF outage probability closed form expressions and the AF numerical approximation for the relay selection strategy. For verification, simulation results are presented. We also perform an analysis of asymptotic results in order to evaluate the impact of the power transmission on the system performances.
Keywords: full-duplex relay; relay selection; amplify-and-forward; decode-and-forward; Doppler effect; outage probability; power transmission.
A novel quantum-inspired binary wolf pack algorithm for difficult knapsack problem
by Yangjun Gao, Fengming Zhang, Yu Zhao, Chao Li
Abstract: 0-1 knapsack problem is a classical combinatorial optimization problem, which is often used to validate the search performance of binary intelligent algorithms. Although the traditional binary wolf pack algorithm (BWPA) can provide an effective solution to the general knapsack problem, it cannot achieve satisfied optimization results for the difficult knapsack problems such as the high-dimensional KP01 and often fall into the local optimum in some extreme cases. In order to improve the BWPAs applicability and searching ability in difficult knapsack problem which has not been well resolved, a novel Quantum-Inspired WPA (QWPA) which based on quantum encoding to enhance the performance of WPA for difficult knapsack problem is presented. In this paper, we have introduced the detailed quantitative design of the three important behaviours in presented QWPA and a modified form of quantum collapse which brings better diversity has been proposed. Moreover, a new diversity analysis mechanism is given to verify the diversity of the proposed algorithm compared to other quantum-inspired intelligent algorithms which including QIEA-PSA, QPSO, and QGA. Numerical simulation is obtained from both general and difficult benchmark instances of knapsack problem and the simulation results show that the QWPA has a more competitive performance than other Quantum-Inspired algorithms with the increasing of the size of knapsack problems
Keywords: binary wolf pack algorithm; quantum encoding; combinatorial optimization; diversity; difficult 0-1 knapsack problem.
A game theoretic approach to maximise payoff and customer retention for differentiated services in a heterogeneous network environment
by Pushpa Singh, Rajeev Agrawal
Abstract: Future networks are being devised with the vision of heterogeneity in which a mobile user/device will be able to connect seamlessly to multiple wireless networks (WLAN, cellular, WMAN, WPAN) and evolve simultaneously. Coexistence of the underlying network is the requirement of telecom industry, which leads to an open competition among the service providers. To survive in the market, telecom operators are investing more in retaining the valuable users rather than acquiring new users. This paper introduces the user agent to check the loyalty of user and application preference, and the network agent is used to rank the network as social, quality and normal network. The user can also set his preference as social trust, quality trust and normal trust. The game between the user agent and the network agent constructs a payoff matrix for loyal users and normal users. Results show seven equilibrium cases for loyal users where the user agent and network agent have equal payoff. In the case of normal users, there is only one case of equilibrium and for the other cases the network agent can maximise his payoff.
Keywords: heterogeneous network; QoS; loyalty; payoff; game theory; traffic class; service provider.
Reliable and energy-aware routing in mobile ad-hoc networks
by Sajal Sarkar
Abstract: In a Mobile Ad-hoc Network (MANET), energy-awareness is a crucial design issue as it consists of a group of mobile nodes. The mobile nodes with limited battery power act as router in MANET. Though establishment of an appropriate and efficient route is an important design aspect, a more challenging task is to establish and select a reliable and energy-efficient route between a source-destination pair. Thus, power failure of a mobile node constituent influences data routing, link failure and network lifetime. Therefore, to meet the above mentioned goal and overcome energy-aware routing design issues, in this paper routing protocols are proposed to construct a reliable and energy-aware route considering energy consumption and remaining energy of nodes. The remaining energy and the energy factor (the ratio of remaining energy and initial energy of a node) are used as important parameters for selection of a node in a route. Under the considered parameters, the proposed routing protocols ensure reliability and energy-awareness in the MANET and avoid link failure due to the node's low power in an established route. Simulation results show that the proposed routing protocols perform better than the similar kind of popular existing routing schemes in terms of energy consumption, throughput, delay and routing overhead in different network scenarios.
Keywords: MANET; routing protocol; energy consumption; energy-aware routing; reliability.
IPCA-SVM based real-time wrinkling detection approaches for strip steel production process
by Tong Zhao, Xiong Chen, Lirong Yang
Abstract: Strip steel wrinkling is one of the common problems in strip steel production line. The wrinkling phenomenon has a serious impact on the quality of the products, resulting in product waste, and even leading to the entire production line downtime. The key point to solve the problem is real-time detection for strip wrinkling while making an early warning. This paper proposes an IPCA-SVM based online wrinkling detection approach. IPCA is used to compress each frame image from industrial camera and extract effective features from frame images. The projection coefficients of each frame image on the principal components are the inputs to SVM model for classification. Experiment results show that the proposed method is valid for real-time wrinkling detection for strip steel production process.
