Can traditional fault prediction models be used for vulnerability prediction?

Finding security vulnerabilities requires a different mindset than finding general faults in software—thinking like an attacker. Therefore, security engineers looking to prioritize security inspection and testing efforts may be better served by a prediction model that indicates security vulnerabilities rather than faults. At the same time, faults and vulnerabilities have commonalities that may allow development teams to use traditional fault prediction models and metrics for vulnerability prediction. The goal of our study is to determine whether fault prediction models can be used for vulnerability prediction or if specialized vulnerability prediction models should be developed when both models are built with traditional metrics of complexity, code churn, and fault history. We have performed an empirical study on a widely-used, large open source project, the Mozilla Firefox web browser, where 21% of the source code files have faults and only 3% of the files have vulnerabilities. Both the fault prediction model and the vulnerability prediction model provide similar ability in vulnerability prediction across a wide range of classification thresholds. For example, the fault prediction model provided recall of 83% and precision of 11% at classification threshold 0.6 and the vulnerability prediction model provided recall of 83% and precision of 12% at classification threshold 0.5. Our results suggest that fault prediction models based upon traditional metrics can substitute for specialized vulnerability prediction models. However, both fault prediction and vulnerability prediction models require significant improvement to reduce false positives while providing high recall.     

Can predicate-argument structures be used for contextual opinion retrieval from blogs?

We present the results of our investigation on the use of predicate-argument structures for contextual opinion retrieval. The use of predicate-argument structure for opinion retrieval is a novel approach that exploits the grammatical derivation of sentences to show contextual and subjective relevance. We do not use frequency of certain keywords as it is usually done in keyword-based opinion retrieval approaches. Rather, our novel solution is based on frequency of contextually relevant and subjective sentences. We use a linear relevance model that leverages semantic similarities among predicate-argument structures of sentences. Thus, this paper presents the evaluation results of the linear relevance model. The model does a linear combination of a popular relevance model, our proposed transformed terms similarity model, and the absolute value of a sentence subjectivity scoring scheme. The predicate-argument structures are derived from the grammatical derivations of natural language query topics and the well formed sentences from blog documents. The derived predicate-argument structures are then semantically compared to compute an opinion relevance score. Our scoring technique uses the highest frequency of semantically related predicate-argument structures enriched with the total subjectivity score from sentences. Evaluation and experimental results show that predicate-argument structures can indeed be used for contextual opinion retrieval as it improves performance of opinion retrieval task by 15% over the popular TREC baselines.     

Dynamic testing: Can a robot as tutor be of help in assessing children's potential for learning?

This study examined whether computerized dynamic testing by utilizing a robot would lead to different patterns in children's (aged 6–9 years) potential for learning and strategy use when solving series‐completion tasks. The robot, in a “Wizard of Oz” setting, provided instructions and prompts during dynamic testing. It was found that a dynamic training resulted in greater accuracy and more correctly placed pieces at the post‐test than repeated testing only. Moreover, children who were dynamically trained appeared to use more heuristic strategies at the post‐test than their peers who were not trained. In general, observations showed that children were excited to work with the robot. All in all, the study revealed that computerized dynamic testing by means of a robot has much potential in tapping into children's potential for learning and strategy use. The implications of using a robot in educational assessment were stressed further in the discussion.     

Could the doctrine of moral rights be used as a basis for understanding the notion of control within data protection law?

This article considers the notion of individual control of personal data as envisaged by the European data protection framework and makes the argument that it is a poorly-understood and under-developed concept, but that our understanding of it may be improved by way of analyses and comparisons with the doctrine of moral rights, an important constituent element of intellectual property law. The article starts by examining the concept of personal data itself, and why an enhanced level of individual control over personal data is thought to be a desirable regulatory objective. Following this, the article examines the scholarly literature pertaining to individual control of personal data, as well as a range of relevant EU policy documents. Having done so, the article argues that the notion of control is muddled and confused from both theoretical and practical perspectives. Following this, the article considers the doctrine of moral rights, and through an exploration of its theoretical and practical elements highlights why it may be of assistance in terms of enhancing our understanding of individual control in the data protection context.     

Can computer models be used for social learning? A serious game in water management

Computer simulation models are increasingly used to support solving complex problems in natural resource management, with social learning as subsidiary goal of the solution process. In this research, a serious game on water management is used where participants receive feedback on consequences of their choices from an Integrated Assessment Meta Model. This study aims to determine if and how social learning takes place and explores the role of the model in social learning. Group discussions were qualitatively analysed to uncover and understand the mechanisms in this process. Results show that social learning took place in 10 of the 12 game sessions. Though model feedback was an important driver for social learning, social learning was driven most by the team's reflection on their perspective. We conclude that using a model can facilitate social learning in a serious-game setting, in particular in combination with reflection on teams' perspectives.     

Can a Shared-Memory Model Serve as a Bridging Model for Parallel Computation?

