International Journal of Wireless and Mobile Computing (53 papers in press)
Multicast stable path routing protocol for wireless ad-hoc networks
by K.S. Saravanan, N. Rajendran
Abstract: Wireless Ad-Hoc Networks (WANETs) enable steady communication between moving nodes through multi-hop wireless routing path. The problem identified is how to improve the lifetime of the route and reduce the need for route maintenance. This helps to save bandwidth and reduce the congestion control available in the network. This paper aims to focus on redesign and development of multicast stable path routing protocol with special features that determine long-living routes in these networks. An extensive ns-2 simulation based performance has been analysed of three widely recognised stability oriented wireless ad-hoc network routing protocols, namely are Associativity Based Routing (ABR) protocol, Flow Oriented Routing Protocol (FORP) and Lifetime Route Assessment Based Routing Protocol (LRABP). The order of ranking of the protocols in terms of packet delivery ratio, average hop count per route, end-to end delay per packet and the number of route transitions is presented.
Keywords: wireless ad-hoc networks; multicast routing protocol; wireless communication; routing protocol.
Study on carbon footprint model and its parameter optimisation of wave soldering process based on response surface method
by Renwang Li, Haixia Liu, Jiaqi Li, Jinyu Song, Rong Jie
Abstract: In order to respond to low carbon manufacturing, from energy, materials and process carbon emissions, etc., this paper constructs a carbon footprint model for the wave soldering process in the module workshop of H Company. Based on this model, the carbon footprint value of the wave soldering process is calculated. On the basis of selecting appropriate parameter factors, a parameter optimisation model of the wave soldering process life-cycle carbon footprint is constructed, and the optimum parameters combination is analysed by the response surface method, which contains surface area, clip velocity, clipping angle, flux flux, purity of solder, temperature of tin furnace, height of wave peak, etc. The the response values obtained are verified. The experimental results show that the optimised parameters are used to process and manufacture the wave soldering process, and the carbon emissions produced by wave wave welding can be controlled from above 15 kg CO2 to 12 kg CO2.
Keywords: wave soldering; carbon footprint; calculation model; response surface method; parameter optimisation.
A trusted behaviour measurement scheme based on feedback and control in a trusted network
by Junxi Zhuang, Xu Zhao, Bei Gong, Jing Zhan
Abstract: A terminal is connected to a trusted network through authentication and integrity measurement. In order to solve the real-time trusted measurement of user behaviour in a trusted network, a new combination of dynamic and static, subjective and objective behaviour trusted measurement scheme is presented. By the combination of state measurement, behaviour measurement and behaviour feedback control, the scheme can guarantee the credibility of user behaviour. The scheme analyses the credibility of the real-time user state and the direct trusted measurement value of the user behaviour, and finally controls the user behaviour by the feedback measurement of the user behaviour. The research results show that when the ratio of untrusted nodes is 15%, 30%, or 50% in the trusted network, the trusted detection rate can reach more than 92%, and the untrusted node in the trusted network can be identified with the increase of time. Compared with traditional measurement schemes, this scheme can be more accurate and reasonable to calculate the credibility of user behaviour, and can reflect the changes of the credibility of users' actual behaviour at all times, and ultimately implement the feedback control on user behaviour. The scheme can more effectively prevent the virus from invading than the traditional scheme. The research results provide technical support for the continuous trusted assessment of user behaviour in trusted networks.
Keywords: trusted network; trusted measurement; state measurement; behaviour feedback control.
Torque calculation model and structural optimisation of axial magnetic drive mechanism
by Qiao Xu, Xiaolong Cui, Zhen Chen, Shunqi Mei, Qiaoling Ji
Abstract: A torque calculation model based on the magnetic energy theory is established to give a more effective calculation method of torque for axial magnetic mechanism. The relationship between the torque and the relative rotation angle, the gap, and the magnetic flux leakage coefficient is analysed. On this basis the structural optimisation model is established and solved. Its purpose is to use the minimum volume magnet to meet the torque requirement. The analysis shows that the gap and the magnetic flux leakage coefficient should be as small as possible under meeting the structural conditions, and there is a certain relative rotation angle to make the torque reach a maximum value. The experiment is carried out and experiment results compared with the calculation results. The results show that when the structure is reasonable, the calculated values of the torque are consistent with the measured values, and the calculation model and structural optimisation model are very effective.
Keywords: torque calculation; structural optimisation; magnetic drive; magnetic energy theory.
Modified JAYA algorithm for solving the flexible job shop scheduling problem considering worker flexibility and energy consumption
by Hongchan Li, Haodong Zhu, Tianhua Jiang
Abstract: This paper investigates a flexible job shop scheduling problem with worker flexibility and energy consumption. A modified JAYA algorithm (MJAYA) is developed to minimise the total energy consumption. In the MJAYA, three improvement strategies are used to improve the algorithms performance, such as modified individual updating method (MIU), adaptive mutation operator (AMO) and local search strategy (LSS). The MIU is developed to improve the exploration ability by adding a random term to the original updating equation. The AMO is used to keep the population diversity. In addition, The LSS is employed to enhance the local search capacity. Finally, extensive simulations are performed to validate the effectiveness of the proposed MJAYA algorithm. Experimental data show that the MJAYA algorithm is effective for solving the considered problem.
Keywords: flexible job shop; production scheduling problem; worker flexibility; energy consumption; modified JAYA algorithm.
Intelligent garage system based on human and vehicle identification
by Xing Wang, Gongfa Li, Ying Liu, Juntong Yun
Abstract: At present, as the number of city cars has greatly increased, fewer garages, parking difficulties and other problems seriously affect people's travel. In this paper, an intelligent garage system is designed, which uses the matching information of face recognition and licence plate recognition to store and retrieve cars. Firstly, the car owner's face is collected through the camera and face image is extracted. Meanwhile, the licence plate information is collected and image preprocessing, licence plate positioning, character segmentation and character recognition are carried out. Face and licence plate information are stored correspondingly. Secondly, according to the tracking car combined with communication, automatic car storage is realised. Face recognition is used to match licence plate or input licence plate information when extracting vehicles. Finally, the design of the garage interface, with anytime feedback parking information, to achieve the software reservation, greatly improves the service efficiency.
Keywords: face recognition; licence plate recognition; intelligent garage; template matching; real-time feedback.
Road recognition and motion target tracking based on infrared image
by Qingqing Wang, Li-Guo Zheng, Jia-Nan Meng
Abstract: Road recognition is a very important link in the safe driving of vehicles. In this paper, a region-based road recognition method is proposed for infrared road images. Noise is eliminated by mean filtering and threshold segmentation. Then, the road boundary segments are obtained by the threshold exhaustive method, and the road boundary segments are obtained by the second-order differential operator. The road boundary segments obtained by the two methods are fused to obtain the candidate road boundary segments. Finally, the real road boundary is obtained by optimising the line fitting. For the identified road, the moving target tracking based on interacting multi-mode Kalman filter is adopted. The simulation results show that the interacting multimode Kalman filter can achieve better trajectory fitting, and the errors in X and Y directions before and after filtering are small. This shows the excellent performance of interacting multimode Kalman filter in moving target detection.
