In the process of Wireless Sensor Network(WSN) node positioning,it is more important to improve the x-axis and y-axis positioning accuracy of an unknown node than z-axis positioning accuracy,so this paper proposes a positioning algorithm based on planar projection on the basis of RSSI Gaussian Mixed(RGM) algorithm.It improves unknown node positioning accuracy on the x-axis and y-axis directions by reducing the projected area of spatial positioning error region.Simulation results show that,compared with RGM algorithm,the proposed algorithm can improve the x-axis and y-axis positioning accuracy without any inscrease in time complexity and network traffic.
Intelligent meter reading system based on Wireless Sensor Network(WSN) can improve efficiency,but it has higher power consumption.Therefore,its nodes need to work under listen-sleep mode to reduce the power consumption.For this working mode,a rapid node wake-up method for WSN is proposed for hand-held meter reading and the system is designed.With the proposed method,higher communication rate is improved between handsets and sensor nodes.As a result,the average current in sensor nodes can be reduced significantly.Performance analysis result shows that the proposed method can reduce the average current.Furthermore,the proposed method yields obvious advantage in saving power consumption when the listen-sleep period is short.Hence,the proposed method is suitable for hand-held meter reading,which generally requires short responding time from sensor nodes.
When events distribute nonuniformly in the wireless sensor monitoring network,hot spots will appear in data-centric storage algorithms.Aiming at this problem,this paper introduces storage thresholds and event priorities,considers nodes’ remaining memory when selecting storage nodes,and proposes a new snake-like slot time data storage algorithm.It determines the distance from event storage location to query node grid according to the event priority,to reduce node’s energy consumption in process of data storage and query.Defining a node storage threshold,nodes reaching the threshold are no longer involved in the next round of time slot allocation.When all nodes in a grid reach the storage threshold,it stores data into neighbor grids with the same priority level.When all nodes in all grids of the same priority reach one storage threshold,it reallocates work slot,which effectively reduces the nonuniform distribution.Simulation results show that the proposed algorithm has better performance than the Snake-like Slot Time Power-saving Data Stroage Algorithm based on Event Priority(P-SLPS) in residual energy of nodes and the network life cycle.
Test suite reduction is an important research questions in software test,its purpose is to test as little as possible to achieve the test objective.This paper presents a test suite reduction method based on bisecting K-means.It uses the bisecting K-means clustering algorithm to reduce regression test suite.Regarding the path coverage of white box test as a criterion,each test case is quantified,so that each case becomes a point,the number of black box test functional needs is taken as the number of clusters,each cluster is sorted in the clustering results according to the distance from the center,the test cases from each cluster are selected,until all testing requirements are met and reduced test suite is got.Simulation experimental results show that this method can effectively reduce the size of the test suite,and effectively reduce the impact on the use case set error detection rate.
Two types of schemes based on pseudonym authentication and group signature authentication are compared and analyzed.This paper proposes a hybrid authentication scheme.The model builds an exchange protocol for exchanging pseudonym between adjacent nodes.The node can apply for the exchange key from the Trusted Authority (TA) with the nearby nodes.TA uses asymmetric key to realize the unforgeability of exchange identity and pseudonym.The proposed protocol can effectively resist the collusion attack.The exchanged pseudonym also can be used to signature and authentication between trusted nodes.And the group signature is introduced as the identity attribute label.The group signature label ensures the message unforgeable and auditable.The theoretical and efficiency analysis shows that the proposed scheme introduces the white list mechanism for pseudonym.Under this mechanism,the verification efficiency of a single message is improved obviously.At the same time,the white list mechanism can effectively resist the replay attacks using pseudonym.
Affinity Propagation Clustering(APC) method shows its limitations in time complexity,data storage and clustering results while handling massive functional Magnetic Resonance Imaging(fMRI) data.Aiming at these problems,this paper proposes a new method named SDAPC,which combines Sparse APC(SAPC) with similarity matrix reduction.It starts from sparse approximation on fMRI data,continues with the density analysis on sparse data by Gaussian density function and Euclidean distance,and finally realizes the detection on the functional connectivity of reduced fMRI data.The task-related data experiment gets the following results:SDAPC produces a fine ROC curve for single subject while running about three times faster than SAPC.SDAPC and SAPC both get better ROC curves for multiple subjects than single subject.The resting-state data experiment leads to the further finding that SDAPC can successfully identify nine resting-state networks.
In view of the decision making problems with multiplicative preference information,the order consistency,acceptable consistency and consistency index of multiplicative preference relation are introduced.An optimization model is developed with the principle of minimum non-negative deviation variables.An algorithm to derive the ranking of alternatives in decision making is investigated based on the consistency of multiplicative preference relation.The main characteristics of the proposed algorithm are that:It helps decision makers make decision quickly and efficiently by using the properties of the order consistent multiplicative preference relation.It repairs the consistency of multiplicative preference relation by using the optimal deviation values and ensures that the repaired multiplicative preference relation is acceptable consistent.The priority weight vector is obtained,and it helps the decision maker to obtain the reasonable and reliable decision making results.A practical application to selection of comprehensive replenishment ship is demonstrated to show the rationality and effectiveness of the proposed algorithm.
To improve the fusion effect of multi-source grayscale image,a new grayscale image fusion algorithm is proposed combining the shift invariance and good directional sensitivity of FDST.The original images after registration are decomposed by FDST,and the low frequency sub-band coefficients and high frequency sub-band coefficients of different scales and directions are obtained.The combination fusion algorithms of regional average energy and average gradient are used for the low frequency,and the combination fusion algorithms of relative region variance and average gradient are used for the high frequency.The fused image is reconstructed by inverse transform of finite discrete shear wave,and the result is evaluated by subjective vision and objective performance.Experimental results show that the algorithm can get better fusion results and image detail extraction compared with low frequency regional energy fusion and high frequency region variance fusion algorithms based on wavelet transform.
In order to improve the Delta robot movement speed,a method of time-optimal trajectory planning is proposed with the combination of off-line optimization and online inquiry.Griding the working area on robot conveyor belt,it selects the center point of each grid as a standard,uses linear and circular interpolation in cartesian space for “door” type track to get the discrete location sequence,and calculates the discrete angle sequence in joint space through the inverse kinematics.It uses the particle swarm algorithm and gravitational search algorithm,based on fitness function of time optimal and under the premise of the joint velocity,acceleration,jerk continuous and smooth and constraints,constructs 7th order B-spline curve to get the off-line interpolation sequence of the angle-time in joint space.The optimal timing sequence is obtained by online query of 3D arrays.Experimental results show that the method is simple and easy.Delta robot in laboratory picks up object from the conveyor belt to the fixed position,and the time range is 0.676 1 s~0.786 9 s,so the method overcomes the shortcomings of low speeds of traditional planning method.