The purpose of this study was to examine the degree of correlation between the Scantron Achievement Series (SAS) benchmark assessment in reading and the Tennessee Comprehensive Assessment Program (TCAP) test in reading in fourth grade students. The goal was to identify the predictive validity of the SAS benchmark instrument. The study included fourth grade students who had taken the SAS and TCAP reading sections during the school years of 2011- 2013. The study was quantitative. Data were collected from a school system in northeast Tennessee with 12 elementary schools. Three of the elementary schools did not qualify for Title I funds but the other 9 schools were Title I funded schools. Data collection tools used in the study included results from the TCAP test using the paper-and-pencil format and the SAS using a computerbased test. Student scaled scores were used for determining the degree of correlation between the TCAP test and SAS assessment. This study was used to examine any correlation between the TCAP and SAS tests used with fourth grade student in Tennessee. The effect was determined by how closely the tests were correlated across gender, race, socioeconomic status, and school Title-I status. The results show that the TCAP and SAS test scores have a strong positive correlation: Both assessments consistently showed that female students scored significantly higher than male students, Students in Non-Title I schools scored significantly higher than those in Title I funded schools, There was no significant difference in scores based on race (Black or White), and There was no significant difference in scores based on socioeconomic status.

This document describes the work for the master’s thesis in Electrical Engineering carried out at Electrolux Laundry Systems. In this project the computers that control the laundry system have been compared in order to verify the performance of the whole system. Three real environment systems are analysed and two of these systems have been set up in the laboratory in order to solve the problem considered. The results show that the tested devices perform better than the device PC1, which is not fulfilling the expectations in the real environment system. Some conclusions and future work are presented.

The purpose of the study was to determine if a correlation existed between the Predictive Assessment Series (PAS) Test, marketed by Discovery Education, and the Tennessee Comprehensive Assessment Program (TCAP) Achievement Test in reading, math, and science for grade 4, grade 6, and grade 8. The study included 4th-grade, 6th-grade, and 8th-grade students during the 2008-2009 school year who had taken the ThinkLink Predictive Assessment Series for reading, math, and science in February 2009 and had taken the TCAP reading, math, and science test in April 2009. The approach of the study was quantitative in nature. Data were collected from one school system in East Tennessee. The school system had 5 elementary schools and 1 middle school. Data collection tools used in the study included results from the TCAP test using the paper and pencil format and a computer test, the ThinkLink PAS. Student scaled scores were used for determining the degree of correlation between the TCAP and PAS tests. The data were analyzed using the Statistical Program for the Social Sciences. Based on the analysis and findings of this study, using the ThinkLink PAS test appears to have been successful in predicting how well students will perform on the state assessment. Overall, the correlations between the PAS and TCAP were consistent across grades, across gender within grade levels, and with Title I and Non-Title I students. The findings also show that it was possible to calculate a predicted TCAP score in reading, mathematics, and science. This was an important finding because the ability of the PAS assessment to predict TCAP scores could be another tool to provide educators the opportunity to target students who are potentially at risk of not meeting state benchmark proficiency levels. Based on the findings, there appears to be a strong relationship between the ThinkLink PAS benchmark assessment and the TCAP assessment in reading, math, and science for grade 4, grade 6, and grade 8. The relationships between PAS and TCAP tests in reading, math, and science were consistent across gender within grade levels. According to the results of the test of homogeneity of slopes, the relationships between PAS and TCAP tests in reading, math, and science were also consistent across Title I and Non-Title I schools. The test of homogeneity of slopes showed the slopes regression lines for the scores of Title I and Non-Title I students were the same (parallel) for grade 4, grade 6, and grade 8. Overall, the correlations between PAS and TCAP scores for Title I and Non-Title I students were moderately strong to very strong. The predictive validity of the PAS provides educators valuable time to reteach grade level skills to students who are at risk of scoring nonproficient on the TCAP.

