Generation of 8.3 dB continuous variable quantum entanglement at a telecommunication wavelength of 1550 nm

NASA Astrophysics Data System (ADS)

Jinxia, Feng; Zhenju, Wan; Yuanji, Li; Kuanshou, Zhang

2018-01-01

Continuous variable quantum entanglement at a telecommunication wavelength of 1550 nm is experimentally generated using a single nondegenerate optical parametric amplifier based on a type-II periodically poled KTiOPO4 crystal. The triply resonant of the nondegenerate optical parametric amplifier is adjusted by tuning the crystal temperature and tilting the orientation of the crystal in the optical cavity. Einstein-Podolsky-Rosen-entangled beams with quantum correlations of 8.3 dB for both the amplitude and phase quadratures are experimentally generated. This system can be used for continuous variable fibre-based quantum communication.

Generation of noncircular gears for variable motion of the crank-slider mechanism

NASA Astrophysics Data System (ADS)

Niculescu, M.; Andrei, L.; Cristescu, A.

2016-08-01

The paper proposes a modified kinematics for the crank-slider mechanism of a nails machine. The variable rotational motion of the driven gear allows to slow down the velocity of the slider in the head forming phase and increases the period for the forming forces to be applied, improving the quality of the final product. The noncircular gears are designed based on a hybrid function for the gear transmission ratio whose parameters enable multiple variations of the noncircular driven gears and crack-slider mechanism kinematics, respectively. The AutoCAD graphical and programming facilities are used (i) to analyse and optimize the slider-crank mechanism output functions, in correlation with the predefined noncircular gears transmission ratio, (ii) to generate the noncircular centrodes using the kinematics hypothesis, (iii) to generate the variable geometry of the gear teeth profiles, based on the rolling method, and (iv) to produce the gears solid virtual models. The study highlights the benefits/limits that the noncircular gears transmission ratio defining hybrid functions have on both crank-slider mechanism kinematics and gears geometry.

Multiple and variable speed electrical generator systems for large wind turbines

NASA Technical Reports Server (NTRS)

Andersen, T. S.; Hughes, P. S.; Kirschbaum, H. S.; Mutone, G. A.

1982-01-01

A cost effective method to achieve increased wind turbine generator energy conversion and other operational benefits through variable speed operation is presented. Earlier studies of multiple and variable speed generators in wind turbines were extended for evaluation in the context of a specific large sized conceptual design. System design and simulation have defined the costs and performance benefits which can be expected from both two speed and variable speed configurations.

Variable speed wind turbine generator with zero-sequence filter

DOEpatents

Muljadi, Eduard

1998-01-01

A variable speed wind turbine generator system to convert mechanical power into electrical power or energy and to recover the electrical power or energy in the form of three phase alternating current and return the power or energy to a utility or other load with single phase sinusoidal waveform at sixty (60) hertz and unity power factor includes an excitation controller for generating three phase commanded current, a generator, and a zero sequence filter. Each commanded current signal includes two components: a positive sequence variable frequency current signal to provide the balanced three phase excitation currents required in the stator windings of the generator to generate the rotating magnetic field needed to recover an optimum level of real power from the generator; and a zero frequency sixty (60) hertz current signal to allow the real power generated by the generator to be supplied to the utility. The positive sequence current signals are balanced three phase signals and are prevented from entering the utility by the zero sequence filter. The zero sequence current signals have zero phase displacement from each other and are prevented from entering the generator by the star connected stator windings. The zero sequence filter allows the zero sequence current signals to pass through to deliver power to the utility.

Variable Speed Wind Turbine Generator with Zero-sequence Filter

DOEpatents

Muljadi, Eduard

1998-08-25

A variable speed wind turbine generator system to convert mechanical power into electrical power or energy and to recover the electrical power or energy in the form of three phase alternating current and return the power or energy to a utility or other load with single phase sinusoidal waveform at sixty (60) hertz and unity power factor includes an excitation controller for generating three phase commanded current, a generator, and a zero sequence filter. Each commanded current signal includes two components: a positive sequence variable frequency current signal to provide the balanced three phase excitation currents required in the stator windings of the generator to generate the rotating magnetic field needed to recover an optimum level of real power from the generator; and a zero frequency sixty (60) hertz current signal to allow the real power generated by the generator to be supplied to the utility. The positive sequence current signals are balanced three phase signals and are prevented from entering the utility by the zero sequence filter. The zero sequence current signals have zero phase displacement from each other and are prevented from entering the generator by the star connected stator windings. The zero sequence filter allows the zero sequence current signals to pass through to deliver power to the utility.

Variable speed wind turbine generator with zero-sequence filter

DOEpatents

Muljadi, E.

1998-08-25

A variable speed wind turbine generator system to convert mechanical power into electrical power or energy and to recover the electrical power or energy in the form of three phase alternating current and return the power or energy to a utility or other load with single phase sinusoidal waveform at sixty (60) hertz and unity power factor includes an excitation controller for generating three phase commanded current, a generator, and a zero sequence filter. Each commanded current signal includes two components: a positive sequence variable frequency current signal to provide the balanced three phase excitation currents required in the stator windings of the generator to generate the rotating magnetic field needed to recover an optimum level of real power from the generator; and a zero frequency sixty (60) hertz current signal to allow the real power generated by the generator to be supplied to the utility. The positive sequence current signals are balanced three phase signals and are prevented from entering the utility by the zero sequence filter. The zero sequence current signals have zero phase displacement from each other and are prevented from entering the generator by the star connected stator windings. The zero sequence filter allows the zero sequence current signals to pass through to deliver power to the utility. 14 figs.

An evolution based biosensor receptor DNA sequence generation algorithm.

PubMed

Kim, Eungyeong; Lee, Malrey; Gatton, Thomas M; Lee, Jaewan; Zang, Yupeng

2010-01-01

A biosensor is composed of a bioreceptor, an associated recognition molecule, and a signal transducer that can selectively detect target substances for analysis. DNA based biosensors utilize receptor molecules that allow hybridization with the target analyte. However, most DNA biosensor research uses oligonucleotides as the target analytes and does not address the potential problems of real samples. The identification of recognition molecules suitable for real target analyte samples is an important step towards further development of DNA biosensors. This study examines the characteristics of DNA used as bioreceptors and proposes a hybrid evolution-based DNA sequence generating algorithm, based on DNA computing, to identify suitable DNA bioreceptor recognition molecules for stable hybridization with real target substances. The Traveling Salesman Problem (TSP) approach is applied in the proposed algorithm to evaluate the safety and fitness of the generated DNA sequences. This approach improves efficiency and stability for enhanced and variable-length DNA sequence generation and allows extension to generation of variable-length DNA sequences with diverse receptor recognition requirements.

GeneratorSE: A Sizing Tool for Variable-Speed Wind Turbine Generators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sethuraman, Latha; Dykes, Katherine L

This report documents a set of analytical models employed by the optimization algorithms within the GeneratorSE framework. The initial values and boundary conditions employed for the generation of the various designs and initial estimates for basic design dimensions, masses, and efficiency for the four different models of generators are presented and compared with empirical data collected from previous studies and some existing commercial turbines. These models include designs applicable for variable-speed, high-torque application featuring direct-drive synchronous generators and low-torque application featuring induction generators. In all of the four models presented, the main focus of optimization is electromagnetic design with themore » exception of permanent-magnet and wire-wound synchronous generators, wherein the structural design is also optimized. Thermal design is accommodated in GeneratorSE as a secondary attribute by limiting the winding current densities to acceptable limits. A preliminary validation of electromagnetic design was carried out by comparing the optimized magnetic loading against those predicted by numerical simulation in FEMM4.2, a finite-element software for analyzing electromagnetic and thermal physics problems for electrical machines. For direct-drive synchronous generators, the analytical models for the structural design are validated by static structural analysis in ANSYS.« less

A conceptual framework for evaluating variable speed generator options for wind energy applications

NASA Technical Reports Server (NTRS)

Reddoch, T. W.; Lipo, T. A.; Hinrichsen, E. N.; Hudson, T. L.; Thomas, R. J.

1995-01-01

Interest in variable speed generating technology has accelerated as greater emphasis on overall efficiency and superior dynamic and control properties in wind-electric generating systems are sought. This paper reviews variable speed technology options providing advantages and disadvantages of each. Furthermore, the dynamic properties of variable speed systems are contrasted with synchronous operation. Finally, control properties of variable speed systems are examined.

Concurrent generation of multivariate mixed data with variables of dissimilar types.

PubMed

Amatya, Anup; Demirtas, Hakan

2016-01-01

Data sets originating from wide range of research studies are composed of multiple variables that are correlated and of dissimilar types, primarily of count, binary/ordinal and continuous attributes. The present paper builds on the previous works on multivariate data generation and develops a framework for generating multivariate mixed data with a pre-specified correlation matrix. The generated data consist of components that are marginally count, binary, ordinal and continuous, where the count and continuous variables follow the generalized Poisson and normal distributions, respectively. The use of the generalized Poisson distribution provides a flexible mechanism which allows under- and over-dispersed count variables generally encountered in practice. A step-by-step algorithm is provided and its performance is evaluated using simulated and real-data scenarios.

Capacity expansion model of wind power generation based on ELCC

NASA Astrophysics Data System (ADS)

Yuan, Bo; Zong, Jin; Wu, Shengyu

2018-02-01

Capacity expansion is an indispensable prerequisite for power system planning and construction. A reasonable, efficient and accurate capacity expansion model (CEM) is crucial to power system planning. In most current CEMs, the capacity of wind power generation is considered as boundary conditions instead of decision variables, which may lead to curtailment or over construction of flexible resource, especially at a high renewable energy penetration scenario. This paper proposed a wind power generation capacity value(CV) calculation method based on effective load-carrying capability, and a CEM that co-optimizes wind power generation and conventional power sources. Wind power generation is considered as decision variable in this model, and the model can accurately reflect the uncertainty nature of wind power.