Keywords: strip wrinkling; IPCA-SVM; real-time detection.
Constrained solution of CEC 2017 with monarch butterfly optimisation
by Hui Hu, Zhaoquan Cai, Song Hu, Yingxue Cai, Jia Chen, Sibo Huang
Abstract: Recently, inspired by the behaviour of monarch butterflies in North America, Wang et al. proposed a new kind of swarm intelligence algorithm, called Monarch Butterfly Optimisation (MBO). Since it was proposed, it has been widely studied and applied in various engineering fields. In this paper, we apply MBO algorithm to solve CEC 2017 competition on constrained real-parameter optimisation. Also, the performance of MBO on 21 constrained CEC 2017 real-parameter optimisation problems is compared with five other state-of-the-art evolutionary algorithms. The experimental results indicate that MBO algorithm performs much better than the other five evolutionary algorithms on most cases. It is strongly proven that MBO is a very promising algorithm for solving constrained engineering problems.
Keywords: monarch butterfly optimisation; migration operator; butterfly adjusting operator; constrained optimisation.
Novel localization algorithms in wireless sensor networks
by Abdelali Hadir, Khalid Zine-Dine, Mohamed Bakhouya, Jamal El Kafi
Abstract: Localisation precision is one of the predominant challenges in static and mobile wireless sensor networks. It is a critical issue to be tackled when developing applications that rely on this type of network. This paper presents three localisation techniques, named eDV-Hop1, eDV-Hop2, and eDV-Hop3, based on geometry principles. The performance of these techniques was evaluated using the network simulator (OMNeT++) and compared with the basic DV-Hop, iDV-Hop1, and iDV-Hop2. Results show that significant improvement is obtained in terms of energy consumption and localisation error according to several parameters, mainly the number of sensors, the number of anchor nodes, and the communication range of sensor nodes.
Keywords: wireless sensor networks; localisation techniques; simulations and performance evaluation.
Surface EMG electrode distribution for thumb motion classification based on wireless communication equipment
by Wanfen Xu, Gongfa Li, Zhaojie Ju, Honghai Liu
Abstract: The interaction between humans and computers has become more necessary and more specific, and the informatisation of human hands has made the human-machine interaction based on gesture recognition more and more extensive. The thumb, as the most important finger, plays a decisive role in decoding the gesture, especially in controlling of the smart phones and many other smart devices. As a result, this study aims to decode the different thumb gestures from sEMG signal and to improve the robustness of gesture recognition and decrease the influence of physiological conditions and the electrode displacement between different users. In this article, we use the Bluetooth wireless communication and focus on the relationship between the EMG signal and the electrode identifier number. We change the electrode's number into a new feature and combining the traditional features with the new features to verify the electrode's number has a correlation with the thumb gesture. Experiments show that after adding new features, the gesture recognition rate has increased.
Keywords: EMG; thumb; gesture recognition; wireless communication.
Survey on WiFi infrastructure attacks
by Rui Guo
Abstract: This article describes WiFi hacking techniques that attackers have used, and suggests various defensive measures. It also shows how easy it is to forge disassociation and deauthentication packets. Its less secure than wired connections because an intruder does not need a physical connection. It also explains man-in-the-middle attacks, Rogue AP, Race Conditions attacks, in wireless networks, and gives a list of selected open-source tools. The article includes several recommendations that will help to improve security in a wireless infrastructure.
Keywords: WiFi network; Rogue AP; Race Conditions; MITM.
A novel DV-hop method based on coupling algorithm used for wireless sensor network localisation
by Yechuang Wang, Penghong Wang, Jiangjiang Zhang, Xingjuan Cai, Wuchao Li, Yanyan Ma
Abstract: Wireless sensor network (WSN) localisation is an essential requirement in the increasing prevalence of WSN applications. As an important part of the Internet of Things (IOT) it has become a hot research area. Distance vector-hop algorithm (DV-Hop), an range-free algorithm, is widely deployed to solve the localisation problem in WSN. However, the results of the estimation precision are usually not satisfactory. In order to improve the WSN positioning accuracy, in this paper, we propose a new coupling algorithm based on bacterial foraging algorithm (BFA) and glowworm swarm optimisation (GSO) (BFO-GSO). The algorithm has good convergence speed, local search ability of BFO and global convergence of GSO. The optimisation performance is verified by CEC2013 benchmarks in those designs against the original algorithm. Furthermore, Wilcoxons rank-sum non-parametric statistical test and Friedman test were carried out to judge whether the results of the proposed algorithm differ from those of the other algorithms in a statistically significant way. The numerical results prove that it is able to significantly outperform others on majority of the benchmark functions. Finally, the proposed algorithm is also combined into the DV-Hop algorithm to improve the WSN positioning accuracy. Experimental results show that our improve algorithm achieves better performance when compared with others DV-Hop algorithms.
