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At least 73 records · Page 4

A Probabilistic Software System Attribute Acceptance Paradigm for COTS Software Evaluation

Standard software requirement formats are written from top-down perspectives only, that is, from an ideal notion of a client s needs. Despite the exactness of the standard format, software and system errors in designed systems have abounded. Bad and inadequate requirements have resulted in cost overruns, schedule slips and lost profitability. Commercial off-the-shelf (COTS) software components are even more troublesome than designed systems because they are often provided as is and subsequently delivered with unsubstantiated validation of described capabilities. For COTS software, there needs to be a way to express the client s software needs in a consistent and formal manner using software system attributes derived from software quality standards. Additionally, the format needs to be amenable to software evaluation processes that integrate observable evidence garnered from historical data. This paper presents a paradigm that effectively bridges the gap between what a client desires (top-down) and what has been demonstrated (bottom-up) for COTS software evaluation. The paradigm addresses the specification of needs before the software evaluation is performed and can be used to increase the shared understanding between clients and software evaluators about what is required and what is technically possible.

Morris, A. Terry↗

Quality assurance and reliability in the Japanese electronics industry

Quality and reliability are two attributes required for all Japanese products, although the JTEC panel found these attributes to be secondary to customer cost requirements. While our Japanese hosts gave presentations on the challenges of technology, cost, and miniaturization, quality and reliability were infrequently the focus of our discussions. Quality and reliability were assumed to be sufficient to meet customer needs. Fujitsu's slogan, 'quality built-in, with cost and performance as prime consideration,' illustrates this point. Sony's definition of a next-generation product is 'one that is going to be half the size and half the price at the same performance of the existing one'. Quality and reliability are so integral to Japan's electronics industry that they need no new emphasis.

Pecht, Michael↗

Data Quality Challenges for Analysis Ready Data (ARD)

Data quality plays a critical role in research and applications. The Earth Science Information Partners (ESIP) Information Quality Cluster (IQC) defines four aspects of information quality: Science, Product, Stewardship, and Services. The ESIP IQC has become internationally recognized as an authoritative and responsive resource of information and guidance to data producers and distributors on how to implement data quality standards and best practices for their science data systems, datasets, and data/metadata dissemination services. In recent years, cloud computing environments have provided scale-up capabilities such as data archives and services, enabling interdisciplinary science and applications. More value-added products are expected from data service providers, including Analysis Ready Data (ARD). ARD refers to data that has been preprocessed into a form that allows immediate analysis by the end user, processed to a minimum set of requirements and provides interoperability over time and across multiple datasets. Once a dataset has been developed from its original form to produce ARD, what quality characteristics should the derived dataset or ARD possess? Also, is it safe to assume that the quality of the ARD is consistent with the quality of the source data, or are there special attributes to an ARD that would warrant a secondary, independent quality assessment? What provenance (also called “data lineage”) information needs to be included in ARD? It is important to answer these questions, especially given the ease of use of ARD, and the consequent temptation by users to trust ARD without understanding the limitations or possible variations in quality compared to the source data. In this presentation, we will discuss data quality challenges for ARD products and services and introduce IQC for participation.

data quality↗

Private, public, and bottled drinking water: Shared contaminant-mixture exposures and effects challenge

Background: Humans are primary drivers of environmental–contaminant exposures worldwide, including in drinking-water (DW). In the United States, point-of-use DW (POU–DW) is supplied via private tapwater (TW), public-supply TW, and bottled water (BW). Differences in management, monitoring, and messaging and lack of directly–intercomparable exposure data influence the actual and perceived quality and safety of different DW supplies and directly impact consumer decision–making. Objectives: The purpose of this paper is to provide a meta-analysis (quantitative synthesis) of POU–DW contaminant–mixture exposures and corresponding potential human–health effects of private-TW, public-TW, and BW by aggregating exposure results and harmonizing apical–health–benchmark–weighted and bioactivity–weighted effects predictions across previous studies by this research group. Discussion: Simultaneous exposures to multiple inorganic and organic contaminants of known or suspected human-health concern are common across all three DW supplies, with substantial variability observed in each and no systematic difference in predicted cumulative risk between supplies. Differences in contaminant or contaminant–class exposures, with important implications for DW–quality improvements, were observed and attributed to corresponding differences in regulation and compliance monitoring. Conclusion: The results indicate that human-health risks from contaminant exposures are common to and comparable in all three DW–supplies, including BW. Importantly, this study’s target analytical coverage, which exceeds that currently feasible for water purveyors or homeowners, nevertheless is a substantial underestimation of the breadth of contaminant mixtures in the environment and potentially present in DW. Thus, the results emphasize the need for improved understanding of the adverse human-health implications of long-term exposures to low–level inorganic–/organic–contaminant mixtures across all three distribution pipelines and do not support commercial messaging of BW as a systematically safer alternative to public-TW. Regardless of the supply, increased public engagement in source-water protection and drinking–water treatment is necessary to reduce risks associated with long-term DW–contaminant exposures, especially in vulnerable populations, and to reduce environmental waste and plastics contamination.

