Knowledge-based system V and V in the Space Station Freedom program

Knowledge Based Systems (KBS's) are expected to be heavily used in the Space Station Freedom Program (SSFP). Although SSFP Verification and Validation (V&V) requirements are based on the latest state-of-the-practice in software engineering technology, they may be insufficient for Knowledge Based Systems (KBS's); it is widely stated that there are differences in both approach and execution between KBS V&V and conventional software V&V. In order to better understand this issue, we have surveyed and/or interviewed developers from sixty expert system projects in order to understand the differences and difficulties in KBS V&V. We have used this survey results to analyze the SSFP V&V requirements for conventional software in order to determine which specific requirements are inappropriate for KBS V&V and why they are inappropriate. Further work will result in a set of recommendations that can be used either as guidelines for applying conventional software V&V requirements to KBS's or as modifications to extend the existing SSFP conventional software V&V requirements to include KBS requirements. The results of this work are significant to many projects, in addition to SSFP, which will involve KBS's

Untrustworthy People Grab Our Attention - Whether We Want Them to or Not

Our automatic attention to injustices and untrustworthy people has the potential to distract us from more relevant concerns. It can make us overly cautious and wary of risk-taking. It can even cause errors in decision-making. There could be a negative impact on our surroundings when we focus on untrustworthy people as a result of second- or third-hand information.York’s Knowledge Mobilization Unit provides services and funding for faculty, graduate students, and community organizations seeking to maximize the impact of academic research and expertise on public policy, social programming, and professional practice. It is supported by SSHRC and CIHR grants, and by the Office of the Vice-President Research & Innovation. [email protected] www.researchimpact.c

Attribution Analysis of Computer Self-Efficacy

Individuals’ reactions to ERP technology and subsequent behaviors are investigated by combining Self- Efficacy Theory and Attribution Theory. Using a field study, this research determined the attributions of computer performance and their causal dimensions (i.e., locus of causality, stability, and controllability). The PLS results indicated that desirable and undesirable attributions are important antecedents to computer self- efficacy

Reassessing policy paradigms : a comparison of the global tobacco and alcohol industries

Tobacco is widely considered to be a uniquely harmful product for human health. Since the mid-1990s, the strategies of transnational tobacco corporations to undermine effective tobacco control policy has been extensively documented through internal industry documents. Consequently, the sale, use and marketing of tobacco products are subject to extensive regulation and formal measures to exclude the industry from policy-making have been adopted in the Framework Convention on Tobacco Control. In contrast to tobacco, alcohol is subject to less stringent forms of regulation, and the alcohol industry continues to play a central role in policymaking in many countries and at the global level. This article examines whether there is a sufficient rationale for such different regulatory approaches, through a comparative analysis of the political economy of the tobacco and alcohol industries including the structure of the industries, and the market and political strategies they pursue. Despite some important differences, the extensive similarities which exist between the tobacco and alcohol industries in terms of market structure and strategy, and political strategy, call into question the rationale for both the relatively weak regulatory approach taken towards alcohol, and the continued participation of alcohol corporations in policy-making processes

Overview of open source codes to assess environmental effects of ocean wave farms (Extended Abstract)

The United States has a theoretical ocean wave energy resource potential of 1,594–2,640 TWh/year, enough to power between 143.5 and 237.6 million homes/year and contribute substantially to the United States’ energy portfolio [1]. However, wave energy converters (WECs) are currently in the early stages of research and development at low technology readiness levels. Open ocean deployment data is from demonstration-scale projects, not from utility-scale deployments. As a result, researchers, developers, and regulators rely heavily on numerical models to understand the environmental effects of wave farms. Preliminary numerical studies have demonstrated that small-scale deployments of ~10 WECs or less have little to no impact on the physical environment. But utility-scale wave farms may affect the near-field and nearshore wave environment, circulation patterns, and nearshore processes such as sediment transport. A suite of open source codes has been developed by Sandia National Laboratories focused on simulating the energy extraction of WECs to better understand and predict their potential environment effects

Overview of open source codes to assess environmental effects of ocean wave farms (Extended Abstract)

