A Bayesian propensity score adjustment for latent variable modeling and MCMC algorithm

The estimation of the differences among groups in observational studies is frequently inaccurate owing to a bias caused by differences in the distributions of covariates. In order to estimate the average treatment effects when the treatment variable is binary, Rosenbaum and Rubin [1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41-55] proposed an adjustment method for pre-treatment variables using propensity scores. Imbens [2000. The role of the propensity score in estimating dose-response functions. Biometrika 87, 706-710] extended the propensity score methodology for estimation of average treatment effects with multivalued treatments.However, these studies focused only on estimating the marginal mean structure. In many substantive sciences such as the biological and social sciences, a general estimation method is required to deal with more complex analyses other than regression, such as testing group differences on latent variables. For latent variable models, the EM algorithm or the traditional Monte Carlo methods are necessary. However, in propensity score adjustment, these methods cannot be used because the full distribution is not specified.In this paper, we propose a quasi-Bayesian estimation method for general parametric models that integrate out the distributions of covariates using propensity scores. Although the proposed Bayes estimates are shown to be consistent, they can be calculated by existing Markov chain Monte Carlo methods such as Gibbs sampler. The proposed method is useful to estimate parameters in latent variable models, while the previous methods were unable to provide valid estimates for complex models such as latent variable models.We also illustrated the procedure using the data obtained from the US National Longitudinal Survey of Children and Youth (NLSY1979-2002) for estimating the effect of maternal smoking during pregnancy on the development of the child's cognitive functioning.     

动态汽车衡测量结果的不确定度评定

本文主要介绍了在动态汽车衡的试验过程中不确定度来源,并以动态试验为例重点介绍了计算各分量的标准不确定度、合成标准不确定度以及扩展不确定度的方法.     

Dynamic modes of Ti combustion in a coflow of N<Subscript>2</Subscript>-Ar mixture

Combustion of bulk density Ti powder (containing 20 wt % TiN as a diluent) in a coflow of N₂-Ar mixture was investigated upon variation in the nitrogen content of the gaseous mixture. The obtained data are believed to open up new horizons for fabrication of layered and composite ceramics by infiltration-mediated combustion.      

Age of acquisition: Its neural and computational mechanisms.

The acquisition of new skills over a life span is a remarkable human ability. This ability, however, is constrained by age of acquisition (AoA); that is, the age at which learning occurs significantly affects the outcome. This is most clearly reflected in domains such as language, music, and athletics. This article provides a perspective on the neural and computational mechanisms underlying AoA in language acquisition. The authors show how AoA modulates both monolingual lexical processing and bilingual language acquisition. They consider the conditions under which syntactic processing and semantic processing may be differentially sensitive to AoA effects in second-language acquisition. The authors conclude that AoA effects are pervasive and that the neural and computational mechanisms underlying learning and sensorimotor integration provide a general account of these effects. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Measuring consistency in TTL-based caches

We propose a general modeling framework to evaluate the performance of cache consistency algorithms. In addition to the usual hit rate, we introduce the hit^* rate as a consistency measure, which captures the fraction of non-stale downloads from the cache. We apply these ideas to the analysis of the fixed TTL consistency algorithm in the presence of network delays. The hit and hit^* rates are evaluated when requests and updates are modeled by renewal processes. Classical results on the renewal function lead to various bounds.     

Performance modeling and evaluation of data/voice services in wireless networks

Application-level performance is a key to the adoption and success of the CDMA 2000. To predict this performance in advance, a detailed end-to-end simulation model of a CDMA network is built to include application traffic characteristics, network architecture, network element details using the proposed simulation methodology. We assess the user-perceived application performance when a RAN and a CN adopt different transport architectures such as ATM and IP. To evaluate the user-perceived quality of voice service, we compare the end-to-end packet delay for different vocoder schemes such as G.711, G.726 (PCM), G.726 (ADPCM), and vocoder bypass scheme. By the simulation results, the vocoder bypass scenario shows 30% performance improvement over the others. We also compare the quality of voice service with and without DPS scheduling scheme. We know that DPS scheme keep the voice delay bound even if the service traffic is high. For data packet performance, HTTP v.1.1 shows better performance than that of HTTP v.1.0 due to the pipelining and TCP persistent connection. We may conclude that IP transport technology is better solution for higher FER environment since the packet overhead of IP is smaller than that of ATM for web browsing data traffic, while it shows opposite effect to the small size voice packet in RAN architecture. We show that the 3G-1X EV-DO system gives much better packet delay performance than 3G-1X RTT. The main conclusion is that end-to-end application-level performance is affected by various elements and layers of the network and thus it must be considered in all phases of the development process. Jae-Hyun Kim He received the B.S., M.S., and Ph.D. degrees, all in computer science and engineering, from Hanyang University, Ansan, Korea, in 1991, 1993, and 1996 respectively. In 1996, he was with the Communication Research Laboratory, Tokyo, Japan, as a Visiting Scholar. From April 1997 to October 1998, he was a post-doctoral fellow at the department of electrical engineering, University of California, Los Angeles. From November 1998 to February 2003, he worked as a member of technical staff in Performance Modeling and QoS management department, Bell laboratories, Lucent Technologies, Holmdel, NJ. He has been with the department of electrical engineering, Ajou University, Suwon, Korea, as an assistant professor since 2003. His research interests include QoS issues and cross layer optimization for high-speed wireless communication. Dr. Kim was the recipient of the LGIC Thesis Prize and Samsung Human-Tech Thesis Prize in 1993 and 1997, respectively. He is a member of the Korean Institute of Communication Sciences (KICS), Korea Institute of Telematics and Electronis (KITE), Korea Information Science Society (KISS), and IEEE. Hyun-Jin Lee received the B.S. degree in electrical engineering from Ajou University, Suwon, Korea, in 2004, and is working toward the M.S. degree and Ph. D. degree in electrical engineering at Ajou University. He has been awarded Samsung Human-Tech Thesis Prize in 2004. His research interests QoS, especially network optimization and wireless packet scheduling. He is a member of the KICS. Sung-Min Oh received the B.S. and M. S. degrees in electrical engineering form Ajou University, Suwon, Korea, in 2004, and is working toward the Ph. D. degree in electrical engineering at Ajou University. His research interests QoS performance analysis and 4G network. He is a member of the KICS. Sung-Hyun Cho received his B.S., M.S., and Ph.D. in computer science and engineering from Hanyang University, Korea, in 1995, 1997, and 2001, respectively. From 2001 to 2005, he has been with Samsung Advanced Institute of Technology, where he has been engaged in the design and standardization of MAC and upper layers of B3G, IEEE 802.16e, and WiBro systems. He is currently a MAC part leader in the telecommunication R&D center of Samsung Electronics. His research interests include 4G air interface design, radio resource management, cross layer design, and handoff in wireless systems.     