Keywords: infrared image; road recognition; target tracking; Kalman filter; chain code tracking.
Numerical simulation of the pool fire behaviours in the aircraft cabin
by Yimeng Hao, Guanbing Cheng, Shuming Li
Abstract: The cabin pool fire is a complicated phenomenon and the cabin misfire may lead to a seriously hazardous accident. Thus, it is significant to study the pool fire behaviour in the cabin for aircraft safety. In this paper, one typical civil transport airplane is considered. The aircraft has a single aisle cabin. Using the fire dynamic simulator, the calculated and physical models of the cabin were constructed accordingly. Four slices along the vertical direction and seven detectors along the cabin aisle at several centimetres above the floor were placed in order to trace the dynamic changes in the significant parameters. The evolution of the parameters such as temperature, flow velocity and species concentrations (e.g. CO, soot, and oxygen together with CO2) were analysed via the parameters sequence diagrams and nephograms. The results show that the changes in those fire characteristic parameters include the transient and steady stages. At the transient stage, the temperature, flow velocity and species concentrations increase within several seconds. But the oxygen concentration decreases in this stage owing to oxygen consumption in the combustion process. In the steady stage, those parameters oscillate around one constant. In the first stage, all the fire characteristic parameters change more importantly in the zones far away from the fuselage doors. Although the seats produce turbulence to some extent, the air entrance from the doors predominantly reduces the combustion temperature and rates and also prolongs the transient period.
Keywords: aircraft cabin; fire behaviour; temperature; velocity; species’ concentration.
Research on public opinion reversal phenomenon of network mass events modelling and simulation
by Liqun Cheng, Yanan Liu
Abstract: At the present, network mass incidents occur frequently, the network public opinion of the non-directional reversal caused great concern. Based on the JA model, this paper focuses on the evolution process of the dynamic attitude reversal of the network group, taking the important information of the outside world as a variable, exploring the influence of the important information release on the whole public opinion, and using the multi-agent Monte Carlo method for experimental simulation. This paper takes the Guizhou bus crash incident as an example to make an empirical analysis.
Keywords: group polarisation; reversal of public opinion; mass events; information interaction.
Research on power regulation service data transmission path optimisation method
by Lei Yan, Zhangshang Yan, Zhifang He, Xiuli Zhang, Xincong Shi, Ting Wang, Zijuan Zhao
Abstract: Owing to the large amount of data transmission and the large number of transmission paths between equipment and applications in the power grid control centre, it is easy to cause problems such as packet loss and incomplete data transmission. An improved Apriori algorithm is proposed to mine multi-dimensional data association rules when multiple service devices are running in parallel, and then optimise the discontinuous data path transmission based on the ant colony algorithm. The ant colony migration probability is used to calculate the pheromone concentration value of the ant on the discontinuous data path in a fixed period, plan the ant travel path, use the direction factor to adjust the discontinuous data transmission path appropriately, determine the optimal path, and realise mining optimisation. Simulation results show that the proposed method can effectively improve the convergence speed of discontinuous data transmission, reduce the delay time of the data transmission network, and ensure the integrity of data transmission.
Keywords: power dispatch data centre; cloud computing; Apriori algorithm; association rules; route optimisation.
Hardware design methodology of multilayer feedforward neural network for spectrum sensing in cognitive radio
by Swagata Roy Chatterjee, Jayanta Chowdhury, Supriya Dhabal, Mohuya Chakraborty
Abstract: This paper aims to design a simple hardware architecture for a Multilayer Feedforward Neural Network (MFNN) and verify its performance in the detection of vacant/busy states of channels. A single neuron with tansigmoid activation function is proposed using the rule of matrix multiplication for simplification in computation. The proposed hardware module of a single neuron, using parallel processing, is assembled to obtain the architecture of desired MFNN. The area-optimised hardware architecture of MFNN is achieved by reusing the hardware resources. The hardware module of a single neuron is compared with the allied design methods, which exhibits its improved performance in terms of mean square error and accuracy over the existing ones. The proposed optimised MFNN provides almost 62% reduction in hardware resources as compared with standard non-optimised MFNN. Further, the performance analyses of the proposed hardware architecture demonstrate almost 90% accuracy in the detection of both vacant and busy states of channels.
Keywords: cognitive radio; hardware architecture; multilayer feedforward neural network; vacant band detection; spectrum sensing.
A new-one-time-pad stream cipher: new design and hardware implementation and its application in security of UAVs
by Mohamed Nabil, Ashraf Khalaf, Sara Hassan
Abstract: Unmanned Aerial Vehicles (UAVs) and drones have become widely used in both military and civilian fields. The security level of the communication system of UAVs' data link is still unsatisfactory especially when a strong adversary model is considered. The aim of this paper is to propose a new design of Authenticated Encryption New-One-Time-Pad algorithm (AENOTP). This new algorithm will be tested for the communication of the security task in UAVs' data link. Furthermore, the AENOTP will be implemented using Arduino Duemilanove microcontroller boards, the used transceivers are X-Bee modules 1 mW. The proposed AENOTP algorithm combines the New-One-Time-Pad (NOTP) algorithm with the Authenticated Encryption (AE) technique to ensure encryption and authentication along with data integrity. AE is a very important technique that ensures the security of the transported data. The design, analysis, and simulation of the proposed AENOTP algorithm is promising to give a fast and enhanced stream cipher authenticated encryption architecture, which is based on the unpredictability concept.
Hardware implementation validates the efficiency of the proposed AENOTP through measuring the quality of the encryption and the decryption of any sent and received data. The AENOTP shows high speed of generating the key stream bits of the OTP stream cipher and high speed of the proposed encryption algorithm of 75 Mbits/sec. It can achieve high level of security for any transmitted data. It can easily resist different attacks, such as linear, differential and algebraic cryptanalysis; it also resists other cryptanalysis attacks.
Keywords: security of UAVs; authenticated encryption; OTP algorithm; unpredictability.