The United States has a theoretical ocean wave energy resource potential of 1,594–2,640 TWh/year, enough to power between 143.5 and 237.6 million homes/year and contribute substantially to the United States’ energy portfolio [1]. However, wave energy converters (WECs) are currently in the early stages of research and development at low technology readiness levels. Open ocean deployment data is from demonstration-scale projects, not from utility-scale deployments. As a result, researchers, developers, and regulators rely heavily on numerical models to understand the environmental effects of wave farms. Preliminary numerical studies have demonstrated that small-scale deployments of ~10 WECs or less have little to no impact on the physical environment. But utility-scale wave farms may affect the near-field and nearshore wave environment, circulation patterns, and nearshore processes such as sediment transport. A suite of open source codes has been developed by Sandia National Laboratories focused on simulating the energy extraction of WECs to better understand and predict their potential environment effects

SAR by MS for Functional Genomics (Structure-Activity Relation by Mass Spectrometry)

Large-scale functional genomics will require fast, high-throughput experimental techniques, coupled with sophisticated computer algorithms for data analysis and experiment planning. In this paper, we introduce a combined experimental-computational protocol called Structure-Activity Relation by Mass Spectrometry (SAR by MS), which can be used to elucidate the function of protein-DNA or protein-protein complexes. We present algorithms for SAR by MS and analyze their complexity. Carefully-designed Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight (MALDI TOF) and Electrospray Ionization (ESI) assays require only femtomolar samples, take only microseconds per spectrum to record, enjoy a resolution of up to one dalton in $10^6$, and (in the case of MALDI) can operate on protein complexes up to a megadalton in mass. Hence, the technique is attractive for high-throughput functional genomics. In SAR by MS, selected residues or nucleosides are 2H-, 13C-, and/or 15N-labeled. Second, the complex is crosslinked. Third, the complex is cleaved with proteases and/or endonucleases. Depending on the binding mode, some cleavage sites will be shielded by the crosslinking. Finally, a mass spectrum of the resulting fragments is obtained and analyzed. The last step is the Data Analysis phase, in which the mass signatures are interpreted to obtain constraints on the functional binding mode. Experiment Planning entails deciding what labeling strategy and cleaving agents to employ, so as to minimize mass degeneracy and spectral overlap, in order that the constraints derived in data analysis yield a small number of binding hypotheses. A number of combinatorial and algorithmic questions arise in deriving algorithms for both Experiment Planning and Data Analysis. We explore the complexity of these problems, obtaining upper and lower bounds. Experimental results are reported from an implementation of our algorithms

Overview of Open Source Codes to Assess Environmental Effects on Ocean Wave Farms

The development of SNL-SWAN by Sandia National Laboratories (SNL) allows users to investigate the interaction between a WEC or WEC array and the wave environment. SNL-SWAN when coupled with a hydrodynamic and sediment transport model such as Delft3D, developed by Deltares Inc, allows for the direct investigation of WEC array effects on the physical environment (e.g. waves, currents, seabed) and the associated site ecology. Ongoing development of these tools has shown how the coupling of SNL-SWAN with Delft3D-Flow can quantify the interaction between device(s) and the hydrodynamic environment at a real-world site

Microbial and metabolic succession on common building materials under high humidity conditions.

Despite considerable efforts to characterize the microbial ecology of the built environment, the metabolic mechanisms underpinning microbial colonization and successional dynamics remain unclear, particularly at high moisture conditions. Here, we applied bacterial/viral particle counting, qPCR, amplicon sequencing of the genes encoding 16S and ITS rRNA, and metabolomics to longitudinally characterize the ecological dynamics of four common building materials maintained at high humidity. We varied the natural inoculum provided to each material and wet half of the samples to simulate a potable water leak. Wetted materials had higher growth rates and lower alpha diversity compared to non-wetted materials, and wetting described the majority of the variance in bacterial, fungal, and metabolite structure. Inoculation location was weakly associated with bacterial and fungal beta diversity. Material type influenced bacterial and viral particle abundance and bacterial and metabolic (but not fungal) diversity. Metabolites indicative of microbial activity were identified, and they too differed by material