Computer-generated tailored feedback letters for smoking cessation: theoretical and empirical variability of tailoring.

PubMed

Schumann, Anja; John, Ulrich; Ulbricht, Sabina; Rüge, Jeannette; Bischof, Gallus; Meyer, Christian

2008-11-01

This study examines tailored feedback letters of a smoking cessation intervention that is conceptually based on the transtheoretical model, from a content-based perspective. Data of 2 population-based intervention studies, both randomized controlled trials, with total N=1044 were used. The procedure of the intervention, the tailoring principle for the feedback letters, and the content of the intervention materials are described in detail. Theoretical and empirical frequencies of unique feedback letters are presented. The intervention system was able to generate a total of 1040 unique letters with normative feedback only, and almost half a million unique letters with normative and ipsative feedback. Almost every single smoker in contemplation, preparation, action, and maintenance had an empirically unique combination of tailoring variables and received a unique letter. In contrast, many smokers in precontemplation shared a combination of tailoring variables and received identical letters. The transtheoretical model provides an enormous theoretical and empirical variability of tailoring. However, tailoring for a major subgroup of smokers, i.e. those who do not intend to quit, needs improvement. Conceptual ideas for additional tailoring variables are discussed.

Effect of age on variability in the production of text-based global inferences.

PubMed

Williams, Lynne J; Dunlop, Joseph P; Abdi, Hervé

2012-01-01

As we age, our differences in cognitive skills become more visible, an effect especially true for memory and problem solving skills (i.e., fluid intelligence). However, by contrast with fluid intelligence, few studies have examined variability in measures that rely on one's world knowledge (i.e., crystallized intelligence). The current study investigated whether age increased the variability in text based global inference generation--a measure of crystallized intelligence. Global inference generation requires the integration of textual information and world knowledge and can be expressed as a gist or lesson. Variability in generating two global inferences for a single text was examined in young-old (62 to 69 years), middle-old (70 to 76 years) and old-old (77 to 94 years) adults. The older two groups showed greater variability, with the middle elderly group being most variable. These findings suggest that variability may be a characteristic of both fluid and crystallized intelligence in aging.

Power Maximization Control of Variable Speed Wind Generation System Using Permanent Magnet Synchronous Generator

NASA Astrophysics Data System (ADS)

Morimoto, Shigeo; Nakamura, Tomohiko; Takeda, Yoji

This paper proposes the sensorless output power maximization control of the wind generation system. A permanent magnet synchronous generator (PMSG) is used as a variable speed generator in the proposed system. The generator torque is suitably controlled according to the generator speed and thus the power from a wind turbine settles down on the maximum power point by the proposed MPPT control method, where the information of wind velocity is not required. Moreover, the maximum available generated power is obtained by the optimum current vector control. The current vector of PMSG is optimally controlled according to the generator speed and the required torque in order to minimize the losses of PMSG considering the voltage and current constraints. The proposed wind power generation system can be achieved without mechanical sensors such as a wind velocity detector and a position sensor. Several experimental results show the effectiveness of the proposed control method.

Generating Variable Wind Profiles and Modeling Their Effects on Small-Arms Trajectories

DTIC Science & Technology

2016-04-01

ARL-TR-7642 ● APR 2016 US Army Research Laboratory Generating Variable Wind Profiles and Modeling Their Effects on Small-Arms... Wind Profiles and Modeling Their Effects on Small-Arms Trajectories by Timothy A Fargus Weapons and Materials Research Directorate, ARL...Generating Variable Wind Profiles and Modeling Their Effects on Small-Arms Trajectories 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM

Variable frequency microprocessor clock generator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Branson, C.N.

A microprocessor-based system is described comprising: a digital central microprocessor provided with a clock input and having a rate of operation determined by the frequency of a clock signal input thereto; memory means operably coupled to the central microprocessor for storing programs respectively including a plurality of instructions and addressable by the central microprocessor; peripheral device operably connected to the central microprocessor, the first peripheral device being addressable by the central microprocessor for control thereby; a system clock generator for generating a digital reference clock signal having a reference frequency rate; and frequency rate reduction circuit means connected between themore » clock generator and the clock input of the central microprocessor for selectively dividing the reference clock signal to generate a microprocessor clock signal as an input to the central microprocessor for clocking the central microprocessor.« less

Reproducibility, stability, and biological variability of thrombin generation using calibrated automated thrombography in healthy dogs.

PubMed

Cuq, Benoît; Blois, Shauna L; Wood, R Darren; Monteith, Gabrielle; Abrams-Ogg, Anthony C; Bédard, Christian; Wood, Geoffrey A

2018-06-01

Thrombin plays a central role in hemostasis and thrombosis. Calibrated automated thrombography (CAT), a thrombin generation assay, may be a useful test for hemostatic disorders in dogs. To describe CAT results in a group of healthy dogs, and assess preanalytical variables and biological variability. Forty healthy dogs were enrolled. Lag time (Lag), time to peak (ttpeak), peak thrombin generation (peak), and endogenous thrombin potential (ETP) were measured. Direct jugular venipuncture and winged-needle catheter-assisted saphenous venipuncture were used to collect samples from each dog, and results were compared between methods. Sample stability at -80°C was assessed over 12 months in a subset of samples. Biological variability of CAT was assessed via nested ANOVA using samples obtained weekly from a subset of 9 dogs for 4 consecutive weeks. Samples for CAT were stable at -80°C over 12 months of storage. Samples collected via winged-needle catheter venipuncture showed poor repeatability compared to direct venipuncture samples; there was also poor agreement between the 2 sampling methods. Intra-individual variability of CAT parameters was below 25%; inter-individual variability ranged from 36.9% to 78.5%. Measurement of thrombin generation using CAT appears to be repeatable in healthy dogs, and samples are stable for at least 12 months when stored at -80°C. Direct venipuncture sampling is recommended for CAT. Low indices of individuality suggest that subject-based reference intervals are more suitable when interpreting CAT results. © 2018 American Society for Veterinary Clinical Pathology.

Numerical investigation for entropy generation in hydromagnetic flow of fluid with variable properties and slip

NASA Astrophysics Data System (ADS)

Khan, M. Ijaz; Hayat, Tasawar; Alsaedi, Ahmed

2018-02-01

This modeling and computations present the study of viscous fluid flow with variable properties by a rotating stretchable disk. Rotating flow is generated through nonlinear rotating stretching surface. Nonlinear thermal radiation and heat generation/absorption are studied. Flow is conducting for a constant applied magnetic field. No polarization is taken. Induced magnetic field is not taken into account. Attention is focused on the entropy generation rate and Bejan number. The entropy generation rate and Bejan number clearly depend on velocity and thermal fields. The von Kármán approach is utilized to convert the partial differential expressions into ordinary ones. These expressions are non-dimensionalized, and numerical results are obtained for flow variables. The effects of the magnetic parameter, Prandtl number, radiative parameter, heat generation/absorption parameter, and slip parameter on velocity and temperature fields as well as the entropy generation rate and Bejan number are discussed. Drag forces (radial and tangential) and heat transfer rates are calculated and discussed. Furthermore the entropy generation rate is a decreasing function of magnetic variable and Reynolds number. The Bejan number effect on the entropy generation rate is reverse to that of the magnetic variable. Also opposite behavior of heat transfers is observed for varying estimations of radiative and slip variables.

Design of a variable width pulse generator feasible for manual or automatic control

NASA Astrophysics Data System (ADS)

Vegas, I.; Antoranz, P.; Miranda, J. M.; Franco, F. J.

2017-01-01

A variable width pulse generator featuring more than 4-V peak amplitude and less than 10-ns FWHM is described. In this design the width of the pulses is controlled by means of the control signal slope. Thus, a variable transition time control circuit (TTCC) is also developed, based on the charge and discharge of a capacitor by means of two tunable current sources. Additionally, it is possible to activate/deactivate the pulses when required, therefore allowing the creation of any desired pulse pattern. Furthermore, the implementation presented here can be electronically controlled. In conclusion, due to its versatility, compactness and low cost it can be used in a wide variety of applications.

The intention to continue nursing: work variables affecting three nurse generations in Australia.

PubMed

Shacklock, Kate; Brunetto, Yvonne

2012-01-01

The aims of the study were to examine how seven variables impacted upon the intention of hospital nurses to continue working as nurses and to investigate whether there are generational differences in these impacts. There is a critical shortage of trained nurses working as nurses in Australia, as in many other Organisation for Economic Co-operation and Development member countries. The retention of nurses has been examined from the traditional management perspectives; however, this paper presents a different approach (Meaning of Working theory). A self-report survey of 900 nurses employed across four states of Australia was completed in 2008. The sample was hospital nurses in Australia from three generational cohorts - Baby Boomers (born in Australia between 1946 and 1964), Generation X (1965-1979) and Generation Y (1980-2000). Six variables were found to influence the combined nurses' intentions to continue working as nurses: work-family conflict, perceptions of autonomy, attachment to work, importance of working to the individual, supervisor-subordinate relationship and interpersonal relationships at work. There were differences in the variables affecting the three generations, but attachment to work was the only common variable across all generations, affecting GenYs the strongest. The shortage of nurses is conceptualized differently in this paper to assist in finding solutions. However, the results varied for the three generations, suggesting the need to tailor different retention strategies to each age group. Implications for management and policy planning are discussed. © 2011 Blackwell Publishing Ltd.

