不规则区域内的测量路径规划方法研究

自由曲面测量路径的规划直接关系到曲面测量效率,现有的行测法测量区域设定和路径规划方法往往会产生一定的空行程而导致测量效率低下。采用简单多边形精确描述不规则测量区域形状,并在分析多边形凹点周边区域特征的基础上对多边形进行剖分,将多边形剖分为一组凸多边形和单调多边形,所产生的子多边形可以直接进行行测法测量路径而不会产生空行程,从而提高整个区域的测量效率。最后,通过对比实验,证明了该方法是有效的。

浅谈热牙胶垂直加压法与iRoot SP 冷侧法行C形根管充填治疗牙体牙髓病的临床效果

目的探讨分别使用热牙胶垂直加压法、iRoot SP冷测法行C形根管充填治疗牙体牙髓病的临床效果。方法选取牙体牙髓病患者86例,按照随机数字表法分为对照组和实验组,各43例。对照组采取常规热牙胶垂直加压法,实验组采取iRoot SP冷测法行C形根管充填法,比较两组治疗效果、患牙充填面积、疼痛评分、预后情况。结果实验组总有效率为95.35%,对照组总有效率为93.02%,两组比较无显著差异(P>0.05);两组患牙充填面积对比无显著差异(P>0.05)。术前,两组VAS评分对比无显著差异(P>0.05);两组术后1个月、3个月VAS评分均较术前明显降低,且实验组明显低于对照组(P<0.05);随访6个月,实验组复发率(2.33%)明显低于对照组(13.95%)(P<0.05)。结论应用iRoot SP冷测法行C形根管充填治疗牙体牙髓病的疗效及预后俱佳。

Electrochemical behavior of galena and jamesonite flotation in high alkaline pulp

In order to effectively separate galena and jamesonite and improve the recovery during the mixing flotation, the interaction mechanisms between the minerals and the collector of diethyl dithiocarbamate （DDTC） were investigated. Single mineral flotation test was organized to research the effect of pulp pH value on the flotation behavior of galena and jamesonite. Electrochemistry property of the interaction of these two minerals with DDTC was investigated by cyclic voltammetry and Tafel tests. Flotation test shows that the recovery of jamesonite in high alkaline pulp is strongly depressed by lime （Ca（OH）2）. The cyclic voltammetry and Tafel tests results show that the interaction between galena and DDTC is an electrochemical process. High pH value has little influence on the interaction between galena and DDTC, while it has great effect on jamesonite due to self-oxidation and specific adsorption of OH^- and CaOH^＋ on jamesonite surface. Non-electroactive hydroxyl compound and low-electroconductive calcium compounds cover the surface of jamesonite, which impedes electron transfer and DDTC adsorption, thus leads to very low floatability of jamesonite.

Intrusion Detection Algorithm Based on Density,Cluster Centers,and Nearest Neighbors

Intrusion detection aims to detect intrusion behavior and serves as a complement to firewalls.It can detect attack types of malicious network communications and computer usage that cannot be detected by idiomatic firewalls.Many intrusion detection methods are processed through machine learning.Previous literature has shown that the performance of an intrusion detection method based on hybrid learning or integration approach is superior to that of single learning technology.However,almost no studies focus on how additional representative and concise features can be extracted to process effective intrusion detection among massive and complicated data.In this paper,a new hybrid learning method is proposed on the basis of features such as density,cluster centers,and nearest neighbors(DCNN).In this algorithm,data is represented by the local density of each sample point and the sum of distances from each sample point to cluster centers and to its nearest neighbor.k-NN classifier is adopted to classify the new feature vectors.Our experiment shows that DCNN,which combines K-means,clustering-based density,and k-NN classifier,is effective in intrusion detection.

Parallel Image Processing Technology of Surface Detection System

To improve image processing speed and detection precision of a surface detection system on a strip surface,based on the analysis of the characteristics of image data and image processing in detection system on the strip surface,the design of parallel image processing system and the methods of algorithm implementation have been studied. By using field programmable gate array(FPGA) as hardware platform of implementation and considering the characteristic of detection system on the strip surface,a parallel image processing system implemented by using multi IP kernel is designed. According to different computing tasks and the load balancing capability of parallel processing system,the system could set different calculating numbers of nodes to meet the system's demand and save the hardware cost.

