ISSN 
2018 Vol. 47, No. 3
2018, 47(3): 321-329.
doi: 10.3969/j.issn.1001-0548.2018.03.001
Abstract:
This paper presents a novel variable virtual impedance control (VVIC) strategy which can adapt HEI to different pilots with a virtual impedance controller. The controller is model-based with a virtual impedance which models HEI between the pilot and the exoskeleton. To adapt different pilots with different HEI, a reinforcement learning method based on policy improvement and path integrals (PI2) is employed to adjust and optimize parameters of virtual impedance. We demonstrate the efficiency of the proposed VVIC strategy on a single degree-of-freedom (DOF) exoskeleton platform as well as a human-powered augmentation lower exoskeleton (HUALEX) system. Experimental results indicate that the proposed VVIC strategy is able to adapt HEI to different pilots and outperforms traditional model-based control strategies in terms of interaction forces.
This paper presents a novel variable virtual impedance control (VVIC) strategy which can adapt HEI to different pilots with a virtual impedance controller. The controller is model-based with a virtual impedance which models HEI between the pilot and the exoskeleton. To adapt different pilots with different HEI, a reinforcement learning method based on policy improvement and path integrals (PI2) is employed to adjust and optimize parameters of virtual impedance. We demonstrate the efficiency of the proposed VVIC strategy on a single degree-of-freedom (DOF) exoskeleton platform as well as a human-powered augmentation lower exoskeleton (HUALEX) system. Experimental results indicate that the proposed VVIC strategy is able to adapt HEI to different pilots and outperforms traditional model-based control strategies in terms of interaction forces.
2018, 47(3): 330-336.
doi: 10.3969/j.issn.1001-0548.2018.03.002
Abstract:
Lower limb exoskeletons enable paraplegics to regain some degree of locomotion ability, i.e., standing and walking. As a human machine system, the human machine interface (HMI) play an important role. The ideal lower limb exoskeleton for paralyzed people can move following the intention of pilot. To achieve it, many kinds of HMI systems are designed. However, for many exoskeletons, manual operation is still necessary for controlling the exoskeleton. In this paper, we designed and implemented an intention recognition method which is able to detect human motion intention. With the detected intention, exoskeleton can be controlled automatically as will of pilot. In this method, zero moment point (ZMP) is chosen as one of features of human intention and an online machine learning algorithm (online SVM) is used to learn intention online. Experiments in real systems show the effectiveness and advantages of our proposed method.
Lower limb exoskeletons enable paraplegics to regain some degree of locomotion ability, i.e., standing and walking. As a human machine system, the human machine interface (HMI) play an important role. The ideal lower limb exoskeleton for paralyzed people can move following the intention of pilot. To achieve it, many kinds of HMI systems are designed. However, for many exoskeletons, manual operation is still necessary for controlling the exoskeleton. In this paper, we designed and implemented an intention recognition method which is able to detect human motion intention. With the detected intention, exoskeleton can be controlled automatically as will of pilot. In this method, zero moment point (ZMP) is chosen as one of features of human intention and an online machine learning algorithm (online SVM) is used to learn intention online. Experiments in real systems show the effectiveness and advantages of our proposed method.
2018, 47(3): 337-342.
doi: 10.3969/j.issn.1001-0548.2018.03.003
Abstract:
By assembling Kinect camera and 2D lidar, this paper proposes a low-cost obstacle detection method for mobile robot. The correspondence between depth image points and laser radar ranging points is constructed based on joint calibration of the Kinect camera and lidar. The location of environmental obstacles is computed from the detection datum of these two sensors. There are three steps for the computations:1) Kinect camera and 2D lidar obtain the depth image and 2D laser points respectively; 2) the depth image is transferred into virtual laser points; 3) according to the correspondence, the obstacles location is calculated from the integration of virtual laser points and 2D laser points. The experiments show this method is proper and effective, and the computations results could be used to determine the obstacles for mobile robot.
