OMV: A simplified mathematical model of the orbital maneuvering vehicle

A model of the orbital maneuvering vehicle (OMV) is presented which contains several simplications. A set of hand controller signals may be used to control the motion of the OMV. Model verification is carried out using a sequence of tests. The dynamic variables generated by the model are compared, whenever possible, with the corresponding analytical variables. The results of the tests show conclusively that the present model is behaving correctly. Further, this model interfaces properly with the state vector transformation module (SVX) developed previously. Correct command sentence sequences are generated by the OMV and and SVX system, and these command sequences can be used to drive the flat floor simulation system at MSFC

Embedded expert system for space shuttle main engine maintenance

The SPARTA Embedded Expert System (SEES) is an intelligent health monitoring system that directs analysis by placing confidence factors on possible engine status and then recommends a course of action to an engineer or engine controller. The technique can prevent catastropic failures or costly rocket engine down time because of false alarms. Further, the SEES has potential as an on-board flight monitor for reusable rocket engine systems. The SEES methodology synergistically integrates vibration analysis, pattern recognition and communications theory techniques with an artificial intelligence technique - the Embedded Expert System (EES)

Preliminary investigations on an enzyme immobilized optical biosensor for arsenite detection

Arsenite is an inorganic form of arsenic that poses hazardous effect to human. It is a common environmental heavy metal contaminant ubiquitously found in water and groundwater. In this study, an optical biosensor for arsenite determination was developed by immobilization of crude arsenite oxidase (Aio) extracted from recombinant E. coli, in chitosan solution coated on triacetyl-cellulose membrane employing DCPIP as colour indicator. The arsenite oxidase (Aio) was successfully expressed and extracted from recombinant E. coli strain BL21 (DE3). The protein concentration and specific activity of the crude arsenite oxidase were determined. Expression of Aio was confirmed by SDS-PAGE. The crude Aio was also successfully immobilized in chitosan and coated on triacetyl cellulose membrane. The response time and dynamic range of the optical biosensor were optimized. The response time of the developed biosensor was 15 minutes. The amount of DCPIP reduced (ΔA) was inversely proportional to the arsenite concentration. Standard calibration curve for arsenite detection was achieved within the range of arsenite concentration from 25 μM to 200 μM. The maximum detection limit was determined to be 250 μM arsenite

An Expected Average Run Length (EARL) Performance Comparison of the SSGR and EWMA Control Charts

The acceleration use of control charts in industrial processes has led to the effectiveness in their evaluation by quality practitioners. This is crucial, as it influences their decisions on the choice of which control charts to employ. This study aims to explore and compare the performance of the side sensitive group runs (SSGR) and exponentially weighted moving average (EWMA) control charts. In general, the average run length (ARL) characteristics were used to evaluate the performance of these control charts. The ARL, which considers the exact shift size in the process, is restricted in the case when the practitioner cannot identify the process shift size (unknown shift size). In this situation, the expected average run length (EARL) is an alternative performance criterion. Upon comparison of the findings obtained, the EWMA chart has superior performance when (δmin, δmax) = (0.1, 0.4). In contrast, the SSGR chart overtakes the EWMA chart when (δmin, δmax) = (0.5, 0.8) and (δmin, δmax) = (0.9, 1.2), except when the sample size n = 3 for (δmin, δmax) = (0.5, 0.8). For this particular combination, the EWMA chart performs slightly better than the SSGR chart. The outcome of this study is expected to contribute to practitioners in identifying suitable control charts in process monitoring and implementation

An Expected Average Run Length (EARL) Performance Comparison of the SSGR and EWMA Control Charts

