A Generic Software Architecture For Prognostics

Prognostics is a systems engineering discipline focused on predicting end-of-life of components and systems. As a relatively new and emerging technology, there are few fielded implementations of prognostics, due in part to practitioners perceiving a large hurdle in developing the models, algorithms, architecture, and integration pieces. As a result, no open software frameworks for applying prognostics currently exist. This paper introduces the Generic Software Architecture for Prognostics (GSAP), an open-source, cross-platform, object-oriented software framework and support library for creating prognostics applications. GSAP was designed to make prognostics more accessible and enable faster adoption and implementation by industry, by reducing the effort and investment required to develop, test, and deploy prognostics. This paper describes the requirements, design, and testing of GSAP. Additionally, a detailed case study involving battery prognostics demonstrates its use

SILHIL Replication of Electric Aircraft Powertrain Dynamics and Inner-Loop Control for V&V of System Health Management Routines

Software-in-the-loop and Hardware-in-the-loop testing of failure prognostics and decision making tools for aircraft systems will facilitate more comprehensive and cost-effective testing than what is practical to conduct with flight tests. A framework is described for the offline recreation of dynamic loads on simulated or physical aircraft powertrain components based on a real-time simulation of airframe dynamics running on a flight simulator, an inner-loop flight control policy executed by either an autopilot routine or a human pilot, and a supervisory fault management control policy. The creation of an offline framework for verifying and validating supervisory failure prognostics and decision making routines is described for the example of battery charge depletion failure scenarios onboard a prototype electric unmanned aerial vehicle

System Engineering Paper

The Iowa State University team, Team LunaCY, is composed of the following sub-teams: the main student organization, the Lunabotics Club; a senior mechanical engineering design course, ME 415; a senior multidisciplinary design course, ENGR 466; and a senior design course from Wartburg College in Waverly, Iowa. Team LunaCY designed and fabricated ART-E III, Astra Robotic Tractor- Excavator the Third, for the team's third appearance in the NASA Lunabotic Mining competition. While designing ART-E III, the team had four main goals for this year's competition:to reduce the total weight of the robot, to increase the amount of regolith simulant mined, to reduce dust, and to make ART-E III autonomous. After many designs and research, a final robot design was chosen that obtained all four goals of Team LunaCY. A few changes Team LunaCY made this year was to go to the electrical, computer, and software engineering club fest at Iowa State University to recruit engineering students to accomplish the task of making ART-E III autonomous. Team LunaCY chose to use LabView to program the robot and various sensors were installed to measure the distance between the robot and the surroundings to allow ART-E III to maneuver autonomously. Team LunaCY also built a testing arena to test prototypes and ART-E III in. To best replicate the competition arena at the Kennedy Space Center, a regolith simulant was made from sand, QuickCrete, and fly ash to cover the floor of the arena. Team LunaCY also installed fans to allow ventilation in the arena and used proper safety attire when working in the arena . With the additional practice in the testing arena and innovative robot design, Team LunaCY expects to make a strong appearance at the 2012 NASA Lunabotic Mining Competition.

Housing and health in an informal settlement upgrade in Cape Town, South Africa

Taking a socio-ecological perspective the World Health Organisation recognizes that housing comprises four interrelated dimensions—the physical structure of the house, the home, the neighbourhood infrastructure and the community. Housing related health vulnerability arises when residents are exposed to poor conditions in any one of these dimensions and augmented when two or more co-exists. Regardless the relationship between housing and health in the global south remains largely under explored; in particular there has been little focus on health outcomes resulting from upgrading of informal settlements. Applying this framework we report from an in situ upgrading of the informal settlement of Imizamo Yethu in Cape Town, South Africa. Data gathered from surveys are used to determine whether differences in each of these dimensions exist between housing type; both formal upgrades and shacks. Results show that whilst no significant differences exist in self-reported physical health, residents of formal housing are less likely to report mental health issues, have a stronger sense of belonging and report greater satisfaction with both neighbourhood and home than shack residents. However, these contested spaces are not easily interpreted and community tension, exclusion and disadvantage highlight the complex interactions between each of the interrelated dimensions and policies regarding housing intervention. The paper highlights the complex relationship between housing and health that is often lost in simplistic measures of housing when outcomes related to the indoor environment alone are considered

Diagnosis of Non-small Cell Lung Cancer for Early Stage Asymptomatic Patients.

BACKGROUND/AIM: In 2016 in the United States, 7 of 10 patients were estimated to die following lung cancer diagnosis. This is due to a lack of a reliable screening method that detects early-stage lung cancer. Our aim is to accurately detect early stage lung cancer using algorithms and protein biomarkers. PATIENTS AND METHODS: A total of 1,479 human plasma samples were processed using a multiplex immunoassay platform. 82 biomarkers and 6 algorithms were explored. There were 351 NSCLC samples (90.3% Stage I, 2.3% Stage II, and 7.4% Stage III/IV). RESULTS: We identified 33 protein biomarkers and developed a classifier using Random Forest. Our test detected early-stage Non-Small Cell Lung Cancer (NSCLC) with a 90% accuracy, 80% sensitivity, and 95% specificity in the validation set using the 33 markers. CONCLUSION: A specific, non-invasive, early-detection test, in combination with low-dose computed tomography, could increase survival rates and reduce false positives from screenings

Blood test shows high accuracy in detecting stage I non-small cell lung cancer.

