基于USB2.0的红外图像数据采集系统

随着红外遥感技术的飞速发展,红外图像数据的实时采集和传输已成为必须研究的课题。基于USB20的图像数据采集系统的设计提出了2个方面的要求一方面,要求接口简单灵活且有较高的数据传输率;另一方面,由于数据量通常都较大,要求主机能够对实时数据作出快速响应,并及时进行分析和处理。在USB2.0协议中,数据传输速率可达到480Mbit/s,且传输稳定,能够满足图像数据的实时传输要求。本文提出了应用USB2.0作为红外图像采集的通讯接口,实现快速、实时的红外图像采集传输。     

面向用户的数据结构及数据访问技术

数据库是实现信息处理技术的基础,构建统一数据格式的输入输出接口,设计风格统一的数据访问界面是设计信息处理软件系统的关键。基于上述观点,笔者以实例论述了基于用户的数据结构组织及数据访问技术,总结了实现信息处理系统的行之有效的技术路线。     

Size,efficiency, and fortune nagazine

Are corporate size and efficiency positively related? New data from FORTUNE, permitting a broad definition of “efficiency,” are applied to a test of this question. The efficiency data for 200 firms reflect corporate rankings on such attributes as quality of management, quality of products or services, innovativeness, and financial soundness. Sales and assets serve as measures of size. According to these data, size and efficiency are not, in general, positively related, at least not with statistical significance.     

Industry characteristics influencing the technical output: A case of small and medium size firms in the US

Using the small and medium size firms in the US as a sample, this paper reports on interrelationship among patents, publications and new products. Correlates of R&D expenditure, patents and papers and new products are presented. Relationships between firm size and R&D output and productivity are also investigated.
Since the study is based on correlational analysis, causal inferences are not drawn. The data indicates that the three indicators are related, but their strength of relationship varies with industries. Growth of sales is related with new products, but not with patents or papers.
Although the data point to the fact that small firms are more productive than their larger counterparts, there are many reasons to come to such a sweeping generalisation. Reporting of R&D data is not reliable for small firms as the very definition of R&D differs from firm to firm. Nature of R&D also changes as the firm grows in size; opportunities for patents or new products also change accordingly. These make it difficult to accurately measure and compare the R&D efficiency across firms of different sizes.     

创新工程数据和知识管理 提升油企增值管理水平

从跨国油企日常工作中面临所需大量工程数据和资料难以按需获取和按时获取的诉求出发,分析了导致工程数据沉寂的体制、机制、企业文化、管理模式、工作方式、保密理念等方面的原因,就如何克服工程数据需求和数据沉寂的瓶颈性矛盾,提出了必须从创新工程数据管理着手来全面实施知识管理工程。指出,工程数据共享是知识管理的基础,对创新工程数据管理提出了要解放思想,打破数据壁垒;实行数据与档案的剥离,统一数据结构,充实完善各类数据库;保密关口前移,变人保为技保;优化资源配置,创新打造数据管理和知识管理中心等建议。     

A paradigm for examining second-order factor models employing structural equation modeling

We present here a paradigm for assessing second-order measurement models. Our approach is hierarchical in nature. We discuss the need for higher-order models from a conceptual perspective and illustrate how some common challenges in empirical research can be resolved through the deployment of higher-order modeling. Essentially, we argue that many constructs can be meaningfully described by a higher-order structure and testing for the existence of such structures requires a careful examination of alternative models. There is a need for conceptual as well as empirical support. In order to demonstrate our paradigm, we use data that relate to airline service quality. Our sample includes two databases. Responses from 170 individuals are employed for exploratory purposes and responses from 437 individuals are used for subsequent data analyses.     

A bootstrapped robust data envelopment analysis model for efficiency estimating of telecommunication companies in Iran

One of the primary concerns in measuring the relative efficiency of a telecommunication unit compared with other similar units is the uncertainty on input/output data. In this paper, a bootstrapped robust data envelopment analysis (BRDEA) model is proposed to measure the efficiency of telecommunication companies. The proposed method is capable of handling different issues such as the uncertainty in data or sampling errors. The model is examined using some real data from a telecommunication company. First, the data from 24 telecommunication companies are assumed with uncertainty and the efficiency of telecommunication companies are estimated using a robust DEA model. Then, the results of the efficiencies are corrected by a bootstrapping technique. The results indicate that the BRDEA method considers the perturbation in data and sampling error with an adaptation of bootstrapped robust data envelopment analysis and could be more reliable for efficiency estimating strategies.     

