基于SPC的电源故障预测系统研究

本文结合飞行器电源系统故障维护特点,利用统计过程控制理论,从数理统计的角度对电源系统测试数据进行分析,设计了电源故障预测系统。文中阐述了系统的工作原理和利用LabView软件的实现过程。实验结果表明此预测系统可以发现故障征兆及时维护,提高系统安全性。最后阐述了进一步研究可能会遇到的问题。

机器人系统的故障预测技术研究

文章针对机器人系统维护特点,提出将故障预测与健康管理(PHM)技术应用到机器人系统的维护上。论述了PHM关键技术——故障预测技术的特点和研究内容。对故障预测技术进行分类和分析,总结出各种预测方法的特点。最后提出了基于统计过程控制(SPC)进行故障预测的方法,并阐述了进一步研究可能遇到的问题。

基于Labview开发统计过程控制软件

统计过程控制是质量管理的重要内容,介绍了SPC的原理,并用Labview软件实现了SPC软件。这种开发方法应用了Labview软件提供的统计过程控制模块,方便了程序的开发,很容易被质量人员掌握,设备改动或软件应用于别的设备时,只需简单地修改参数,大大方便了统计过程控制的普及,提高企业的质量水平。

生产线监控与管理系统的设计

介绍在Labview的开发环境下,装配检测生产线监控与管理系统的开发方法。该系统实现了检测数据的人机界面显示,查询打印,统计过程控制(SPC)以及每月的不合格工件计数。统计过程控制(SPC)实现了对生产线的实时监控及质量管理,其他三个软件模块实现了对生产线的自动化生产管理。这种模块化的生产线管理系统对设计同类软件具有借鉴意义。

黄骅坳陷大港探区油气资源潜力与资源结构预测

Facing the problems that Dagang region of Huanghua Depression has high exploration degree and its remaining resource potential and structure are not clear, the theory of Petroleum Accumulation System (PAS) is applied to divide and evaluate the oil/gas systems quantitatively. Then, the petroleum accumulation systems are taken as units to forecast and analyse the oil/gas resources and their structure using statistical methods of sampling analysis of discovery process model and generalized pareto distribution model. The exploration benefit of the unit is estimated using exploration simulation methods. On the basis of the above study, the resource potential of Huanghua Depression is discussed.Huanghua Depression can be diveded into four petroleum accumulation systems, i.e. North PAS5 Middle Qibei PAS, Middle Qinan PAS and South PAS. Each PAS can be diveded futher into several sub- PASs. Using the basic princple of Analytical Hierarchy Process, the method of quantitative evaluation of PAS is established. Then the elements and maturity of PAS are evaluated quantitatively.Taking migration and accumulation units and sub-PASs as prediction units, sampling analysis of discovery process model and generalized pareto distribution model are applied comparatively to forecast the resource structure of eight migration and accumulation units in six PASs of medium-high exploration degree. The results of these two methods are contrasted and analyzed. An examination of X2 data of these two models from exploration samples shows that generalized pareto distribution model is more effective than sampling analysis of discovery process model in Huanghua Depression. It is concluded that minimum and maximum size of reservoir and discovery sequence of reservoirs are the sensitive parameters of these two methods.Aiming at the difficult problem of forecast in low exploration degree, by analysis of relativity between resource parameters and their possible influential geological factors, forecast models for resource parameters were established by liner regressing. Then the resource structure is forecasted in PASs of low exploration degree.Based on the forecast results, beginning with the analysis of exploration history and benefit variation, the exploration benefit variation of the above PASs is fitted effectively using exploration simulation method. The single well exploration benefit of remaining oil resource is also forecasted reasonably.The results of resource forecast show that the total oil resources ofHuanghua Depression amount to 2.28 b illion ton. By the end o f 2 003, the accumulative total proved oil reserve is 0.90 billion ton and the remaining oil resources is 1.38 billion ton. The remaining oil resource is concentrated in Kongdian-Dengmingshi, Banqiao-Beidagang, Qidong-Yangerzhuang and Baidong-Qizhong sub-PASs.