Keywords: WSN; localisation; DV-Hop; coupling algorithm; BFO algorithm; GSO; CEC2013.
Demand estimation of water resources based on algorithm comparison
by Junyan Wang, Jiangjiang Zhang, Xingjuan Cai, Yanyan Ma
Abstract: Water is the source of life and the correct assessment of water resources is an important prerequisite for the rational use of water resources. In this paper, water resources are evaluated and predicted by three different algorithms, including Bat Algorithm (BA), Particle Swarm Optimisation (PSO) and Pigeon-inspired Optimisation (PIO). Comparing the errors of water resources assessed for the three algorithms, we select an algorithm of the minimum error to predict the future water demand. In the experiments, firstly, the water data from 2003 to 2012 are used to find the optimal weights of the models. Then the weight factor is combined with the given model to gain the error between predicted value and the rest data (2013-2015). Finally, the simulation results show that PIO algorithm has a better performance than the BA and PSO algorithms.
Keywords: water resources; bat algorithm; particle swarm optimisation; pigeon-inspired optimisation.
Research on parameter search of the worst operating condition for explosion overpressure in utility tunnels based on genetic algorithm
by Shangqun Xie, De-Ying Li, Hui Lv, Rui Zhou
Abstract: In this paper, the 2D numerical simulation model for the gas pipe tank of utility tunnels is established. Aiming at optimising the maximum overpressure produced by an explosion in the gas pipe tank, in restricted conditions of vent position, premixed gas concentration in the tank and ignition position, a method of parameter optimisation of the worst operating condition for explosion overpressure in the gas pipe tank of utility tunnels is proposed by combining computational fluid mechanics and genetic algorithm. The results show that genetic algorithm is feasible in searching for the worst operating condition for explosion overpressure in the gas pipe tank of utility tunnels and can improve the searching efficiency significantly. Methane-air premixed gas under the two conditions being both pre- and post-optimised can form deflagration phenomenon. The deflagration wave is the direct factor of the overpressure formed at the boundary of the model. Both the pressure and temperature imposed by the deflagration wave acting on the model boundaries show an evident rise compared with those before optimisation. The maximum overpressure is increased by 15% and the maximum temperature is increased by 7%.
Keywords: genetic algorithm; utility tunnel; explosion overpressure; numerical simulation.
A novel method for user relationship measuring in social networks
by Jie Wang, Chonghuan Xu
Abstract: Recommender systems are widely used to provide users with appropriate items, and have emerged in response to the problem of information overload. The measuring method of user relationship in social networks is the core of personalised recommendation. To a certain extent, the measuring quality of users relationships determines the accuracy of recommendation results. In this paper, we propose a novel measuring method of user relationship that considers direct and indirect relationships among users. The experimental results on two famous microblog datasets shows that the presented algorithm is of high performance.
Keywords: online social networks; user relationship; direct relationship; indirect relationship.
Smooth terminal sliding mode control of Buck converter for wireless mobile devices
by Yuye Wang
Abstract: The performances of wireless mobile portable devices are constantly improving, and the response speed and robustness of the device power supplies need to be researched. In general, wireless devices are powered by batteries, which require various Buck converters. In order to improve the response speed and robustness of the Buck converter, a smooth terminal sliding mode (TSM) control method is proposed. The TSM surface and the control law are designed. The sliding mode existence condition is proved theoretically, and the robustness of the closed-loop system under disturbance is analysed. The smooth TSM overcomes the chattering phenomenon that occurs in the traditional TSM, so a fixed-frequency pulse width modulation can be realised, which will have a good application prospect. The simulation results show that the proposed control method has the advantages of fast dynamic response and strong robustness.
Keywords: wireless mobile device; Buck converter; smooth terminal sliding mode; finite-time convergence.
Research on multi-objective path planning of robot based on artificial potential field method
by Hu Yunqiang, Ke Wende, Chang Lin, Leng Xiaokun
Abstract: Aiming at the shortcomings of traditional artificial potential field method which easily falls into zero potential field in the case of complex obstacles and cant guarantee the optimal path, a multi-objective path planning based on artificial potential field method is proposed. The method takes the path length and path security as the optimisation targets, and the obstacle repulsion coefficient as the decision variable. The objective function is calculated by establishing the artificial potential field performance model, and the NSGA-II algorithm is used for multi-objective optimisation to obtain the optimal path. The flexibility of decision variables prevents the path from falling into zero potential field points, and multi-objective optimisation ensures path length and security optimisation. The simulation results prove the feasibility and superiority of the method.