Logistic Regression Analysis of Customer Satisfaction Data

Variation exists in all processes. Significant work has been done to identify and remove sources of variation in manufacturing processes resulting in large returns for companies. However, business process optimization is an area that has a large potential return for a company. Business processes can be difficult to optimize due to the nature of the output variables associated with them. Business processes tend to have output variables that are binary, nominal or ordinal. Examples of these types of output include whether a particular event occurred, a customer's color preference for a new product and survey questions that assess the extent of the survey respondent's agreement with a particular statement. Output variables that are binary, nominal or ordinal cannot be modeled using ordinary least‐squares regression. Logistic regression is a method used to model data where the output is binary, nominal or ordinal. This article provides a review of logistic regression and demonstrates its use in modeling data from a business process involving customer feedback. Copyright © 2006 John Wiley & Sons, Ltd.     

A framework to integrate software behavior into dynamic probabilistic risk assessment

Software plays an increasingly important role in modern safety-critical systems. Although, research has been done to integrate software into the classical probabilistic risk assessment (PRA) framework, current PRA practice overwhelmingly neglects the contribution of software to system risk. Dynamic probabilistic risk assessment (DPRA) is considered to be the next generation of PRA techniques. DPRA is a set of methods and techniques in which simulation models that represent the behavior of the elements of a system are exercised in order to identify risks and vulnerabilities of the system. The fact remains, however, that modeling software for use in the DPRA framework is also quite complex and very little has been done to address the question directly and comprehensively. This paper develops a methodology to integrate software contributions in the DPRA environment. The framework includes a software representation, and an approach to incorporate the software representation into the DPRA environment SimPRA. The software representation is based on multi-level objects and the paper also proposes a framework to simulate the multi-level objects in the simulation-based DPRA environment. This is a new methodology to address the state explosion problem in the DPRA environment. This study is the first systematic effort to integrate software risk contributions into DPRA environments.     

Automating application software generation

Many approaches have been proposed to enhance software productivity and reliability. These approaches typically fall into three categories: the engineering approach, the formal approach and the knowledge-based approach. But the optimal gain in software productivity cannot be obtained if one relies on only one of these approaches. This paper describes the work in knowledge-based software engineering conducted by the authors for the past 10 years. The final goal of the research is to develop a paradigm for software engineering which integrates the three approaches mentioned above. A knowledge-based tool which can support the whole process of software development is provided in this paper.     

Education-driven research in CAD

We argue for a new research category, named education-driven research (EDR), which fills the gap between traditional field-specific research that is not concerned with educational objectives and research in education that focuses on fundamental teaching and learning principles and possibly on their customization to broad areas (such as mathematics or physics), but not to specific disciplines (such as CAD). The objective of EDR is to simplify the formulation of the underlying theoretical foundations and of specific tools and solutions in a specialized domain, so as to make them easy to understand and internalize. As such, EDR is a difficult and genuine research activity, which requires a deep understanding of the specific field and can rarely be carried out by generalists with primary expertise in broad education principles. We illustrate the concept of EDR with three examples in CAD: (1) the Split and Tweak subdivisions of a polygon and its use for generating curves, surfaces, and animations; (2) the construction of a topological partition of a plane induced by an arbitrary arrangement of edges; and (3) a romantic definition of the minimal and Hausdorff distances. These examples demonstrate the value of using analogies, of introducing evocative terminology, and of synthesizing the simplest fundamental building blocks. The intuitive understanding provided by EDR enables the students (and even the instructor) to better appreciate the limitations of a particular solution and to explore alternatives. In particular, in these examples, EDR has allowed the author to: (1) reduce the cost of evaluating a cubic B-spline curve; (2) develop a new subdivision curve that is better approximated by its control polygon than either a cubic B-spline or an interpolating 4-point subdivision curve; (3) discover how a circuit inclusion tree may be used for identifying the faces in an arrangement; and (4) rectify a common misconception about the computation of the Hausdorff error between triangle meshes. We invite the scientific community to encourage the development of EDR by publishing its results as genuine research contributions in peer-reviewed professional journals.