工作流赋权性能有色Petri网建模方法

针对经典Petri网存在工作流无严格限制和定义,不同方式下变迁的托肯(Token)(包括了种类、数量、流向)绑定、后续库所到达以及对多性能描述与分析无法有效处理的问题,通过明确定义Petri网工作流结构、颜色集和加入多性能的衡量分析,提出工作流赋权性能有色Petri网。介绍了该方法的基本概念、权值向量和基本结构,并以危化品物流流程为实例,从时间和安全两个维度给出了危化品物流流程建模及性能测算方法;然后对危化品物流流程进行了建模、性能测算和分析,经测算其总体性能为3.809 4;最后利用筛选模型中各路径的时间性能和危险度的差路,找出制约危化品物流流程的瓶颈,从而证明该方法是工作流多性能分析的有效方法。

Closed BER expression of multi-user DS UWB systemsin indoor fading channel

The bit error rate （BER） performance of multi-user direct spreading bi-phase shift keying （DSBPSK） direct impulse ultra wideband （UWB） systems is analyzed and simulated based on a statistical indoor multi-path fading channel model. The BER of the system is theoretically derived and given in closed form, which is expressed in terms of channel parameters and system parameters such as pulse width parameter, pulse repeat period, user number and pulse waveform. With this BER expression, the effect of these parameters on the system performance can be evaluated in a uniform way. Simulation results well match the theory numerical results, and prove that the multi-access interference （MAI） of DS-BPSK UWB is a normal distribution.

New Math Model for Designing Engine Radiator

Aim To raise the H-NE math model for designing engine radiators.Methods Thismodel was founded on multi-nonlinear regression technology,and the quadratic equatingmethod was used to smooth original data.Through the sensitivity analysis about radiatoroptimization designing,some major restraints were obtained.Results Type 1301C radiator wasoptimizingly renwed by use o this model,and the new radiator is more excellent than theold one in respect of the heat transfer factor and the manufacturing cost.Conclusion Theradiation performance can be improved,the area can be reduced,and the fitting scope can bewidened if this model is used in designing radiators.

Differential effects of physical activity and sleep duration on cognitive function in young adults

Purpose: Although exercise and sleep duration habits are associated with cognitive function, their beneficial effects on cognitive function remain unclear. We aimed to examine the effect of sleep duration and daily physical activity on cognitive function, elucidating the neural mechanisms using near-infrared spectroscopy(NIRS).Methods: A total of 23 healthy young adults(age 22.0 ± 2.2 years) participated in this study. Exercise amount was assessed using a uniaxial accelerometer. We evaluated total sleep time(TST) and sleep efficiency by actigraphy. Cognitive function was tested using the N-back task, the Wisconsin Card Sorting Test(WCST), and the Continuous Performance Test—Identical Pairs(CPT-IP), and the cortical oxygenated hemoglobin levels during a word fluency task were measured with NIRS.Results: Exercise amount was significantly correlated with reaction time on 0- and 1-back tasks(r = —0.602, p = 0.002; r = —0.446, p = 0.033,respectively), whereas TST was significantly correlated with % corrects on the 2-back task(r = 0.486, p = 0.019). Multiple regression analysis,including exercise amount, TST, and sleep efficiency, revealed that exercise amount was the most significant factor for reaction time on 0- and 1-back tasks(b = —0.634, p = 0.002; b = —0.454, p = 0.031, respectively), and TST was the most significant factor for % corrects on the 2-back task(b = 0.542, p = 0.014). The parameter measured by WCST and CPT-IP was not significantly correlated with TST or exercise amount. Exercise amount, but not TST, was significantly correlated with the mean area under the NIRS curve in the prefrontal area(r = 0.492, p = 0.017).Conclusion: Exercise amount and TST had differential effects on working memory and cortical activation in the prefrontal area. Daily physical activity and appropriate sleep duration may play an important role in working memory.