Teleportation-based continuous variable quantum cryptography

NASA Astrophysics Data System (ADS)

Luiz, F. S.; Rigolin, Gustavo

2017-03-01

We present a continuous variable (CV) quantum key distribution (QKD) scheme based on the CV quantum teleportation of coherent states that yields a raw secret key made up of discrete variables for both Alice and Bob. This protocol preserves the efficient detection schemes of current CV technology (no single-photon detection techniques) and, at the same time, has efficient error correction and privacy amplification schemes due to the binary modulation of the key. We show that for a certain type of incoherent attack, it is secure for almost any value of the transmittance of the optical line used by Alice to share entangled two-mode squeezed states with Bob (no 3 dB or 50% loss limitation characteristic of beam splitting attacks). The present CVQKD protocol works deterministically (no postselection needed) with efficient direct reconciliation techniques (no reverse reconciliation) in order to generate a secure key and beyond the 50% loss case at the incoherent attack level.

Direct generation of spatial quadripartite continuous variable entanglement in an optical parametric oscillator.

PubMed

Liu, Kui; Guo, Jun; Cai, Chunxiao; Zhang, Junxiang; Gao, Jiangrui

2016-11-15

Multipartite entanglement is used for quantum information applications, such as building multipartite quantum communications. Generally, generation of multipartite entanglement is based on a complex beam-splitter network. Here, based on the spatial freedom of light, we experimentally demonstrated spatial quadripartite continuous variable entanglement among first-order Hermite-Gaussian modes using a single type II optical parametric oscillator operating below threshold with an HG0245° pump beam. The entanglement can be scalable for larger numbers of spatial modes by changing the spatial profile of the pump beam. In addition, spatial multipartite entanglement will be useful for future spatial multichannel quantum information applications.

Effect of Age on Variability in the Production of Text-Based Global Inferences

PubMed Central

Williams, Lynne J.; Dunlop, Joseph P.; Abdi, Hervé

2012-01-01

As we age, our differences in cognitive skills become more visible, an effect especially true for memory and problem solving skills (i.e., fluid intelligence). However, by contrast with fluid intelligence, few studies have examined variability in measures that rely on one’s world knowledge (i.e., crystallized intelligence). The current study investigated whether age increased the variability in text based global inference generation–a measure of crystallized intelligence. Global inference generation requires the integration of textual information and world knowledge and can be expressed as a gist or lesson. Variability in generating two global inferences for a single text was examined in young-old (62 to 69 years), middle-old (70 to 76 years) and old-old (77 to 94 years) adults. The older two groups showed greater variability, with the middle elderly group being most variable. These findings suggest that variability may be a characteristic of both fluid and crystallized intelligence in aging. PMID:22590523

Demonstration of variable speed permanent magnet generator at small, low-head hydro site

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown Kinloch, David

Small hydro developers face a limited set of bad choices when choosing a generator for a small low-head hydro site. Direct drive synchronous generators are expensive and technically complex to install. Simpler induction generators are higher speed, requiring a speed increaser, which results in inefficiencies and maintenance problems. In addition, both induction and synchronous generators turn at a fixed speed, causing the turbine to run off its peak efficiency curve whenever the available head is different than the designed optimum head.The solution to these problems is the variable speed Permanent Magnet Generators (PMG). At the Weisenberger Mill in Midway, KY,more » a variable speed Permanent Magnet Generator has been installed and demonstrated. This new PMG system replaced an existing induction generator that had a HTD belt drive speed increaser system. Data was taken from the old generator before it was removed and compared to data collected after the PMG system was installed. The new variable speed PMG system is calculated to produce over 96% more energy than the old induction generator system during an average year. This significant increase was primarily due to the PMG generator operating at the correct speed at the maximum head, and the ability for the PMG generator to reduce its speed to lower optimum speeds as the stream flow increased and the net head decreased.This demonstration showed the importance of being able to adjust the speed of fixed blade turbines. All fixed blade turbines with varying net heads could achieve higher efficiencies if the speed can be matched to the optimum speed as the head changes. In addition, this demonstration showed that there are many potential efficiencies that could be realized with variable speed technology at hydro sites where mismatched turbine and generator speeds result in lower power output, even at maximum head. Funding for this project came from the US Dept. of Energy, through Award Number DE-EE0005429.« less

Variable speed generator application on the MOD-5A 7.3 mW wind turbine generator

NASA Technical Reports Server (NTRS)

Barton, Robert S.

1995-01-01

This paper describes the application of a Scherbiustat type variable speed subsystem in the MOD-5A Wind Turbine Generator. As designed by General Electric Company, Advanced Energy Programs Department, under contract DEN3-153 with NASA Lewis Research Center and DOE, the MOD-5A utilizes the subsystem for both starting assistance in a motoring mode and generation in a controlled airgap torque mode. Reactive power control is also provided. The Scherbiustat type arrangement of a wound rotor machine with a cycloconverter in the rotor circuit was selected after an evaluation of variable speed technologies that followed a system evaluation of drivetrain cost and risk. The paper describes the evaluation factors considered, the results of the evaluations and summarizes operating strategy and performance simulations.

Competency-Based, Time-Variable Education in the Health Professions: Crossroads.

PubMed

Lucey, Catherine R; Thibault, George E; Ten Cate, Olle

2018-03-01

Health care systems around the world are transforming to align with the needs of 21st-century patients and populations. Transformation must also occur in the educational systems that prepare the health professionals who deliver care, advance discovery, and educate the next generation of physicians in these evolving systems. Competency-based, time-variable education, a comprehensive educational strategy guided by the roles and responsibilities that health professionals must assume to meet the needs of contemporary patients and communities, has the potential to catalyze optimization of educational and health care delivery systems. By designing educational and assessment programs that require learners to meet specific competencies before transitioning between the stages of formal education and into practice, this framework assures the public that every physician is capable of providing high-quality care. By engaging learners as partners in assessment, competency-based, time-variable education prepares graduates for careers as lifelong learners. While the medical education community has embraced the notion of competencies as a guiding framework for educational institutions, the structure and conduct of formal educational programs remain more aligned with a time-based, competency-variable paradigm.The authors outline the rationale behind this recommended shift to a competency-based, time-variable education system. They then introduce the other articles included in this supplement to Academic Medicine, which summarize the history of, theories behind, examples demonstrating, and challenges associated with competency-based, time-variable education in the health professions.

The experimental studies of operating modes of a diesel-generator set at variable speed

NASA Astrophysics Data System (ADS)

Obukhov, S. G.; Plotnikov, I. A.; Surkov, M. A.; Sumarokova, L. P.

2017-02-01

A diesel generator set working at variable speed to save fuel is studied. The results of experimental studies of the operating modes of an autonomous diesel generator set are presented. Areas for regulating operating modes are determined. It is demonstrated that the transfer of the diesel generator set to variable speed of the diesel engine makes it possible to improve the energy efficiency of the autonomous generator source, as well as the environmental and ergonomic performance of the equipment as compared with general industrial analogues.

UDE-based control of variable-speed wind turbine systems

NASA Astrophysics Data System (ADS)

Ren, Beibei; Wang, Yeqin; Zhong, Qing-Chang

2017-01-01

In this paper, the control of a PMSG (permanent magnet synchronous generator)-based variable-speed wind turbine system with a back-to-back converter is considered. The uncertainty and disturbance estimator (UDE)-based control approach is applied to the regulation of the DC-link voltage and the control of the RSC (rotor-side converter) and the GSC (grid-side converter). For the rotor-side controller, the UDE-based vector control is developed for the RSC with PMSG control to facilitate the application of the MPPT (maximum power point tracking) algorithm for the maximum wind energy capture. For the grid-side controller, the UDE-based vector control is developed to control the GSC with the power reference generated by a UDE-based DC-link voltage controller. Compared with the conventional vector control, the UDE-based vector control can achieve reliable current decoupling control with fast response. Moreover, the UDE-based DC-link voltage regulation can achieve stable DC-link voltage under model uncertainties and external disturbances, e.g. wind speed variations. The effectiveness of the proposed UDE-based control approach is demonstrated through extensive simulation studies in the presence of coupled dynamics, model uncertainties and external disturbances under varying wind speeds. The UDE-based control is able to generate more energy, e.g. by 5% for the wind profile tested.

PCA-LBG-based algorithms for VQ codebook generation

NASA Astrophysics Data System (ADS)

Tsai, Jinn-Tsong; Yang, Po-Yuan

2015-04-01

Vector quantisation (VQ) codebooks are generated by combining principal component analysis (PCA) algorithms with Linde-Buzo-Gray (LBG) algorithms. All training vectors are grouped according to the projected values of the principal components. The PCA-LBG-based algorithms include (1) PCA-LBG-Median, which selects the median vector of each group, (2) PCA-LBG-Centroid, which adopts the centroid vector of each group, and (3) PCA-LBG-Random, which randomly selects a vector of each group. The LBG algorithm finds a codebook based on the better vectors sent to an initial codebook by the PCA. The PCA performs an orthogonal transformation to convert a set of potentially correlated variables into a set of variables that are not linearly correlated. Because the orthogonal transformation efficiently distinguishes test image vectors, the proposed PCA-LBG-based algorithm is expected to outperform conventional algorithms in designing VQ codebooks. The experimental results confirm that the proposed PCA-LBG-based algorithms indeed obtain better results compared to existing methods reported in the literature.

Active Power and Flux Control of a Self-Excited Induction Generator for a Variable-Speed Wind Turbine Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Na, Woonki; Muljadi, Eduard; Leighty, Bill

A Self-Excited Induction Generation (SEIG) for a variable speed wind turbine generation(VS-WG) is normally considered to be a good candidate for implementation in stand-alone applications such as battery charging, hydrogenation, water pumping, water purification, water desalination, and etc. In this study, we have examined a study on active power and flux control strategies for a SEIG for a variable speed wind turbine generation. The control analysis for the proposed system is carried out by using PSCAD software. In the process, we can optimize the control design of the system, thereby enhancing and expediting the control design procedure for this application.more » With this study, this control design for a SEIG for VS-WG can become the industry standard for analysis and development in terms of SEIG.« less

Variable-speed Generators with Flux Weakening

NASA Technical Reports Server (NTRS)

Fardoun, A. A.; Fuchs, E. F.; Carlin, P. W.