交易型领导的结构和作用机制研究

The Multifactor Leadership theory developed by Bass (1985) has become the new paradigm of leadership research. The empirical results of the effectiveness of transformational and transactional leadership in the literature, however, are not consentient. Researchers in China found the different structure of transformational leadership, but have not developed the transactional leadership. This study attempts to investigate three key questions in the unique Chinese socio-economic context: 1) what is the structure of transactional leadership in China? 2) What are the differences between western countries and China? And 3) what is the relationship between the transformational and transactional leadership mechanism? This study examines data collected from 3,500 participants, using Explored Factor Analysis (EFA), Confirmed Factor Analysis (CFA), Hierarchical Regression Analyses, partial correlations and other statistics methods. The major finings are listed as follows： Firstly, inductive methods was used to explore the structure of transactional leadership and the result show that transactional leadership is a four dimensions structure which includes contingent reward, contingent punishment , process control and anticipated investment. Reliability analysis, item analysis, EFA and CFA show the reliability and validity of the transactional leadership questionnaire we designed is good enough, the design of the item is effectively and properly. Contrast to other researches, anticipated investment emphasis on the leader’s recessive investment for subordinate, and this kind of transaction is quite special under the Chinese culture. While the content of the contingent reward with the contingent punishment is wider than the contingent reward in the western country, and the process control is wider than the management by exception and including goal setting and the management during the process. Secondly, hierarchical regression analyses showed that transformational and transactional leadership were significant positively related with in-role performance, extra-role performance, satisfaction and leadership effectiveness while negatively related to intention to leave. The effects of transactional and transformational leadership are different. Transactional leadership could significantly predict intention to leave controlling for transformational leadership, while transformational leadership could significantly predict in-role performance, extra-role performance, satisfaction and leadership effectiveness controlling for transactional leadership. Thirdly, the income level and the rank of subordinates are the moderators between the transformational, transactional leadership and leadership effectiveness. The leadership effectiveness of transactional leadership would decrease as the rank of subordinates increased, while the leadership effectiveness of transformational leadership would increase as the rank of subordinates increased. Transactional leadership is positively related to the effectiveness when the level of the subordinate income is low, but negatively related to the effectiveness when the level of the subordinate income is high. However the income level of the subordinate could not influence the leadership effectiveness of transformational leadership.

心算年老化的认知心理机制及功能磁共振成像研究

Mechanisms underlying cognitive psychology and cerebral physiological of mental arithmetic with increasing are were studied by using behavioral methods and functional magnetic resonance imaging (fMRI). I. Studies on mechanism underlying cognitive psychology of mental arithmetic with increasing age These studies were accomplished in 172 normal subjects ranging from 20 to 79 years of age with above 12 years of education (Mean = 1.51, SD = 1.5). Five mental arithmetic tasks, "1000-1", "1000-3", "1000-7", "1000-13", "1000-17", were designed with a serial calculation in which subjects sequentially subtracted the same prime number (1, 3, 7, 13, 17) from another number 1000. The variables studied were mental arithmetic, age, working memory, and sensory-motor speed, and four studies were conducted: (1) Aging process of mental arithmetic with different difficulties, (2) mechanism of aging of mental arithmetic processing. (3) effects of working memory and sensory-motor speed on aging process of mental arithmetic, (4) model of cognitive aging of mental arithmetic, with statistical methods such as MANOVA, hierarchical multiple regression, stepwise regression analysis, structural equation modelling (SEM). The results were indicated as following: Study 1: There was an obvious interaction between age and mental arithmetic, in which reaction time (RT) increased with advancing age and more difficult mental arithmetic, and mental arithmetic efficiency (the ratio of accuracy to RT) deceased with advancing age and more difficult mental arithmetic; Mental arithmetic efficiency with different difficulties decreased in power function: Study 2: There were two mediators (latent variables) in aging process of mental arithmetic, and age had an effect on mental arithmetic with different difficulties through the two mediators; Study 3: There were obvious interactions between age and working memory, working memory and mental arithmetic; Working memory and sensory-motor speed had effects on aging process of mental arithmetic, in which the effect of working memory on aging process of mental arithmetic was about 30-50%, and the effect of sensory-motor speed on aging process of mental arithmetic was above 35%. Study 4: Age, working memory, and sensory-motor speed had effects on two latent variables (factor 1 and factor 2), then had effects on mental arithmetic with different difficulties through factor 1 which was relative to memory component, and factor 2 which relative to speed component and had an effect on factor 1 significantly. II. Functional magnetic resonance imaging study on metal arithmetic with increasing age This study was accomplished in 14 normal right-handed subjects ranging from 20 to 29 (7 subjects) and 60 to 69 (7 subjects) years of age by using functional magnetic resonance imaging apparatus, a superconductive Signa Horizon 1.5T MRI system. Two mental arithmetic tasks, "1000-3" and "1000-17", were designed with a serial calculation in which subjects sequentially subtracted the same prime number (3 or 17) from another number 1000 silently, and controlling task, "1000-0", in which subjects continually rehearsed number 1000 silently, was regarded as baseline, based on current "baseline-task" OFF-ON subtraction pattern. Original data collected by fMRI apparatus, were analyzed off-line in SUN SPARC working station by using current STIMULATE software. The analytical steps were composed of within-subject analysis, in which brain activated images about mental arithmetic with two difficulties were obtained by using t-test, and between-subject analysis, in which features of brain activation about mental arithmetic with two difficulties, the relationship between left and right hemisphere during mental arithmetic, and age differences of brain activation in young and elderly adults were examined by using non-parameter Wilcoxon test. The results were as following:

Using Warp to Control Network Contention in Mermera

Parallel computing on a network of workstations can saturate the communication network, leading to excessive message delays and consequently poor application performance. We examine empirically the consequences of integrating a flow control protocol, called Warp control [Par93], into Mermera, a software shared memory system that supports parallel computing on distributed systems [HS93]. For an asynchronous iterative program that solves a system of linear equations, our measurements show that Warp succeeds in stabilizing the network's behavior even under high levels of contention. As a result, the application achieves a higher effective communication throughput, and a reduced completion time. In some cases, however, Warp control does not achieve the performance attainable by fixed size buffering when using a statically optimal buffer size. Our use of Warp to regulate the allocation of network bandwidth emphasizes the possibility for integrating it with the allocation of other resources, such as CPU cycles and disk bandwidth, so as to optimize overall system throughput, and enable fully-shared execution of parallel programs.

Statistical method of modeling and optimization for wireless sensor nodes with different interconnect technologies and substrates

A comparison study was carried out between a wireless sensor node with a bare die flip-chip mounted and its reference board with a BGA packaged transceiver chip. The main focus is the return loss (S parameter S11) at the antenna connector, which was highly depended on the impedance mismatch. Modeling including the different interconnect technologies, substrate properties and passive components, was performed to simulate the system in Ansoft Designer software. Statistical methods, such as the use of standard derivation and regression, were applied to the RF performance analysis, to see the impacts of the different parameters on the return loss. Extreme value search, following on the previous analysis, can provide the parameters' values for the minimum return loss. Measurements fit the analysis and simulation well and showed a great improvement of the return loss from -5dB to -25dB for the target wireless sensor node.

Genetic signatures in the envelope glycoproteins of HIV-1 that associate with broadly neutralizing antibodies.

A steady increase in knowledge of the molecular and antigenic structure of the gp120 and gp41 HIV-1 envelope glycoproteins (Env) is yielding important new insights for vaccine design, but it has been difficult to translate this information to an immunogen that elicits broadly neutralizing antibodies. To help bridge this gap, we used phylogenetically corrected statistical methods to identify amino acid signature patterns in Envs derived from people who have made potently neutralizing antibodies, with the hypothesis that these Envs may share common features that would be useful for incorporation in a vaccine immunogen. Before attempting this, essentially as a control, we explored the utility of our computational methods for defining signatures of complex neutralization phenotypes by analyzing Env sequences from 251 clonal viruses that were differentially sensitive to neutralization by the well-characterized gp120-specific monoclonal antibody, b12. We identified ten b12-neutralization signatures, including seven either in the b12-binding surface of gp120 or in the V2 region of gp120 that have been previously shown to impact b12 sensitivity. A simple algorithm based on the b12 signature pattern was predictive of b12 sensitivity/resistance in an additional blinded panel of 57 viruses. Upon obtaining these reassuring outcomes, we went on to apply these same computational methods to define signature patterns in Env from HIV-1 infected individuals who had potent, broadly neutralizing responses. We analyzed a checkerboard-style neutralization dataset with sera from 69 HIV-1-infected individuals tested against a panel of 25 different Envs. Distinct clusters of sera with high and low neutralization potencies were identified. Six signature positions in Env sequences obtained from the 69 samples were found to be strongly associated with either the high or low potency responses. Five sites were in the CD4-induced coreceptor binding site of gp120, suggesting an important role for this region in the elicitation of broadly neutralizing antibody responses against HIV-1.

Qualitative analysis of the interdisciplinary interaction between data analysis specialists and novice clinical researchers.

BACKGROUND: The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time. METHODS/PRINCIPAL FINDINGS: We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of "what if" situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal. CONCLUSION/SIGNIFICANCE: The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors.

Assessment of LD matrix measures for the analysis of biological pathway association.