The impact of survey characteristics on the measurement of food consumption

Survey characteristics affect the quality of the measurement of food consumption within households; thus, it is important to identify best practices for designing surveys that collect food data. This paper analyses the impact of survey characteristics on the measurement of food consumption from a sample of 81 national surveys. Results highlight regularities that can inform best practices in designing surveys and promoting the use of the data for multiple purposes. Surveys focused on food acquisition collect higher food quantities compared to those that target food consumption. Surveys based on recall interviews collect higher food quantities compared to those based on diaries, but the difference decreases with long reference periods. The use of standard units of measurement as well as the consideration of partakers in meals and of seasonality generates significant differences in the survey results. The impact of the different survey characteristics carries substantive implications when food consumption data are employed for assessing food security conditions. The results are part of a wider work program aimed at improving the quality of household survey data. More evidence is needed, ideally through coordinated sets of analyses and experiments in different contexts. Additionally, survey characteristics must be complemented by effective field work in order to generate high quality data. Towards this end, statistical capacity development is crucial to promote better data and more evidence-based decision making.     

Diversification,vertical integration,and industry analysis: New perspectives and measurement

Vertical integration, diversification, and industry analysis are fundamental topics in strategic management content research. We develop the conceptualization of these issues by exploring their nature as well as their correct measurement. Toward these ends, we conduct an extensive analysis of the COMPUSTAT II data base and the TRINET data base in all three research contexts. In addition to these two data bases, we also evaluate the Census of Manufacturers, S&P's Financial Dynamics, S&P's Industry Surveys and Dun and Bradstreet's Industry Norms and Key Business Ratios, for purposes of industry analysis. Important contributions include our identification of the potential of COMPUSTAT 11 data to distinguish within-stage forward and backward vertical integration, and between-stage forward and backward vertical integration, as well as our recommendations for the protection of the integrity of studies based on the COMPUSTA T II and TRINET data bases.     

User participation and management information system use: A path analysis

This article proposes and empirically tests a causal model of user participation and management information system use. Based on a review of available literature, three variables including user understanding, system quality and user acceptance are identified as intervening in the relationship between user participation and system use. Causal orders among these variables are assumed and a causal model is constructed for empirical testing. Task complexity is introduced as a contingent variable affecting the structure of these causal relationships. The data are collected from 134 users of 77 different information systems in 32 Korean business firms. The results of data analysis support the causal model in general, but suggest that causal relationships among the variables are different according to task complexity. Two separate models of user participation and management information system use, based on the empirical results, are presented for further research, one for more complex and the other for less complex systems.     

An Empirical Comparison of Sales Forecasting Models

There has been a veritable industry of forecasting models in recent decades, spurred partly by planners' search for certainty and partly by the data crunching capabilities of computers. In this article, Sanjay-kumar Rao tests two families of models on some common data sets to see how they compare. He examines how well the models fit the data and how reliable they are as forecasting tools.     

On the Nature of Self‐Assessed House Prices

In models of optimal household behavior, the value of housing affects consumption, savings and other variables. But homeowners do not know the value of their house for certain until they sell, so while they live in their home they must rely on local house price data to estimate its value. This article uses data from the recent housing boom and bust to demonstrate that changes in households' self‐assessed home values are strongly consistent with the predictions of a model in which households optimally filter available house price data. Specifically, we show that self‐assessed house prices did not increase as rapidly as house price indexes during the boom and did not decline as severely during the bust. A Kalman filter model nearly perfectly replicates these data. These findings have direct implications for economists studying asking prices during booms and busts, optimal default decisions and other key housing‐related phenomena.     