By assembling Kinect camera and 2D lidar, this paper proposes a low-cost obstacle detection method for mobile robot. The correspondence between depth image points and laser radar ranging points is constructed based on joint calibration of the Kinect camera and lidar. The location of environmental obstacles is computed from the detection datum of these two sensors. There are three steps for the computations:1) Kinect camera and 2D lidar obtain the depth image and 2D laser points respectively; 2) the depth image is transferred into virtual laser points; 3) according to the correspondence, the obstacles location is calculated from the integration of virtual laser points and 2D laser points. The experiments show this method is proper and effective, and the computations results could be used to determine the obstacles for mobile robot.
2018, 47(3): 343-349.
doi: 10.3969/j.issn.1001-0548.2018.03.004
Abstract:
The traditional neural network only uses the end-layer feature and needs massive and time-consuming computation in the traffic sign recognition, thereby resulting in an inaccurate and non-real-time classification. To solve the problem, a traffic sign recognition (TSR) method based on multi-layer feature expression and extreme learning machine (ELM) is proposed. Firstly, the multi-layer features of traffic signs are extracted using the convolutional neural network (CNN). Then, the multi-scale pooling operation is used to combine the extracted feature vectors of each layer to form a multi-scale multi-attribute traffic sign feature vector. Finally, the extreme learning machine (ELM) classifier is used to realize the classification of traffic signs. Experimental results show that the proposed method can effectively improve the accuracy and it has strong generalization ability and real-time performance in TSR.
The traditional neural network only uses the end-layer feature and needs massive and time-consuming computation in the traffic sign recognition, thereby resulting in an inaccurate and non-real-time classification. To solve the problem, a traffic sign recognition (TSR) method based on multi-layer feature expression and extreme learning machine (ELM) is proposed. Firstly, the multi-layer features of traffic signs are extracted using the convolutional neural network (CNN). Then, the multi-scale pooling operation is used to combine the extracted feature vectors of each layer to form a multi-scale multi-attribute traffic sign feature vector. Finally, the extreme learning machine (ELM) classifier is used to realize the classification of traffic signs. Experimental results show that the proposed method can effectively improve the accuracy and it has strong generalization ability and real-time performance in TSR.
2018, 47(3): 350-355.
doi: 10.3969/j.issn.1001-0548.2018.03.005
Abstract:
An intelligent detection model for mobile traffic enforcement is presented to detect the vehicle violations on highways. The system model is divided into four sub-modules including the lane detection, vehicle detection and tracking, inverse perspective transformation and geometric measurement, and map matching for lane locating. The system model algorithm is tested in highway road environment, as well as special tests such as lane line detection, vehicle target and tracking to characterize its performance to detect vehicle violations. The test results show that the system model has certain ability to recognize vehicle violations in complex traffic environment. At the same time, the relevant special tests show that the model can detect and record illegal vehicles quickly and accurately.
An intelligent detection model for mobile traffic enforcement is presented to detect the vehicle violations on highways. The system model is divided into four sub-modules including the lane detection, vehicle detection and tracking, inverse perspective transformation and geometric measurement, and map matching for lane locating. The system model algorithm is tested in highway road environment, as well as special tests such as lane line detection, vehicle target and tracking to characterize its performance to detect vehicle violations. The test results show that the system model has certain ability to recognize vehicle violations in complex traffic environment. At the same time, the relevant special tests show that the model can detect and record illegal vehicles quickly and accurately.
2018, 47(3): 356-361.
doi: 10.3969/j.issn.1001-0548.2018.03.006
Abstract:
In order to meet the requirements of the accuracy and timeliness of lane detection in intelligent vehicle video forensics equipment for vehicle violation behavior forensics, a fast lane detection algorithm based on region of interest (ROI) model is proposed. Firstly, the edge detection operator is used to detect the lane edge information based on the characteristic that the lane and road have high contrast. Then the improved Hough transform is used to detect the possible lane based on the region of interest model. In order to extract the lane accurately, the algorithm is based on the vanishing point principle of the perspective image, and uses the inverse perspective transformation to eliminate the pseudo lane and complete the lane accurate positioning. Experiments show that the algorithm has the advantages of high positioning accuracy, high speed, and good robustness, which can meet the performance requirements of highway intelligent vehicle video equipment forensics.