Performance Monitoring and Diagnosis of Multivariable Model Predictive Control Using Statistical Analysis

A statistic-based benchmark was proposed for performance assessment and monitoring of model predic- tive control; the benchmark was straightforward and achievable by recording a set of output data only when the control performance was good according to the user’s selection. Principal component model was built and an auto- regressive moving average filter was identified to monitor the performance; an improved T2 statistic was selected as the performance monitor index. When performance changes were detected, diagnosis was done by model validation using recursive analysis and generalized likelihood ratio (GLR) method. This distinguished the fact that the per- formance change was due to plant model mismatch or due to disturbance term. Simulation was done about a heavy oil fractionator system and good results were obtained. The diagnosis result was helpful for the operator to improve the system performance.

Performance Analysis for Multimedia Communication Systems with a Multilayer Queuing Network Model

Software performance evaluation in multimedia communication systems is typically formulated into a multi-layered client-server queuing network(MLCSQN) problem. However, the existing analytical methods to MLCSQN model cannot provide satisfactory solution in terms of accuracy, convergence and consideration of interlocking effects. To this end, this paper proposes a heuristic solving method for MLCSQN model to boost the performance prediction of distributed multimedia software systems. The core concept of this method is referred to as the basic model, which can be further decomposed into two sub-models: client sub-model and server sub-model. The client sub-model calculates think time for server sub-model, and the server sub-model calculates waiting time for client sub-model. Using a breadthfirst traversal from leaf nodes to the root node and vice versa, the basic model is then adapted to MLCSQN, with net sub-models iteratively resolved. Similarly, the interlocking problem is effectively addressed with the help of the basic model. This analytical solver enjoys advantages of fast convergence, independence on specific average value analysis(MVA) methods and eliminating interlocking effects.Numerical experimental results on accuracy and computation efficiency verify its superiority over anchors.

Performance Analysis of Robotic Arm Manipulators Control System under Multitasking Environment

This work is to observe the performance of PC based robot manipulator under general purpose （Windows）, Soft （Linux） and Hard （RT Linux） Real Time Operating Systems （OS）. The same open loop control system is observed in different operating systems with and without multitasking environment. The Data Acquisition （DAQ, PLC-812PG） card is used as a hardware interface. From the experiment, it could be seen that in the non real time operating system （Windows）, the delay of the control system is larger than the Soft Real Time OS （Linux）. Further, the authors observed the same control system under Hard Real Time OS （RT-Linux）. At this point, the experiment showed that the real time error （jitter） is minimum in RT-Linux OS than the both of the previous OS. It is because the RT-Linux OS kernel can set the priority level and the control system was given the highest priority. The same experiment was observed under multitasking environment and the comparison of delay was similar to the preceding evaluation.

Characteristics of soil microbial community functional and structure diversity with coverage of Solidago Canadensis L

The relationship between Solidago canadensis L. invasion and soil microbial community diversity including functional and structure diversities was studied across the invasive gradients varying from 0 to 40%, 80%, and 100% coverage of Solidago canadensis L. using sole carbon source utilization profiles analyses, principle component analysis （PCA） and phospholipid fatty acids （PLFA） profiles analyses. The results show the characteristics of soil microbial community functional and structure diversity in invaded soils strongly changed by Solidago canadensis L. invasion. Solidago canadensis L. invasion tended to result in higher substrate richness, and functional diversity. As compared to the native and ecotones, average utilization of specific substrate guilds of soil microbe was the highest in Solidago canadensis L. monoculture. Soil microbial functional diversity in Solidago canadensis L. monoculture was distinctly separated from the native area and the ecotones. Aerobic bacteria, fungi and actinomycetes population significantly increased but anaerobic bacteria decreased in the soil with Solidago canadensis L. monoculture. The ratio of cyl9：0 to 18：1 co7 gradually declined but mono/sat and fung/bact PLFAs increased when Solidago canadensis L. became more dominant. The microbial community composition clearly separated the native soil from the invaded soils by PCA analysis, especially 18： lco7c, 16： lco7t, 16： lco5c and 18：2co6, 9 were present in higher concentrations for exotic soil. In conclusion, Solidago canadensis L. invasion could create better soil conditions by improving soil microbial community structure and functional diversity, which in turn was more conducive to the growth ofSolidago canadensis L.