54 ENVIRONMENTAL SCIENCES↗

First Light Measurements with the XMM-Newton Reflection Grating Spectrometers: Evidence for an Inverse First Ionization Potential Effect and Anomalous Ne Abundance in the Coronae of HR 1099

The RS CVn binary system HR 1099 was extensively observed by the XMM-Newton observatory in February 2000 as its first-light target. A total of 570 ks of exposure time was accumulated with the Reflection Grating Spectrometers (RGS). The integrated X-ray spectrum between 5-38A is of unprecedented quality and shows numerous features attributed to transitions of the elements C, N, O, Ne, Mg, Si, S, Fe. Ni, and probably others. We perform an in-depth study of the elemental composition of the average corona of this system, and find that the elemental abundances strongly depend on the first ionisation potential (FIP) of the elements. But different from the solar coronal case, we find an inverse FIP effect, i.e., the abundances (relative to oxygen) increase with increasing FIP. Possible scenarios, e.g., selective enrichment due to Ne-rich flare-like events, are discussed.

Brinkman, A. C.↗

Flight Tests of a Ministick Controller in an F/A-18 Airplane

In March of 1999, five pilots performed flight tests to evaluate the handling qualities of an F/A-18 research airplane equipped with a small-displacement center stick (ministick) controller that had been developed for the JAS 39 Gripen airplane (a fighter/attack/ reconnaissance airplane used by the Swedish air force). For these tests, the ministick was installed in the aft cockpit (see figure) and production support flight control computers (PSFCCs) were used as interfaces between the controller hardware and the standard F/A-18 flight-control laws. The primary objective of the flight tests was to assess any changes in handling qualities of the F/A-18 airplane attributable to the mechanical characteristics of the ministick. The secondary objective was to demonstrate the capability of the PSFCCs to support flight-test experiments.

Stoliker, Patrick C.↗

MODIS and VIIRS Calibration History and Future Outlook

The MODIS is a key instrument for NASA’s EOS program, currently operated onboard the Terra and Aqua spacecraft launched in 1999 and 2002, respectively. The VIIRS is a MODIS follow-on instrument for the JPSS program. Adding to the ones operated onboard the S-NPP and NOAA-20 satellites launched in 2011 and 2017, respectively, three nearly identical VIIRS instruments will also be launched. This will enable the data records from MODIS and VIIRS to be extended beyond 2040. In addition to various applications and scientific studies of the Earth’s system, long-term data records from MODIS and VIIRS observations will greatly benefit the space-based climate observing system. This is attributed to the high-quality measurements and extensive calibration efforts, from pre-launch to post-launch. This paper provides an overview of MODIS and VIIRS calibration history and approaches applied to establish and maintain sensor calibration traceability and accuracy. It illustrates calibration and performance issues through different phases of the mission using examples derived from ground testing equipment, on-board calibrators, and other calibration targets. Moreover, discussed in this paper are outstanding challenges and future efforts to maintain and improve sensor calibration stability and long-term data quality, and to better support the space-based climate observing system.

MODIS↗

Quality Assurance Program Plan for SFR Metallic Fuel Data Qualification

This document contains an evaluation of the applicability of the current Quality Assurance Standards from the American Society of Mechanical Engineers Standard NQA-1 (NQA-1) criteria and identifies and describes the quality assurance process(es) by which attributes of historical, analytical, and other data associated with sodium-cooled fast reactor [SFR] metallic fuel will be evaluated. This process is being instituted to facilitate validation of data to the extent that such data may be used to support future licensing efforts associated with advanced reactor designs. The initial data to be evaluated under this program were generated during the US Integral Fast Reactor program between 1984-1994, where the data include, but are not limited to, research and development data and associated documents, test plans and associated protocols, operations and test data, technical reports, and information associated with past United States Nuclear Regulatory Commission reviews of SFR designs. It is recognized that managing the data generated by large research and development projects presents a significant challenge for retaining data integrity and availability. American Society of Mechanical Engineers Standard NQA-1 (NQA-1) 2008/2009a provides appropriate requirements for this plan.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hydropower Infrastructure - LAkes, Reservoirs, and RIvers (HILARRI), v4