The effect of entrepreneurial social capital on dynamic capability: the moderating role of the entrepreneurial spirit
by Junjie Wu, Su Chen, Xin Geng
Abstract: Existing studies have shown that entrepreneurs social capital is one of the key factors for success of enterprise innovation. The resources mobilised by entrepreneurs through their formal and informal relational network provide guarantee for enterprise innovation. However, the negative effects that entrepreneurs social capital may bring cannot be ignored. Therefore, the impact of entrepreneurs' social capital is complex, and the fact that the existing theoretical research conclusions are not uniform shows that the theory of entrepreneurs social capital is still not mature enough and needs to be re-examined and clarified through empirical research. Based on the empirical study of 173 private enterprises, this paper explores the moderating effect of entrepreneurship on the relationship between entrepreneurs' social capital and dynamic ability. It is found that the structural dimension of positive regulation of entrepreneurship has no moderating effect on the dynamic capabilities of technology and the market. At the same time, entrepreneurship plays a positive moderating role in the relationship dimension, in the cognitive dimension of entrepreneurs' social capital, in the technological dynamic capabilities and in the market dynamic capabilities of enterprise. This paper shows that effective resource mobilization of entrepreneurs' social capital acts as the key for enterprises to maintain sustainable development of organisational dynamic capacity.
Keywords: entrepreneurship; social capital; dynamic ability.
Research on the current situation and norms of public welfare crowdfunding
by Bo Peng
Abstract: Public welfare crowdfunding is a new type of internet+ public welfare crowdfunding. It has the characteristics of wide audience, low cost, and high influence, which is conducive to solving the difficulties of the public and exerting the spirit of mutual help. In this paper, the basic process of public welfare crowdfunding in China is analysed, and the status and trends of public welfare crowdfunding development are studied. At same time, specific aspects are proposed from multiple dimensions, such as the public welfare crowdfunding sponsor, crowdfunding platform, third-party regulatory agencies, and government recommendations for healthy development of public welfare crowdfunding, in order to make public welfare crowdfunding a healthy development.
Keywords: public welfare; situation; standard; independent third party supervision; improvement the laws and regulations; measure.
Modelling and simulation of a thermo-fluid system with one-dimensional distributed parameters on Modelica
by Yiming Yuan, Zefei Zhu, Guojin Chen, Chang Chen
Abstract: Thermo-fluid systems are applied to industrial production and daily life widely and influence human activities deeply. This paper describes a modelling and simulation method for a thermo-fluid system with one-dimensional parameters on Modelica, aiming at providing a framework and modelling process of a one-dimensional thermo-fluid system model. The method of lines is introduced to convert the partial differential equation, which is used to describe the one-dimensional thermo-fluid system, into a group of differential-algebraic equations. Based on the Newton-Gregory polynomial, the discretisation method and step is presented and the difference expression is deduced for the first and second order spatial derivative terms in PDE. Two illustrative examples, wave equation and human body heat loss model, are presented to confirm the veracity and accuracy of the proposed method.
Keywords: thermo-fluid system; one-dimensional distributed parameter; partial differential equation; differential algebra equation; Modelica.
Coexistence between 5G wireless sensor communication systems and Wi-Fi IEEE802.11n networks
by Ehab M. Shaheen
Abstract: This paper investigates the coexistence between the fifth generation (5G) wireless sensor communication systems and Wi-Fi communication networks. The 5G wireless sensor communication system is considered as the victim system and is modelled as the polyphase network (PPN) filter bank multicarrier (FBMC) offset quadrature amplitude modulation (OQAM) communication system. The Wi-Fi communication network is considered as the interference signal. It is modelled as the orthogonal frequency division multiplexing (OFDM) based 2x2 multi-input multi-output (MIMO) IEEE802.11n communication signal. A closed form analytical formula to the bit error rate performance of 5G PPN FBMC OQAM communication system in presence of IEEE802.11n interference signal in additive white Gaussian noise channel is evaluated. The obtained analytical results are validated by the aid of extensive simulation results. The simulation results are experimentally done using the software defined radio (SDR) Keysight SystemVue software. It will be shown that the impact of the Wi-Fi interference signal is severe on the performance of the 5G PPN FBMC communication system.
Keywords: 5G; Wi-Fi IEEE802.11n wireless networks; interference; PPN FBMC OQAM; SDR SystemVue software.
Analysis and optimisation of server load balancing based multi-factor integrated algorithm
by Xiang Li, Anan Jin, Li Wei
Abstract: In distributed server application service deployment, load balancing is an important factor that affects service performance. However, the biggest factor affecting load balancing is the performance of the server and the performance ratio of the requested service execution. This paper uses the application of service-oriented architecture system as the embedding point, which based on the analysis and comparison with traditional load balancing algorithms, such as random load balancing algorithm, round-robin algorithm, and consistent hash algorithm. This paper is aimed to design a new load factor-based algorithm to solve some defects of traditional load balancing algorithm by improving minimum concurrency number and integrating various factors that affect server performance. This paper proposes an optimisation algorithm that can more fully reflect server load capacity. The experiment results show that the load balancing effect of this algorithm has a better effect than the traditional load balancing algorithm.
Keywords: load balancing; SOA structure; load factor; minimum concurrent number.
Semi-supervised learning of pose-specific detector for human lying-pose detection
by Xia Daoxun, Liu Haojie, Li Weian
Abstract: Under the superlow-altitude aerial image, human lying-pose detection is an important problem in object detection. This paper is mainly focused on the application study of an unmanned aerial vehicle (UAV) life detector after a disaster, and we study the problem of learning an effective pose-specific detector using weakly annotated images and a deep neural network. This typical approach 1) clusters a series of human poses for the human lying-pose and assigns an image-level label to all human lying-poses in each image and breaks them down into several categories; 2) trains multiple classifiers for each category using a deep neural network; and 3) uses the boosted semi-supervised CNN forest classifier to select a human lying-pose with high confidence scores as the positive instances for another round of training. Experiments on the XiaMen University Lying-Pose Dataset (XMULP) show that significant performance improvement can be achieved with our proposed method.
Keywords: human lying-pose detection; pose-specific detector; semi-supervised learning; object detection.
Survey on throughput enhancement techniques for real time wireless link deployment
by Thiyagarajan Krishnan, T. Vetrivel Chelian
Abstract: Over the recent decades, the emergence of advanced wireless technologies has attracted many researchers and industries to explore the field of next generation wireless links towards capacity optimisation with minimal energy requirements. This gave beginning to a new dimension of research in the field of green yet high capacity links, which can connect our physical world to the digital reality with support from environment friendly networks. The phenomenal growth in wireless applications and technology development also demands a step-up in link capacity. This paper focuses on reviewing recent concepts and methodologies to improve link capacity for the next generation wireless systems. The main aim of this paper is to provide a conceptual understanding about the impact of modulation techniques and error control codes towards capacity improvement.
Keywords: hierarchical modulation; OFDM; FBMC; LDPC; polar codes; turbo codes; spatial modulation.