A parallel multithreaded program that is ostensibly deterministic may nevertheless behave nondeterministically due to bugs in the code. These bugs are called determinacy races, and they result when one thread updates a location in shared memory while another thread is concurrently accessing the location. We have implemented a provably efficient determinacy-race detector for Cilk, an algorithmic multithreaded programming language. If a Cilk program is run on a given input data set, our debugging tool, which we call the ``Nondeterminator,' either determines at least one location in the program that is subject to a determinacy race, or else it certifies that the program is race free when run on the data set. The core of the Nondeterminator is an asymptotically efficient serial algorithm (inspired by Tarjan's nearly linear-time least-common-ancestors algorithm) for detecting determinacy races in series-parallel directed acyclic graphs. For a Cilk program that runs in T time on one processor and uses v shared-memory locations, the Nondeterminator runs in O(T α(v,v)) time, where α is Tarjan's functional inverse of Ackermann's function, a very slowly growing function which, for all practical purposes, is bounded above by 4 . The Nondeterminator uses at most a constant factor more space than does the original program. On a variety of Cilk program benchmarks, the Nondeterminator exhibits a slowdown of less than 12 compared with the serial execution time of the original optimized code, which we contend is an acceptable slowdown for debugging purposes. Received November 11, 1997, and in final form September 21, 1998.     

Can privacy concerns for insurance of connected cars be compensated?

Internet-of-things technologies enable service providers such as insurance companies to collect vast amounts of privacy-sensitive data on car drivers. This paper studies whether and how privacy concerns of car owners can be compensated by offering monetary benefits. We study the case of usage based car insurance services for which the insurance fee is adapted to measured mileage and driving behaviour. A conjoint experiment shows that consumers prefer their current insurance products to usage based car insurance. However, when offered a minor financial compensation, they are willing to give up their privacy to car insurers. Consumers find privacy of behaviour and action more valuable than privacy of location and space. The study is a first to compare different forms of privacy in the acceptance of connected car services. Hereby, we contribute to more fine-grained understanding of privacy concerns in the acceptance of digital services, which will become more important in the upcoming Internet-of-things era.     

Can Efficiency of Returns Be Considered as a Pricing Factor?

We add to the investments literature by employing new techniques to estimate asset performance. We estimate a data envelopment analysis based efficiency score that allows for direct comparison between ex-post efficiency rankings and test the ex-ante relevance of such scores by including them into asset pricing models. We find that knowing the fund efficiency score can help explain time-series returns. When efficiency is included in an asset pricing model, the absolute value of the average mispricing error is decreased, which we take as evidence of the explanatory power of efficiency scores. But more importantly, we show that efficacy scores can be used as next period predictors of stock returns. In addition, we further use the efficiency scores to differentiate between the performance of constrained and unconstrained investment assets, as in the case of socially responsible investments. Our findings give robustness to the literature on constrained investments showing significant underperformance of socially and responsible investments.     

Can virtual reality be used to measure and train surgical skills?

The quantitative literature on the use of virtual environments to measure and train a variety of surgical skills is critically reviewed. We selected works from the years 1995-2000. Theoretical perspectives, such as those of Saltzman (1979), Bernstein (1967) and Schmidt (1975) and techniques, such as hierarchical task analysis, are presented and contrasted with the largely atheoretical approach of the practitioners of virtual surgery. It is concluded that the quantitative work discussed provides few findings of value to practising surgeons. This may be due in part to the lack of consideration paid to fundamental issues in the learning of motor skills, such as whether motor skills learning is most effective with varying training conditions and the distinction between purely motoric aspects and knowledge of procedures. Possible ways forward for surgical training are outlined. It is suggested that the theoretical perspectives and techniques available in the area of motor behaviour should be incorporated into future experimental studies of surgery in virtual environments.     

Can regions learn? Critical assessment of regions as arenas for regional development

Summary  The article locates work on regional development, and in particular action research, within the context of debates on neo-liberalism and democracy. The learning regions approach is explored, but the scale of the challenges to overcome is emphasised.

Can a rational agent afford to be affectless? a formal approach

In this article, we expose some of the issues raised by the critics of the neoclassical approach to rational agent modeling and we propose a formal approach for the design of artificial rational agents that includes some of the functions of emotions found in the human system. We suggest that emotions and rationality are closely linked in the human mind (and in the body, for that matter) and, therefore, need to be included in architectures for designing rational artificial agents, whether these agents are to interact with humans, to model humans' behaviors and actions, or both. We describe an Affective Knowledge Representation (AKR) scheme to represent emotion schemata, which we developed to guide the design of a variety of socially intelligent artificial agents. Our approach focuses on the notion of "social expertise" of socially intelligent agents in terms of their external behavior and internal motivational goal-based abilities. AKR, which uses probabilistic frames, is derived from combining multiple emotion theories into a hierarchical model of affective phenomena useful for artificial agent design. AKR includes a taxonomy of affect, mood, emotion, and personality, and a framework for emotional state dynamics using probabilistic Markov Models.     

Can a satellite-derived estimate of the fraction of PAR absorbed by chlorophyll (FAPARchl) improve predictions of light-use efficiency and ecosystem photosynthesis for a boreal aspen forest?