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include: – Dams from the National Inventory of Dams (2025) and the Global Reservoir and Dam Database (GRanD v1.3) – Hydropower plants from the Existing Hydropower Assets dataset (EHA 2025) – Power plants that are listed in the 2025 U.S. Hydropower Development Pipeline Data or were listed in previous versions of the dataset These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from: – Products from the National Hydrography Dataset (NHD) – NHDPlusV2 Medium Resolution river network flowlines, – NHD waterbodies (limited to lakes and reservoirs), – NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS)) – NHD High Resolution waterbodies – HydroLAKES water bodies (lakes and reservoirs) – LAGOS-US lakes and reservoirs – EPA National Lakes Assessment (2007, 2012, 2017, and 2022) – The Reservoir Sedimentation Database (RESSED) – EPA SuRGE sampling locations Unique identifiers are used to facilitate joining to the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites. The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in data usage for individual to large-scale analyses.

Hansen, Carly [ORNL] (ORCID:0000000193280838)↗

Seasonal Impact of Regional Outdoor Biomass Burning on Air Pollution in Three Indian Cities: Delhi, Bengaluru, and Pune

Air pollution in many of India's cities exceeds national and international standards, and effective pollution control strategies require knowledge of the sources that contribute to air pollution and their spatiotemporal variability. In this study, we examine the influence of a single pollution source, outdoor biomass burning, on particulate matter (PM) concentrations, surface visibility, and aerosol optical depth (AOD) from 2007 to 2013 in three of the most populous Indian cities. We define the upwind regions, or "airsheds," for the cities by using atmospheric back trajectories from the HYSPLIT model. Using satellite fire radiative power (FRP) observations as a measure of fire activity, we target pre-monsoon and post-monsoon fires upwind of the Delhi National Capital Region and pre-monsoon fires surrounding Bengaluru and Pune. We find varying contributions of outdoor fires to different air quality metrics. For the post-monsoon burning season, we find that a subset of local meteorological variables (air temperature, humidity, sea level pressure, wind speed and direction) and FRP as the only pollution source explained 39% of variance in Delhi station PM(sub 10) anomalies, 77% in visibility, and 30% in satellite AOD; additionally, per unit increase in FRP within the daily airshed (1000 MW), PM(sub 10) increases by 16.34 micrograms per cubic meter, visibility decreases by 0.097 km, and satellite AOD increases by 0.07. In contrast, for the pre-monsoon burning season, we find less significant contributions from FRP to air quality in all three cities. Further, we attribute 99% of FRP from post-monsoon outdoor fires within Delhi's average airshed to agricultural burning. Our work suggests that although outdoor fires are not the dominant air pollution source in India throughout the year, post-monsoon fires contribute substantially to regional air pollution and high levels of population exposure around Delhi. During 3-day blocks of extreme PM(sub 2.5) in the 2013 post-monsoon burning season, which coincided with statistically significant high fire activity, concentrations in Delhi averaged 304 micrograms per cubic meter, or more than 1000% above the 24-h PM(sub 2.5) guideline (25 micrograms per cubic meter) of the World Health Organization. These results suggest that providing viable alternatives to agricultural residue burning could help improve post-monsoon air quality for a growing population of 63 million (39% in urban areas) within Delhi's airshed.

Air quality; Outdoor fires; Crop residue burning; ↗

Reliability Models and Attributable Risk

The intention of this report is to bring a developing and extremely useful statistical methodology to greater attention within the Safety, Reliability, and Quality Assurance Office of the NASA Johnson Space Center. The statistical methods in this exposition are found under the heading of attributable risk. Recently the Safety, Reliability, and Quality Assurance Office at the Johnson Space Center has supported efforts to introduce methods of medical research statistics dealing with the survivability of people to bear on the problems of aerospace that deal with the reliability of component hardware used in the NASA space program. This report, which describes several study designs for which attributable risk is used, is in concert with the latter goals. The report identifies areas of active research in attributable risk while briefly describing much of what has been developed in the theory of attributable risk. The report, which largely is a report on a report, attempts to recast the medical setting and language commonly found in descriptions of attributable risk into the setting and language of the space program and its component hardware.

Jarvinen, Richard D.↗

InGaAsP CW Lasers on (110) InP Substrates

Quality InGaAsP/InP CW laser structures grown by conventional liquidphase epitaxy on (110) InP substrates without using special growth procedures. Improved surface quality and grown-layer morphology are attributable to nearlyperfect surface stoichiometry of (110) surface which makes available equal numbers of In and P deposition sites.