QANet-based candidate answer rethink model for machine reading Comprehension
by Yong Wang, Chong Lei
Abstract: The current model applied to the span extraction reading comprehension task fuses the information of context and question, and outputs the index with the highest probability calculated in the context as the prediction span. In this process, the model discards all the remaining candidate answers, which results in a waste of the available information in the candidate answers. Our model is designed to simulate the behavior of human beings choosing multiple candidate answers and comprehensively judging the final answer in reading comprehension tasks. We propose the QANet-based candidate answer rethink model. The model interacts with and fuses multiple candidate answers with context and question, prompting the model to obtain a more accurate answer by synthesising these three aspects of information. Experiments show that our model has made new progress in performance.
Keywords: machine reading comprehension; candidate answer rethink; information interaction.
Research on the DouDiZhu's playing strategy based on XGBoost
by Hengyang Cao, Shuqin Li
Abstract: In recent years, imperfect information games have received extensive attention in computer game research. As a three-person imperfect information game in China, DouDiZhu not only has competitive relationship but also has cooperative relationship between the players, which makes the model more complicated, hence it has high research value. In this paper, the DouDiZhu's playing strategy is converted into 182 legal playing multi-classification problems, by extracting the characteristics of winning data of different players, using the XGBoost model and setting reasonable model parameters. In addition, the strategy of playing cards is made more reasonable through phased training, character training, and rule correction methods. In this paper, a new data representation method of DouDiZhu game is proposed. The XGBoost model is innovatively used to solve the poker game problem. By adjusting the parameters and multi-model training, a better card playing strategy is obtained. The experiment results show that the playing strategy predicted by the playing strategy model proposed in this paper is basically consistent with the human playing strategy, and has a good playing strategies for different situations. The method in this paper has achieved a third-place excellent result in the Chinese University Student Computer Game Contest 2019.
Keywords: DouDiZhu; computer game; imperfect information game; XGBoost.
A modified quantum-inspired evolutionary algorithm for minimising network coding operations
by Zhijian Qu
Abstract: Network coding operations will benefit the multicast network performances in improving both the transmission throughput and the reliability. Meanwhile, the network coding operations can also bring some additional resource consumption and transmission delay into the multicast network. Thus, minimising the network coding operations is worthy of in-depth studying. To address this resource optimization problem, an adaptive evolution mechanism based modified quantum-inspired evolutionary algorithm was presented in the paper. There are three evaluation operators were defined and added into the algorithm to improve the global optimization ability. In the modified quantum-inspired evolutionary algorithm, the state of each population was jointly determined by these three operators. In the algorithm evolution process, the evolution parameters of the algorithm can be determined by the state of each population. To illustrate the effectiveness of the modified algorithm, it was applied to resolve the function optimisation and the network coding recourse minimization problems respectively. The experiment results indicated that our adaptive evolution mechanism based modified quantum-inspired evolutionary algorithm have better performances both in searching global optimal solution and convergence speed.
Keywords: multicast network; resource optimisation; network coding; evolutionary algorithm.
Mobile lung cancer early warning based on Windows Azure cloud computing
by Jun Lv, Pan Wang, Zijuan Zhao
Abstract: In view of the repeated investment in the current medical lung cancer early warning system, "information island" and the low rate of lung cancer early warning, this paper proposes a mobile lung cancer early warning system based on Windows Azure cloud computing with the application requirements of medical information system. The system is applied to the smart phones of windows system, and the windows azure Microsoft cloud platform is accessed through wireless network, using SQL azure to store medical data (such as lung CT image, ECG curve and high-resolution colour ultrasound image), embed the medical lung cancer early warning model based on deep learning in the cloud computing platform to process and analyze the patient's medical data, and realize the real-time synchronous update of doctors, patients and cloud platform data. The accuracy of lung cancer early-warning system on lidc-idri is high, and the detection results are uploaded to doctors and patients' smart phones in real time. The results show that the mobile lung cancer early warning system based on Windows azure cloud computing not only effectively integrates medical resources, but also provides patients with medical services and consultation at home, which integrates the advantages of all aspects and adapts to the development of the times.
Keywords: pulmonary nodule detection; cloud computing; mobile medicine; CT image of lung.
Image feature point matching method based on improved BRISK
by Qian Shi, Yong Liu, Yichun Xu
Abstract: In order to improve the accuracy of the BRISK algorithm of feature point matching, an improved BRISK feature point matching method is proposed by combining the SIFT algorithm idea with high matching accuracy. Firstly, the Gaussian image pyramid is established, then the FAST algorithm is used to detect the feature points of each image layer in the image pyramid, and the intensity centroid method is used to determine the direction of the feature points, so the feature points obtained have scale information and direction information. Then using the BRISK descriptor to describe the feature points, using the Hamming distance to measure the similarity of the feature descriptors, and calculating the matching accuracy and matching time. The experimental results show that the accuracy of the method proposed in this paper is higher than that of the BRISK algorithm and the time is better than that of the SIFT algorithm and the BRISK algorithm.
Keywords: image matching; feature point matching; intensity centroid; improved BRISK; image pyramid.
Research on pipe crack detection based on image processing algorithm
by Licheng Huang, Bo Tao, Donghai Chen, Xun Zhang, Gongfa Li
Abstract: The detection of pipe cracks based on machine vision is a new and effective technology. However, it requires high quality of the image. Moreover, images with adequately lighting, evident cracks, and clean backgrounds are difficult to obtain in practice. This paper proposes an algorithm for pipe crack detection in natural background. The algorithm performs filtering, background segmentation, edge detection, threshold segmentation, morphological contour extraction, and annotation on the image. This paper also proposes an adaptive threshold segmentation method to obtain the clear crack. By comparing the proposed algorithm with the DEE algorithm, the result shows that the proposed algorithm has certain advantages in experiments. The experiment results show that the algorithm proposed can also be used in the detection of significant pipe cracks.
Keywords: pipe cracks; noise reduce; Sobel operator; edge detection; image processing.
An optimal condition of robust low-rank matrices recovery
by Jianwen Huang, Sanfu Wang, Jianjun Wang, Feng Zhang, Hailin Wang, Jinping Jia
Abstract: In this paper we investigate the reconstruction conditions of nuclear norm minimisation for low-rank matrix recovery. We obtain a sufficient condition to guarantee the robust reconstruction or exact reconstruction of all rank matrices via nuclear norm minimisation. Furthermore, we not only show that when $t=1$, the upper bound is the same as the result of Cai and Zhang, but also demonstrate that the gained upper bounds concerning the recovery error are better. Moreover, we prove that the restricted isometry property condition is sharp. Besides, the numerical experiments are conducted to reveal the nuclear norm minimisation method is stable and robust for the recovery of low-rank matrix.
Keywords: low-rank matrix recovery; nuclear norm minimisation; restricted isometry property condition; compressed sensing; convex optimisation.