1993-01-01

A cost-competitive, permanent-magnet 20 kW generator is designed such that the following criteria are satisfied: an (over) load capability of at least 30 kW over the entire speed range of 60-120 rpm, generator weight of about 550 lbs with a maximum radial stator flux density of 0.82 T at low speed, unity power factor operation, acceptably small synchronous reactances and operation without a gear box. To justify this final design four different generator designs are investigated: the first two designs are studied to obtain a speed range from 20 to 200 rpm employing rotor field weakening, and the latter two are investigated to obtain a maximum speed range of 40 to 160 rpm based on field weakening via the stator excitation. The generator reactances and induced voltages are computed using finite element/difference solutions. Generator losses and efficiencies are presented for all four designs at rated temperature of Tr=120C.

Recent Trends in Variable Generation Forecasting and Its Value to the Power System

DOE PAGES

Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; ...

2014-12-23

We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value ofmore » adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.« less

Internal Variability-Generated Uncertainty in East Asian Climate Projections Estimated with 40 CCSM3 Ensembles.

PubMed

Yao, Shuai-Lei; Luo, Jing-Jia; Huang, Gang

2016-01-01

Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation and surface air temperature (SAT) trends during 2005-2055 over East Asia based on 40 member ensemble projections of the Community Climate System Model Version 3 (CCSM3). The model ensembles are generated from a suite of different atmospheric initial conditions using the same SRES A1B greenhouse gas scenario. We find that projected precipitation trends are subject to considerably larger internal uncertainty and hence have lower confidence, compared to the projected SAT trends in both the boreal winter and summer. Projected SAT trends in winter have relatively higher uncertainty than those in summer. Besides, the lower-level atmospheric circulation has larger uncertainty than that in the mid-level. Based on k-means cluster analysis, we demonstrate that a substantial portion of internally-induced precipitation and SAT trends arises from internal large-scale atmospheric circulation variability. These results highlight the importance of internal climate variability in affecting regional climate projections on multi-decadal timescales.

A variable-speed, constant-frequency wind power generation scheme using a slip-ring induction generator

NASA Astrophysics Data System (ADS)

Velayudhan, C.; Bundell, J. H.

This paper investigates a variable-speed, constant-frequency double output induction generator which is capable of absorbing the mechanical energy from a fixed pitch wind turbine and converting it into electrical energy at constant grid voltage and frequency. Rotor power at varying voltage and frequency is either fed to electronically controlled resistances and used as heat energy or is rectified, inverted by a controllable line-commutated inverter and returned to the grid. Optimal power tracking is by means of an adaptive controller which controls the developed torque of the generator by monitoring the shaft speed.

Variable directionality of gene expression changes across generations does not constitute negative evidence of epigenetic inheritance.

PubMed

Sharma, Abhay

2015-01-01

Transgenerational epigenetic inheritance in mammals has been controversial due to inherent difficulties in its experimental demonstration. A recent report has, however, opened a new front in the ongoing debate by claiming that endocrine disrupting chemicals, contrary to previous findings, do not cause effects across generations. This claim is based on the observation that gene expression changes induced by these chemicals in the exposed and unexposed generations are mainly in the opposite direction. This analysis shows that the pattern of gene expression reported in the two generations is not expected by chance and is suggestive of transmission across generations. A meta-analysis of diverse data sets related to endocrine disruptor-induced transgenerational gene expression alterations, including the data provided in the said report, further suggests that effects of endocrine disrupting chemicals persist in unexposed generations. Based on the prior evidence of phenotypic variability and gene expression alterations in opposite direction between generations, it is argued here that calling evidence of mismatched directionality in gene expression in experiments testing potential of environmental agents in inducing epigenetic inheritance of phenotypic traits as negative is untenable. This is expected to settle the newly raised doubts over epigenetic inheritance in mammals.

Battery Energy Storage Systems to Mitigate the Variability of Photovoltaic Power Generation

NASA Astrophysics Data System (ADS)

Gurganus, Heath Alan

Methods of generating renewable energy such as through solar photovoltaic (PV) cells and wind turbines offer great promise in terms of a reduced carbon footprint and overall impact on the environment. However, these methods also share the attribute of being highly stochastic, meaning they are variable in such a way that is difficult to forecast with sufficient accuracy. While solar power currently constitutes a small amount of generating potential in most regions, the cost of photovoltaics continues to decline and a trend has emerged to build larger PV plants than was once feasible. This has brought the matter of increased variability to the forefront of research in the industry. Energy storage has been proposed as a means of mitigating this increased variability --- and thus reducing the need to utilize traditional spinning reserves --- as well as offering auxiliary grid services such as peak-shifting and frequency control. This thesis addresses the feasibility of using electrochemical storage methods (i.e. batteries) to decrease the ramp rates of PV power plants. By building a simulation of a grid-connected PV array and a typical Battery Energy Storage System (BESS) in the NetLogo simulation environment, I have created a parameterized tool that can be tailored to describe almost any potential PV setup. This thesis describes the design and function of this model, and makes a case for the accuracy of its measurements by comparing its simulated output to that of well-documented real world sites. Finally, a set of recommendations for the design and operational parameters of such a system are then put forth based on the results of several experiments performed using this model.

Interlaboratory variability in the quantification of new generation antiepileptic drugs based on external quality assessment data.

PubMed

Williams, John; Bialer, Meir; Johannessen, Svein I; Krämer, Günther; Levy, René; Mattson, Richard H; Perucca, Emilio; Patsalos, Philip N; Wilson, John F

2003-01-01

To assess interlaboratory variability in the determination of serum levels of new antiepileptic drugs (AEDs). Lyophilised serum samples containing clinically relevant concentrations of felbamate (FBM), gabapentin (GBP), lamotrigine (LTG), the monohydroxy derivative of oxcarbazepine (OCBZ; MHD), tiagabine (TGB), topiramate (TPM), and vigabatrin (VGB) were distributed monthly among 70 laboratories participating in the international Heathcontrol External Quality Assessment Scheme (EQAS). Assay results returned over a 15-month period were evaluated for precision and accuracy. The most frequently measured compound was LTG (65), followed by MHD (39), GBP (19), TPM (18), VGB (15), FBM (16), and TGB (8). High-performance liquid chromatography was the most commonly used assay technique for all drugs except for TPM, for which two thirds of laboratories used a commercial immunoassay. For all assay methods combined, precision was <11% for MHD, FBM, TPM, and LTG, close to 15% for GBP and VGB, and as high as 54% for TGB (p < 0.001). Mean accuracy values were <10% for all drugs other than TGB, for which measured values were on average 13.9% higher than spiked values, with a high variability around the mean (45%). No differences in precision and accuracy were found between methods, except for TPM, for which gas chromatography showed poorer accuracy compared with immunoassay and gas chromatography-mass spectrometry. With the notable exception of TGB, interlaboratory variability in the determination of new AEDs was comparable to that reported with older-generation agents. Poor assay performance is related more to individual operators than to the intrinsic characteristics of the method applied. Participation in an EQAS scheme is recommended to ensure adequate control of assay variability in therapeutic drug monitoring.

The comparative effect of individually-generated vs. collaboratively-generated computer-based concept mapping on science concept learning

NASA Astrophysics Data System (ADS)

Kwon, So Young

Using a quasi-experimental design, the researcher investigated the comparative effects of individually-generated and collaboratively-generated computer-based concept mapping on middle school science concept learning. Qualitative data were analyzed to explain quantitative findings. One hundred sixty-one students (74 boys and 87 girls) in eight, seventh grade science classes at a middle school in Southeast Texas completed the entire study. Using prior science performance scores to assure equivalence of student achievement across groups, the researcher assigned the teacher's classes to one of the three experimental groups. The independent variable, group, consisted of three levels: 40 students in a control group, 59 students trained to individually generate concept maps on computers, and 62 students trained to collaboratively generate concept maps on computers. The dependent variables were science concept learning as demonstrated by comprehension test scores, and quality of concept maps created by students in experimental groups as demonstrated by rubric scores. Students in the experimental groups received concept mapping training and used their newly acquired concept mapping skills to individually or collaboratively construct computer-based concept maps during study time. The control group, the individually-generated concept mapping group, and the collaboratively-generated concept mapping group had equivalent learning experiences for 50 minutes during five days, excepting that students in a control group worked independently without concept mapping activities, students in the individual group worked individually to construct concept maps, and students in the collaborative group worked collaboratively to construct concept maps during their study time. Both collaboratively and individually generated computer-based concept mapping had a positive effect on seventh grade middle school science concept learning but neither strategy was more effective than the other. However

Uncertainty and Variability in Physiologically-Based ...

EPA Pesticide Factsheets

EPA announced the availability of the final report, Uncertainty and Variability in Physiologically-Based Pharmacokinetic (PBPK) Models: Key Issues and Case Studies. This report summarizes some of the recent progress in characterizing uncertainty and variability in physiologically-based pharmacokinetic models and their predictions for use in risk assessment. This report summarizes some of the recent progress in characterizing uncertainty and variability in physiologically-based pharmacokinetic models and their predictions for use in risk assessment.

