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.
Artificial bee colony algorithm for energy efficiency optimisation in massive MIMO system
by Fatma Bouchibane, Messaoud 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 feature selection method based on effective range and SVM-RFE
by Yifei Mao, Yuansheng Yang
Abstract: Identification of discriminative features from information-rich data with the goal of clinical diagnosis is crucial in the field of biomedical science. Support Vector Machine Recursive Feature Elimination (SVM-RFE), an efficient feature selection method, has been widely applied in the domain and has achieved remarkable results. However, biological data are usually class-imbalanced and contain outliers, which largely affect the feature ranking in SVM-RFE. This paper proposes a new feature selection method based on SVM-RFE and Effective Range (SVM-RFE-ER). The proposed method ranks the features by means of combining the SVM weight and the feature weight based on the effective ranges. Experiments on the simulated and real datasets have shown that SVM-RFE-ER is robust, especially against outlier and imbalanced data, and it is effective in identifying biologically meaningful biomarkers for disease study.
Keywords: feature selection; imbalanced data; outlier data; effective range; SVM-RFE.
Maximum match filtering algorithm to defend spectrum-sensing data falsification attack in cognitive wireless sensor networks
by Pinaki Sankar Chatterjee, Monideepa Roy
Abstract: Cognitive wireless sensor networks (CWSNs) are a new technology to provide better bandwidth usage compared with a normal wireless sensor network. CWSNs
use opportunistic spectrum access to transfer data. They transmit data through the primary user's spectrum band when there is heavy traffic in its own network. IEEE 802.22 is the first standard that tells us about the concept of cognitive radio. It also helps the network to eliminate collisions and delays in data delivery. While doing so, however, CWSNs are subject to several security threats, attacks on secrecy and authentication, attacks on network availability, stealthy attacks on service integrity, etc. The attacks on network availability are known as the Denial of Service (DOS) attacks. The Spectrum Sensing Data Falsification (SSDF) attack is a type of DOS attack. In SSDF attack the attackers modify the spectrum sensing report in order to compel the base station to take a wrong collaborative decision regarding the vacant spectrum band in other networks. In this paper, we have proposed a new algorithm for collaborative spectrum sensing and spectrum decision making in CWSNs, named the Maximum-Match Filtering algorithm (MMF). This algorithm is executed at the base station to counter the SSDF attack.
Keywords: cognitive wireless sensor network; denial of service attack; spectrum sensing data falsification attack; multiple linear regression.
A flexible visual quality control algorithm for perceptual video encryption based on H.264
by Cao Yuqiang, Gong Weiguo, Bai Sen
Abstract: In order to meet all kinds of video security applications, especially pay-digital-TV system, a perceptual video encryption scheme based on visual quality control strategy is proposed. The optimal syntax elements and sensitive coded elements are chosen to encrypt by using mathematical XOR operations with stream ciphers generated by Chen chaos system. In order to enhance the security, the encryption scheme of this paper synthetically uses three strategies, including MVD encryption, intra-prediction mode encryption and levels of low coefficients encryption. The variable length keys are used to encrypt the syntax elements to improve key usage. Experimental results show that the proposed perceptual encryption scheme can achieve high security at a relatively high compression ratio and bandwidth cost, as well as about 2% coding rate and 6% encoding time increased, at the cost of slightly sacrificing code rate and encoding time. Especially, the degraded visual quality can be controlled gradually with a simple quality factor.
Keywords: video encryption; perceptual video encryption; H.264.
Randomness-driven global particle swarm optimisation for unconstrained optimisation problems
by Zhen Hu, Dexuan Zou, Zichen Zhang, Xin Zhang, Xin Shen
Abstract: This paper proposes a randomness-driven global particle swarm optimisation (R-dGPSO) algorithm to solve the unconstrained optimisation problems. First, an opposition learning strategy is modified and applied to the population initialisation of R-dGPSO, which is helpful to improve the quality of the initial solutions. Second, cosine mapping and random factors are used to adjust the inertia weight and improve the convergence of the algorithm. Third, an impact factor is incorporated into the velocity updating formula in order to regulate the impact of personal best particles and global best particle on particles flight trajectories. Fourth, a new location updating strategy is devised to help R-dGPSO to get rid of local optima. Experimental results show that R-dGPSO can effectively accomplish the task of numerical optimisation in most cases. Furthermore, it can produce better objective function values than the other methods. Therefore, R-dGPSO is an effective numerical optimisation method for solving unconstrained optimisation problems.