The acceleration use of control charts in industrial processes has led to the effectiveness in their evaluation by quality practitioners. This is crucial, as it influences their decisions on the choice of which control charts to employ. This study aims to explore and compare the performance of the side sensitive group runs (SSGR) and exponentially weighted moving average (EWMA) control charts. In general, the average run length (ARL) characteristics were used to evaluate the performance of these control charts. The ARL, which considers the exact shift size in the process, is restricted in the case when the practitioner cannot identify the process shift size (unknown shift size). In this situation, the expected average run length (EARL) is an alternative performance criterion. Upon comparison of the findings obtained, the EWMA chart has superior performance when (δmin, δmax) = (0.1, 0.4). In contrast, the SSGR chart overtakes the EWMA chart when (δmin, δmax) = (0.5, 0.8) and (δmin, δmax) = (0.9, 1.2), except when the sample size n = 3 for (δmin, δmax) = (0.5, 0.8). For this particular combination, the EWMA chart performs slightly better than the SSGR chart. The outcome of this study is expected to contribute to practitioners in identifying suitable control charts in process monitoring and implementation

Improved fuzzy hashing technique for biometric template protection

Biometrics provides a new dimension of security to modern automated applications since each user will need to prove his identity when attempting an access. However, if a stored biometric template is compromised, then the conventional biometric recognition system becomes vulnerable to privacy invasion. This invasion is a permanent one because the biometric template is not replaceable. In this paper, we introduce an improved FuzzyHashing technique for biometric template protection purpose. We demonstrate our implementation in the context of fingerprint biometrics. The experimental results and the security analysis on FVC 2004 DB1 and DB2 fingerprint datasets suggest that the technique is highly feasible in practice

Opinion diversity and community formation in adaptive networks

It is interesting and of significant importance to investigate how network structures co-evolve with opinions. The existing models of such co-evolution typically lead to the final states where network nodes either reach a global consensus or break into separated communities, each of which holding its own community consensus. Such results, however, can hardly explain the richness of real-life observations that opinions are always diversified with no global or even community consensus, and people seldom, if not never, totally cut off themselves from dissenters. In this article, we show that, a simple model integrating consensus formation, link rewiring and opinion change allows complex system dynamics to emerge, driving the system into a dynamic equilibrium with co-existence of diversified opinions. Specifically, similar opinion holders may form into communities yet with no strict community consensus; and rather than being separated into disconnected communities, different communities remain to be interconnected by non-trivial proportion of inter-community links. More importantly, we show that the complex dynamics may lead to different numbers of communities at steady state with a given tolerance between different opinion holders. We construct a framework for theoretically analyzing the co-evolution process. Theoretical analysis and extensive simulation results reveal some useful insights into the complex co-evolution process, including the formation of dynamic equilibrium, the phase transition between different steady states with different numbers of communities, and the dynamics between opinion distribution and network modularity, etc.Comment: 12 pages, 8 figures, Journa

Cholesterol-lowering drugs cause dissolution of cholesterol crystals and disperse Kupffer cell crown-like structures during resolution of NASH

Cholesterol crystals form within hepatocyte lipid droplets in human and experimental nonalcoholic steatohepatitis (NASH) and are the focus of crown-like structures (CLSs) of activated Kupffer cells (KCs). Obese, diabetic Alms1 mutant ( foz/foz ) mice were a fed high-fat (23%) diet containing 0.2% cholesterol for 16 weeks and then assigned to four intervention groups for 8 weeks: a ) vehicle control, b ) ezetimibe (5 mg/kg/day), c ) atorvastatin (20 mg/kg/day), or d ) ezetimibe and atorvastatin. Livers of vehicle-treated mice developed fibrosing NASH with abundant cholesterol crystallization within lipid droplets calculated to extend over 3.3% (SD, 2.2%) of liver surface area. Hepatocyte lipid droplets with prominent cholesterol crystallization were surrounded by TNFα -positive (activated) KCs forming CLSs ( ≥ 3 per high-power field). KCs that formed CLSs stained positive for NLRP3, implicating activation of the NLRP3 inflammasome in response to cholesterol crystals. In contrast, foz/foz mice treated with ezetimibe and atorvastatin showed near-complete resolution of cholesterol crystals [0.01% (SD, 0.02%) of surface area] and CLSs (0 per high-power field), with amelioration of fibrotic NASH. Ezetimibe or atorvastatin alone had intermediate effects on cholesterol crystallization, CLSs, and NASH. These findings are consistent with a causative link between exposure of hepatocytes and KCs to cholesterol crystals and with the development of NASH possibly mediated by NLRP3 activation