An advanced stochastic weather generator for simulating 2-D high-resolution climate variables

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2017-07-01

A new stochastic weather generator, Advanced WEather GENerator for a two-dimensional grid (AWE-GEN-2d) is presented. The model combines physical and stochastic approaches to simulate key meteorological variables at high spatial and temporal resolution: 2 km × 2 km and 5 min for precipitation and cloud cover and 100 m × 100 m and 1 h for near-surface air temperature, solar radiation, vapor pressure, atmospheric pressure, and near-surface wind. The model requires spatially distributed data for the calibration process, which can nowadays be obtained by remote sensing devices (weather radar and satellites), reanalysis data sets and ground stations. AWE-GEN-2d is parsimonious in terms of computational demand and therefore is particularly suitable for studies where exploring internal climatic variability at multiple spatial and temporal scales is fundamental. Applications of the model include models of environmental systems, such as hydrological and geomorphological models, where high-resolution spatial and temporal meteorological forcing is crucial. The weather generator was calibrated and validated for the Engelberg region, an area with complex topography in the Swiss Alps. Model test shows that the climate variables are generated by AWE-GEN-2d with a level of accuracy that is sufficient for many practical applications.

Fault Diagnosis Strategies for SOFC-Based Power Generation Plants

PubMed Central

Costamagna, Paola; De Giorgi, Andrea; Gotelli, Alberto; Magistri, Loredana; Moser, Gabriele; Sciaccaluga, Emanuele; Trucco, Andrea

2016-01-01

The success of distributed power generation by plants based on solid oxide fuel cells (SOFCs) is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI) system. However, the numerous operating conditions under which such plants can operate and the random size of the possible faults make identifying damaged plant components starting from the physical variables measured in the plant very difficult. In this context, we assess two classical FDI strategies (model-based with fault signature matrix and data-driven with statistical classification) and the combination of them. For this assessment, a quantitative model of the SOFC-based plant, which is able to simulate regular and faulty conditions, is used. Moreover, a hybrid approach based on the random forest (RF) classification method is introduced to address the discrimination of regular and faulty situations due to its practical advantages. Working with a common dataset, the FDI performances obtained using the aforementioned strategies, with different sets of monitored variables, are observed and compared. We conclude that the hybrid FDI strategy, realized by combining a model-based scheme with a statistical classifier, outperforms the other strategies. In addition, the inclusion of two physical variables that should be measured inside the SOFCs can significantly improve the FDI performance, despite the actual difficulty in performing such measurements. PMID:27556472

Dual stator winding variable speed asynchronous generator: optimal design and experiments

NASA Astrophysics Data System (ADS)

Tutelea, L. N.; Deaconu, S. I.; Popa, G. N.

2015-06-01

In the present paper is carried out a theoretical and experimental study of dual stator winding squirrel cage asynchronous generator (DSWA) behavior in the presence of saturation regime (non-sinusoidal) due to the variable speed operation. The main aims are the determination of the relations of calculating the equivalent parameters of the machine windings to optimal design using a Matlab code. Issue is limited to three phase range of double stator winding cage-induction generator of small sized powers, the most currently used in the small adjustable speed wind or hydro power plants. The tests were carried out using three-phase asynchronous generator having rated power of 6 [kVA].

Next-Generation Satellite Precipitation Products for Understanding Global and Regional Water Variability

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.

2011-01-01

A major challenge in understanding the space-time variability of continental water fluxes is the lack of accurate precipitation estimates over complex terrains. While satellite precipitation observations can be used to complement ground-based data to obtain improved estimates, space-based and ground-based estimates come with their own sets of uncertainties, which must be understood and characterized. Quantitative estimation of uncertainties in these products also provides a necessary foundation for merging satellite and ground-based precipitation measurements within a rigorous statistical framework. Global Precipitation Measurement (GPM) is an international satellite mission that will provide next-generation global precipitation data products for research and applications. It consists of a constellation of microwave sensors provided by NASA, JAXA, CNES, ISRO, EUMETSAT, DOD, NOAA, NPP, and JPSS. At the heart of the mission is the GPM Core Observatory provided by NASA and JAXA to be launched in 2013. The GPM Core, which will carry the first space-borne dual-frequency radar and a state-of-the-art multi-frequency radiometer, is designed to set new reference standards for precipitation measurements from space, which can then be used to unify and refine precipitation retrievals from all constellation sensors. The next-generation constellation-based satellite precipitation estimates will be characterized by intercalibrated radiometric measurements and physical-based retrievals using a common observation-derived hydrometeor database. For pre-launch algorithm development and post-launch product evaluation, NASA supports an extensive ground validation (GV) program in cooperation with domestic and international partners to improve (1) physics of remote-sensing algorithms through a series of focused field campaigns, (2) characterization of uncertainties in satellite and ground-based precipitation products over selected GV testbeds, and (3) modeling of atmospheric processes and

Effects of ion channel noise on neural circuits: an application to the respiratory pattern generator to investigate breathing variability.

PubMed

Yu, Haitao; Dhingra, Rishi R; Dick, Thomas E; Galán, Roberto F

2017-01-01

Neural activity generally displays irregular firing patterns even in circuits with apparently regular outputs, such as motor pattern generators, in which the output frequency fluctuates randomly around a mean value. This "circuit noise" is inherited from the random firing of single neurons, which emerges from stochastic ion channel gating (channel noise), spontaneous neurotransmitter release, and its diffusion and binding to synaptic receptors. Here we demonstrate how to expand conductance-based network models that are originally deterministic to include realistic, physiological noise, focusing on stochastic ion channel gating. We illustrate this procedure with a well-established conductance-based model of the respiratory pattern generator, which allows us to investigate how channel noise affects neural dynamics at the circuit level and, in particular, to understand the relationship between the respiratory pattern and its breath-to-breath variability. We show that as the channel number increases, the duration of inspiration and expiration varies, and so does the coefficient of variation of the breath-to-breath interval, which attains a minimum when the mean duration of expiration slightly exceeds that of inspiration. For small channel numbers, the variability of the expiratory phase dominates over that of the inspiratory phase, and vice versa for large channel numbers. Among the four different cell types in the respiratory pattern generator, pacemaker cells exhibit the highest sensitivity to channel noise. The model shows that suppressing input from the pons leads to longer inspiratory phases, a reduction in breathing frequency, and larger breath-to-breath variability, whereas enhanced input from the raphe nucleus increases breathing frequency without changing its pattern. A major source of noise in neuronal circuits is the "flickering" of ion currents passing through the neurons' membranes (channel noise), which cannot be suppressed experimentally. Computational

Freshwater ecosystems and resilience of Pacific salmon: Habitat Management based on natural variability

USGS Publications Warehouse

Bisson, P.A.; Dunham, J.B.; Reeves, G.H.

2009-01-01

In spite of numerous habitat restoration programs in fresh waters with an aggregate annual funding of millions of dollars, many populations of Pacific salmon remain significantly imperiled. Habitat restoration strategies that address limited environmental attributes and partial salmon life-history requirements or approaches that attempt to force aquatic habitat to conform to idealized but ecologically unsustainable conditions may partly explain this lack of response. Natural watershed processes generate highly variable environmental conditions and population responses, i.e., multiple life histories, that are often not considered in restoration. Examples from several locations underscore the importance of natural variability to the resilience of Pacific salmon. The implication is that habitat restoration efforts will be more likely to foster salmon resilience if they consider processes that generate and maintain natural variability in fresh water. We identify three specific criteria for management based on natural variability: the capacity of aquatic habitat to recover from disturbance, a range of habitats distributed across stream networks through time sufficient to fulfill the requirements of diverse salmon life histories, and ecological connectivity. In light of these considerations, we discuss current threats to habitat resilience and describe how regulatory and restoration approaches can be modified to better incorporate natural variability. ?? 2009 by the author(s).

Frequency Regulation and Oscillation Damping Contributions of Variable-Speed Wind Generators in the U.S. Eastern Interconnection (EI)

DOE PAGES

Liu, Yong; Gracia, Jose R,; King, Jr, Thomas J.; ...

2014-05-16

The U.S. Eastern Interconnection (EI) is one of the largest electric power grids in the world and is expected to have difficulties in dealing with frequency regulation and oscillation damping issues caused by the increasing wind power. On the other side, variable-speed wind generators can actively engage in frequency regulation or oscillation damping with supplementary control loops. This paper creates a 5% wind power penetration simulation scenario based on the 16 000-bus EI system dynamic model and developed the user-defined wind electrical control model in PSS (R) E that incorporates additional frequency regulation and oscillation damping control loops. We evaluatedmore » the potential contributions of variable-speed wind generations to the EI system frequency regulation and oscillation damping, and simulation results demonstrate that current and future penetrations of wind power are promising in the EI system frequency regulation and oscillation damping.« less

Assessing the variables affecting on the rate of solid waste generation and recycling: An empirical analysis in Prespa Park.

PubMed

Grazhdani, Dorina

2016-02-01

Economic development, urbanization, and improved living standards increase the quantity and complexity of generated solid waste. Comprehensive study of the variables influencing household solid waste production and recycling rate is crucial and fundamental for exploring the generation mechanism and forecasting future dynamics of household solid waste. The present study is employed in the case study of Prespa Park. A model, based on the interrelationships of economic, demographic, housing structure and waste management policy variables influencing the rate of solid waste generation and recycling is developed and employed. The empirical analysis is based on the information derived from a field questionnaire survey conducted in Prespa Park villages for the year 2014. Another feature of this study is to test whether a household's waste generation can be decoupled from its population growth. Descriptive statistics, bivariate correlation analysis and F-tests are used to know the relationship between variables. One-way and two-way fixed effects models data analysis techniques are used to identify variables that determine the effectiveness of waste generation and recycling at household level in the study area. The results reveal that households with heterogeneous characteristics, such as education level, mean building age and income, present different challenges of waste reduction goals. Numerically, an increase of 1% in education level of population corresponds to a waste reduction of 3kg on the annual per capita basis. A village with older buildings, in the case of one year older of the median building age, corresponds to a waste generation increase of 12kg. Other economic and policy incentives such as the mean household income, pay-as-you-throw, percentage of population with access to curbside recycling, the number of drop-off recycling facilities available per 1000 persons and cumulative expenditures on recycling education per capita are also found to be effective

Experimental investigation of a variable speed constant frequency electric generating system from a utility perspective

NASA Technical Reports Server (NTRS)

Herrera, J. I.; Reddoch, T. W.; Lawler, J. S.