Keywords: particle swarm optimisation; randomness-driven; global; unconstrained problems.
Turning mechanism and optimisation design of automatic screen printing machine
by Zhang Zhiming, Sun Jun, Lu Binbin, Duan Yaoshuai
Abstract: Screen printing technology is now widely used in garment printing, such as T-shirts, cultural shirts and so on. This technology has become the most important printing method for garment printing because of the advantages of large quantity, high efficiency and low price. Automatic screen printing machine is an automatic screen printing device with the advantages of saving energy and reducing labour intensity. The automatic screen printing machine can print about 1000 pieces per hour. In recent years, the printing industry has developed rapidly. The demand for automatic screen printing machines is increasing and the requirement for it is higher and higher. In this paper, the principle and process characteristics of automatic screen printing are studied. A new design scheme for turning device is proposed in the light of the turning mechanism. Meanwhile, the idea of axiomatic design is used to optimise the design of the turning mechanism. The new turning mechanism overcomes the shortcomings of the traditional mechanism and reduces the friction and noise in the printing process. The turning process is flexible and the transmission is accurate. The practical application shows that the scheme is in conformity with the technical requirements and the reliability is good and improves the working efficiency of screen printing machine and enhances versatility.
Keywords: automatic screen printing machine; turning mechanism; axiomatic design; optimal design.
Research on productive efficiency measurement and influence factors based on DEA window analysis and Tobit model: an illustrative example of Chinese Toll Highway Enterprises
by Shufang Li, Changbing Jiang, Liang Li
Abstract: According to varied and highly complex characteristics of Chinese Toll Highway Enterprises' productive efficiency, we propose a hierarchical efficiency and factor analysis method that integrates environmental factors and DEA window analysis and Tobit model. Through two output variables, three input variables, eleven environment variables, and panel data analysis during 2007 to 2014, we found that: 1) the overall productive efficiency of Chinese Toll Highway Enterprises is at a high level and shows fluctuating growth; 2) the factors of establishment life of Toll Highway Enterprises, the management efficiency and growth in total retail sales of social consumer goods positively affect the productive efficiency of Chinese Toll Highway Enterprises; 3) the factors of rates of employees' wages, China's economic growth and possession of highway business transportation vehicles showed a negative correlation on productive efficiency of Chinese Toll Highway Enterprises.
Keywords: productive efficiency; DEA window analysis; Tobit model.
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.
DBSCAN-based modular design for the crane grab
by Xianfu Cheng, Jing Li, Chong Wan, Haoyang Qiu, Yongsheng Wan
Abstract: In order to shorten the design period and improve the design efficiency of the crane grab to rapid response to market demands, a modular design for the crane grab is one of the effective methods to enhance design efficiency. The design structure matrix (DSM) was used as a tool to capture the physical relationships between components within the grab and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm was used to cluster the components into modules. A method of module partition DBSCAN-based for product design is proposed, which considers the asymmetric relationship between components and the association relationship between two modules. The rule of modularity metric was to maximise high cohesion degree within the modules and minimise coupling degree between the modules.
Keywords: modular design; DSM; DBSCAN algorithm; crane grab.
A novel image encryption method based on hyperchaotic system and pixel information association
by Zhenhu Ning, Lijuan Duan, Dongkui Zhang, Fan Xu, Guoqin Cui, Peng Liang
Abstract: In recent years, a variety of image encryption methods based on chaotic systems have been proposed, and have achieved good results. However, the existing encryption methods do not take the relevant image information into consideration, leading to low sensitivity, low information entropy, large correlation between adjacent pixels of cipher image, and being more vulnerable to differential attacks. In order to improve the security of image encryption, this paper proposes a new image encryption method with a dynamic key, based on a hyperchaotic system and the association of pixel information, and designs a three-level encryption structure with diffusion encryption, scrambling encryption and re-diffusion encryption, and analyses the rationality of the three-level encryption structure by experiments. In the three-level encryption structure, the key of each level is dynamically generated by different chaotic sequences and pixel information encrypted, and the whole image data and pixel data and position data are added in the encryption process. Experiments demonstrate that the image encryption method proposed in this paper has the characteristics of strong sensitivity, low correlation between adjacent pixels, anti-differential attack and high security.