In order to meet the requirements of the accuracy and timeliness of lane detection in intelligent vehicle video forensics equipment for vehicle violation behavior forensics, a fast lane detection algorithm based on region of interest (ROI) model is proposed. Firstly, the edge detection operator is used to detect the lane edge information based on the characteristic that the lane and road have high contrast. Then the improved Hough transform is used to detect the possible lane based on the region of interest model. In order to extract the lane accurately, the algorithm is based on the vanishing point principle of the perspective image, and uses the inverse perspective transformation to eliminate the pseudo lane and complete the lane accurate positioning. Experiments show that the algorithm has the advantages of high positioning accuracy, high speed, and good robustness, which can meet the performance requirements of highway intelligent vehicle video equipment forensics.
2018, 47(3): 362-367.
doi: 10.3969/j.issn.1001-0548.2018.03.007
Abstract:
A lane detection algorithm based on parallel coordinate system is proposed to solve the problem of slow detection rate caused by the Hough detection. The lane is visualized based on the parallel coordinate system and its detection rate are compared and analyzed. In the simulation environment, the results show that the accuracy of lane detection algorithm based on parallel coordinates is similar to that of the Hoough detection, and the speed is greatly improved.
A lane detection algorithm based on parallel coordinate system is proposed to solve the problem of slow detection rate caused by the Hough detection. The lane is visualized based on the parallel coordinate system and its detection rate are compared and analyzed. In the simulation environment, the results show that the accuracy of lane detection algorithm based on parallel coordinates is similar to that of the Hoough detection, and the speed is greatly improved.
2018, 47(3): 368-375.
doi: 10.3969/j.issn.1001-0548.2018.03.008
Abstract:
In order to prejudge driving intention of preceding car and enhance the adaptability of adaptive cruise control (ACC) against complex traffic scenarios simultaneously, a multi-objective adaptive cruise control algorithm considering multi-mode switching strategy is proposed. Based on the model predictive control (MPC) framework, it is hopeful to comprehensively coordinate various conflicting objectives such as driver's desired response, rear-end safety, and vehicular physical limits. Meanwhile, the slack variable vector is introduced to deal with non-feasible solution owing to hard constraints during online optimization. The desired response as well as constraint boundary varies with traffic scenarios, and consequently multiple ACC modes are designed by means of slightly adjusting weights of control objectives and system input, constraint boundary as well as slack relaxation. Further, we can obtain relatively suitable mode as well as smooth transition by fuzzy inference and the weighted average method. The simulations show that under emergent traffic scenarios, the multi-objective control algorithm together with multi-mode switching strategy is able to achieve good expectation during the car-following.
In order to prejudge driving intention of preceding car and enhance the adaptability of adaptive cruise control (ACC) against complex traffic scenarios simultaneously, a multi-objective adaptive cruise control algorithm considering multi-mode switching strategy is proposed. Based on the model predictive control (MPC) framework, it is hopeful to comprehensively coordinate various conflicting objectives such as driver's desired response, rear-end safety, and vehicular physical limits. Meanwhile, the slack variable vector is introduced to deal with non-feasible solution owing to hard constraints during online optimization. The desired response as well as constraint boundary varies with traffic scenarios, and consequently multiple ACC modes are designed by means of slightly adjusting weights of control objectives and system input, constraint boundary as well as slack relaxation. Further, we can obtain relatively suitable mode as well as smooth transition by fuzzy inference and the weighted average method. The simulations show that under emergent traffic scenarios, the multi-objective control algorithm together with multi-mode switching strategy is able to achieve good expectation during the car-following.
2018, 47(3): 376-381.
doi: 10.3969/j.issn.1001-0548.2018.03.009
Abstract:
A synovial variable structure and Lyapunov power distribution stability control strategy of hybrid energy storage system (HESS) in hybrid electric vehicles (HEV) is presented. The strategy aims to control power converters based on the synovial variable structure in order to satisfy the following requirements:stabilized dc bus voltage regulations and perfectly tracked of SC current to its reference. At the same time, the stability of the closed-loop control system based on the Lyapunov theory is analyzed. The HESS and control strategy are modeled and simulated under the ADVISOR simulation environment, and a prototype of HESS is also built. The results show that the designed control strategy meets all the objectives and achieves asymptotic stability of the closed loop system.