1985-01-01

As efforts are accelerated to improve the overall capability and performance of wind electric systems, increased attention to variable speed configurations has developed. A number of potentially viable configurations have emerged. Various attributes of variable speed systems need to be carefully tested to evaluate their performance from the utility points of view. With this purpose, the NASA experimental variable speed constant frequency (VSCF) system has been tested. In order to determine the usefulness of these systems in utility applications, tests are required to resolve issues fundamental to electric utility systems. Legitimate questions exist regarding how variable speed generators will influence the performance of electric utility systems; therefore, tests from a utility perspective, have been performed on the VSCF system and an induction generator at an operating power level of 30 kW on a system rated at 200 kVA and 0.8 power factor.

A generator for unique quantum random numbers based on vacuum states

NASA Astrophysics Data System (ADS)

Gabriel, Christian; Wittmann, Christoffer; Sych, Denis; Dong, Ruifang; Mauerer, Wolfgang; Andersen, Ulrik L.; Marquardt, Christoph; Leuchs, Gerd

2010-10-01

Random numbers are a valuable component in diverse applications that range from simulations over gambling to cryptography. The quest for true randomness in these applications has engendered a large variety of different proposals for producing random numbers based on the foundational unpredictability of quantum mechanics. However, most approaches do not consider that a potential adversary could have knowledge about the generated numbers, so the numbers are not verifiably random and unique. Here we present a simple experimental setup based on homodyne measurements that uses the purity of a continuous-variable quantum vacuum state to generate unique random numbers. We use the intrinsic randomness in measuring the quadratures of a mode in the lowest energy vacuum state, which cannot be correlated to any other state. The simplicity of our source, combined with its verifiably unique randomness, are important attributes for achieving high-reliability, high-speed and low-cost quantum random number generators.

Optimized Next-Generation Sequencing Genotype-Haplotype Calling for Genome Variability Analysis

PubMed Central

Navarro, Javier; Nevado, Bruno; Hernández, Porfidio; Vera, Gonzalo; Ramos-Onsins, Sebastián E

2017-01-01

The accurate estimation of nucleotide variability using next-generation sequencing data is challenged by the high number of sequencing errors produced by new sequencing technologies, especially for nonmodel species, where reference sequences may not be available and the read depth may be low due to limited budgets. The most popular single-nucleotide polymorphism (SNP) callers are designed to obtain a high SNP recovery and low false discovery rate but are not designed to account appropriately the frequency of the variants. Instead, algorithms designed to account for the frequency of SNPs give precise results for estimating the levels and the patterns of variability. These algorithms are focused on the unbiased estimation of the variability and not on the high recovery of SNPs. Here, we implemented a fast and optimized parallel algorithm that includes the method developed by Roesti et al and Lynch, which estimates the genotype of each individual at each site, considering the possibility to call both bases from the genotype, a single one or none. This algorithm does not consider the reference and therefore is independent of biases related to the reference nucleotide specified. The pipeline starts from a BAM file converted to pileup or mpileup format and the software outputs a FASTA file. The new program not only reduces the running times but also, given the improved use of resources, it allows its usage with smaller computers and large parallel computers, expanding its benefits to a wider range of researchers. The output file can be analyzed using software for population genetics analysis, such as the R library PopGenome, the software VariScan, and the program mstatspop for analysis considering positions with missing data. PMID:28894353

Non-Darcy flow of water-based carbon nanotubes with nonlinear radiation and heat generation/absorption

NASA Astrophysics Data System (ADS)

Hayat, T.; Ullah, Siraj; Khan, M. Ijaz; Alsaedi, A.; Zaigham Zia, Q. M.

2018-03-01

Here modeling and computations are presented to introduce the novel concept of Darcy-Forchheimer three-dimensional flow of water-based carbon nanotubes with nonlinear thermal radiation and heat generation/absorption. Bidirectional stretching surface induces the flow. Darcy's law is commonly replace by Forchheimer relation. Xue model is implemented for nonliquid transport mechanism. Nonlinear formulation based upon conservation laws of mass, momentum and energy is first modeled and then solved by optimal homotopy analysis technique. Optimal estimations of auxiliary variables are obtained. Importance of influential variables on the velocity and thermal fields is interpreted graphically. Moreover velocity and temperature gradients are discussed and analyzed. Physical interpretation of influential variables is examined.

Micromotor-based energy generation.

PubMed

Singh, Virendra V; Soto, Fernando; Kaufmann, Kevin; Wang, Joseph

2015-06-01

A micromotor-based strategy for energy generation, utilizing the conversion of liquid-phase hydrogen to usable hydrogen gas (H2), is described. The new motion-based H2-generation concept relies on the movement of Pt-black/Ti Janus microparticle motors in a solution of sodium borohydride (NaBH4) fuel. This is the first report of using NaBH4 for powering micromotors. The autonomous motion of these catalytic micromotors, as well as their bubble generation, leads to enhanced mixing and transport of NaBH4 towards the Pt-black catalytic surface (compared to static microparticles or films), and hence to a substantially faster rate of H2 production. The practical utility of these micromotors is illustrated by powering a hydrogen-oxygen fuel cell car by an on-board motion-based hydrogen and oxygen generation. The new micromotor approach paves the way for the development of efficient on-site energy generation for powering external devices or meeting growing demands on the energy grid. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Waste generated in high-rise buildings construction: a quantification model based on statistical multiple regression.

PubMed

Parisi Kern, Andrea; Ferreira Dias, Michele; Piva Kulakowski, Marlova; Paulo Gomes, Luciana

2015-05-01

Reducing construction waste is becoming a key environmental issue in the construction industry. The quantification of waste generation rates in the construction sector is an invaluable management tool in supporting mitigation actions. However, the quantification of waste can be a difficult process because of the specific characteristics and the wide range of materials used in different construction projects. Large variations are observed in the methods used to predict the amount of waste generated because of the range of variables involved in construction processes and the different contexts in which these methods are employed. This paper proposes a statistical model to determine the amount of waste generated in the construction of high-rise buildings by assessing the influence of design process and production system, often mentioned as the major culprits behind the generation of waste in construction. Multiple regression was used to conduct a case study based on multiple sources of data of eighteen residential buildings. The resulting statistical model produced dependent (i.e. amount of waste generated) and independent variables associated with the design and the production system used. The best regression model obtained from the sample data resulted in an adjusted R(2) value of 0.694, which means that it predicts approximately 69% of the factors involved in the generation of waste in similar constructions. Most independent variables showed a low determination coefficient when assessed in isolation, which emphasizes the importance of assessing their joint influence on the response (dependent) variable. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fault Diagnosis for Rolling Bearings under Variable Conditions Based on Visual Cognition

PubMed Central

Cheng, Yujie; Zhou, Bo; Lu, Chen; Yang, Chao

2017-01-01

Fault diagnosis for rolling bearings has attracted increasing attention in recent years. However, few studies have focused on fault diagnosis for rolling bearings under variable conditions. This paper introduces a fault diagnosis method for rolling bearings under variable conditions based on visual cognition. The proposed method includes the following steps. First, the vibration signal data are transformed into a recurrence plot (RP), which is a two-dimensional image. Then, inspired by the visual invariance characteristic of the human visual system (HVS), we utilize speed up robust feature to extract fault features from the two-dimensional RP and generate a 64-dimensional feature vector, which is invariant to image translation, rotation, scaling variation, etc. Third, based on the manifold perception characteristic of HVS, isometric mapping, a manifold learning method that can reflect the intrinsic manifold embedded in the high-dimensional space, is employed to obtain a low-dimensional feature vector. Finally, a classical classification method, support vector machine, is utilized to realize fault diagnosis. Verification data were collected from Case Western Reserve University Bearing Data Center, and the experimental result indicates that the proposed fault diagnosis method based on visual cognition is highly effective for rolling bearings under variable conditions, thus providing a promising approach from the cognitive computing field. PMID:28772943

One-step generation of continuous-variable quadripartite cluster states in a circuit QED system

NASA Astrophysics Data System (ADS)

Yang, Zhi-peng; Li, Zhen; Ma, Sheng-li; Li, Fu-li

2017-07-01

We propose a dissipative scheme for one-step generation of continuous-variable quadripartite cluster states in a circuit QED setup consisting of four superconducting coplanar waveguide resonators and a gap-tunable superconducting flux qubit. With external driving fields to adjust the desired qubit-resonator and resonator-resonator interactions, we show that continuous-variable quadripartite cluster states of the four resonators can be generated with the assistance of energy relaxation of the qubit. By comparison with the previous proposals, the distinct advantage of our scheme is that only one step of quantum operation is needed to realize the quantum state engineering. This makes our scheme simpler and more feasible in experiment. Our result may have useful application for implementing quantum computation in solid-state circuit QED systems.

A rule-based software test data generator

NASA Technical Reports Server (NTRS)

Deason, William H.; Brown, David B.; Chang, Kai-Hsiung; Cross, James H., II

1991-01-01

Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100,000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further.

Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

NASA Astrophysics Data System (ADS)

Karpatne, A.; Kumar, V.

2017-12-01

Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

Description and test results of a variable speed, constant frequency generating system

NASA Astrophysics Data System (ADS)

Brady, F. J.

1985-12-01

The variable-speed, constant frequency generating system developed for the Mod-0 wind turbine is presented. This report describes the system as it existed at the conclusion of the project. The cycloconverter control circuit is described including the addition of field-oriented control. The laboratory test and actual wind turbine test results are included.

Integration of Variable Speed Pumped Hydro Storage in Automatic Generation Control Systems

NASA Astrophysics Data System (ADS)

Fulgêncio, N.; Moreira, C.; Silva, B.