BACKGROUND: In a previous study (Goebel et. al, Cancer Genomics Proteomics 16:229-244, 2019), we identified 33 biomarkers for an early stage (I-II) Non-Small Cell Lung Cancer (NSCLC) test with 90% accuracy, 80.3% sensitivity, and 95.4% specificity. For the current study, we used a narrowed ensemble of 21 biomarkers while retaining similar accuracy in detecting early stage lung cancer. METHODS: A multiplex platform, 486 human plasma samples, and 21 biomarkers were used to develop and validate our algorithm which detects early stage NSCLC. The training set consisted of 258 human plasma with 79 Stage I-II NSCLC samples. The 21 biomarkers with the statistical model (Lung Cancer Detector Test 1, LCDT1) was then validated using 228 novel samples which included 55 Stage I NSCLC. RESULTS: The LCDT1 exhibited 95.6% accuracy, 89.1% sensitivity, and 97.7% specificity in detecting Stage I NSCLC on the blind set. When only NSCLC cancers were analyzed, the specificity increased to 99.1%. CONCLUSIONS: Compared to current approved clinical methods for diagnosing NSCLC, the LCDT1 greatly improves accuracy while being non-invasive; a simple, cost-effective, early diagnostic blood test should result in expanding access and increase survival rate

Systematic review of outcome domains and instruments used in clinical trials of tinnitus treatments in adults

BACKGROUND: There is no evidence-based guidance to facilitate design decisions for confirmatory trials or systematic reviews investigating treatment efficacy for adults with tinnitus. This systematic review therefore seeks to ascertain the current status of trial designs by identifying and evaluating the reporting of outcome domains and instruments in the treatment of adults with tinnitus. METHODS: Records were identified by searching PubMed, EMBASE CINAHL, EBSCO, and CENTRAL clinical trial registries (ClinicalTrials.gov, ISRCTN, ICTRP) and the Cochrane Database of Systematic Reviews. Eligible records were those published from 1 July 2006 to 12 March 2015. Included studies were those reporting adults aged 18 years or older who reported tinnitus as a primary complaint, and who were enrolled into a randomised controlled trial, a before and after study, a non-randomised controlled trial, a case-controlled study or a cohort study, and written in English. Studies with fewer than 20 participants were excluded. RESULTS: Two hundred and twenty-eight studies were included. Thirty-five different primary outcome domains were identified spanning seven categories (tinnitus percept, impact of tinnitus, co-occurring complaints, quality of life, body structures and function, treatment-related outcomes and unclear or not specified). Over half the studies (55 %) did not clearly define the complaint of interest. Tinnitus loudness was the domain most often reported (14 %), followed by tinnitus distress (7 %). Seventy-eight different primary outcome instruments were identified. Instruments assessing multiple attributes of the impact of tinnitus were most common (34 %). Overall, 24 different patient-reported tools were used, predominantly the Tinnitus Handicap Inventory (15 %). Loudness was measured in diverse ways including a numerical rating scale (8 %), loudness matching (4 %), minimum masking level (1 %) and loudness discomfort level (1 %). Ten percent of studies did not clearly report the instrument used. CONCLUSIONS: Our findings indicate poor appreciation of the basic principles of good trial design, particularly the importance of specifying what aspect of therapeutic benefit is the main outcome. No single outcome was reported in all studies and there was a broad diversity of outcome instruments. PROSPERO REGISTRATION: The systematic review protocol is registered on PROSPERO (International Prospective Register of Systematic Reviews): CRD42015017525. Registered on 12 March 2015 revised on 15 March 2016. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13063-016-1399-9) contains supplementary material, which is available to authorized users

Quantifying the Resilience-Informed Scenario Cost Sum: A Value-Driven Design Approach for Functional Hazard Assessment

Complex engineered systems can carry risk of high failure consequences, and as a result, resilience-the ability to avoid or quickly recover from faults-is desirable. Ideally, resilience should be designed-in as early in the design process as possible so that designers can best leverage the ability to explore the design space. Toward this end, previous work has developed functional modeling languages which represent the functions which must be performed by a system and function-based fault modeling frameworks have been developed to predict the resulting fault propagation behavior of a given functional model. However, little has been done to formally optimize or compare designs based on these predictions, partially because the effects of these models have not been quantified into an objective function to optimize. The work described herein closes this gap by introducing the resilience-informed scenario cost sum (RISCS), a scoring function which integrates with a fault scenario-based simulation, to enable the optimization and evaluation of functional model resilience. The scoring function accomplishes this by quantifying the expected cost of a design's fault response using probability information, and combining this cost with design and operational costs such that it may be parameterized in terms of designer-specified resilient features. The usefulness and limitations of using this approach in a general optimization and concept selection framework are discussed in general, and demonstrated on a monopropellant system design problem. Using RISCS as an objective for optimization, the algorithm selects the set of resilient features which provides the optimal trade-off between design cost and risk. For concept selection, RISCS is used to judge whether resilient concept variants justify their design costs and make direct comparisons between different model structures