A synovial variable structure and Lyapunov power distribution stability control strategy of hybrid energy storage system (HESS) in hybrid electric vehicles (HEV) is presented. The strategy aims to control power converters based on the synovial variable structure in order to satisfy the following requirements:stabilized dc bus voltage regulations and perfectly tracked of SC current to its reference. At the same time, the stability of the closed-loop control system based on the Lyapunov theory is analyzed. The HESS and control strategy are modeled and simulated under the ADVISOR simulation environment, and a prototype of HESS is also built. The results show that the designed control strategy meets all the objectives and achieves asymptotic stability of the closed loop system.
2018, 47(3): 382-388.
doi: 10.3969/j.issn.1001-0548.2018.03.010
Abstract:
Vehicle rapid movement causes time varying channel, which will reduce the symbol error rate (SER) performance of intelligent vehicular cooperative system. Based on first-order autoregressive (AR1) model, a hybrid decode amplify forward (HDAF) cooperative strategy is presented, where the characteristics of time- varying channel are described by correlation coefficient of Doppler shift. The proposed strategy can select adaptively cooperative approach according to the variation of channel gain, and thus the controllable security of intelligent transportation system is enhanced. Moreover, vehicular velocities and estimation precision of channel state information (CSI) are analyzed. Numerical results show that the improvement of the CSI estimation precision will reduce the error-floor-value caused by vehicle rapid movement. Compared to amplify and forward (AF) and decode and forward (DF) strategies, the SER performance of the proposed strategy can be increased about 3.6 dB and 1.5 dB, respectively.
Vehicle rapid movement causes time varying channel, which will reduce the symbol error rate (SER) performance of intelligent vehicular cooperative system. Based on first-order autoregressive (AR1) model, a hybrid decode amplify forward (HDAF) cooperative strategy is presented, where the characteristics of time- varying channel are described by correlation coefficient of Doppler shift. The proposed strategy can select adaptively cooperative approach according to the variation of channel gain, and thus the controllable security of intelligent transportation system is enhanced. Moreover, vehicular velocities and estimation precision of channel state information (CSI) are analyzed. Numerical results show that the improvement of the CSI estimation precision will reduce the error-floor-value caused by vehicle rapid movement. Compared to amplify and forward (AF) and decode and forward (DF) strategies, the SER performance of the proposed strategy can be increased about 3.6 dB and 1.5 dB, respectively.
2018, 47(3): 389-396.
doi: 10.3969/j.issn.1001-0548.2018.03.011
Abstract:
An efficient data dissemination protocol with the assistance of parked vehicles on the roadside is proposed. It organizes the parked vehicles on the roadside into clusters, which buffer and relay data sent from mobile vehicle on the road. Simulation results show that the proposed protocol achieves higher data delivery ratio with lower delivery latency.
An efficient data dissemination protocol with the assistance of parked vehicles on the roadside is proposed. It organizes the parked vehicles on the roadside into clusters, which buffer and relay data sent from mobile vehicle on the road. Simulation results show that the proposed protocol achieves higher data delivery ratio with lower delivery latency.
2018, 47(3): 397-401.
doi: 10.3969/j.issn.1001-0548.2018.03.012
Abstract:
In order to enhance the quality factor (Q) of micro-electro-mechanical system (MEMS) resonator, this paper proposes an energy-decoupling frame structure which is applied in an MEMS resonator for energy decoupling and Q enhancement. An aluminium nitride (AlN) piezoelectric resonator is designed to work at 30 MHz frequency (f) in the lateral-extension mode. The resonator Q is significantly enlarged to 4.3×104 and the value of f·Q reaches to 1.29×1012. The energy coupling between the resonator and the substrate is effectively reduced by controlling the resonant frequency ratio of the resonator to the frame structure in around 10:1. Both theoretical analysis and finite-element analysis (FEA) simulation show that the energy loss reduction and Q enhancement of resonator can be achieved by using the proposed structure.