Modeling the mashup ecosystem: structure and growth

Mashups combine data and services provided by third parties through open APIs (such as Google Maps and Flickr), as well as internal data sources owned by users. The creation of mashups is supported by a complex ecosystem of interconnected data providers, mashup platforms, and users. In this paper, we examine the structure of the mashup ecosystem and its growth over time. Several observations follow from our analysis. First, we can conclude that while the number of new APIs and mashups over time follows a linear growth pattern, the distribution of mashups over APIs is not uniform but follows a power law. This implies that a small number of APIs provides the basis for the majority of mashups, and the other APIs are only used in certain application niches. Second, our analysis suggests that mashup platforms were introduced in response to the increasing complexity of mashups, as mashups evolved from one‐feature mashups (widgets). Third, we observe that complementary relationships between open APIs are formed based on the position of the APIs in the ecosystem. The propensity of two APIs to be used together in the same mashup depends on the existing number of mashups to which they both contribute. The growth of the mashup ecosystem follows a pattern where keystone data providers or ‘powerful hubs’ attract niche data providers as complementors, and the positions of keystones in the ecosystem are mutually reinforcing.     

第三代移动通信3GPP规范中的HSDPA技术

高速下行分组接入HSDPA(HighSpeedDownlinkPackageAccess)是第三代移动通信后继发展中非常重要的增强技术。HSDPA以5MHz的带宽向WCDMA的下行提供高达10～14Mbps的分组数据,用以实现多用户高速下行数据以及流媒体业务。本文通过研究高速下行分组技术的发展现状及在发展过程中遇到的问题,分析了影响该项技术发展的几个重要因素,并对这些问题提出了笔者的观点。     

Learning from Postproject Reviews: A Cross‐Case Analysis*

Every new product development (NPD) project should not only deliver a successful new product but also should generate learning for the organization. Postproject reviews (PPRs) are recognized by both practitioners and academics as an appropriate mechanism to stimulate and capture learning in NPD teams. However, relatively few companies use PPRs, and those that do use them often fail to do so effectively. Although they are widely perceived to be a useful tool, empirical research on how PPRs are typically organized and the learning that results is limited. The present article addresses this gap in the extant knowledge and describes five in‐depth case studies, which were conducted at leading companies in Germany. A detailed investigation was made of how PPRs are conducted and of the type of learning that can result. Three main sources of data were used for each case: company documentation, in‐depth interviews with managers responsible for NPD, and observation of an actual PPR. The different data sources enabled extensive triangulation of data to be conducted and a high degree of reliability and validity to be achieved. The analysis enabled a number of key characteristics of the way PPRs are managed to be identified. Various characteristics of PPRs influence their utility, such as the time at which they take place and the way discussions are moderated. In addition, the data show that participants in the discussions at PPRs often use metaphors and stories, which indicates that PPRs have the potential to generate tacit knowledge. Interestingly, the data also show that there are various different ways in which metaphors and stories appear to stimulate discussions on NPD projects. Based on the cross‐case analysis, a wide range of implications are identified. Researchers need to investigate PPRs further to identify how they can generate tacit and explicit knowledge and support project‐to‐project learning. The generation of tacit knowledge in NPD is a topic that particularly needs further investigation. The research also led to a range of recommendations for practitioners. Companies need to strongly communicate the purpose and value of PPRs, to run them effectively to stimulate the maximum possible learning, and to disseminate the findings widely. PPRs have the potential to create and transfer knowledge amongst NPD professionals, but, as they are seldom currently used, many companies are missing an important opportunity.     

Comparing U.S. and Japanese corporate-level operating performance using financial statement data

This study uses financial statement data restated to a similar reporting basis to compare the operating performance of U.S. and Japanese companies, identifying possible strategic and environmental explanations for the differences observed. Comparisons are made for U.S. and Japanese samples as a whole, for groups of Japanese firms (keiretsu v. nonkeiretsu), and for 11 industries. The results show that neither country appears to generate systematically higher profit margins, but that U.S. firms turnover assets other than inventory more quickly and therefore have higher rates of return on assets. More intensive examination of these results suggests that environmental factors, such as cultural or structural differences, are the primary causes of the observed differences in the data analyzed.     

Chart Turnover and Sales in the Recorded Music Industry: 1990–2005

Chart turnover and sales in the recorded music industry are examined before and during the growth of the Internet as a music source. Chart turnover is measured as the monthly turnover in Billboard’s Top 200 albums chart. Monthly data on expenditures and price indices for music and related goods, as well as demographic and income data, are used in a multivariate structural time series analysis that allows the capture of an unobserved component. We find that turnover positively affects sales, but also that sales are affected positively by an unobserved component that declines in magnitude after 2000.