So far the optimization of integration processes between heterogeneous data sources is still an open challenge. A first step towards sufficient techniques was the specification of a universal benchmark for integration systems. This DIPBench allows to compare solutions under controlled conditions and would help generate interest in this research area. However, we see the requirement for providing a sophisticated toolsuite in order to minimize the effort for benchmark execution. This demo illustrates the use of the DIPBench toolsuite. We show the macro-architecture as well as the micro-architecture of each tool. Furthermore, we also present the first reference benchmark implementation using a federated DBMS. Thereby, we discuss the impact of the defined benchmark scale factors. Finally, we want to give guidance on how to benchmark other integration systems and how to extend the toolsuite with new distribution functions or other functionalities.

The ever increasing demand for Internet traffic, storage and processing requires an ever increasing amount of hardware resources. In addition to this, infrastructure providers over-provision system architectures to serve users at peak times without performance delays. Over-provisioning leads to underutilization and thus to unnecessary power consumption. Therefore, there is a need for workload management strategies to map and schedule different services simultaneously in an energy-efficient manner without compromising performance, specially for heterogeneous micro-server architectures. This requires statistical models of how services interfere with each other, thereby affecting both performance and energy consumption. Indeed, the performance-energy behavior when mixing workloads is not well understood. This paper presents an interference analysis for heterogeneous workloads (i.e., CPU- and memory-intensive) on a big.LITTLE MPSoC architecture. We employ state-of-the-art tools to generate multiple single-application mappings and characterize the interference among two different services. We observed a performance degradation factor between 1.1 and 2.5. For some configurations, executing on different clusters resulted in reduced energy consumption with no performance penalty. This kind of detailed analysis give us first insights towards more general models for future workload management systems.

Data centres and similar server clusters consume a large amount of energy. However, not all consumed energy produces useful work. Servers consume a disproportional amount of energy when they are idle, underutilised, or overloaded. The effect of these conditions can be minimised by attempting to balance the demand for and the supply of resources through a careful prediction of future workloads and their efficient consolidation. In this paper we extend the cutting stock problem for consolidating workloads having stochastic characteristics. Hence, we employ the aggregate probability density function of co-located and simultaneously executing services to establish valid patterns. A valid pattern is one yielding an overall resource utilisation below a set threshold. We tested the scope and usefulness of our approach on a 16-core server with 29 different benchmarks. The workloads of these benchmarks have been generated based on the CPU utilisation traces of 100 real-world virtual machines which we obtained from a Google data centre hosting more than 32000 virtual machines. Altogether, we considered 600 different consolidation scenarios during our experiment. We compared the performance of our approach-system overload probability, job completion time, and energy consumption-with four existing/proposed scheduling strategies. In each category, our approach incurred a modest penalty with respect to the best performing approach in that category, but overall resulted in a remarkable performance clearly demonstrating its capacity to achieve the best trade-off between resource consumption and performance.

The current research study investigates the predictive value of two frequently-used benchmark reading assessments: Developmental Reading Assessment (DRA) and the Dynamic Indicators of Basic Early Literacy Skills (DIBELS). With an increasing emphasis on high-stakes testing to measure reading proficiency, benchmark assessments may assist in predicting end-of-year performance on high-stakes testing. Utah's high-stakes measurement of end-of-year reading achievement is the English Language Arts Criterion-Referenced Test (ELA-CRT). A Utah urban school district provided data for students who completed the DRA, DIBELS, and ELA-CRT in the 2005-2006 school year. The primary purpose of the study was to determine the accuracy to which the Fall administrations of the DRA and the DIBELS predicted performance on the ELA-CRT. Supplementary analysis also included cross-sectional data for the DIBELS. Results indicated that both Fall administrations of the DRA and the DIBELS were statistically significant in predicting performance on the ELA-CRT. Students who were high risk on the benchmark assessments were less likely to score proficiently on the ELA-CRT. Also, demographic factors did not appear to affect individual performance on the ELA-CRT. Important implications include the utility of data collected from benchmark assessments to address immediate interventions for students at risk of failing end-of-year, high-stakes testing.