基于AFC数据的城轨站间客流量分布预测

基于轨道交通自动售检票系统(Automatic Fare Collection,AFC)统计获得的集计型客流数据,依据行为分析理论,提出1种适用于路网结构变化条件下的城轨站间客流量分布预测模型。首先,基于随机效用最大化理论,构建乘客目的地选择模型,选取终点站吸引客流量、列车运行时间、乘客在站换乘时间、乘客换乘次数、起终点站的线位关系和站点属性6个指标构建效用函数,以反映目的地吸引力、城轨服务水平、起终点站之间的线位匹配关系等对乘客目的地选择行为的影响,在此基础上,建立站间客流量分布预测模型;然后,利用代表个人法将AFC数据转化为非集计型数据,基于WESML(Weighted Exogenous Sampling Maximum Likelihood)估计方法,实现对目的地选择的非集计预测模型的参数标定。采用广州地铁6号线开通前后的AFC数据,对该预测模型的预测效果进行检验。结果表明:在新线接入导致地铁线网结构发生变化的条件下,全线网站间客流量分布预测的平均绝对误差仅为36人,因此该预测模型具有较高的预测精度。

城市快速路异常事件发生频率的时间差异性分析

城市快速路系统长时间处于高流量高密度状态时,异常事件等小的扰动就可能引发较大规模的拥堵.根据连接路段的匝道类型对路段进行分类,利用上海市内环和中环浦西段一年的异常事件监控数据,分析了不同路段上异常事件发生频率的月变、周变与时变特征,并分别探讨了抛锚和碰撞两类异常事件与交通流特征的关系.运用负二项回归建立了异常事件发生频率基于时间差异性的估计模型.分析发现,公休日变量估计结果显著,温度只对抛锚类事件产生明显影响,天气状况对不同快速路、不同时间段和不同事件的影响显著性有较大差异.

嵌入式软件测试平台配置

本文总结了建立软件评测中心必要条件,论述了软件测试过程并给出了各阶段的软件测试工具。在对市场充分调研的基础上,结合嵌入式软件的技术特点及具体工作需求,构建了一个嵌入式软件测试平台。

Reliability modeling of hydraulic system of drum shearer machine

The hydraulic system plays an important role in supplying power and its transition to other working parts of a coal shearer machine. In this paper, the reliability of the hydraulic system of a drum shearer was analyzed. A case study was done in the Tabas Coal Mine in Iran for failure data collection. The results of the statistical analysis show that the time between failures （TBF） data of this system followed the 3-parameters Weibull distribution. There is about a 54% chance that the hydraulic system of the drum shearer will not fail for the first 50 h of operation. The developed model shows that the reliability of the hydraulic system reduces to a zero value after approximately 1 650 hours of operation. The failure rate of this system decreases when time increases. Therefore, corrective maintenance （run-to-t^ailure） was selected as the best maintenance strategy for it.

Automatic relational database compression scheme design based on swarm evolution

Compression is an intuitive way to boost the performance of a database system. However, compared with other physical database design techniques, compression consumes large amount of CPU power. There is a trade-off between the re- duction of disk access and the overhead of CPU processing. Automatic design and adaptive administration of database systems are widely demanded, and the automatic selection of compression schema to compromise the trade-off is very important. In this paper, we present a model with novel techniques to integrate a rapidly convergent agent-based evolution framework, i.e. the SWAF (SWarm Algorithm Framework), into adaptive attribute compression for relational database. The model evolutionally consults statistics of CPU load and IO bandwidth to select compression schemas considering both aspects of the trade-off. We have im- plemented a prototype model on Oscar RDBMS with experiments highlighting the correctness and efficiency of our techniques.