2017-04-01

Pumped storage power (PSP) plants are expected to be an important player in modern electrical power systems when dealing with increasing shares of new renewable energies (NRE) such as solar or wind power. The massive penetration of NRE and consequent replacement of conventional synchronous units will significantly affect the controllability of the system. In order to evaluate the capability of variable speed PSP plants participation in the frequency restoration reserve (FRR) provision, taking into account the expected performance in terms of improved ramp response capability, a comparison with conventional hydro units is presented. In order to address this issue, a three area test network was considered, as well as the corresponding automatic generation control (AGC) systems, being responsible for re-dispatching the generation units to re-establish power interchange between areas as well as the system nominal frequency. The main issue under analysis in this paper is related to the benefits of the fast response of variable speed PSP with respect to its capability of providing fast power balancing in a control area.

Power Quality Control and Design of Power Converter for Variable-Speed Wind Energy Conversion System with Permanent-Magnet Synchronous Generator

PubMed Central

Oğuz, Yüksel; Güney, İrfan; Çalık, Hüseyin

2013-01-01

The control strategy and design of an AC/DC/AC IGBT-PMW power converter for PMSG-based variable-speed wind energy conversion systems (VSWECS) operation in grid/load-connected mode are presented. VSWECS consists of a PMSG connected to a AC-DC IGBT-based PWM rectifier and a DC/AC IGBT-based PWM inverter with LCL filter. In VSWECS, AC/DC/AC power converter is employed to convert the variable frequency variable speed generator output to the fixed frequency fixed voltage grid. The DC/AC power conversion has been managed out using adaptive neurofuzzy controlled inverter located at the output of controlled AC/DC IGBT-based PWM rectifier. In this study, the dynamic performance and power quality of the proposed power converter connected to the grid/load by output LCL filter is focused on. Dynamic modeling and control of the VSWECS with the proposed power converter is performed by using MATLAB/Simulink. Simulation results show that the output voltage, power, and frequency of VSWECS reach to desirable operation values in a very short time. In addition, when PMSG based VSWECS works continuously with the 4.5 kHz switching frequency, the THD rate of voltage in the load terminal is 0.00672%. PMID:24453905

Power quality control and design of power converter for variable-speed wind energy conversion system with permanent-magnet synchronous generator.

PubMed

Oğuz, Yüksel; Güney, İrfan; Çalık, Hüseyin

2013-01-01

The control strategy and design of an AC/DC/AC IGBT-PMW power converter for PMSG-based variable-speed wind energy conversion systems (VSWECS) operation in grid/load-connected mode are presented. VSWECS consists of a PMSG connected to a AC-DC IGBT-based PWM rectifier and a DC/AC IGBT-based PWM inverter with LCL filter. In VSWECS, AC/DC/AC power converter is employed to convert the variable frequency variable speed generator output to the fixed frequency fixed voltage grid. The DC/AC power conversion has been managed out using adaptive neurofuzzy controlled inverter located at the output of controlled AC/DC IGBT-based PWM rectifier. In this study, the dynamic performance and power quality of the proposed power converter connected to the grid/load by output LCL filter is focused on. Dynamic modeling and control of the VSWECS with the proposed power converter is performed by using MATLAB/Simulink. Simulation results show that the output voltage, power, and frequency of VSWECS reach to desirable operation values in a very short time. In addition, when PMSG based VSWECS works continuously with the 4.5 kHz switching frequency, the THD rate of voltage in the load terminal is 0.00672%.

Smoothing Control of Wind Farm Output by Using Kinetic Energy of Variable Speed Wind Power Generators

NASA Astrophysics Data System (ADS)

Sato, Daiki; Saitoh, Hiroumi

This paper proposes a new control method for reducing fluctuation of power system frequency through smoothing active power output of wind farm. The proposal is based on the modulation of rotaional kinetic energy of variable speed wind power generators through power converters between permanent magnet synchronous generators (PMSG) and transmission lines. In this paper, the proposed control is called Fluctuation Absorption by Flywheel Characteristics control (FAFC). The FAFC can be easily implemented by adding wind farm output signal to Maximum Power Point Tracking control signal through a feedback control loop. In order to verify the effectiveness of the FAFC control, a simulation study was carried out. In the study, it was assumed that the wind farm consisting of PMSG type wind power generator and induction machine type wind power generaotors is connected with a power sysem. The results of the study show that the FAFC control is a useful method for reducing the impacts of wind farm output fluctuation on system frequency without additional devices such as secondary battery.

Analysis Methodology for Balancing Authority Cooperation in High Penetration of Variable Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makarov, Yuri V.; Etingov, Pavel V.; Zhou, Ning

2010-02-01

With the rapidly growing penetration level of wind and solar generation, the challenges of managing variability and the uncertainty of intermittent renewable generation become more and more significant. The problem of power variability and uncertainty gets exacerbated when each balancing authority (BA) works locally and separately to balance its own subsystem. The virtual BA concept means various forms of collaboration between individual BAs must manage power variability and uncertainty. The virtual BA will have a wide area control capability in managing its operational balancing requirements in different time frames. This coordination results in the improvement of efficiency and reliability ofmore » power system operation while facilitating the high level integration of green, intermittent energy resources. Several strategies for virtual BA implementation, such as ACE diversity interchange (ADI), wind only BA, BA consolidation, dynamic scheduling, regulation and load following sharing, extreme event impact study are discussed in this report. The objective of such strategies is to allow individual BAs within a large power grid to help each other deal with power variability. Innovative methods have been developed to simulate the balancing operation of BAs. These methods evaluate the BA operation through a number of metrics — such as capacity, ramp rate, ramp duration, energy and cycling requirements — to evaluate the performances of different virtual BA strategies. The report builds a systematic framework for evaluating BA consolidation and coordination. Results for case studies show that significant economic and reliability benefits can be gained. The merits and limitation of each virtual BA strategy are investigated. The report provides guidelines for the power industry to evaluate the coordination or consolidation method. The application of the developed strategies in cooperation with several regional BAs is in progress for several off-spring projects.« less

Optimal Output of Distributed Generation Based On Complex Power Increment

NASA Astrophysics Data System (ADS)

Wu, D.; Bao, H.

2017-12-01

In order to meet the growing demand for electricity and improve the cleanliness of power generation, new energy generation, represented by wind power generation, photovoltaic power generation, etc has been widely used. The new energy power generation access to distribution network in the form of distributed generation, consumed by local load. However, with the increase of the scale of distribution generation access to the network, the optimization of its power output is becoming more and more prominent, which needs further study. Classical optimization methods often use extended sensitivity method to obtain the relationship between different power generators, but ignore the coupling parameter between nodes makes the results are not accurate; heuristic algorithm also has defects such as slow calculation speed, uncertain outcomes. This article proposes a method called complex power increment, the essence of this method is the analysis of the power grid under steady power flow. After analyzing the results we can obtain the complex scaling function equation between the power supplies, the coefficient of the equation is based on the impedance parameter of the network, so the description of the relation of variables to the coefficients is more precise Thus, the method can accurately describe the power increment relationship, and can obtain the power optimization scheme more accurately and quickly than the extended sensitivity method and heuristic method.

Analysis of the electrical harmonic characteristics of a slip recovery variable speed generating system for wind turbine applications

NASA Astrophysics Data System (ADS)

Herrera, J. I.; Reddoch, T. W.

1988-02-01

Variable speed electric generating technology can enhance the general use of wind energy in electric utility applications. This enhancement results from two characteristic properties of variable speed wind turbine generators: an improvement in drive train damping characteristics, which results in reduced structural loading on the entire wind turbine system, and an improvement in the overall efficiency by using a more sophisticated electrical generator. Electronic converter systems are the focus of this investigation -- in particular, the properties of a wound-rotor induction generator with the slip recovery system and direct-current link converter. Experience with solid-state converter systems in large wind turbines is extremely limited. This report presents measurements of electrical performances of the slip recovery system and is limited to the terminal characteristics of the system. Variable speed generating systems working effectively in utility applications will require a satisfactory interface between the turbine/generator pair and the utility network. The electrical testing described herein focuses largely on the interface characteristics of the generating system. A MOD-O wind turbine was connected to a very strong system; thus, the voltage distortion was low and the total harmonic distortion in the utility voltage was less than 3 percent (within the 5 percent limit required by most utilities). The largest voltage component of a frequency below 60 Hz was 40 dB down from the 60-Hz less than component.

The impact of monsoon intraseasonal variability on renewable power generation in India

NASA Astrophysics Data System (ADS)

Dunning, C. M.; Turner, A. G.; Brayshaw, D. J.

2015-06-01

India is increasingly investing in renewable technology to meet rising energy demands, with hydropower and other renewables comprising one-third of current installed capacity. Installed wind-power is projected to increase 5-fold by 2035 (to nearly 100GW) under the International Energy Agency's New Policies scenario. However, renewable electricity generation is dependent upon the prevailing meteorology, which is strongly influenced by monsoon variability. Prosperity and widespread electrification are increasing the demand for air conditioning, especially during the warm summer. This study uses multi-decadal observations and meteorological reanalysis data to assess the impact of intraseasonal monsoon variability on the balance of electricity supply from wind-power and temperature-related demand in India. Active monsoon phases are characterized by vigorous convection and heavy rainfall over central India. This results in lower temperatures giving lower cooling energy demand, while strong westerly winds yield high wind-power output. In contrast, monsoon breaks are characterized by suppressed precipitation, with higher temperatures and hence greater demand for cooling, and lower wind-power output across much of India. The opposing relationship between wind-power supply and cooling demand during active phases (low demand, high supply) and breaks (high demand, low supply) suggests that monsoon variability will tend to exacerbate fluctuations in the so-called demand-net-wind (i.e., electrical demand that must be supplied from non-wind sources). This study may have important implications for the design of power systems and for investment decisions in conventional schedulable generation facilities (such as coal and gas) that are used to maintain the supply/demand balance. In particular, if it is assumed (as is common) that the generated wind-power operates as a price-taker (i.e., wind farm operators always wish to sell their power, irrespective of price) then investors in

Surface display of a massively variable lipoprotein by a Legionella diversity-generating retroelement.