Hawrylo, F. Z.↗

Towards an optimised sputtered MoS2 lubricant film

It is shown that the tribological quality of MoS2 lubricant films formed by magnetron sputtering is determined by the choice of sputtering conditions. By selecting the appropriate conditions, films of extremely high lubricity and endurance (in vacuum), which are well suited to many space applications, are obtained. Such MoS2 films, when applied to precision ball hearings, give rise to the lowest torques (for the given test conditions) yet seen in our laboratory. While a remarkably good performance is obtained in vacuum, tests in air show a marked deterioration in lubricating qualities. It is demonstrated that this is attributable to the adsorption of water vapor on MoS2 surfaces and that the degree of deterioration is related to the partial pressure of water vapor present. Analysis of results indicates that the factors relevant to obtaining optimum films are deposition rate and film composition.

Roberts, E. W.↗

Understanding software faults and their role in software reliability modeling

This study is a direct result of an on-going project to model the reliability of a large real-time control avionics system. In previous modeling efforts with this system, hardware reliability models were applied in modeling the reliability behavior of this system. In an attempt to enhance the performance of the adapted reliability models, certain software attributes were introduced in these models to control for differences between programs and also sequential executions of the same program. As the basic nature of the software attributes that affect software reliability become better understood in the modeling process, this information begins to have important implications on the software development process. A significant problem arises when raw attribute measures are to be used in statistical models as predictors, for example, of measures of software quality. This is because many of the metrics are highly correlated. Consider the two attributes: lines of code, LOC, and number of program statements, Stmts. In this case, it is quite obvious that a program with a high value of LOC probably will also have a relatively high value of Stmts. In the case of low level languages, such as assembly language programs, there might be a one-to-one relationship between the statement count and the lines of code. When there is a complete absence of linear relationship among the metrics, they are said to be orthogonal or uncorrelated. Usually the lack of orthogonality is not serious enough to affect a statistical analysis. However, for the purposes of some statistical analysis such as multiple regression, the software metrics are so strongly interrelated that the regression results may be ambiguous and possibly even misleading. Typically, it is difficult to estimate the unique effects of individual software metrics in the regression equation. The estimated values of the coefficients are very sensitive to slight changes in the data and to the addition or deletion of variables in the regression equation. Since most of the existing metrics have common elements and are linear combinations of these common elements, it seems reasonable to investigate the structure of the underlying common factors or components that make up the raw metrics. The technique we have chosen to use to explore this structure is a procedure called principal components analysis. Principal components analysis is a decomposition technique that may be used to detect and analyze collinearity in software metrics. When confronted with a large number of metrics measuring a single construct, it may be desirable to represent the set by some smaller number of variables that convey all, or most, of the information in the original set. Principal components are linear transformations of a set of random variables that summarize the information contained in the variables. The transformations are chosen so that the first component accounts for the maximal amount of variation of the measures of any possible linear transform; the second component accounts for the maximal amount of residual variation; and so on. The principal components are constructed so that they represent transformed scores on dimensions that are orthogonal. Through the use of principal components analysis, it is possible to have a set of highly related software attributes mapped into a small number of uncorrelated attribute domains. This definitively solves the problem of multi-collinearity in subsequent regression analysis. There are many software metrics in the literature, but principal component analysis reveals that there are few distinct sources of variation, i.e. dimensions, in this set of metrics. It would appear perfectly reasonable to characterize the measurable attributes of a program with a simple function of a small number of orthogonal metrics each of which represents a distinct software attribute domain.