Keywords: image encryption; hyperchaotic system; pixel information association.
The trusted virtual machine cluster construction method based on particle wave equation
by Fazhi Qi, Zhihui Sun, Shiqiang Zhang
Abstract: In current cloud computing platforms, multiple virtual machines run together in a physical computing platform, if we still solve the trust of single virtual machine, the trust of the entire virtual machine groups cant be ensured. But studies of the security of the virtual machine in cloud computing has not considered the cloud environment, which is a complex clustering, and it also has not considered the effect of which virtual machine cluster resides on a single virtual machine. In order to solve the above problems, a method to build a trusted virtual machine group based on the particle wave equation is proposed. According to the output, which is based on the predictive control for a single virtual machine, the Sine-Cordon particle wave equation is used to complete macro-fitting of the virtual machine cluster's microscopic output, and based on the fitting stable point of Sine-Cordon equation, the trusted state of the virtual machine cluster can be described, so we can build a trusted virtual machine group. Compared with the traditional security policy for a single virtual machine, the measurement parameters of our method can be formulated according to the different environment. It has a better environmental adaptability, and by constructing a virtual machine cluster it can effectively reduce the security threats to virtual machines. A virtual machine cluster can be used to constrain single entity action in the cloud environment, and it can safeguard the continued trust of individuals and groups with a strong fault tolerance.
Keywords: cloud computing; virtual machine; predictive control; Boltzmann equation.
A rational threshold signature protocol based on generalised projective transformation
by Xue Fei, Su Qinghua
Abstract: The prevalence of threshold structures is mainly based on the Lagrange interpolation polynomial, Chinese Remainder Theorem, RSA key segmentation techniques, circular features and so forth. Combining with above-mentioned threshold structures, a series of threshold signature plans can be constructed. Because of the change of interpolation nodes the Lagrange interpolation polynomial causes the recalculation of interpolation coefficient. Moreover, the degree of algebraic curve sometimes is so high that an efficiency problem occurs. Chinese Remainder Theorem is not easy to use to construct an ultra-increment sequence, and circular features has a poor performance. RSA key segmentation technique is not the real threshold structure, so it can be used only by group signature. This paper aims at drawbacks of the above-mentioned threshold structures and constructs a new threshold structure based on generalised projective transformation. In order to put this into use, gives an ID-based rational threshold signature protocol. We analyse the threshold plan by using the crisp cooperative game theory, the theorems turns out to be that this threshold structure scheme is ideal.
Keywords: generalised projective transformation; cooperative game; threshold structure.
Modular design method of EOD robot based on genetic algorithm
by Qiang Yin, Zhichao Xiong, Shaoyun Song, Guoquan Zhang
Abstract: With the rapid development of product design, the modular design method shows unique advantages in the design of the product. Modular design has become a hot spot in the manufacturing and design industry. The aim of the modular design method is to make up the products that include many types and specifications with fewer types and quantities of modules. In this paper, EOD robot design as the research object according to the module division principle, from the point of view of the EOD robot products, is divided into several basic units by clustering algorithm, genetic algorithm, qualitative and quantitative module clustering, and the application of genetic algorithm to solve the problem of modular design. By analysing the design example of modular EOD robot, the feasibility and effectiveness of the module partition method are verified.
Keywords: modular design; module division; module clustering; genetic algorithm.