Analysis of influence factors on employment and entrepreneurship of ex-college soldiers
by Keqing Ni
Abstract: With the increasing number of ex-college soldiers, how to transform these high-quality human resources into social capital has become a hot topic of concern for government and academia. Based on social cognition theory, self-efficacy theory and ternary interaction theory, as well as combining with data mining technique, this paper studies the influence factors of employment and entrepreneurship of ex-college soldiers. Detailed analysis indicates that entrepreneurial self-efficacy has a significant positive effect on entrepreneurial behaviour, and external environmental factors such as external support and entrepreneurial education have a significant positive effect on entrepreneurial cognition. In addition, entrepreneurial cognition has a significant positive effect on entrepreneurial behaviour. In conclusion, there are significant differences of entrepreneurial experience, business experience and family income on entrepreneurial behaviour. This study complements the theoretical research on entrepreneurship of ex-college soldiers.
Keywords: entrepreneurial cognition; self-efficacy; entrepreneurial behaviour; structural equation; K-means clustering.
Multi-model fusion framework based on multi-input cross-language emotional speech recognition
by Guohua Hu, Qingshan Zhao
Abstract: Aiming at the limitations of the present time domain and frequency domain attribute characteristics and the emotion classification network in cross-language emotional speech recognition, a multi-model fusion framework based on multi-input cross-language emotional speech recognition is proposed. Firstly, happiness, sadness, neutrality and anger, which are common to the four corpus of Chinese, English, Urdu and German, were selected as experimental samples. Secondly, the acoustic features, MFCC spectrogram features and language spectrogram features of multilingual emotional speech signals were used as the inputs of the multi-model fusion framework, and then SVM, MobileNet26 and ResNet38 constituted the basic framework of multi-input corresponding multi-model fusion, the feature map after the convolution operation of MobileNet26 and ResNet38 models was global max pooling and global average pooling, so as to capture different features and double the diversity of the models, and finally forming a framework for fusion of five models. Finally, an experimental scheme was designed to verify the effectiveness of the multi-model fusion framework based on multi-input in cross-language emotional speech recognition. The experimental results show that, compared with the traditional acoustic features and the network model with a single feature, the multi-model fusion framework based on multi-input can not only effectively distinguish the emotion differences of multiple languages, but also realise the transfer learning of emotional speech recognition of small languages through the learning of large languages.
Keywords: multi-input; cross-language; emotional speech recognition; multi-model fusion; transfer learning.
A DV-Hop dynamic weight positioning model with genetic algorithm
by Penghong Wang, Tian Fan, Xingjuan Cai, Wuchao Li
Abstract: Wireless sensor networks (WSNs), as an important part of the Internet of Things (IoT), are widely deployed to the location estimation in WSNs. However, at present, the study of DV-Hop algorithm is still limited to the improvement of the sensor nodes in the ordinary region. In this paper, aiming at the complex areas under different application backgrounds, based on the analysis of the localisation principle of the traditional DV-Hop model based on optimisation algorithm, a dynamic weight positioning model based on genetic algorithm (DWMGA-DV-Hop) is proposed. The algorithm performs simulation experiments on three different types of test set by adopting dynamic weight calculation model. Experiment results demonstrate that, under different test sets, compared with the standard DV-Hop algorithm, TW-PSODV-Hop and OCS-DV-Hop algorithm, this algorithm has the highest positioning accuracy and stability.
Keywords: DV-Hop; genetic algorithm; dynamic weight positioning model; internet of things.
Application of many-objective particle swarm algorithm based on fitness allocation in WSN coverage optimisation
by Weiwei Yu, Chengwang Xie
Abstract: In order to improve the situation that the wireless sensor network (WSN) nodes in the random deployment is not uniform, the network coverage performance is improved. The traditional particle swarm optimisation has slow convergence speed and is easy to fall into local extremum. The many-objective Particle Swarm Algorithm based on Fitness Allocation (FAMPSO) is proposed by combining fuzzy information theory and new mutation methods. The algorithm combines the fuzzy information theory to associate the ideal solution with the Pareto solution and proposes a new fitness allocation method, which increases the pressure of population selection and enhances the convergence of the algorithm. The FAMPSO algorithm is compared with three other representative multi-objective evolution algorithms on the DTLZ series test function set. At the same time, the FAMPSO algorithm is applied to the coverage optimisation of WSN, and the simulation analysis is carried out. The simulation results show that the FAMPSO algorithm has a significant performance advantage in terms of convergence, diversity, and robustness. FAMPSO algorithm improves the coverage performance of WSN.
Keywords: wireless sensor network; network coverage;particle swarm optimisation; many-objective optimisation; fitness allocation;.
Finite impulse response low-pass digital filter based on particle swarm optimisation for image denoising
by Peng Shao, Le Yang, Xing Li
Abstract: Noise has very important influence on image quality. Finite Impulse Response (FIR) digital filter is an effective technique for removing image noise. But the effectiveness of FIR digital filter designed by traditional methods in image denoising needs to be improved further because of their demerits such as lower accuracy. Therefore, in order to suppress noise and improve image quality, the FIR low-pass digital filter designed by the improved particle swarm optimisation algorithm based on refraction principle (refrPSO) is employed to remove image noise. In the method, firstly, the coefficients of FIR low-pass digital filter are mapped to the candidate solution of refrPSO, and then the refrPSO is invoked to optimise it. Finally, the designed FIR low-pass digital filter is used to make images denoise. In the next experiments, two images with different sizes are tested and experimental results and analysis show that the FIR digital filter designed by the refrPSO has better effect on image denoising compared with FIR digital filters by traditional methods such as the window function method, the best equivalent ripple approximation method, and the particle swarm optimisation algorithm.
Keywords: particle swarm optimisation; refraction principle; FIR low-pass digital filter; image denoising.
Research on lightweight detection model of fake domain name
by Tao Ye, Jianbiao Zhang, Fengbiao Zan
Abstract: In recent years, phishing websites and other fake domain name attacks have become more frequent, posing a serious threat to the security of society and individuals. Fake domain name detection has thus become an important part of network protection. At present, fake domain name detection is mainly for public domain names, and detection methods are mainly based on edit distance. It is difficult to express the visual characteristics of domain names fully. Based on that, this paper studies the lightweight detection strategy of domain name string for the educational fake domain names and improves the detection efficiency by comprehensively considering the effect of character position, character similarity and operation type on the vision of domain name. Experimental results show that our method has a higher precision rate and recall rate on the position of the character, the character similarity, the type of operation than the traditional edit distance algorithms.
Keywords: educational domain name; fake domain name; edit distance; visual similarity.