Complex diseases will have multiple functional sites, and it will be invaluable to understand the cross-locus interaction in terms of linkage disequilibrium (LD) between those sites (epistasis) in addition to the haplotype-LD effects. We investigated the statistical properties of a class of matrix-based statistics to assess this epistasis. These statistical methods include two LD contrast tests (Zaykin et al., 2006) and partial least squares regression (Wang et al., 2008). To estimate Type 1 error rates and power, we simulated multiple two-variant disease models using the SIMLA software package. SIMLA allows for the joint action of up to two disease genes in the simulated data with all possible multiplicative interaction effects between them. Our goal was to detect an interaction between multiple disease-causing variants by means of their linkage disequilibrium (LD) patterns with other markers. We measured the effects of marginal disease effect size, haplotype LD, disease prevalence and minor allele frequency have on cross-locus interaction (epistasis). In the setting of strong allele effects and strong interaction, the correlation between the two disease genes was weak (r=0.2). In a complex system with multiple correlations (both marginal and interaction), it was difficult to determine the source of a significant result. Despite these complications, the partial least squares and modified LD contrast methods maintained adequate power to detect the epistatic effects; however, for many of the analyses we often could not separate interaction from a strong marginal effect. While we did not exhaust the entire parameter space of possible models, we do provide guidance on the effects that population parameters have on cross-locus interaction.

Integrated vector management for malaria control in Uganda: knowledge, perceptions and policy development.

BACKGROUND: Integrated vector management (IVM) is increasingly being recommended as an option for sustainable malaria control. However, many malaria-endemic countries lack a policy framework to guide and promote the approach. The objective of the study was to assess knowledge and perceptions in relation to current malaria vector control policy and IVM in Uganda, and to make recommendations for consideration during future development of a specific IVM policy. METHODS: The study used a structured questionnaire to interview 34 individuals working at technical or policy-making levels in health, environment, agriculture and fisheries sectors. Specific questions on IVM focused on the following key elements of the approach: integration of chemical and non-chemical interventions of vector control; evidence-based decision making; inter-sectoral collaboration; capacity building; legislation; advocacy and community mobilization. RESULTS: All participants were familiar with the term IVM and knew various conventional malaria vector control (MVC) methods. Only 75% thought that Uganda had a MVC policy. Eighty percent (80%) felt there was inter-sectoral collaboration towards IVM, but that it was poor due to financial constraints, difficulties in involving all possible sectors and political differences. The health, environment and agricultural sectors were cited as key areas requiring cooperation in order for IVM to succeed. Sixty-seven percent (67%) of participants responded that communities were actively being involved in MVC, while 48% felt that the use of research results for evidence-based decision making was inadequate or poor. A majority of the participants felt that malaria research in Uganda was rarely used to facilitate policy changes. Suggestions by participants for formulation of specific and effective IVM policy included: revising the MVC policy and IVM-related policies in other sectors into a single, unified IVM policy and, using legislation to enforce IVM in development projects. CONCLUSION: Integrated management of malaria vectors in Uganda remains an underdeveloped component of malaria control policy. Cooperation between the health and other sectors needs strengthening and funding for MVC increased in order to develop and effectively implement an appropriate IVM policy. Continuous engagement of communities by government as well as monitoring and evaluation of vector control programmes will be crucial for sustaining IVM in the country.

Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer.

BACKGROUND: We analyzed the association between 53 genes related to DNA repair and p53-mediated damage response and serous ovarian cancer risk using case-control data from the North Carolina Ovarian Cancer Study (NCOCS), a population-based, case-control study. METHODS/PRINCIPAL FINDINGS: The analysis was restricted to 364 invasive serous ovarian cancer cases and 761 controls of white, non-Hispanic race. Statistical analysis was two staged: a screen using marginal Bayes factors (BFs) for 484 SNPs and a modeling stage in which we calculated multivariate adjusted posterior probabilities of association for 77 SNPs that passed the screen. These probabilities were conditional on subject age at diagnosis/interview, batch, a DNA quality metric and genotypes of other SNPs and allowed for uncertainty in the genetic parameterizations of the SNPs and number of associated SNPs. Six SNPs had Bayes factors greater than 10 in favor of an association with invasive serous ovarian cancer. These included rs5762746 (median OR(odds ratio)(per allele) = 0.66; 95% credible interval (CI) = 0.44-1.00) and rs6005835 (median OR(per allele) = 0.69; 95% CI = 0.53-0.91) in CHEK2, rs2078486 (median OR(per allele) = 1.65; 95% CI = 1.21-2.25) and rs12951053 (median OR(per allele) = 1.65; 95% CI = 1.20-2.26) in TP53, rs411697 (median OR (rare homozygote) = 0.53; 95% CI = 0.35 - 0.79) in BACH1 and rs10131 (median OR( rare homozygote) = not estimable) in LIG4. The six most highly associated SNPs are either predicted to be functionally significant or are in LD with such a variant. The variants in TP53 were confirmed to be associated in a large follow-up study. CONCLUSIONS/SIGNIFICANCE: Based on our findings, further follow-up of the DNA repair and response pathways in a larger dataset is warranted to confirm these results.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.