Model knowledge matching algorithm for steelmaking casting scheduling
by Guozhang Jiang, Xiaowu Chen, Xiaoyong Li, Gongfa Li, Feng Xiang
Abstract: The scheduling model matching of steelmaking casting is a critical process in steel production scheduling. At present, few studies have concentrated on the common feature about the production scheduling model. Applying model matching and knowledge representation to steel production scheduling is rarely reported. In order to meet the increasingly complex production requirements and the time precision control of the intelligent scheduling, the object-oriented knowledge representation method is used to represent the scheduling model and the disturbance events in steelmaking casting process. A model knowledge component and a disturbance events knowledge framework are established in this paper. A distance algorithm and Euclidean distance are used to calculate the matching degree between the model and the disturbance events. A set of examples are analyzed, the result shows that the algorithm can quickly match the steelmaking casting scheduling model and the disturbance events, and improve the accuracy and efficiency of the model matching.
Keywords: steelmaking casting; scheduling model; knowledge representation; model matching.
Path planning for EOD robots
by Qiang Yin, Zhichao Xiong, Guoquan Zhang
Abstract: EOD robots play a vital role in a dangerous mission, and path planning is an important research content of the technical field of EOD robots, which could help the EOD robot avoid obstacles correctly and perform the detonation task according to given instructions and environmental information. Path planning is an important part of the autonomous mobile robot. Its task is to find a collision-free path from the initial state to the target state according to certain evaluation criteria in the environment with obstacles. The path planning technology can be divided into two main categories: the traditional path planning method and the intelligent path planning method. This article reviews a variety of traditional methods and multiple intelligent planning methods and their applicable fields, and compares the advantages and disadvantages of various methods. With the development of the current situation and existing problems of path planning, planning for the future research of EOD robots is summarised and discussed.
Keywords: EOD robot; path planning; artificial potential field; bionic algorithm.
Hyperheuristic genetic algorithm for steelmaking continuous casting rescheduling based on strong disturbance of task
by Guozhang Jiang, Hushi Dong, Le Yang, Gongfa Li, Feng Xiang
Abstract: The problem of steelmaking and continuous casting rescheduling is the key problem in the steel production scheduling. Aiming at this problem under strong disturbance of task in this paper, to minimise the difference degree before and after the scheduling adjustment as the objective function, a fast and efficient hyperheuristic genetic algorithm is proposed. In the framework of the hyperheuristic algorithm, the high layer strategy is designed as a self-learning heuristic rule selection strategy, the low layer design is a series of genetic operators related to steelmaking and continuous casting scheduling, search for each other through high and low two layers of strategy in the effective threshold, optimal solution of update iteration. The simulation experiments show that the effectiveness of the algorithm can meet the needs of real-time and stability of production to the maximum extent.
Keywords: steelmaking and continuous casting rescheduling; strong disturbance; hyperheuristic genetic algorithm; heuristic rule.
Sustainable lean redesign of manufacturing enterprises
by GuoZhang Jiang, Le Yang, Feng Xiang, Gongfa Li
Abstract: Lean manufacturing has been widely used to develop manufacturing processes. Lack of lean and lean over have become common problems in the process of production. Searching for sustainable lean production has become a research hot topic. Through research on the factors influencing lean sustainability, a lean redesign method is proposed, by reconstructing the traditional lean indicators and the sustainability indicators from the three aspects of economy, society and environment to regenerate the lean redesign indicators, determining the sustainability evaluation methods in the production process, integrating them into the VSM (Value Stream Mapping), describing the manufacturing system to redesign VSM, and assessing the lean sustainability of the manufacturing system to improve productivity. Case studies show that the lean redesign method can determine the level of lean sustainability in each operation and describe manufacturing systems in more detail than traditional methods to help enterprises make reasonable decisions and establish their lean sustainability aims.
Keywords: lean manufacturing; sustainability; lean redesign; value stream mapping.
Improved location algorithm based on DV-Hop for the indoor Internet of Things
by Qian Cai
Abstract: Information perception is the basic function of the Internet of Things (IoT) and the basic means by which an IoT information system is capable of comprehensive perception. In this paper, the DV-Hop localization algorithm is improved by modifying the average jump distance and weighting factor to improve the information localization and perception accuracy of the IoT. The simulation results show that the algorithm meets the requirements of the information sense of the internet.
Keywords: Internet of Things; DV-Hop; information perception; weighting factor; average jump distance.