Operating speed models for curved segments of highways in plateau regions

To examine the influence of the harsh environment in plateau areas on the operating speed of vehicles,advanced speed prediction models for curved segments are established based on observed actual speed data.First,the speed characteristics at the starting,mid,and end points of a plane curve were observed on Lalin Highway and China National Highway 318 with Bushnell s handheld radar speedometer 10-1911CN.Second,the stepwise regression method was proposed to determine the significant parameters and propose the prediction models of the operating speed of cars and large vehicles for the two highways.Finally,reserved test group data were utilized to prove the validity and practicality of the proposed models.Compared with traditional methods,the established models can produce more accurate prediction results and deeply examine the nonlinear relationships between parameters and the predicted operating speed.This study provides a considerate direction and basis for the operating speed prediction model for other segments in plateau regions.

A Probabilistic Rating Prediction and Explanation Inference Model for Recommender Systems

Collaborative Filtering(CF) is a leading approach to build recommender systems which has gained considerable development and popularity. A predominant approach to CF is rating prediction recommender algorithm, aiming to predict a user's rating for those items which were not rated yet by the user. However, with the increasing number of items and users, thedata is sparse.It is difficult to detectlatent closely relation among the items or users for predicting the user behaviors. In this paper,we enhance the rating prediction approach leading to substantial improvement of prediction accuracy by categorizing according to the genres of movies. Then the probabilities that users are interested in the genres are computed to integrate the prediction of each genre cluster. A novel probabilistic approach based on the sentiment analysis of the user reviews is also proposed to give intuitional explanations of why an item is recommended.To test the novel recommendation approach, a new corpus of user reviews on movies obtained from the Internet Movies Database(IMDB) has been generated. Experimental results show that the proposed framework is effective and achieves a better prediction performance.

Study of the helicopter blade running elevation measurement system

Helicopter blade running elevation measurement is an important measure target in helicopter blade dynamic balance experimentation. The elevation influences the helicopter＇ s security and other performance capabilities. In testing, however, it has been difficult to measure the elevation when the rotor reaches high speeds. To get a simple, fast and highly accurate measurement system, photo electricity technology was applied to measuring the blade running elevation. Discussed is the measurement principle of blade running elevation, tire design of the measurement system and analysis of the measurement precision.

Simple Scheme for Directly Measuring Concurrence of Two-Qubit Pure States in One Step

In the present work, a simple scheme for the direct measurement of the concurrence of two-qubit pure states is proposed. The scheme is based on trapped ions and only needs one step when the two identical pure states are given. The vibrational mode in our proposal is only virtually excited, which is important in view of decoherence.Furthermore, the scheme is feasible based on current technologies.

玉米自交系的提纯

所谓自交系提纯是指已经混杂退化的自交系，生产上又迫切需要，不得不重新整理。对某一自交系来讲，防杂保纯是根本措施，提纯只是不得已的情况下，采取的补救办法。

Determination method of load balance ranges for train operation safety under strong wind

The aerodynamic performances of a passenger car and a box car with different heights of windbreak walls under strong wind were studied using the numerical simulations, and the changes of aerodynamic side force, lift force and overturning moment with different wind speeds and wall heights were calculated. According to the principle of static moment balance of vehicles, the overturning coefficients of trains with different wind speeds and wall heights were obtained. Based on the influence of wind speed and wall height on the aerodynamic performance and the overturning stability of trains, a method of determination of the load balance ranges for the train operation safety was proposed, which made the overturning coefficient have nearly closed interval. A min(|A1|+|A2|), s.t. |A1|→|A2|(A1 refers to the downwind overturning coefficient and A2 refers to the upwind overturning coefficient)was found. This minimum value helps to lower the wall height as much as possible, and meanwhile, guarantees the operation safety of various types of trains under strong wind. This method has been used for the construction and improvement of the windbreak walls along the Lanzhou–Xinjiang railway(from Lanzhou to Urumqi, China).