Geochip-based analysis of microbial functional genes diversity in rutile bio-desilication reactor

Biological desilication process is an effective way to remove silicate from rutile so that high purity rutile could be obtained. However, little is known about the molecular mechanism of this process. In this work, a newly developed rutile bio-desilication reactor was applied to enrich rutile from rough rutile concentrate obtained from Nanzhao rutile mine and a comprehensive high through-put functional gene array(Geo Chip 4.0) was used to analyze the functional gene diversity, structure and metabolic potential of microbial communities in the biological desilication reactor. The results show that TiO2 grade of the rutile concentrate could increase from 78.21% to above 90% and the recovery rate could reach to 96% or more in 8-12 d. The results also show that almost all the key functional genes involved in the geochemical cycling process, totally 4324 and 4983 functional microorganism genes, are detected in the liquid and ore surface, respectively. There are totally 712 and 831 functional genes involved in nitrogen cycling for liquid and ore surface samples, respectively. The relative abundance of functional genes involved in the phosphorus and sulfur cycling is higher in the ore surface than liquid. These results indicate that nitrogen, phosphorus and sulfur cycling are also present in the desiliconization process of rutile. Acetogenesis genes are detected in the liquid and ore surface, which indicates that the desiliconizing process mainly depends on the function of acetic acid and other organic acids. Four silicon transporting genes are also detected in the sample, which proves that the bacteria have the potential to transfer silicon in the molecule level. It is shown that bio-desilication is an effective and environmental-friendly way for enrichment of rough rutile concentrate and presents an overview of functional diversity and structure of desilication microbial communities, which also provides insights into our understanding of metabolic potential in biological desilication reactor ecosystems.

Green Value Chain： A Case Study in Turkey about the Relationships among Antecedents, Initiatives and Results of Green Value Chain Implementations

The present study was conducted to determine the green value chain implementations of large and medium size businesses and to investigate the relationships among antecedents, initiatives and results of green value chain implementations. The antecedents of green value chain implementations were considered from four dimensions namely regulations, public concerns, expected competitive advantage and top management commitment; green value chain initiatives were considered from three dimensions namely green primary activities, green internal support activities and green external support activities; the results of green value chain implementations were considered from two dimensions namely economic performance and socio-ecologic performance. A model was created according to the objectives of the study and hypotheses were formed. Multiple regression analyses were performed to investigate the relationships between the antecedents and initiatives of green value chain implementations. A relationship was not observed between green primary activities and economic and socio-ecologic performance. While a positive relationship was observed between green external support activities and economic performance, a positive relationship was observed between green internal support activities and both economic and socio-ecologic performance.

Current University Environmental Management Practices

Universities can be regarded as ＂small cities＂ because of their large size, population and the various complex activities taking place in campuses. Due to their inherent nature universities have a considerable impact on the environment. In this research a test was devised and completed for a sample of Australian universities to analyze the current environmental management practices of the universities over several key areas including： energy management, water management, waste management, transportation, biodiversity and sustainable development. It was discovered that in terms of environmental management universities are currently not performing at a level that is consistent with social and political expectations. In the assessment it was observed that universities have taken it upon themselves to improve to rectify this with many improvements to their current environmental management practices currently under development.

Performance Behaviour Analysis of the Present 3-Level Cache System for Multi-Core Processors

In this paper, a study related to the expected performance behaviour of present 3-level cache system for multi-core systems is presented. For this a queuing model for present 3-level cache system for multi-core processors is developed and its possible performance has been analyzed with the increase in number of cores. Various important performance parameters like access time and utilization of individual cache at different level and overall average access time of the cache system is determined. Results for up to 1024 cores have been reported in this paper.

Optimization of Grease Properties to Prolong the Life of Lubricating Greases

Grease life refers to the time it takes for the grease to lose its ability to keep the lubrication due to grease degradation. As grease life is generally shorter than fatigue life of bearing, the service life of grease-lubricated rolling bearings is often dominated by grease life. When designing a bearing systemolecular weightith grease lubrication, it is necessary to define the operating conditions limits of the bearing, for which grease life becomes a determining factor. Prolongation of grease life becomes an especially important challenge when the bearing is to be operated trader high-speed, high-temperature, and other severe conditions. Selecting a number of commercially sold greases composed of varying base oils, the author evaluated their properties and analyzed how each property affected the grease life by performing a multiple regression analysis. The optimum grease composition to best exploit each property was also examined. The results revealed among others that one would need to first determine the base oil type and then maximize ultimate bleeding while minimizing the evaporation rate.