Regression-Based Artificial Neural Network Methodology in Response Surface Methodology

Response surface methodology (RSM) is an important tool for process parameter optimization, robust design and other quality improvement efforts. When the relationship between influential input variables and output response is very complex, it’s hard to find the real response surface using RSM. In recent years artificial neural network(ANN) has been used in RSM. But the classical ANN does not work well under the constraints of real applications. An algorithm of regression-based ANN(R-ANN) is proposed in this paper, which is a supplement to the classical ANN methodology. It makes network closer to the response surface, so that training time is reduced and robustness is strengthened. The procedure of improving ANN by regressions is described and the comparisons among R-ANN,RSM and classical ANN are computed graphically in three examples. Our research shows that the R-ANN methodology is a good supplement to the RSM and classical ANN methodology, which can yield lower standard error of prediction under conditions that the scope of experiment is rigidly restricted.

A Hierarchical Virus Immunization Method for Community Networks

Due to the enormous harm of virus propagation,research regarding virus immunizations still absolutely necessary.In comparison to current researches,a new virus immunization method the hierarchical virus immunization method(HVIM) for community networks is proposed.Based on the virus transmission dynamic model SusceptibleInfectious-Removed and SusceptibleRemoved(SIRSR),HVIM considered the influence of external factors on the spread of viruses and only needs a portion of the network structure to be able to carry out immunization.Another pro for HVIM is that it is scalable and suitable for parallel computing which is a requirement in the big data era.Finally,a simulation dataset and a real dataset were used to run experiments,and the results of simulation showed that HVIM obviously is superior to others on the aspect of immunity.

AN IMPROVED GENETIC ALGORITHM FOR SEARCHING OPTIMAL PARAMETERS IN n-DIMENSIONAL SPACE

An improved genetic algorithm for searching optimal parameters in n-dimensional space is presented, which encodes movement direction and distance and searches from coarse to precise. The algorithm can realize global optimization and improve the search efficiency, and can be applied effectively in industrial optimization, data mining and pattern recognition.

A version management model of PDM system and its realization

Based on the key function of version management in PDM system, this paper discusses the function and the realization of version management and the transitions of version states with a workflow. A directed aeyclic graph is used to describe a version model. Three storage modes of the directed acyelic graph version model in the database, the bumping block and the PDM working memory are presented and the conversion principle of these three modes is given. The study indicates that building a dynamic product structure configuration model based on versions is the key to resolve the problem. Thus a version model of single product object is built. Then the version management model in product structure configuration is built and the application of version management of PDM syster is presented as a case.

Inverse Estimation on Trigger Factors of Simultaneous Slope Failures with Purification of Training Data Sets

This paper presents an procedure for purifying training data sets （i.e., past occurrences of slope failures） for inverse estimation on unobserved trigger factors of ＂different types of simultaneous slope failures＂. Due to difficulties in pixel-by-pixel observations of trigger factors, as one of the measures, the authors had proposed an inverse analysis algorithm on trigger factors based on SEM （structural equation modeling）. Through a measurement equation, the trigger factor is inversely estimated, and a TFI （trigger factor influence） map can be also produced. As a subsequence subject, a purification procedure of training data set should be constructed to improve the accuracy of TFI map which depends on the representativeness of given training data sets of different types of slope failures. The proposed procedure resamples the matched pixels between original groups of past slope failures （i.e., surface slope failures, deep-seated slope failures, landslides） and classified three groups by K-means clustering for all pixels corresponding to those slope failures. For all cases of three types of slope failures, the improvement of success rates with respect to resampled training data sets was confirmed. As a final outcome, the differences between TFI maps produced by using original and resampled training data sets, respectively, are delineated on a DIF map （difference map） which is useful for analyzing trigger factor influence in terms of ＂risky- and safe-side assessment＂ sub-areas with respect to ＂different types of simultaneous slope failures＂.