Parallel Test Tasks Scheduling and Resources Configuration Based on GA-ACA

A Genetic Algorithm-Ant Colony Algorithm(GA-ACA),which can be used to optimize multi-Unit Under Test(UUT)parallel test tasks sequences and resources configuration quickly and accurately,is proposed in the paper.With the establishment of the mathematic model of multi-UUT parallel test tasks and resources,the condition of multi-UUT resources mergence is analyzed to obtain minimum resource requirement under minimum test time.The definition of cost efficiency is put forward,followed by the design of gene coding and path selection project,which can satisfy multi-UUT parallel test tasks scheduling.At the threshold of the algorithm,GA is adopted to provide initial pheromone for ACA,and then dual-convergence pheromone feedback mode is applied in ACA to avoid local optimization and parameters dependence.The practical application proves that the algorithm has a remarkable effect on solving the problems of multi-UUT parallel test tasks scheduling and resources configuration.

THE MIGRATION SCHEME BASED ON SCHEMA THEOREM OF PGAs

Genetic Algorithms (GAs) are efficient non-gradient stochastic search methods and Parallel GAs (PGAs) are proposed to overcome the deficiencies of the sequential GAs, such as low speed, aptness to local convergence, etc. However, the tremendous increase in the communication costs accompanied with the parallelization stunts the further improvements of PGAs. This letter takes the decrease of the communication costs as the key to this problem and advances a new Migration Scheme based on Schema Theorem (MSST). MSST distills schemata from the populations and then proportionately disseminates them to other populations, which decreases the total communication cost among the populations and arms the multiple-population model with higher speed and better scalability.

Mixed-Weights Least-Squares Stable Predictive Control Algorithm with Soft and Hard Constraints

Mixed-weight least-squares (MWLS) predictive control algorithm, compared with quadratic programming (QP) method, has the advantages of reducing the computer burden, quick calculation speed and dealing with the case in which the optimization is infeasible. But it can only deal with soft constraints. In order to deal with hard constraints and guarantee feasibility, an improved algorithm is proposed by recalculating the setpoint according to the hard constraints before calculating the manipulated variable and MWLS algorithm is used to satisfy the requirement of soft constraints for the system with the input constraints and output constraints. The algorithm can not only guarantee stability of the system and zero steady state error, but also satisfy the hard constraints of input and output variables. The simulation results show the improved algorithm is feasible and effective.

A Concurrent Security Monitoring Method for Virtualization Environments

Recently,virtualization technologies have been widely used in industry.In order to monitor the security of target systems in virtualization environments,conventional methods usually put the security monitoring mechanism into the normal functionality of the target systems.However,these methods are either prone to be tempered by attackers or introduce considerable performance overhead for target systems.To address these problems,in this paper,we present a concurrent security monitoring method which decouples traditional serial mechanisms,including security event collector and analyzer,into two concurrent components.On one hand,we utilize the SIM framework to deploy the event collector into the target virtual machine.On the other hand,we combine the virtualization technology and multi-core technology to put the event analyzer into a trusted execution environment.To address the synchronization problem between these two concurrent components,we make use of Lamport's ring buffer algorithm.Based on the Xen hypervisor,we have implemented a prototype system named COMO.The experimental results show that COMO can monitor the security of the target virtual machine concurrently within a little performance overhead.

Determination Method of Focal Depth of Local Earthquake Using the Travel-time Difference between Pn and sPn

In this paper,we derived the relationships between the travel time difference of sPn and Pn and the local earthquake focal depth.In these equations,the travel time difference of sPn and Pn is not related to the epicentral distance,but depends only on the regional crustal mode and the focal depth.According to the equations,we provided a simple and accurate method to determine local earthquake focal depth by using the travel time difference between phase sPn and Pn.This method has been used to determine the focal depths of two earthquake of MS6.1 and MS5.6 which occurred at the junction of Panzhihua and Huili,Sichuan on August 30 and 31,2008.The results were compared to those from other sources such as the China Earthquake Networks Center,and the comparison shows that the results are accurate and reliable.