Experimental study on modal characteristics of flame tube in a can-type combustor in an aero-engine
by Guanbing Cheng, Yinsheng Chai
Abstract: The flame tube is a key component in the combustor of gas turbines. The fuel air mixtures burn efficiently in the tube and control the temperature distribution in both the radial and circumferential directions by adjusting the air entrance from the various geometrical holes in the liner. Thus, understanding the dynamic characteristics of the flame tube structure is one of the key problems in understanding performance of the combustor and turbine. The present paper, from both FEM and experimental aspects, studied the vibrating modal characteristics of a flame tube in a can-type combustor. First, the tube FEM model was constructed by Solidworks and analysed in ANSYS Workbench. Then, its first six orders modal parameters, such as frequency and mode, were obtained. Afterwards, the modal experiments were effectuated by the classical hammering method and the resonant frequencies and modes of the tube were identified. Finally, we compared the calculated frequencies in FEM with the experimental ones. The results show that in the calculated modal of the flame tube, the flame tube vibrates along the x and y directions. The periodic tangential vibration with several circumferential waves and few horizontal half waves was observed. The tube's lower order resonant frequencies varied from 145 Hz to 600 Hz, and its higher order frequencies are on the order of 1000 Hz. In the tubes experimental modal, the first order frequency is about 100 Hz, its second and third order vibrating frequencies are about 400 Hz. The last three orders frequencies vary around 1000 Hz. The damping ratio is higher in the first order case than in the other orders. In the FEM and experimental methods, the relative maximum amplitude of the flame tube still occurs at its rear part. Finally, the first three orders frequencies of the tube in the experiment are lower by about 30% than those by the FEM method. This difference probably results from the constraint condition of the swirl section. The calculated last three orders frequencies are consistent with the experimental ones.
Keywords: flame tube; can-type combustor; vibration mode; resonant frequency; FEM; experimental modal analysis method.
New transformation method in continuous particle swarm optimisation for feature selection
by Kangshun Li, Dunmin Chen, Zhaolian Zeng, Guang Chen, James Tin-Yau Kwok
Abstract: Feature selection is a very important task in many real-world problems. Because of its powerful search ability, particle swarm optimisation (PSO) is widely applied to feature selection. However, PSO was originally designed for continuous problems, and therefore, the transformation between continuous particles and binary solutions is needed. This paper proposes a new transformation methods-based PSO (PSOS) in which the related feature subset of a particle is decided by a sine function rather than comparing with a single threshold. To further upgrade the performance of the proposed method, an extra increment generated by the Gaussian distribution is added to the marginal positions (PSOSI). The experimental results show that PSOS and PSOSI can select smaller feature subsets with higher classification accuracy than all the other algorithms compared in this paper. Furthermore, in most cases, the performance of the second method is better than the first one.
Keywords: particle swarm optimisation; feature selection; classification; sine function; Gaussian distribution; transformation method.
Research of small fabric defects detection method based on deep learning network
by Siqing You, Kexin Fu, Peiran Peng, Ying Wang
Abstract: For quality improvement of textile products, fabric defects detection is significant. In this paper, the detection capacity of SSD for small defects was studied. The loss of feature information was reduced through the reduction of layers of SSD network; then the size of the default box was adjusted based on the K-means clustering algorithm, and the adaptive histogram equalisation algorithm was applied to enhance the defect features and effectively improve the detection accuracy. The improved SSD network model was tested to verify the fabric defects dataset, which further improved the accuracy of detection. In addition, the two-stage algorithm was compared to find the optimal algorithm for small object detection. According to the test results, the subsequent improvement method for small object detection with SSD was proposed.
Keywords: fabric defects detection; default box; feature enhancement; SSD; faster RCNN.
Field theory trusted measurement model for IoT transactions
by Meng Xu, Bei Gong, Wei Wang
Abstract: The Internet of Things (IoT) allows the concept of connecting billions of tiny devices to retrieve and share information regarding numerous applications, such as healthcare, environment, and industries. Trusted measurement technology is crucial for the security of the sensing layer of the IoT, especially the trusted measurement technology oriented to transaction IoT nodes. In the traditional trust management system, historical behaviour data are considered to predict the trust value of the network entity, while the nodes' trust between network entities is rarely considered. This paper proposes a novel field theory trusted measurement model of the sensing layer network, which can well adapt to the transaction scenarios of the IoT.
Keywords: field theory; internet of things; trust measurement; transaction scenario.
Experimental and numerical study for dynamic characteristics of truck fuel tank based on fluid-structure interaction
by Xianfu Cheng, Junjie Liu, Rongqing Bao, Jing Li
Abstract: It was found that the fuel tank containing 50% fuel was prone to damage in truck road test. Thence, numerical simulation and experiment are combined to investigate the vibration features of the fuel tank with different liquid-filling ratios. The Fluid-Structure Interaction (FSI) vibration of the fuel tank concerns service life and dynamic characteristics. The FSI model is used for modal analysis of natural frequencies and mode shapes of the fuel tank, where corresponding vibration response behaviours are obtained. Modal analysis indicates that the modal frequency of the fuel tank with 50% fuel fluctuated significantly, subsequently random vibration analysis aims at the fuel tank with 50% fuel. The horizontal direction is determined as the harsh direction by extracting the welded joints stress of horizontal, longitudinal and vertical directions. Hereafter conducting the random vibration simulation and experiment with the RMS of 2g, 4g and 6g respectively, it is turned out that the calculation error is within 5% compared with the experimental data, which verifies the correctness of the proposed numerical simulation.
Keywords: fluid-structure interaction; modal frequency; random vibration; dynamic characteristics; fuel tank.
Research on point cloud generation algorithm of virtual depth camera
by Ke Li, Shilin Wu, Qinxia Huang, Zhen Zheng
Abstract: In this paper, based on the example of insulator taken by Realsence camera, a virtual camera is designed using OpenGL to take a picture of the STL model of the insulator, and the surface information of the model is extracted to obtain the three-dimensional point cloud data of the insulator. The experimental results show that the virtual depth camera can replace the solid camera to collect point cloud data from the STL model of the object.
Keywords: virtual depth camera; insulator; STL model.
3D object detection based on synthetic RGB image
by Chao Xu, Zeshen Li, Du Jiang, Juntong Yun, Ying Liu, Yibo Liu, Dongxu Bai, Ying Sun
Abstract: With the rapid development of computer vision technology and the maturity of 2D object detection technology, 3D object detection has attracted more and more attention of scholars. As an extension of 2D object detection, 3D object detection can not only detect the object category and position in the image, but also output the spatial position and pose angle of the object in a certain three-dimensional coordinate system. It has a considerable application prospect in automatic driving, robot operation and augmented reality. However, 3D object detection is much more difficult than 2D object detection, and it is very difficult to make and label the dataset, which requires high hardware requirements. At present, there is no dominant algorithm, and scholars use a variety of methods. In order to solve the above problems, this paper proposes a method of making and synthesising a 3D object detection dataset. Based on the improved 2D object detection algorithm, 3D object detection of a single RGB image is realised.