Web-services-based Integration Design of PDM and DNC Systems

In a networked manufacturing environment, product data integration is the foundation of collaborative manufacturing among manufacturing enterprises. It is very important to build an effective integration mechanism for product data sharing of manufacturing enterprises in geographically dispersed, heterogeneous system platform. In order to integrate enterprise level product data management (PDM) system and shop floor level distributed numerical control (DNC) system, based on the description of Web services technology, a Web-services-based integration approach is presented for facilitating seamless sharing of product data between PDM and DNC systems in a networked manufacturing environment. In order to verify the validity of the proposed approach, an example-based integration development has been implemented with Java 2 Software Development Kit and Java Web Services Developer Pack in Windows 2000 Professional environment.

Teletandem as a Way of Enhancing Language Learning Between Brazilian and German Students

This paper aims at investigating the teletandem learning interactions between a group of Brazilian students from Instituto Federal de Educagao, Ciencia e Tecnologia do Estado de Goias, Brazil, and a group of foreign students from two German universities. In this study, the Brazilian students helped their foreign partners with Portuguese learning and were helped by them in the English learning. The participants used a synchronous computer software called Openmeetings and also an electronic dictionary as a complementary tool. Adopting a qualitative perspective in the data collection and analysis, this case study was conducted in the second semester of 2010. The data were collected by means of conversation sessions through Openmeetings and were analyzed in the light of studies on sociocultural theory as well as on tandem/teletandem language learning researches. The data analyses showed that the participants used English as an anchoring language to work with Portuguese and English itself, and German was introduced in the teletandem sessions. The data also showed that the whiteboard and the electronic dictionary were used as complementary resources to the use of audio and video for the language learning process the participants engaged in.

Comparison of total splenic artery embolization and partial splenic embolization for hypersplenism

AIM:To evaluate whether total splenic artery embolization(TSAE) for patients with hypersplenism delivers better long-term outcomes than partial splenic embolization(PSE).METHODS:Sixty-one patients with hypersplenism eligible for TSAE(n = 27,group A) or PSE(n = 34,group B) were enrolled into the trial,which included clinical and computed tomography follow-up.Data on technical success,length of hospital stay,white blood cell(WBC) and platelet(PLT) counts,splenic volume and complications were collected at 2 wk,6 mo,and 1,2,3,4 years postoperatively.RESULTS:Both TSAE and PSE were technically successful in all patients.Complications were significantly fewer(P = 0.001),and hospital stay significantly shorter(P = 0.007),in group A than in group B.Postprocedure WBC and PLT counts in group A were significantly higher than those in group B from 6 mo to 4 years(P = 0.001),and post-procedure residual splenic volume in group A was significantly less than that observed in group B at 1,2,3 and 4 years post-procedure(P = 0.001).No significant differences were observed in red blood cell counts and liver function parameters between the two groups following the procedure.CONCLUSION:Our results indicate that TSAE for patients with hypersplenism not only delivers a better longterm outcome,but is also associated with lower complication rates and a shorter hospital stay than PSE.

The Design and Implementation of Multi-user Data Sharing Platform for Remote Monitoring System Based on Virtual Instruments

Remote data monitoring system which adopts virtual instrument usually applies data sharing, acquisition and remote transmission technology via internet. It is able to finish concurrent data acquisition and processing for multi-user and multi-task and also build a personalized virtual testing environment for more people but with fewer instruments. In this paper, we＇ 11 elaborate on the design and implementation of information sharing platform through a typical example of how to build multi-user concurrent virtual testing environment based on the virtnal software LabVIEW.

Integrating Data Mining Into Managerial Accounting System： Challenges and Opportunities

Data mining involves extracting information from large data sets, discovering the hidden relationships and unknown dependencies, and supporting strategic decision-making tasks. The alignment of data mining and business would bring benefits to the organization＇s management. The study investigated the adoption of data mining technologies in managerial accounting system, concentrating on the challenges and opportunities. The research showed that with the technology adoption, managerial functions could be improved and current information system could be upgraded. Since the technical progresses are reshaping the world of business and accountancy, it is significant for accountants and finance professionals to exploit information technologies.