Munson, John C.↗

Contracting Quality Early in the Lifecycle Using AS9145 Data Deliverables

Development schedules and a highly dynamic supply chain are a challenge to developers of complex systems produced at low volume. Flaws in designs, parts and materials availability problems, poor manufacturability, and a lack of knowledge about critical items and key process attributes can be realized well before traditional second-party quality assurance activities begin. Supplier audits and product inspections may have little mitigating effect once these foundational problems have been realized. Their impacts can be significant lifecycle disruption, cost overruns, inability to deliver to plan, and even project cancellation. AS9145, Requirements for Advanced Product Quality Planning and Production Part Approval Process, can be used to drive quality engineering practices into early development lifecycles to significantly reduce this late-cycle risk and to reduce the cost of quality overall. Since its initial publication in 2016, it has had very limited adoption by the DoD, no adoption by NASA, and sparse adoption in the aerospace and defense supply chain. A task group within the Aerospace Industries Association's (AIA) Joint Strategic Quality Council (JSQC) identified that both acquirers and suppliers see as AS9145 as a cost-adder and are hesitant to use it as an alternative to late-stage-heavy quality assurance approaches. A lack of prior use creates large capability gaps in request-for-proposal (RFP) teams, proposal teams, suppliers’ quality management systems (QMS), and in experienced personnel executing the early lifecycle approach. To create a more realizable on-ramp for using AS9145 in the space and defense sectors, the AIA JSQC task team created five deliverable requirements descriptions (DRDs) that can be used in a contract to begin to engage both parties in early lifecycle quality engineering and quality assurance activities, that reduce exposure to late-stage cost and schedule collapse due to unidentified risks in design, supply chain, and manufacturability. These DRDs drive the parties to engage in planning and analysis discussions early on to understand what production risks can be known and how they will focus resources based on safety criticality and the key elements of design and construction. The suppliers and acquirers who will produce the data and information required by the DRD will be able to incrementally evolve their QMS and the acquirer will incrementally be able to track and understand the benefits of cost shifting from late to early development phases. A white paper describing this approach and the five recommended DRDs will be published by the AIA in late 2024 or early 2025.

Jeannette Plante↗

Low-Loss Charge Transfer Plasmons in Graphene/α-RuCl 3 Heterostructures Below 40 K

Charge transfer at material interfaces governs a wide range of physical properties, from electronic band structures to emergent collective excitations. In two-dimensional (2D) material heterostructures, charge transfer phenomena play important roles in enabling novel quantum phases, proximity effects, and tunable plasmonic responses. One representative charge transfer interface is formed between α-RuCl 3 , a van der Waals material with high electron affinity, and graphene. Significant charge transfer across this interface induces the formation of charge-transfer plasmon polaritons (CPPs), hybrid excitations between light and charge oscillations. However, previous studies found that as the charge transfer process takes place, α-RuCl 3 becomes lossy, which limits the quality factor of CPPs. Here, we investigate CPPs down to 10 K using a home-built scattering-type scanning near-field optical microscope (s-SNOM) optimized for low-temperature measurements. Our study reveals a dramatic suppression of plasmon loss channels below 40 K, contributing to a significant enhancement in the plasmonic quality factor. This reduction in loss is likely attributed to the blue shift of the correlation-induced Mott gap in α-RuCl 3 with decreasing temperature, along with the reduction of phonon scattering at low temperature. In conclusion, our results highlight the potential of using s-SNOM and CPPs to study complex 2D interfaces and reveal correlated electron dynamics in the underlying material.

36 MATERIALS SCIENCE↗

Differential Seismic Phase Detection Probability as a Potential Discriminant of Explosions and Earthquakes

Deep learning models trained to estimate the probability of seismic P and S phases are rapidly expanding the scale of local event detections. Here, we evaluate the potential for deep learning model output phase detection probabilities to contribute to event‐type classification, particularly discrimination of single‐fired borehole explosions and earthquakes at local distances (<300 km). Motivated by the empirical success of P/S amplitude ratios, we consider the difference between P and S pick probability output from previously developed phase detection models, P prob −S prob ⁠, as a discriminant. Test data include M L ∼1–4 earthquakes and explosions observed by common seismographs in ten geologically diverse localities. Depending on the picking model and training data, binary classification using P prob −S prob with at least three stations can achieve approximately equivalent classification accuracy as P/S amplitude ratios without requiring any customization. Joint classification with P/S and P prob −S prob improves accuracy for most quality control scenarios. Pick probabilities are an efficient attribute to consider in explosion discrimination because they can be automated byproducts of event detection. They avoid the binary choice of picking or not picking weakly visible S waves common to explosions.

Duan, Chenglong [Rice Univ., Houston, TX (United S↗

COSMIC/NASTRAN-PATRAN Interface

A three dimensional solid modeling and finite element pre and postprocessing program, PATRAN, uses the latest interactive computer graphics technology, provides a visual means to define a finite element model and its environment, and reviews its resultant model behavior. The capabilities provided by the PATRAN-COSMIC/NASTRAN interface are discussed. While the translator capabilities give some indication of the interface quality between the two programs, there are other attributes to be considered. The ideal interface would be a user transparent union of the two programs so that the engineer could move from one program to the other fluently and naturally. Hence, a valid assessment of the interface completeness must consider how close the current capabilities are to the idealized case. An example problem is presented to demonstrate how COSMIC/NASTRAN and PATRAN can be used together to meet the requirements of an actual engineering application.

Libby, D. H.↗