Keywords: 3D object detection; RGB image; synthetic dataset.
Effects of fuel pool on temperature profiles of fire in one engine nacelle
by Yicun Chen, Guanbing Cheng, Shuming LI
Abstract: The pool geometries, configuration and position have significant influence on the pool fire behaviour in an enclosed compartment. An attempt is made in the present paper to investigate the effects of a fuel pool on the fire temperature in an engine nacelle. We established the nacelle physical model based on classical turbofan engine CFM56 by AutoCAD, then introduced the Pyrosim to construct its numerical model. Three pool areas, A0404, A0303 and A0202, three pool shapes, S0404, S0208 and S0802, and three pool positions, front, middle and rear locations, were considered. The slice and four detectors were installed in the middle plane vertical to the nacelle longitudinal direction in order to obtain the temperature evolution and cloud charts at the left-right sides and top-bottom of the nacelle. The results indicate that for the pools with different areas, shapes and positions the temperature evolution divides into both an increasing stage within a few seconds and a steady stage, with an oscillation around an average temperature. For the pools with different areas, the increase of the pool areas contributes to the temperature augmentation at the left-right sides or the top and bottom of the nacelle. This change reveals that more fuel participates in the chemical reaction. More combustion heat boosts the fluid temperature in the nacelle by convection and radiation. For the pools with different shapes, the temperature at the left and top sides of the nacelle is higher for the pools farther away from the fire source. But it is always slightly higher at the right and bottom of the nacelle for the pools closer to the inner cylinder. For the pools with different positions, the temperature at the nacelle left and top sides is higher for the front and middle pools. However, it is always higher at the right and bottom of the nacelle for the front and rear pools.
Keywords: engine nacelle; pool area; pool shape; pool position; fire temperature; FDS.
Rating of catering enterprises based on fuzzy hierarchy and K-means clustering
by Xiaoyang Zheng, Yafeng Chen, Chengting Lin, Wei Zhang, Xinyi Zhou
Abstract: This paper firstly collects the credit
Keywords: catering enterprises; fuzzy analytic hierarchy process; K-means; rating.
Comparative analysis of fuzzy logic and AHP method for QoS management in LTE network: IMS case study
by Ouafae Kasmi, Nawal Ait Aali, Amine Baina, Mostafa Bellafkih, Loubna Echabbi
Abstract: In recent years, increasing demand for IP Multimedia Subsystem (IMS) services raised several problems and challenges concerning the Quality of Service (QoS) management. Thus, each operator has to make its network more efficient for ensuring an acceptable level of QoS. The 3rd Generation Partnership Project (3GPP) offers several scenarios for providing services, but without any control or correction for QoS degradation. However, reaching the QoS satisfaction becomes more difficult and complicated due to changes in preferences and mobility of customers. In this regard, a new approach of multi-level criticality for managing the customer's request for guaranteeing a QoS at any time is proposed. To achieve this goal, several criteria were used for decision-making to offer the appropriate QoS level to the customers according to their levels of criticality. In this paper, a comparative analysis of the fuzzy logic and Analytic Hierarchy Process (AHP) method for multi-criteria has been presented to evaluate QoS and criticality levels for QoS management in the IMS network. The simulation results describe the comparison between these two methods to illustrate their feasibility for QoS management to find who gives better results in the aspect of the chance value of QoS and criticality levels.
Keywords: multi-level criticality; QoS; quality of service; multi-criteria; fuzzy logic; AHP.
A novel multiuser detection based on honey bees mating optimisation and tabu search algorithm for SDMA-OFDM systems
by Imane Chiali, Fatima Debbat, Fethi Tarik Bendimerad
Abstract: In the wireless communication systems, the classic Multi-User Detection (MUD) techniques such as the Minimum Mean Square Error (MMSE) detector have some limitations and imperfections due to Multi-Access Interference (MAI) especially in overloaded scenarios when the number of users is more than the number of receiving antennas. The optimal Maximum Likelihood (ML) detector gives an excellent result to estimate the transmitted data but suffers from a computational complexity that grows exponentially with the number of users. In this paper, we propose a new metaheuristic approach for multiuser detection based on Honey Bees Mating Optimisation (HBMO) hybridised with Tabu Search (TS) for an uplink Space Division Multiple Access-Orthogonal Frequency Division Multiplexing (SDMA-OFDM) system in a flat Rayleigh fading channel. Indeed, the HBMO algorithm provides a good estimation for TS while exploring the largest regions, while the TS algorithm uses this estimation to find the best solution of the problem. The simulation results show that the proposed algorithm HBMO-TS-MUD provides the best trade-off between performance and computational complexity comparing to the conventional detector and the other MUD detectors proposed as Genetic Algorithm hybridised with the Tabu Search (GA-TS).
Keywords: MIMO; multi-input-multi-output; SDMA; space division multiple access; OFDM; orthogonal frequency division multiplexing; MUD; multi-user detection; HBMO; honey bees mating optimisation; tabu search.
Research on vehicle weld clearance detection algorithm based on image processing
by Xiaoli Zhang, Xiaoyong Han
Abstract: The realisation of weld clearance detection algorithm is the key to vehicle weld detection based on image processing. In this paper, the weld detection area of the acquired image is set on the high resolution CCD image of vehicle weld gap, and then the weld line is detected by combining Hough transform and least squares method. Owing to abnormalities such as broken lines, overlapping lines, and slopes in the detected straight lines, all the checked straight lines are first optimised to extract valid weld straight lines. Finally, the distance of the weld gap is calculated using a formula. The method can be used to measure the weld gap of vehicles quickly and accurately.
Keywords: image processing; weld detection; weld straight line detection.
Automatic generation of Chinese abstract based on vocabulary and LSTM neural network
by Guijun Zhang
Abstract: Most methods of Chinese short text summarisation are based on extraction, and it's hard to guarantee that the abstract is consistent. In this paper, we present an effective automatic method of Chinese abstract by using vocabulary and long-short term memory neural networks. The method utilises the seq2seq architecture, and introduces the candidate vocabulary in the decoding stage, to reduce the decoder vocabulary size. Thus, the training process is faster and the result is more concise and grammatical. In the end, experimental results validate the correctness and effectiveness of the method by taking a Large-Scale Chinese Short Text Summarisation (LCSTS) data set and Recall-Oriented Understudy for Gisting Evaluation (ROUGE).
Keywords: Chinese text summarisation; Seq2Seq model; LSTM neural network.
