Project for the analysis of technology transfer

The special task of preparing technology transfer profiles during the first six months of 1971 produced two major results: refining a new method for identifying and describing technology transfer activities, and generating practical insights into a number of issues associated with transfer programs

No tests required : comparing traditional and dynamic predictors of programming success.

Research over the past fifty years into predictors of programming performance has yielded little improvement in the identification of at-risk students. This is possibly because research to date is based upon using static tests, which fail to reflect changes in a student's learning progress over time. In this paper, the effectiveness of 38 traditional predictors of programming performance are compared to 12 new data-driven predictors, that are based upon analyzing directly logged data, describing the programming behavior of students. Whilst few strong correlations were found between the traditional predictors and performance, an abundance of strong significant correlations based upon programming behavior were found. A model based upon two of these metrics (Watwin score and percentage of lab time spent resolving errors) could explain 56.3% of the variance in coursework results. The implication of this study is that a student's programming behavior is one of the strongest indicators of their performance, and future work should continue to explore such predictors in different teaching contexts

No Tests Required: Comparing Traditional and Dynamic Predictors of Programming Success

Research over the past fifty years into predictors of programming performance has yielded little improvement in the identification of at-risk students. This is possibly because research to date is based upon using static tests, which fail to reflect changes in a student's learning progress over time. In this paper, the effectiveness of 38 traditional predictors of programming performance are compared to 12 new data-driven predictors, that are based upon analyzing directly logged data, describing the programming behavior of students. Whilst few strong correlations were found between the traditional predictors and performance, an abundance of strong significant correlations based upon programming behavior were found. A model based upon two of these metrics (Watwin score and percentage of lab time spent resolving errors) could explain 56.3% of the variance in coursework results. The implication of this study is that a student's programming behavior is one of the strongest indicators of their performance, and future work should continue to explore such predictors in different teaching contexts

Differences in intention to use educational RSS feeds between Lebanese and British students: A multi‑group analysis based on the technology acceptance model

Really Simple Syndication (RSS) offers a means for university students to receive timely updates from virtual learning environments. However, despite its utility, only 21% of home students surveyed at a university in Lebanon claim to have ever used the technology. To investigate whether national culture could be an influence on intention to use RSS, the survey was extended to British students in the UK. Using the Technology Adoption Model (TAM) as a research framework, 437 students responded to a questionnaire containing four constructs: behavioral intention to use; attitude towards benefit; perceived usefulness; and perceived ease of use. Principle components analysis and structural equation modelling were used to explore the psychometric qualities and utility of TAM in both contexts. The results show that adoption was significantly higher, but also modest, in the British context at 36%. Configural and metric invariance were fully supported, while scalar and factorial invariance were partially supported. Further analysis shows significant differences between perceived usefulness and perceived ease of use across the two contexts studied. Therefore, it is recommended that faculty demonstrate to students how educational RSS feeds can be used effectively to increase awareness and emphasize usefulness in both contexts

Economic growth and financial statement verification

We use a proprietary data set of financial statements collected by banks to examine whether economic growth is related to the use of financial statement verification in debt financing. Exploiting the distinct economic growth and contraction patterns of the construction industry over the years 2002–2011, our estimates reveal that banks reduced their collection of unqualified audited financial statements from construction firms at nearly twice the rate of firms in other industries during the housing boom period before 2008. This reduction was most severe in the regions that experienced the most significant construction growth. These trends reversed during the subsequent housing crisis in 2008–2011 when construction activity contracted. Moreover, using bank‐ and firm‐level data, we find a strong negative (positive) relation between audited financial statements during the growth period, and subsequent loan losses (construction firm survival) during the contraction period. Collectively, our results reveal that macroeconomic fluctuations produce temporal shifts in the overall level of financial statement verification and temporal shifts in verification are related to bank loan portfolio quality and borrower performance.Accepted manuscrip

The wider context of performance analysis and it application in the football coaching process

The evolving role of PA and the associated proliferation of positions and internships within high performance sport has driven consideration for a change, or at least a broadening, of emphasis for use of PA analysis. In order to explore the evolution of PA from both an academic and practitioner perspective this paper considers the wider conceptual use of PA analysis. In establishing this, the paper has 4 key aims: (1) To establish working definitions of PA and where it sits within the contemporary sports science and coaching process continuum; (2) To consider how PA is currently used in relation to data generation; (3) To explore how PA could be used to ensure transfer of information, and; (4) To give consideration to the practical constrains potentially faced by coach and analyst when implementing PA strategies in the future

Comparing One with Many -- Solving Binary2source Function Matching Under Function Inlining

Binary2source function matching is a fundamental task for many security applications, including Software Component Analysis (SCA). The "1-to-1" mechanism has been applied in existing binary2source matching works, in which one binary function is matched against one source function. However, we discovered that such mapping could be "1-to-n" (one query binary function maps multiple source functions), due to the existence of function inlining. To help conduct binary2source function matching under function inlining, we propose a method named O2NMatcher to generate Source Function Sets (SFSs) as the matching target for binary functions with inlining. We first propose a model named ECOCCJ48 for inlined call site prediction. To train this model, we leverage the compilable OSS to generate a dataset with labeled call sites (inlined or not), extract several features from the call sites, and design a compiler-opt-based multi-label classifier by inspecting the inlining correlations between different compilations. Then, we use this model to predict the labels of call sites in the uncompilable OSS projects without compilation and obtain the labeled function call graphs of these projects. Next, we regard the construction of SFSs as a sub-tree generation problem and design root node selection and edge extension rules to construct SFSs automatically. Finally, these SFSs will be added to the corpus of source functions and compared with binary functions with inlining. We conduct several experiments to evaluate the effectiveness of O2NMatcher and results show our method increases the performance of existing works by 6% and exceeds all the state-of-the-art works