Detection of Selfish Behavior in Wireless Ad Hoc Networks Based on CUSUM Algorithm

The cumulative sum （CUSUM） algorithm is proposed to detect the selfish behavior of a node in a wireless ad hoc network. By tracing the statistics characteristic of the backoff time between successful transmissions, a wireless node can distinguish if there is a selfish behavior in the wireless network. The detection efficiency is validated using a Qualnet simulator. An IEEE 802.11 wireless ad hoc network with 20 senders and 20 receivers spreading out randomly in a given area is evaluated. The well-behaved senders use minimum contention window size of 32 and maximum con- tention window size of I 024, and the selfish nodes are assumed not to use the binary exponential strategy for which the contention window sizes are both fixed as 16. The transmission radius of all nodes is 250 m. Two scenarios are investigated： a single-hop network with nodes spreading out in 100 m^100 m, and all the nodes are in the range of each other; and a multi-hop network with nodes spreading out in 1 000 m~ 1 000 m. The node can monitor the backoff time from all the other nodes and run the detection algorithms over those samples. It is noted that the threshold can significantly affect the detection time and the detection accuracy. For a given threshold of 0.3 s, the false alarm rates and the missed alarm rates are less than 5%. The detection delay is less than 1.0 s. The simulation results show that the algorithm has short detection time and high detection accuracy.

Square Wave Voltammetric Behavior of N,N-DiethyI-P-Nitroso Aniline an Indirect Method for Determination of Chlorpheniramin Maleate, Application of Pharmaceutical Formulations

The electrochemical behavior of N,N-diethyl-p-nitroso aniline was carried out using SWV （square wave voltammetric） at HMDE. A well defined reduction peak was observed at （-0.214） volt versus the reference electrode （Ag/AgC1/sat. KCI）, calibration curve was constructed in phosphate buffer （pH = 7.0）, the relationship is linear within the concentration range 1.283 × 10.5 M - 3.66 × 10.5 M with the correlation （R = 0.9923）. The serial addition ofCPM （chlorpheniramine maleate） leads to the decrease in the reduction current peak （Ip）, quantitatively, the plot of Alp （Ip - Ip） where, Ip： Peak current of N, N-diethyl-p-nitroso aniline alone, lp： peak current of N,N-diethyl-p-nitroso aniline in the presence of CPM, versus concentration is linear within the concentration range 0.984 × 10-6 M - 9.756 × 10-6 M, the correlation coefficient was 0.9954. The method was successfully applied to determine CPM in different types of pharmaceutical formulations, and compared with standard method from British Pharmacopeia [1].

The Effect of Power upon Unethical Behavior in the Organization

Based on the undertaken research, it is explored whether power can affect the judgment made by individual about unethical behavior. Research 1 uses questionnaire as measuring method. The results demonstrate that individuals with different levels of power make judgment on various unethical behaviors. Their judgments are not different. It does not agree with the hypothesis. The reason may lie in that it may be affected by social desirability, or that there exist defects in the design of questionnaire. Research 2 uses laboratory investigation. The results demonstrate that individuals in high-power group conduct unethical behavior more frequently and more fiercely. It agrees with the hypothesis. The inconsistent results of the two researches can be reasonably explained from the two angles of moral permission and moral hypocrisy.

PV Power Short-Term Forecasting Model Based on the Data Gathered from Monitoring Network

The degree of accuracy in predicting the photovoltaic power generation plays an important role in appropriate allocations and economic operations of the power plants based on the generating capacity data gathered from the geographically separated photovoltaic plants through network. In this paper, a forecasting model is designed with an optimization algorithm which is developed with the combination of PSO （Particle Swarm Optimization） and BP （Back Propagation） neural network. The proposed model is further validated and the experiment results show that the predication model assures the prediction accuracy regardless the day type transitions and other relevant factors, in the proposed model, the prediction error rate is worth less than 20% in all different climatic conditions and most of the prediction error accuracy is less than 10% in sunny day, and whose precision satisfies the management requirements of the power grid companies, reflecting the significance of the proposed model in engineering applications.