Attrition Bias in Economic Relationships Estimated with Matched CPS Files

Short panel data sets constructed by matching individuals across monthly files of the Current Population Survey (CPS) have been used to study a wide range of questions in labor economics. Such panels offer unique advantages. But because the CPS makes no effort to follow movers, these panels exhibit significant attrition, which may lead to bias in longitudinal estimates using matched CPS files. Because the Survey of Income and Program Participation (SIPP) uses essentially the same sampling frame and design as the CPS, but makes substantial efforts to follow individuals that move, we use the SIPP to construct 'data-based' rather than 'model-based' corrections for bias from selective attrition. The approach is applied to a couple of standard economic relationships that have been studied with the CPS specifically union wage differentials and the male marriage wage premium. The results for the longitudinal analysis of union wage effects reveal negligible and statistically insignificant evidence of attrition bias. In contrast, the longitudinal analysis of the marriage premium for males finds statistically significant evidence of attrition bias, although the amount of bias does not seem to be serious in an economic sense. We regard the evidence as suggesting that in many applications the advantages of using matched CPS panels to obtain longitudinal estimates are likely to far outweigh the disadvantages from attrition biases, although we should allow for the possibility that attrition bias leads the longitudinal estimates to be understated.

A model-driven engineering process for autonomic sensor-actuator networks

Cyber-Physical Systems (CPS) are the next generation of embedded ICT systems designed to be aware of the physical environment by using sensor-actuator networks to provide users with a wide range of smart applications and services. Many of these smart applications are possible due to the incorporation of autonomic control loops that implement advanced processing and analysis of historical and real-time data measured by sensors; plan actions according to a set of goals or policies; and execute plans through actuators. The complexity of this kind of systems requires mechanisms that can assist the system?s design and development. This paper presents a solution for assisting the design and development of CPS based on Model-Driven Development: MindCPS (doMaIN moDel for CPS) solution. MindCPS solution is based on a model that provides modelling primitives for explicitly specifying the autonomic behaviour of CPS and model transformations for automatically generating part of the CPS code. In addition to the automatic code generation, the MindCPS solution offers the possibility of rapidly configuring and developing the core behaviour of a CPS, even for nonsoftware engineers. The MindCPS solution has been put into practice to deploy a smart metering system in a demonstrator located at the Technical University of Madrid

AngelCast: cloud-based peer-assisted live streaming using optimized multi-tree construction

Increasingly, commercial content providers (CPs) offer streaming solutions using peer-to-peer (P2P) architectures, which promises significant scalabil- ity by leveraging clients’ upstream capacity. A major limitation of P2P live streaming is that playout rates are constrained by clients’ upstream capac- ities – typically much lower than downstream capacities – which limit the quality of the delivered stream. To leverage P2P architectures without sacri- ficing quality, CPs must commit additional resources to complement clients’ resources. In this work, we propose a cloud-based service AngelCast that enables CPs to complement P2P streaming. By subscribing to AngelCast, a CP is able to deploy extra resources (angel), on-demand from the cloud, to maintain a desirable stream quality. Angels do not download the whole stream, nor are they in possession of it. Rather, angels only relay the minimal fraction of the stream necessary to achieve the desired quality. We provide a lower bound on the minimum angel capacity needed to maintain a desired client bit-rate, and develop a fluid model construction to achieve it. Realizing the limitations of the fluid model construction, we design a practical multi- tree construction that captures the spirit of the optimal construction, and avoids its limitations. We present a prototype implementation of AngelCast, along with experimental results confirming the feasibility of our service.Supported in part by NSF awards #0720604, #0735974, #0820138, #0952145, #1012798 #1012798 #1430145 #1414119. (0720604 - NSF; 0735974 - NSF; 0820138 - NSF; 0952145 - NSF; 1012798 - NSF; 1430145 - NSF; 1414119 - NSF

On-board processing for future satellite communications systems: Satellite-Routed FDMA

A frequency division multiple access (FDMA) 30/20 GHz satellite communications architecture without on-board baseband processing is investigated. Conceptual system designs are suggested for domestic traffic models totaling 4 Gb/s of customer premises service (CPS) traffic and 6 Gb/s of trunking traffic. Emphasis is given to the CPS portion of the system which includes thousands of earth terminals with digital traffic ranging from a single 64 kb/s voice channel to hundreds of channels of voice, data, and video with an aggregate data rate of 33 Mb/s. A unique regional design concept that effectively smooths the non-uniform traffic distribution and greatly simplifies the satellite design is employed. The satellite antenna system forms thirty-two 0.33 deg beam on both the uplinks and the downlinks in one design. In another design matched to a traffic model with more dispersed users, there are twenty-four 0.33 deg beams and twenty-one 0.7 deg beams. Detailed system design techniques show that a single satellite producing approximately 5 kW of dc power is capable of handling at least 75% of the postulated traffic. A detailed cost model of the ground segment and estimated system costs based on current information from manufacturers are presented

A Model-Based Approach to Security Analysis for Cyber-Physical Systems

Evaluating the security of cyber-physical systems throughout their life cycle is necessary to assure that they can be deployed and operated in safety-critical applications, such as infrastructure, military, and transportation. Most safety and security decisions that can have major effects on mitigation strategy options after deployment are made early in the system's life cycle. To allow for a vulnerability analysis before deployment, a sufficient well-formed model has to be constructed. To construct such a model we produce a taxonomy of attributes; that is, a generalized schema for system attributes. This schema captures the necessary specificity that characterizes a possible real system and can also map to the attack vector space associated with the model's attributes. In this way, we can match possible attack vectors and provide architectural mitigation at the design phase. We present a model of a flight control system encoded in the Systems Modeling Language, commonly known as SysML, but also show agnosticism with respect to the modeling language or tool used.Comment: 8 pages, 5 figures, conferenc

An Evaluation of Design-based Properties of Different Composite Estimators

For the last several decades, the US Census Bureau has been using the AK composite estimation method to produce statistics on employment from the Current Population Survey (CPS) data. The CPS uses a rotating design and AK estimators are linear combinations of monthly survey weighted averages (called month-in-sample estimates) in each rotation groups. Denoting by $X$ the vector of month-in-sample estimates and by $\Sigma$ its design based variance, the coefficients of the linear combination were optimized by the Census Bureau after substituting $\Sigma$ by an estimate and under unrealistic stationarity assumptions. To show the limits of this approach, we compared the AK estimator with different competitors using three different synthetic populations that mimics the Current Population Survey (CPS) data and a simplified sample design that mimics the CPS design. In our simulation setup, empirically best estimators have larger mean square error than simple averages. In the real data analysis, the AK estimates are constantly below the survey-weighted estimates, indicating potential bias. Any attempt to improve on the estimated optimal estimator in either class would require a thorough investigation of the highly non-trivial problem of estimation of $\Sigma$ for a complex setting like the CPS (we did not entertain this problem in this paper). A different approach is to use a variant of the regression composite estimator used by Statistics Canada. The regression composite estimator does not require estimation of $\Sigma$ and is less sensitive to the rotation group bias in our simulations. Our study demonstrates that there is a great potential for improving the estimation of levels and month to month changes in the unemployment rates by using the regression composite estimator