In order to enhance the quality factor (Q) of micro-electro-mechanical system (MEMS) resonator, this paper proposes an energy-decoupling frame structure which is applied in an MEMS resonator for energy decoupling and Q enhancement. An aluminium nitride (AlN) piezoelectric resonator is designed to work at 30 MHz frequency (f) in the lateral-extension mode. The resonator Q is significantly enlarged to 4.3×104 and the value of f·Q reaches to 1.29×1012. The energy coupling between the resonator and the substrate is effectively reduced by controlling the resonant frequency ratio of the resonator to the frame structure in around 10:1. Both theoretical analysis and finite-element analysis (FEA) simulation show that the energy loss reduction and Q enhancement of resonator can be achieved by using the proposed structure.
2018, 47(3): 402-409.
doi: 10.3969/j.issn.1001-0548.2018.03.013
Abstract:
By improving the classical Lü system and introducing a generalized memristor, a novel memristor-based modified Lü system is proposed. The most important feature of this memristive system is that there does not exist any equilibrium point, thereby leading to that the forming dynamical behaviors are all hidden. By utilizing theoretical analyses and nonlinear system analysis methods of Lyapunov exponent spectrum and bifurcation diagram, the complex hidden dynamical behaviors, such as period, quasi-period, chaos, hyperchaos, and so on, with the variation of memristor gain for the memristive system are studied. In addition, when different initial conditions are used, the memristive system exhibits coexisting multiple attractors' phenomena of three different limit cycles as well as chaotic attractor and limit cycle. The hardware circuit is made and the experimental results verify the theoretical analysis and numerical simulations, and demonstrate that the proposed memristive Lü system has very abundant and complex hidden dynamical characteristics.
By improving the classical Lü system and introducing a generalized memristor, a novel memristor-based modified Lü system is proposed. The most important feature of this memristive system is that there does not exist any equilibrium point, thereby leading to that the forming dynamical behaviors are all hidden. By utilizing theoretical analyses and nonlinear system analysis methods of Lyapunov exponent spectrum and bifurcation diagram, the complex hidden dynamical behaviors, such as period, quasi-period, chaos, hyperchaos, and so on, with the variation of memristor gain for the memristive system are studied. In addition, when different initial conditions are used, the memristive system exhibits coexisting multiple attractors' phenomena of three different limit cycles as well as chaotic attractor and limit cycle. The hardware circuit is made and the experimental results verify the theoretical analysis and numerical simulations, and demonstrate that the proposed memristive Lü system has very abundant and complex hidden dynamical characteristics.
2018, 47(3): 410-414.
doi: 10.3969/j.issn.1001-0548.2018.03.014
Abstract:
In this paper, a novel planar single spiral diamond resonator is designed, which is convenient to achieve the compact CT unit without the cross-coupling line for the filter design. By using this kind of CT unit, transmission zeros can be generated for improving the filter's selectivity and realize a miniaturized size, and also present an artistic three-dimensional sense. A 6-order novel high temperature superconducting (HTS) compact CT structure filter with passband covering 2 850~3 000 MHz is fabricated on the double-sided YBCO/LaAlO3/YBCO thin film with the size of 13.5 mm×3.8 mm, the thickness of 0.5 mm and the dielectric constant of 24.1. The measured results show that there are two transmission zeros; the out-of-band rejection is greater than 45 dB/MHz; and the second-harmonic passband is located at 6 GHz, which means the filter possesses a wide stopband. The measured results agree rather well with the simulated ones.
In this paper, a novel planar single spiral diamond resonator is designed, which is convenient to achieve the compact CT unit without the cross-coupling line for the filter design. By using this kind of CT unit, transmission zeros can be generated for improving the filter's selectivity and realize a miniaturized size, and also present an artistic three-dimensional sense. A 6-order novel high temperature superconducting (HTS) compact CT structure filter with passband covering 2 850~3 000 MHz is fabricated on the double-sided YBCO/LaAlO3/YBCO thin film with the size of 13.5 mm×3.8 mm, the thickness of 0.5 mm and the dielectric constant of 24.1. The measured results show that there are two transmission zeros; the out-of-band rejection is greater than 45 dB/MHz; and the second-harmonic passband is located at 6 GHz, which means the filter possesses a wide stopband. The measured results agree rather well with the simulated ones.