We used daily MODerate resolution Imaging Spectroradiometer (MODIS) imagery obtained over a five-year period to analyze the seasonal and inter-annual variability of the fraction of absorbed photosynthetically active radiation (FAPAR) and photosynthetic light use efficiency (LUE) for the Southern Old Aspen (SOA) flux tower site located near the southern limit of the boreal forest in Saskatchewan, Canada. To obtain the spectral characteristics of a standardized land area to compare with tower measurements, we scaled up the nominal 500 m MODIS products to a 2.5 km × 2.5 km area (5 × 5 MODIS 500 m grid cells). We then used the scaled-up MODIS products in a coupled canopy-leaf radiative transfer model, PROSAIL-2, to estimate the fraction of absorbed photosynthetically active radiation (APAR) by the part of the canopy dominated by chlorophyll (FAPAR_chl) versus that by the whole canopy (FAPAR_canopy). Using the additional information provided by flux tower-based measurements of gross ecosystem production (GEP) and incident PAR, we determined 90-minute averages for APAR and LUE (slope of GEP:APAR) for both the physiologically active foliage (APAR_chl, LUE_chl) and for the entire canopy (APAR_canopy, LUE_canopy).The flux tower measurements of GEP were strongly related to the MODIS-derived estimates of APAR_chl (r² = 0.78) but only weakly related to APAR_canopy (r² = 0.33). Gross LUE between 2001 and 2005 for LUE_chl was 0.0241 µmol C µmol^− 1 PPFD whereas LUE_canopy was 36% lower. Time series of the 5-year normalized difference vegetation index (NDVI) were used to estimate the average length of the core growing season as days of year 152-259. Inter-annual variability in the core growing season LUE_chl (µmol C µmol^− 1 PPFD) ranged from 0.0225 in 2003 to 0.0310 in 2004. The five-year time series of LUE_chl corresponded well with both the seasonal phase and amplitude of LUE from the tower measurements but this was not the case for LUE_canopy. We conclude that LUE_chl derived from MODIS observations could provide a more physiologically realistic parameter than the more commonly used LUE_canopy as an input to large-scale photosynthesis models.     

Virtuality as a basis for problem solving?

This paper is an attempt to develop a paradigm in problem solving where the notion of virtuality plays a central role. Following a brief discussion on virtual simulation, the paper attempts to identify a notion of virtuality based on the identification of the self (man or computer) with the problem solver. It is shown that such an identification/distinction possibly violates some general principle of the problem environment.To deal with this violation, a new problem is generated and a new virtualization act is required, in order to attain a correspondence between virtuality and reality. A better understanding of this approach requires a combination of analog and digital reasoning: the analog being related to the environment in which the problem solving is required, and the digital to the problem solver's mental activities.We will briefly analyze the recursive approach to problem solving and suggest a possible problem solving methodology based on virtuality. The paper concludes with comments on the relation between etnology and virtual reality.     

Can I find a partner? Undecidability of partner existence for open nets

We study open nets as Petri net models of web services, with a link to the practically relevant language WS-BPEL. For those nets, we investigate the problem of operability which we consider as fundamental as the successful notion of soundness for workflow nets, i.e., Petri net models of business processes and workflows. While we could give algorithmic solutions to the operability problem for subclasses of open nets in earlier work, this article shows that the problem is in general undecidable.     

Computer games created by middle school girls: Can they be used to measure understanding of computer science concepts?

Computer game programming has been touted as a promising strategy for engaging children in the kinds of thinking that will prepare them to be producers, not just users of technology. But little is known about what they learn when programming a game. In this article, we present a strategy for coding student games, and summarize the results of an analysis of 108 games created by middle school girls using Stagecast Creator in an after school class. The findings show that students engaged in moderate levels of complex programming activity, created games with moderate levels of usability, and that the games were characterized by low levels of code organization and documentation. These results provide evidence that game construction involving both design and programming activities can support the learning of computer science concepts.     

Vibration and passenger comfort: Can data from subjects be used to predict passenger comfort?

This paper presents a review of both field and laboratory studies of human reaction to vibration, to try to answer the question whether laboratory based studies may be used to predict comfort levels for passenger vehicles. The conclusion is reached that such studies may be used, provided their restrictions are understood. Finally, tentative suggestions are made for acceptable levels of vibration in passenger transport vehicles.     

Can mobile TV be a new revolution in the television industry?

The development within the mobile communications industry has provided a new mechanism for individuals to watch television programs via mobile device, known as mobile television (m-TV). Considering that m-TV is an emerging technology among traditional television services where critical success factors depend on user-centered, it is important to understand users' behavioral intention (BI). Unlike previous studies which have mainly focused on flow experience, perceived value, motivation and social cognitive theories, this study examines user-centered factors of technology readiness (TR) and technical support and training (TST). Therefore, 244 valid data were tested using partial least squares structural equation modeling (PLS-SEM) to measure both reflective and formative constructs based on the proposed framework. Findings reported that performance expectancy (PE), effort expectancy (EE) and TST have a positive and significant impact on BI. TR however has a negative relationship with BI. In addition, TR was also found to influence PE and EE. Similarly, TST has a direct effect factor on EE and EE was a significant determinant of PE. The findings of this study not only provide guidance for future researchers, but also valuable insights for designers, marketers and system providers of m-TV to tailor their services in the near future.