Study On the Influencing Factors of Energy-Saving and Environmental Protection Industries in Shanghai

By using principal component analysis, this paper selected some appropriate influencing indicators, and constructed multiple linear regression models to predict the development of energy-saving environmental protection industry（ESEPl） in Shanghai. The Influencing Factors can be categorized into comprehensive economic factors and environmental factors, and GDP of the second industries and the total industries GDP in comprehensive economic factors have the strongest correlation, while in the environmental index factors, the total discharge of waste water has the strongest correlation. On the basis of influencing factors study, the regression model shows that by the end of 2020, the industry investment will reach 89.788 billion RMB, which proves that the development of ESEPI in Shanghai would grow continuously and dramatically.

A model for parameter estimation of multistage centrifugal compressor and compressor performance analysis using genetic algorithm

A model for performance prediction of multistage centrifugal compressor is proposed. The model allows the users to predict the compressor performance, e.g. pressure ratio, efficiency and losses using the compressor geometric information and speed by a stage stacking calculation based on the characteristics of each stage. To develop the compressor elemental stage charac- teristics, the compressor losses, such as incidence losses and friction losses, are mathematically modeled. For a composite sys- tems, for instance a gas turbine power plant, the performance of the multistage centrifugal compressor can be evaluated. Since some important parameters of the compressor model, e.g., the slip factor or, shock loss coefficient （and reference diameter DI, are hard to be determined by empirical laws, a genetic algorithm （GA） is used to solve the parameter estimation problem of the proposed model, and in turn the compressor performance analysis and parameters study are performed. The surge line for the multistage centrifugal compressor can also be determined from the simulation results. Furthermore, the model presented here provides a valuable tool for evaluating the multistage centrifugal compressor performance as a function of various operation parameters.

Improving performance portability for GPU-specific Open CL kernels on multi-core/many-core CPUs by analysis-based transformations

OpenCL is an open heterogeneous programming framework. Although OpenCL programs are func- tionally portable, they do not provide performance portability, so code transformation often plays an irreplaceable role. When adapting GPU-specific OpenCL kernels to run on multi-core/many-core CPUs, coarsening the thread granularity is necessary and thus has been extensively used. However, locality concerns exposed in GPU-specific OpenCL code are usually inherited without analysis, which may give side-effects on the CPU performance. Typi- cally, the use of OpenCL＇s local memory on multi-core/many-core CPUs may lead to an opposite performance effect, because local-memory arrays no longer match well with the hardware and the associated synchronizations are costly. To solve this dilemma, we actively analyze the memory access patterns using array-access descriptors derived from GPU-specific kernels, which can thus be adapted for CPUs by （1） removing all the unwanted local-memory arrays together with the obsolete barrier statements and （2） optimizing the coalesced kernel code with vectorization and locality re-exploitation. Moreover, we have developed an automated tool chain that makes this transformation of GPU-specific OpenCL kernels into a CPU-friendly form, which is accompanied with a scheduler that forms a new OpenCL runtime. Experiments show that the automated transformation can improve OpenCL kernel performance on a multi-core CPU by an average factor of 3.24. Satisfactory performance improvements axe also achieved on Intel＇s many-integrated-core coprocessor. The resultant performance on both architectures is better than or comparable with the corresponding OpenMP performance.

Generalized Multivariate Gumbel Distributions——Dependence,Aging Properties and Applications

This paper introduces a generalized multivariate Gumbel(GMG) distribution using a survival copula.Various dependence properties of the GMG distribution and some analytical properties of the generators of the GMG distribution are studied.Furthermore,the authors also investigate the dependence behavior of the residual lifetime vector of the GMG distribution.As an illustration,the GMG distribution is applied to fit a real data set.