2018, 47(3): 415-420.
doi: 10.3969/j.issn.1001-0548.2018.03.015
Abstract:
In order to improve the accuracy of localization, the paper applies particle filtering to fuse WiFi fingerprinting and pedestrian dead reckoning (PDR). The map matching algorithm. The map matching algorithm first makes use of the indoor map to constrain the improper transitions of particles to reduce wall-crossing problems of them and then corrects wall-crossing problems of trajectories with a trace-back method. Evaluations show that the trajectories of the fused solution are closer to the real trajectories than WiFi fingerprinting and PDR, and after map matching the trajectories are more accurate and reasonable.
In order to improve the accuracy of localization, the paper applies particle filtering to fuse WiFi fingerprinting and pedestrian dead reckoning (PDR). The map matching algorithm. The map matching algorithm first makes use of the indoor map to constrain the improper transitions of particles to reduce wall-crossing problems of them and then corrects wall-crossing problems of trajectories with a trace-back method. Evaluations show that the trajectories of the fused solution are closer to the real trajectories than WiFi fingerprinting and PDR, and after map matching the trajectories are more accurate and reasonable.
2018, 47(3): 421-429.
doi: 10.3969/j.issn.1001-0548.2018.03.016
Abstract:
In order to enhance the optimization performance of the particle swarm optimization algorithm with Levy Flight (LFPSO), this paper proposes an improved LFPSO (ILFPSO), namely PSO based on combining the global-best operator and Levy Flight. First, the Levy Flight operator is accurately improved so that it can prevent the algorithm from generating invalid solutions, and an improved Levy Flight operator is obtained. Then because of the advantage of the global-best operator which has both some global and strong local search ability, this paper combines the global-best operator and improved Levy Flight in order to balance the global and local optimization ability of the algorithm. Finally, the velocity boundary is updated dynamically, which is helpful to find the global optimal solution in the early search stage and local optimal solutions in the later stage. 28 benchmark functions are used to evaluate the feasibility of ILFPSO. The experimental results show that, compared with 4 state-of-the-art PSO variants, such as LFPSO, ELPSO, SRPSO and RLPSO, ILFPSO obtains stronger competitive power, better universality and faster running speed.
In order to enhance the optimization performance of the particle swarm optimization algorithm with Levy Flight (LFPSO), this paper proposes an improved LFPSO (ILFPSO), namely PSO based on combining the global-best operator and Levy Flight. First, the Levy Flight operator is accurately improved so that it can prevent the algorithm from generating invalid solutions, and an improved Levy Flight operator is obtained. Then because of the advantage of the global-best operator which has both some global and strong local search ability, this paper combines the global-best operator and improved Levy Flight in order to balance the global and local optimization ability of the algorithm. Finally, the velocity boundary is updated dynamically, which is helpful to find the global optimal solution in the early search stage and local optimal solutions in the later stage. 28 benchmark functions are used to evaluate the feasibility of ILFPSO. The experimental results show that, compared with 4 state-of-the-art PSO variants, such as LFPSO, ELPSO, SRPSO and RLPSO, ILFPSO obtains stronger competitive power, better universality and faster running speed.
2018, 47(3): 430-435.
doi: 10.3969/j.issn.1001-0548.2018.03.017
Abstract:
In order to effectively exploit the lip feature of human speech, a lip segmentation method based on Markov random field (MRF) and model calibration is proposed. In this paper, we conduct the color space transformation from RGB to LUX color space for the lip region image, and we make use of the logarithmic chroma U to determine the initial contour. A mask with fixed radius is selected along the contour to define the local region, the Markov random field is used to segment the lips, and the Kullback-Leiller (KL) distance based model calibration method is used to coordinate the segmentation results between the local regions. Experiments show that the method can separate the lips in the skin with high accuracy and robustness and is of high practical value.
