过程分析仪表

当需要监视一个不属于"四大类(压力、流量.温度、液位)"的过程变量时,可以通过一些过程分析仪表完成。这类仪表同样也有自己的"四大类":成分-探测计量过程流体中的某种化学成分;电化学-测量某种离子浓度,大多数是氢(pH);分光光度法-利用光的吸收特性测量某种成分。物理特性-测量重力、密度、粘度等物     

Physics-Informed Multistage Machine Learning Strategy for the Nanomachining-Induced Plastic Deformation Behavior

The evolution of the dislocation density induced by the nanomachining process dominates the plastic deformation behaviors of materials, thus affecting the mechanical properties significantly. However, a challenging topic related to how to establish an accurate model for predicting the dislocation density based on the limited simulations and experiments arises due to the complicated thermal–mechanical coupling mechanism during the machining process. Herein, a multistage method integrating machine learning, physics, and high-throughput atomic simulation is proposed to investigate the effect of cutting speed on the dislocation behavior in polycrystal copper. Compared with the traditional one-step machine learning method, the constraint of physical features effectively improves the accuracy and generalization ability of the model. The results indicate that the dislocation behaviors depend on the competition between the cutting force and temperature. In the low-cutting speed, the predominated role of the cutting temperature leads to a rapid decline of the dislocation density. In contrast, the dislocation density tends to be stable under a high-speed cutting process due to the dynamic balance between the effects of the cutting force and temperature. Notably, the proposed strategy provides a new and universal framework to design the machining parameters to obtain high-quality products.     

Regional patterns of affirmative action compliance costs

In this paper we estimate the amount by which firms' labor costs are increased by compliance with affirmative action regulations imposed on federal contractors for 160 SMSAs in 1980. The paper focuses on determining the cause(s) for variation in these compliance costs across SMSAs and in identifying areas of high and low compliance cost. We find that compliance costs are lower in larger SMSAs, more rapidly growing SMSAs, and SMSAs that have relatively large proportions of minorities and females in the labor market.The authors would like to thank Fred Wildes and Long Gen Ying, both of San Diego State University, for their assistance on this project. In addition, support for Prof. Getis' work was provided by the National Science Foundation, Grant No. SES-9123832.This paper was presented at the annual conference of the Western Regional Science Association in Tucson, Arizona.     

Fuzzy grey relational analysis for software effort estimation

Accurate and credible software effort estimation is a challenge for academic research and software industry. From many software effort estimation models in existence, Estimation by Analogy (EA) is still one of the preferred techniques by software engineering practitioners because it mimics the human problem solving approach. Accuracy of such a model depends on the characteristics of the dataset, which is subject to considerable uncertainty. The inherent uncertainty in software attribute measurement has significant impact on estimation accuracy because these attributes are measured based on human judgment and are often vague and imprecise. To overcome this challenge we propose a new formal EA model based on the integration of Fuzzy set theory with Grey Relational Analysis (GRA). Fuzzy set theory is employed to reduce uncertainty in distance measure between two tuples at the k ^th continuous feature ( | ( x_o(k) - x_i(k) | ) \left( {\left| {\left( {{x_o}(k) - {x_i}(k)} \right.} \right|} \right) .GRA is a problem solving method that is used to assess the similarity between two tuples with M features. Since some of these features are not necessary to be continuous and may have nominal and ordinal scale type, aggregating different forms of similarity measures will increase uncertainty in the similarity degree. Thus the GRA is mainly used to reduce uncertainty in the distance measure between two software projects for both continuous and categorical features. Both techniques are suitable when relationship between effort and other effort drivers is complex. Experimental results showed that using integration of GRA with FL produced credible estimates when compared with the results obtained using Case-Based Reasoning, Multiple Linear Regression and Artificial Neural Networks methods.     

Parameter sensitivity study of the Nelder-Mead Simplex Method

This paper presents a parameter sensitivity study of the Nelder-Mead Simplex Method for unconstrained optimization. Nelder-Mead Simplex Method is very easy to implement in practice, because it does not require gradient computation; however, it is very sensitive to the choice of initial points selected. Fan-Zahara conducted a sensitivity study using a select set of test cases and suggested the best values for the parameters based on the highest percentage rate of successful minimization. Begambre-Laier used a strategy to control the Particle Swarm Optimization parameters based on the Nelder Mead Simplex Method in identifying structural damage. The main purpose of the paper is to extend their parameter sensitivity study to better understand the parameter’s behavior. The comprehensive parameter sensitivity study was conducted on seven test functions: B2, Beale, Booth, Wood, Rastrigin, Rosenbrock and Sphere Functions to search for common patterns and relationships each parameter has in producing the optimum solution. The results show important relations of the Nelder-Mead Simplex parameters: reflection, expansion, contraction, and Simplex size and how they impact the optimum solutions. This study is crucial, because better understanding of the parameters behavior can motivate current and future research using Nelder-Mead Simplex in creating an intelligent algorithm, which can be more effective, efficient, and save computational time.     

Psychosocial causes and consequences of pathological gaming

Pathological use of computer and video games has been associated with indicators of psychosocial well-being, such as loneliness, low self-esteem, low social competence, and low life satisfaction. However, few studies have decisively demonstrated whether these indicators of psychosocial well-being are causes or consequences of pathological gaming. To address this gap in the literature, we conducted a two-wave panel study among 851 Dutch adolescents (543 gamers). Causal relations were analyzed using autoregressive structural equation models. These analyses indicated that social competence, self-esteem, and loneliness were significant predictors of pathological gaming six months later. Thus, lower psychosocial well-being can be considered an antecedent of pathological gaming among adolescent gamers. Our analyses further indicated that loneliness was also a consequence of pathological gaming. This suggests that displacement of real-world social interaction resulting from pathological use of video games may deteriorate existing relationships, which could explain the increase in adolescent gamers’ feelings of loneliness.     

Variations and Commonalities in Processes of Collaboration: The Need for Multi-Site Workplace Studies

Workplace studies have made a major contribution to the field of CSCW, drawing attention to subtle practices that enable effective collaboration. However, workplace studies typically focus on a single setting, making it difficult to assess the generalisability of the findings. Through a multi-site workplace study, we explore a specific collaborative process, that of the handover which occurs when a patient is transferred from one hospital or ward to another. The study demonstrates that the term ??handover?? captures a variety of collaborative practices that vary in both their form and content, reflecting aspects of the setting in which they occur. Multi-site workplace studies are shown to be essential for CSCW, not only generating findings that have relevance beyond a single setting but also focusing attention on aspects of work practice that may otherwise go unnoticed.     

Coherency Hub Design for Multisocket Sun Servers with CoolThreads Technology

CoHub, a coherency hub ASIC, provides a cost-effective way to extend a glueless two-node chip-multithreading system to a four-node system without changes to the processor. The four-node, 256-thread system achieves near-linear scaling of performance with thread count on transaction-processing workloads. Time-to-market pressure, 800-MHz operation, and a six-stage pipeline were among the constraints that shaped CoHub's design.     

Efficient model checking for LTL with partial order snapshots

Certain behavioral properties of distributed systems are difficult to express in interleaving semantics, whereas they are naturally expressed in terms of partial orders of events or, equivalently, Mazurkiewicz traces. Two examples of such properties are serializability of a database and global snapshots of concurrent systems. Recently, a modest extension for LTL by an operator that expresses snapshots, has been proposed. It combines the ease of linear (interleaving) specification with this useful partial order concept. The new construct allows one to assert that a global snapshot appeared in the past, perhaps not in the observed execution sequence, but possibly in an equivalent one.