Enhanced chicken swarm optimisation for function optimisation problem
by Min Lin, Yiwen Zhong, Juan Lin, Xiaoyu Lin
Abstract: Chicken Swarm Optimization (CSO) algorithm is a novel swarm intelligence algorithm. Improper balance between the diversification and intensification may degrade its performance. In order to tackle this problem, this paper proposes an enhanced CSO (ECSO) algorithm which can get better balance between diversification and intensification for the swarm. Specifically, a novel adaptive neighbourhood strategy is used by the location update equation of roosters, so roosters can focus on exploration in early stage and on exploitation in late stage. In addition, learning from chicks is introduced into the location update equation of hens, so that hens can learn from chicks occasionally and increase the diversity of swarm. Experiments on 16 benchmark problems were conducted to compare the proposed ECSO algorithm with the original CSO algorithm and other classical swarm intelligent algorithms. The results show that ECSO algorithm can achieve good optimization results in terms of both optimization accuracy and robustness.
Keywords: chicken swarm optimisation; adaptive neighbourhood; learning from chicks; function optimisation; swarm intelligence.
A microstrip UWB antenna for next generation communication system
by Arun Kumar
Abstract: A novel microstrip truncated ultra-wideband (UWB) antenna with T-shaped band notching is implemented for insusceptibility at 5.2 GHz to 5.8 GHz and can be used in next generation wireless communication. Agreeing to the obligation to spread the bandwidth of antenna more, the T-shaped slot is cut on the spot with a height of 1.50 mm, and T-shaped notching is designed to achieve a manifold frequency band. In this work, a dielectric material of 2.2 and lossless tangent .4 is applied. The optimal results are obtained by selecting the parameters of an antenna. The return loss and gain of the proposed structure are -46.1 dB and 5.49 dB. The proposed antenna can be applied in cellular communication, x-ray, and W-LAN.
Keywords: UWB; band notching; truncated; microstrip; return loss.
Bat algorithm with ddimension-recommended mechanism
by Chen Meiwen, Yiwen Zhong, Lijin Wang
Abstract: Bat algorithm (BA) is a heuristic algorithm based on echolocation characteristic of bats and developed by the mimicking of bats foraging behaviour. In daily life, we always select something good by the friends recommendation. Inspired by this phenomenon, in this paper, we propose dimension-recommended mechanism (DRM) in neighbourhood search. The mechanism detects the dimension that has a high influence on the objective function and is recommended to the other bat. The new approach drives the algorithm towards the promising dimension of the search space in the progress of iteration. Extensive experiments, which are carried on 19 benchmark functions with different properties, demonstrate the improvement in effectiveness and efficiency of DRM.
Keywords: bat algorithm; dimension-recommended mechanism; neighbourhood search;.
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.
An investigation into e-commerce service chain model algorithm
by Guanglan Zhou, Weihua Su, Renan Liu, Jun Hu
Abstract: On the basis of the traditional fixed-fee contract, three specific contract forms models: single contract, menu contract and confused contract are discussed in service supply chain with effort-sensitive demand and asymmetric information. Under the service supply chain management, there is a class of demand with effort-sensitive members and asymmetric information. While the efforts of service supply chain members have an impact on market demand, the members can have more choices in pursuing profit maximisation in terms of price, volume and effort level. Under such circumstances, there is another route to realise service supply chain coordination, namely choosing the suitable effort level in the scope of service effort to realise the balance between pricing and effort level on the basis of negotiated price, volume and effort level. Solutions of the three contract models are optimised and analysed. The solutions effect and the meaning are pointed out for the service supply chain contract forms.
Keywords: supply chain; effort level; information asymmetry; contract effect; sensitive demand.
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
Abstract: A very compact coplanar waveguide (CPW) fed fractal monopole antenna with a modified ground plane is presented. The main objective is to obtain ultra wideband (UWB) characteristics from a simple microstrip monopole antenna. A wideband behavior 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 18×12×1.6 mm3. The measurements are carried out to validate the simulations and the performance of the proposed antenna is analysed.
Keywords: CPW, fractal antenna, self-similar, ultra wideband (UWB), wireless communication