In order to effectively exploit the lip feature of human speech, a lip segmentation method based on Markov random field (MRF) and model calibration is proposed. In this paper, we conduct the color space transformation from RGB to LUX color space for the lip region image, and we make use of the logarithmic chroma U to determine the initial contour. A mask with fixed radius is selected along the contour to define the local region, the Markov random field is used to segment the lips, and the Kullback-Leiller (KL) distance based model calibration method is used to coordinate the segmentation results between the local regions. Experiments show that the method can separate the lips in the skin with high accuracy and robustness and is of high practical value.
2018, 47(3): 436-442.
doi: 10.3969/j.issn.1001-0548.2018.03.018
Abstract:
Material diffusion recommendation algorithm has received wide attention for its simplicity and effectiveness. However, up to now, most of researches on this algorithm were confined to two-step diffusion process of a bipartite network. In this paper, we use the method of matrix analysis to study the multi-step material diffusion process in the bipartite network. By analyzing the nature of the diffusion transfer matrix of W, we prove that WN converges when the diffusion step N tends to infinity. Eventually, the distribution of resources will reach a steady state. At this point, the number of resources that each node obtains is proportional to its degree, but not the proportion of the initial distribution of resources. At the same time, the algorithm is transformed into a global recommendation algorithm and the recommendation result is no longer personalized. It reveals that the material diffusion recommendation algorithm will gradually lose its personalized feature with the increase of the number of diffusion steps.
Material diffusion recommendation algorithm has received wide attention for its simplicity and effectiveness. However, up to now, most of researches on this algorithm were confined to two-step diffusion process of a bipartite network. In this paper, we use the method of matrix analysis to study the multi-step material diffusion process in the bipartite network. By analyzing the nature of the diffusion transfer matrix of W, we prove that WN converges when the diffusion step N tends to infinity. Eventually, the distribution of resources will reach a steady state. At this point, the number of resources that each node obtains is proportional to its degree, but not the proportion of the initial distribution of resources. At the same time, the algorithm is transformed into a global recommendation algorithm and the recommendation result is no longer personalized. It reveals that the material diffusion recommendation algorithm will gradually lose its personalized feature with the increase of the number of diffusion steps.
2018, 47(3): 443-448.
doi: 10.3969/j.issn.1001-0548.2018.03.019
Abstract:
The quality of service (QoS) of Web services that serve the Internet business is inherently uncertain, which increases the difficulty of QoS-aware Web service composition optimization problem. Assuming that QoS and its aggregation of services are normally distributed, the calculation methods of expectation and standard deviation of the addition, maximum, minimum and multiplication of two independent normally distributed random variables are focused and a QoS-aware robust Web service composition optimization model is built. By overloading the addition and subtraction operators, and choosing suitable fitness function, a discrete particle swarm optimization algorithm with constraints is designed to solve the model. The simulation experiments illustrate that the model has a good accuracy and the composite service gained has a good robustness.
The quality of service (QoS) of Web services that serve the Internet business is inherently uncertain, which increases the difficulty of QoS-aware Web service composition optimization problem. Assuming that QoS and its aggregation of services are normally distributed, the calculation methods of expectation and standard deviation of the addition, maximum, minimum and multiplication of two independent normally distributed random variables are focused and a QoS-aware robust Web service composition optimization model is built. By overloading the addition and subtraction operators, and choosing suitable fitness function, a discrete particle swarm optimization algorithm with constraints is designed to solve the model. The simulation experiments illustrate that the model has a good accuracy and the composite service gained has a good robustness.
2018, 47(3): 449-454.
doi: 10.3969/j.issn.1001-0548.2018.03.020
Abstract:
To address the intersecting region of the continuous range queries needs to repeat queries in the location-based service, this paper proposes a method of trajectory privacy protection based on caching candidate result set. The method utilizes two-level cache mechanism to cache user's candidate result set at client and anonymizer, and the next query point on the trajectory can obtain the answer from the cached data, which can reduce the interaction between the user and the server to reduce the risk of user's information exposed to the server. At the same time, we propose the k-anonymity of the mobile location prediction based on the Markov model, which can improve the hit ratio of cache and enhance the user's trajectory privacy. Security analysis shows that the method can effectively protect the user's trajectory privacy. Experiments show this method can reduce the computation and communication overhead of the server.