Keywords: robot path planning; multi-objective optimization; artificial potential field.
Contact analysis and simulation of high performance round link chain
by Xiangjuan Bian, Youping Gong, Longbiao Gao
Abstract: High performance round link chains are applied in many fields, such as mining, metallurgy, hoisting, shipping, etc., and accidents can easily happen under bad and complicated working conditions. This paper studies the dynamic analysis of the round link chain transmission process. The kinematics analysis is carried out first, and then the dynamic analysis is carried out after the force analysis of each component. By establishing the mathematical equation of the structural model of the round link chain, the two static analysis models for the contact of the chain links are derived. Then, the collision process between the round link chains is simulated and analysed. Finally, the fatigue fracture mechanism of round link chain and the propagation law of fatigue crack are studied, and experiments verified that the round link chain satisfies the actual requirement in special needs such as mining.
Keywords: round link chain; kinetic analysis; fatigue analysis; numerical simulation.
A dynamic resource allocation scheme based on cognition in LTE system
by Junshe Wang, Yanfei Wang, Songhua Wang
Abstract: In this paper, we propose a dynamic spectrum allocation scheme based on cognition in LTE system. The new scheme is to address the poor communication service problem caused by co-channel interference between the cell-edge users in the LTE system. The scheme leverages the cognitive characteristic in the LTE system to enable the base station to dynamically obtain the idle resource status information of the adjacent cells and integrates the idle resource information of the target cell, and then employs the ant colony optimisation technique to allocate the resource blocks to users. Experimental results show that the proposed scheme allows the cell-edge users to dynamically use the idle resource blocks of adjacent cells, which enhances resource blocks usage and system throughput while ensuring fairness among users, which may improve the quality of user service at the cell-edge.
Keywords: LTE system; resource allocation; cell edge user; cognitive characteristic; ant colony optimisation.
Energy balanced adaptive clustering routing protocol for heterogeneous wireless sensor networks
by Hu Zhongdong, Wu Hualin, Wang Zhendong
Abstract: In wireless sensor networks (WSNs), the main problem is how to design an energy efficient routing protocol, but one of the bottlenecks is that the WSN's energy is limited. Owing to the current cluster routing protocols unconsidered node location and adopted single hop routing mechanism in routing communication in heterogeneous WSNs, a large number of cluster heads that are far away from the base station will consume a large amount of energy. In this paper, an energy balanced adaptive clustering routing protocol is proposed for heterogeneous WSNs, node location and the residual energy are considered to improve the cluster heads elected mechanism, which increases the probability to become cluster heads that the nodes are close to the base station and have high residual energy. In addition, the protocol uses an adaptive routing communication mechanism combining multi-hop with single-hop to balance the network energy consumption. Theoretical and simulation results show that compared with DEEC and SEP, the protocol can prolong the lifetime of the network and increase the network throughput.
Keywords: heterogeneous wireless sensor networks; energy consumption; adaptive; clustering protocol.
Efficient multi-vehicle navigation based on trajectory vector features considering non-uniform destination distribution for emergency evacuation
by Yang Cao, Zhiming Ding, Fujie Ren, Limin Guo
Abstract: In recent years, large-scale events have been held frequently, and more and more people are participating in these activities. When encountering an emergency, it is necessary to quickly evacuate the participating people. A reasonable traffic evacuation plan is an important part of the efficient evacuation. However, the uneven geographical distribution of a large number of vehicles and participants poses a challenge for efficient evacuation planning. An efficient emergency evacuation plan needs to minimize evacuation time and traffic congestion. Reasonable route selection and traffic flow assessment are key to the evacuation plan.
In this paper, we proposed an efficient multi-vehicles navigation method based on trajectory vector features considering non-uniform destination distribution for emergency evacuation. First, we employed the CrossRank algorithm to extract the real-time state vector of roads and then navigate the vehicle based on these state vectors. In addition, spatial diversity theory was introduced into our model for the non-uniform distribution of multiple vehicle evacuation. We conduct a series of multi-vehicle navigation simulation experiment on a real taxi trajectory dataset. The experimental results demonstrate that our approach is effective and efficient.
Keywords: multi-vehicles navigation; vector features; trajectory data; non-uniform
destination distribution; emergency evacuation