Phase analysis and error compensation of anti-jamming nulling algorithm for satellite navigation array antenna
by Kejin Cao, Zhengwang Luo, Hengchao Ma, Bao Li
Abstract: The traditional adaptive nulling antenna array anti-interference algorithm can cause phase distortion, make the antenna phase unstable, and produce positioning error. Based on the analysis of the adaptive nulling antenna array anti-jamming algorithm, this article deduces the calculation method of its phase centre and the stage of real-time change, determines the phase centre error, and calculates the compensation value which can be used for the repositioning after correction. Simulation and experimental results verify the rationality and effectiveness of the algorithm, which can be used to improve the positioning accuracy of anti-jamming array antenna GNSS receiver.
Keywords: array antenna; phase centre error; anti-jamming; high precision; power inversion; GNSS; anti-interference; adaptive nulling antenna.
A locally weighted KNN algorithm based on eigenvector of SVM
by Yonghua Wang, Jingyi Lu, Kaidi Zhao
Abstract: K-Nearest Neighbours (KNN) is one of the fundamental classification methods in machine learning. The performance of KNN method is restricted by the number of neighbours k. It is obvious that the outliers appear when dealing with small data samples. In this paper, we propose a hybrid framework of the feature weighted support vector machine as well as locally weighted k-nearest neighbour (SLKNN) to overcome this problem. In our method, we first use support vector machine to calculate the eigenvector of feature of data, then apply this eigenvector into distance metric as the weight of the feature. Finally, the distance metric is used in locally weighted k-nearest neighbour. The experiments on UCI data sets show that the proposed SLKNN performs better than some KNN-based methods.
Keywords: artificial intelligence; eigenvector; K-nearest neighbours; locally weighted.
Iteratively weighted principal component analysis and orientation consistency for normal estimation in point cloud
by Bo Wen, Bo Tao, Wei Pan, Guozhang Jiang
Abstract: In this paper, we present a method to robustly estimate normal of unorganised point clouds, namely Iterative Weighted Principal Component Analysis (IWPCA). Since the neighbourhood of a point in a smooth region can be well approximated by a plane, the classical Principal Component Analysis (PCA) is a widely used approach for normal estimation. Iterations are applied and bilateral spatial normal weights are introduced in each iteration for the local plane fitting to enhance the reliability of the PCA results. Minimal Spanning Tree (MST) is used to reorient flipped normals. We demonstrate the effectiveness and robustness of the proposed method on a variety of examples.
Keywords: point cloud normal; local plane fitting; least squares; iterative weighting; principal component analysis; minimal spanning tree; orientation consistency.
Modelling and simulation of electric loading test-device system for tilting axle of one special types of vehicle
by Zixia Chen, Zelin Chen, Xuyong Wang
Abstract: There is a certain oblique angle between the steering axis of the steering wheel of a special type of vehicle with the vertical direction clamp. In order to test the performance of the steering wheel when there is resistance to turn, this paper designs an electric torque loading test-device for the inclined axle, and analyses the basic working principle, main technical problems and system structure of the electric load simulator. According to the characteristics of the tilt axis moment loading test-device, the generation mechanism of the main interference moment is obtained. By analysing the mathematical model of disturbance torque, a feedforward compensation control method based on the principle of structure invariance is proposed. The simulation results of MATLAB-Simulink show that the design strategy of the tilting axis electric torque loading test-device is effective, and its control method can effectively suppress the influence of interference torque and improve the accuracy of torque loading. This paper has technical innovation and practical application value in the field of aerospace special vehicle driving and steering test research.
Keywords: tilt axis; electric load; interference moment; modelling and simulation.
Distributed mobile sensor load balancing deployment algorithm based on probability coverage model
by Xiaoqing Yang, Chaozong Xiang
Abstract: Load imbalance of distributed mobile sensors in distributed mobile sensor networks can easily lead to premature death of low-energy nodes, resulting in network partition and even network collapse, thus reducing the practicability of the network. Therefore, a distributed mobile sensor load balancing deployment algorithm based on Probabilistic Coverage Model (PCM) is proposed to deal with the relationship between residual energy of nodes and transmission power. With PCM as load balancing deployment condition, Lyapunov second method is used to deploy load balancing. The proposed distributed control law minimises the load difference among nodes. The algorithm only needs the relative location information of single hop neighbour nodes, and only carries out single hop communication. Therefore, the delay and communication load are small, and the scalability is strong. It confirms that the power system control module has a stable solution. The simulation results show that the algorithm can balance the load and energy consumption of nodes and improve the practicability of the network.
Keywords: distributed mobile sensor network; load balancing; load balancing deployment.
Modified multi-strategy artificial bee colony algorithm for optimising node coverage problem
by Xinyu Zhou, Yunan Liu, Jianyi Wan, Mingwen Wang
Abstract: To enhance exploitation for artificial bee colony (ABC) algorithm, we propose a modified multi-strategy ABC variant in which a superior information learning strategy is employed. In this strategy, the individuals can learn superior information from an exemplar which has better fitness value, and the exemplar is no longer acted by the global best individual or the elite group. In experiments, 22 well-known test functions are used and six well-established ABC variants are involved in the comparison. The results show that our approach performs better on most of test functions. Furthermore, our approach is applied to solve the node coverage optimisation problem in wireless sensor network. To this end, an improved Boolean sensing model is used to model the objective function, and simulation results indicate that our approach can provide promising performance.
Keywords: artificial bee colony; superior information learning; node coverage optimisation problem.
Formation and simulation of network aggregation behaviour
by Xiaohong Chen, Ruohan Chen
Abstract: Network aggregation behaviour appears more and more frequently with the development of internet. In the virtual world, the speed and degree of network aggregation are much faster than those in the real world. In this paper, Monte Carlo simulation method is used for modelling and analysing network aggregation behaviour, to discuss the influence of different influence parameters on aggregation behaviour, and verify the rationality and effectiveness of the model through empirical analysis. The simulation results show that the speed of gathering is determined by the degree of influence of followers. In addition, the larger initial number is, the slower the aggregation will be.
Keywords: network aggregation behaviour; simulation analysis; individual selection.
Design of intelligent tracking robot
by Yibo Liu, Ying Sun, Du Jiang, Juntong Yun, Ying Liu, Dongxu Bai, Gongfa Li, Dalin Zhou
Abstract: With the trend of world trade entering a period of rapid growth, the logistics industry is developing very rapidly. At the same time, it also has higher requirements for logistics handling and work efficiency. Therefore, this article designs a robot with mechanical arm and claw crawler tracking for unmanned logistics warehouse and production workshop. The robot has the functions of detecting signals, identifying signals, autonomously grasping objects, and transporting objects. Intelligent tracking robot is an industrial robot that can be automated for handling operations such as flexible grasping and handling of materials. The robot can automatically do tracking, self-grasping objects, and independent transportation of objects. Compared with the traditional crawler transport robot, the robot has the characteristics of fewer sensors, high accuracy, sensitive response and good adaptability. This article details the robot design process and functional module analysis.
Keywords: crawler robot; handling robot; mechanical arm; autonomous tracking.