To address the intersecting region of the continuous range queries needs to repeat queries in the location-based service, this paper proposes a method of trajectory privacy protection based on caching candidate result set. The method utilizes two-level cache mechanism to cache user's candidate result set at client and anonymizer, and the next query point on the trajectory can obtain the answer from the cached data, which can reduce the interaction between the user and the server to reduce the risk of user's information exposed to the server. At the same time, we propose the k-anonymity of the mobile location prediction based on the Markov model, which can improve the hit ratio of cache and enhance the user's trajectory privacy. Security analysis shows that the method can effectively protect the user's trajectory privacy. Experiments show this method can reduce the computation and communication overhead of the server.
2018, 47(3): 455-461.
doi: 10.3969/j.issn.1001-0548.2018.03.021
Abstract:
Traditional approaches to optimize the operation of the urban bus network rely on surveys, which are expensive, time-consuming, inaccurate and with limited spatial coverage of lines and areas. In this paper, we analyze the operation state of bus networks for two typical zones in Shenzhen based on bus GPS data and ST-Matching method. Percolation theory is applied to find the bottlenecks in the bus network. The pinpointed bottlenecks are different from the most congested road segments. Therefore, this paper provides a method to improve a whole bus network operation efficiency in a highly efficient and lower cost way.
Traditional approaches to optimize the operation of the urban bus network rely on surveys, which are expensive, time-consuming, inaccurate and with limited spatial coverage of lines and areas. In this paper, we analyze the operation state of bus networks for two typical zones in Shenzhen based on bus GPS data and ST-Matching method. Percolation theory is applied to find the bottlenecks in the bus network. The pinpointed bottlenecks are different from the most congested road segments. Therefore, this paper provides a method to improve a whole bus network operation efficiency in a highly efficient and lower cost way.
2018, 47(3): 462-468.
doi: 10.3969/j.issn.1001-0548.2018.03.022
Abstract:
This paper focuses on the influence of time series on the topology and spreading modes in Chinese aviation network. The network is divided into 24 time windows to study the characteristics of the topological structure in the sequence. Considering the time interval of events in this network, the SIR (susceptible- infective-removed) propagation model and the node classification method based on time characteristics are established. The results show that the correlations among the degree and clustering coefficient, betweenness and clustering coefficient have changed from positive to negative at 8:00am. And there are obvious differences among nodes in terms of the burstiness of exporting time related to flights, but it has reduced the propagation speed and the scope of infection. The results are of great significance for the further understanding of the aviation network and its dynamic process, such as the propagation of diseases.
This paper focuses on the influence of time series on the topology and spreading modes in Chinese aviation network. The network is divided into 24 time windows to study the characteristics of the topological structure in the sequence. Considering the time interval of events in this network, the SIR (susceptible- infective-removed) propagation model and the node classification method based on time characteristics are established. The results show that the correlations among the degree and clustering coefficient, betweenness and clustering coefficient have changed from positive to negative at 8:00am. And there are obvious differences among nodes in terms of the burstiness of exporting time related to flights, but it has reduced the propagation speed and the scope of infection. The results are of great significance for the further understanding of the aviation network and its dynamic process, such as the propagation of diseases.
2018, 47(3): 469-480.
doi: 10.3969/j.issn.1001-0548.2018.03.023
Abstract:
This paper reviews the related research of international trade network. Firstly, the paper presents a brief introduction to models of the international trade network:classic network model, fitness model, hyperbolic model, flow network model, multi-layer network model and bipartite network model. Subsequently, the research on the international trade network is reviewed from four aspects:statistical characteristics, community structure, evolution model and dynamic behavior. Finally, the research on international trade network is briefly summarized and some future directions are pointed out.
This paper reviews the related research of international trade network. Firstly, the paper presents a brief introduction to models of the international trade network:classic network model, fitness model, hyperbolic model, flow network model, multi-layer network model and bipartite network model. Subsequently, the research on the international trade network is reviewed from four aspects:statistical characteristics, community structure, evolution model and dynamic behavior. Finally, the research on international trade network is briefly summarized and some future directions are pointed out.