Manifold alignment using discrete surface Ricci flow

Manifold alignment is useful to extract the shared latent structure among multiple data sets and the similarity among different datasets. As many kinds of real world data can be analyzed using low dimensional representations, manifold alignment algorithms can be used in a wide range of applications, such as data mining. In this paper, we propose a three-stage approach to manifold alignment using discrete surface Ricci flow. Our approach transforms the original intrinsic manifolds to hyper spheres using confonnal mapping in the first stage, and then zooms these hyper spheres into the same scale and aligns them in the following stages. We describe in details about our algorithm, its theoretical principles, our experimental results, and the comparison to previous alignment methods. To prove the effectiveness of our algorithm, three kinds of experiments are presented, including a toy dataset, one containing parallel corpus of parliament proceedings and another containing both images and texts. With these experiments, the latent utility in discovering the similarity among different kinds of data sets can be demonstrated, whether within the same kind of data or across different kinds of modals of data.

Sequential Bag-of-Words model for human action classification

Recently, approaches utilizing spatial-temporal features to form Bag-of-Words （BoWs） models have achieved great success due to their simplicity and effectiveness. But they still have difficulties when distinguishing between actions with high inter-ambiguity. The main reason is that they describe actions by orderless bag of features, and ignore the spatial and temporal structure information of visual words. In order to improve classification performance, we present a novel approach called sequential Bag-of-Words. It captures temporal sequential structure by segmenting the entire action into sub-actions. Meanwhile, we pay more attention to the distinguishing parts of an action by classifying sub- actions separately, which is then employed to vote for the final result. Extensive experiments are conducted on challenging datasets and real scenes to evaluate our method. Concretely, we compare our results to some state-of-the-art classification approaches and confirm the advantages of our approach to distinguish similar actions. Results show that our approach is robust and outperforms most existing BoWs based classification approaches, especially on complex datasets with interactive activities, cluttered backgrounds and inter-class action ambiguities.

Design and Description of a Photovoltaic Pumping System： Application in the Site of Adrar

The Saharan areas and in particular the isolated sites are characterized by low levels of population, in dispersed cores, which suffer from serious problems of water supply for consumption and the irrigation. The photovoltaic pumping systems （PV） are an ideal solution for these problems. Despite the presence of several photovoltaic pumping systems （PVPS） projects, data acquisition system is still missing in most cases. In this work, the authors will present the PVPS installed at the unit of research in renewable energies in Saharan medium （URERMS, Algeria）. This system will enable us to better analyze the performances ofa photovoltaic pumping system in Saharan medium. The principal elements of the chain of the photovoltaic pumping system are： a photovoltaic generator, the power conditioning system, a motor-driven pump immersed group, an electric wiring, a hydraulic infrastructure which comprises a water tank.

Compression techniques of mechanical vibration signals based on optimal sparse representations

This paper presents the result of an experimental study on the compression of mechanical vibration signals. The signals are collected from both rotating and reciprocating machineries by the accelerometers and a data acquisition （DAQ） system. Four optimal sparse representation methods for compression have been considered including the method of frames （ MOF）, best orthogonal basis （ BOB）, matching pursuit （MP） and basis pursuit （BP）. Furthermore, several indicators including compression ratio （CR）, mean square error （MSE）, energy retained （ER） and Kurtosis are taken to evaluate the performance of the above methods. Experimental results show that MP outperforms other three methods.

Design and Implementation of Image Acquisition System Based on STM32

In order to solve the difficulty of reading inconvenience in the measurement process of digital track gauge, a kind of image data acquisition system with low cost and stable performance is designed. The system uses the Cortex-M4 as the core of the STM32F407ZGT6 as the control core, the use of OV2640 as an image sensor to collect images, and the collection of image files stored in the SD card for subsequent image processing to achieve the goal of rail adjustment to lay the foundation. The experimental results show that the image acquisition is stable and refiable and the collected images are clear and meet the design requirements.