PubMed

Arambula, Diego; Wong, Wenge; Medhekar, Bob A; Guo, Huatao; Gingery, Mari; Czornyj, Elizabeth; Liu, Minghsun; Dey, Sanghamitra; Ghosh, Partho; Miller, Jeff F

2013-05-14

Diversity-generating retroelements (DGRs) are a unique family of retroelements that confer selective advantages to their hosts by facilitating localized DNA sequence evolution through a specialized error-prone reverse transcription process. We characterized a DGR in Legionella pneumophila, an opportunistic human pathogen that causes Legionnaires disease. The L. pneumophila DGR is found within a horizontally acquired genomic island, and it can theoretically generate 10(26) unique nucleotide sequences in its target gene, legionella determinent target A (ldtA), creating a repertoire of 10(19) distinct proteins. Expression of the L. pneumophila DGR resulted in transfer of DNA sequence information from a template repeat to a variable repeat (VR) accompanied by adenine-specific mutagenesis of progeny VRs at the 3'end of ldtA. ldtA encodes a twin-arginine translocated lipoprotein that is anchored in the outer leaflet of the outer membrane, with its C-terminal variable region surface exposed. Related DGRs were identified in L. pneumophila clinical isolates that encode unique target proteins with homologous VRs, demonstrating the adaptability of DGR components. This work characterizes a DGR that diversifies a bacterial protein and confirms the hypothesis that DGR-mediated mutagenic homing occurs through a conserved mechanism. Comparative bioinformatics predicts that surface display of massively variable proteins is a defining feature of a subset of bacterial DGRs.

Stability Augmentation of Wind Farm using Variable Speed Permanent Magnet Synchronous Generator

NASA Astrophysics Data System (ADS)

Rosyadi, Marwan; Muyeen, S. M.; Takahashi, Rion; Tamura, Junji

This paper presents a new control strategy of variable speed permanent magnet wind generator for stability augmentation of wind farm including fixed speed wind turbine with Induction Generator (IG). A new control scheme is developed for two levels back-to-back converters of Permanent Magnet Synchronous Generator (PMSG), by which both active and reactive powers delivered to the grid can be controlled easily. To avoid the converter damage, the DC link protection controller is also proposed in order to protect the dc link circuit during fault condition. To evaluate the control capability of the proposed controllers, simulations are performed on two model systems composed of wind farms connected to an infinite bus. From transient and steady state analyses by using PSCAD/EMTDC, it is concluded that the proposed control scheme is very effective to improve the stability of wind farm for severe network disturbance and randomly fluctuating wind speed.

Potential Occupational Exposures and Health Risks Associated with Biomass-Based Power Generation.

PubMed

Rohr, Annette C; Campleman, Sharan L; Long, Christopher M; Peterson, Michael K; Weatherstone, Susan; Quick, Will; Lewis, Ari

2015-07-22

Biomass is increasingly being used for power generation; however, assessment of potential occupational health and safety (OH&S) concerns related to usage of biomass fuels in combustion-based generation remains limited. We reviewed the available literature on known and potential OH&S issues associated with biomass-based fuel usage for electricity generation at the utility scale. We considered three potential exposure scenarios--pre-combustion exposure to material associated with the fuel, exposure to combustion products, and post-combustion exposure to ash and residues. Testing of dust, fungal and bacterial levels at two power stations was also undertaken. Results indicated that dust concentrations within biomass plants can be extremely variable, with peak levels in some areas exceeding occupational exposure limits for wood dust and general inhalable dust. Fungal spore types, identified as common environmental species, were higher than in outdoor air. Our review suggests that pre-combustion risks, including bioaerosols and biogenic organics, should be considered further. Combustion and post-combustion risks appear similar to current fossil-based combustion. In light of limited available information, additional studies at power plants utilizing a variety of technologies and biomass fuels are recommended.

Potential Occupational Exposures and Health Risks Associated with Biomass-Based Power Generation

PubMed Central

Rohr, Annette C.; Campleman, Sharan L.; Long, Christopher M.; Peterson, Michael K.; Weatherstone, Susan; Quick, Will; Lewis, Ari

2015-01-01

Biomass is increasingly being used for power generation; however, assessment of potential occupational health and safety (OH&S) concerns related to usage of biomass fuels in combustion-based generation remains limited. We reviewed the available literature on known and potential OH&S issues associated with biomass-based fuel usage for electricity generation at the utility scale. We considered three potential exposure scenarios—pre-combustion exposure to material associated with the fuel, exposure to combustion products, and post-combustion exposure to ash and residues. Testing of dust, fungal and bacterial levels at two power stations was also undertaken. Results indicated that dust concentrations within biomass plants can be extremely variable, with peak levels in some areas exceeding occupational exposure limits for wood dust and general inhalable dust. Fungal spore types, identified as common environmental species, were higher than in outdoor air. Our review suggests that pre-combustion risks, including bioaerosols and biogenic organics, should be considered further. Combustion and post-combustion risks appear similar to current fossil-based combustion. In light of limited available information, additional studies at power plants utilizing a variety of technologies and biomass fuels are recommended. PMID:26206568

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution

DOE PAGES

Cai, Hong; Long, Christopher M.; DeRose, Christopher T.; ...

2017-01-01

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution.

PubMed

Cai, Hong; Long, Christopher M; DeRose, Christopher T; Boynton, Nicholas; Urayama, Junji; Camacho, Ryan; Pomerene, Andrew; Starbuck, Andrew L; Trotter, Douglas C; Davids, Paul S; Lentine, Anthony L

2017-05-29

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Silicon photonic transceiver circuit for high-speed polarization-based discrete variable quantum key distribution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, Hong; Long, Christopher M.; DeRose, Christopher T.

We demonstrate a silicon photonic transceiver circuit for high-speed discrete variable quantum key distribution that employs a common structure for transmit and receive functions. The device is intended for use in polarization-based quantum cryptographic protocols, such as BB84. Our characterization indicates that the circuit can generate the four BB84 states (TE/TM/45°/135° linear polarizations) with >30 dB polarization extinction ratios and gigabit per second modulation speed, and is capable of decoding any polarization bases differing by 90° with high extinction ratios.

Analysis of the electrical harmonic characteristics of a slip recovery variable speed generating system for wind turbine applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Herrera, J.I.; Reddoch, T.W.

1988-02-01

Variable speed electric generating technology can enhance the general use of wind energy in electric utility applications. This enhancement results from two characteristic properties of variable speed wind turbine generators: an improvement in drive train damping characteristics, which results in reduced structural loading on the entire wind turbine system, and an improvement in the overall efficiency by using a more sophisticated electrical generator. Electronic converter systems are the focus of this investigation -- in particular, the properties of a wound-rotor induction generator with the slip recovery system and direct-current link converter. Experience with solid-state converter systems in large wind turbinesmore » is extremely limited. This report presents measurements of electrical performances of the slip recovery system and is limited to the terminal characteristics of the system. Variable speed generating systems working effectively in utility applications will require a satisfactory interface between the turbine/generator pair and the utility network. The electrical testing described herein focuses largely on the interface characteristics of the generating system. A MOD-O wind turbine was connected to a very strong system; thus, the voltage distortion was low and the total harmonic distortion in the utility voltage was less than 3% (within the 5% limit required by most utilities). The largest voltage component of a frequency below 60 Hz was 40 dB down from the 60-Hz< component. 8 refs., 14 figs., 8 tabs.« less

Coping with Variability in Model-Based Systems Engineering: An Experience in Green Energy

NASA Astrophysics Data System (ADS)

Trujillo, Salvador; Garate, Jose Miguel; Lopez-Herrejon, Roberto Erick; Mendialdua, Xabier; Rosado, Albert; Egyed, Alexander; Krueger, Charles W.; de Sosa, Josune

Model-Based Systems Engineering (MBSE) is an emerging engineering discipline whose driving motivation is to provide support throughout the entire system life cycle. MBSE not only addresses the engineering of software systems but also their interplay with physical systems. Quite frequently, successful systems need to be customized to cater for the concrete and specific needs of customers, end-users, and other stakeholders. To effectively meet this demand, it is vital to have in place mechanisms to cope with the variability, the capacity to change, that such customization requires. In this paper we describe our experience in modeling variability using SysML, a leading MBSE language, for developing a product line of wind turbine systems used for the generation of electricity.

Analysis of operating reserve demand curves in power system operations in the presence of variable generation

DOE PAGES

Krad, Ibrahim; Gao, David Wenzhong; Ela, Erik; ...

2017-06-07

The electric power industry landscape is continually evolving. As emerging technologies such as wind and solar generating systems become more cost effective, traditional power system operating strategies will need to be re-evaluated. The presence of wind and solar generation (commonly referred to as variable generation or VG) can increase variability and uncertainty in the net-load profile. One mechanism to mitigate this issue is to schedule and dispatch additional operating reserves. These operating reserves aim to ensure that there is enough capacity online in the system to account for the increased variability and uncertainty occurring at finer temporal resolutions. A newmore » operating reserve strategy, referred to as flexibility reserve, has been introduced in some regions. A similar implementation is explored in this study, and its implications on power system operations are analyzed. Results show that flexibility reserve products can improve economic metrics, particularly in significantly reducing the number of scarcity pricing events, with minimal impacts on reliability metrics and production costs. Furthermore, the production costs increased due to increased VG curtailment - i.e. including the flexible ramping product in the commitment of excess thermal capacity that needed to remain online at the expense of VG output.« less

Analysis of operating reserve demand curves in power system operations in the presence of variable generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krad, Ibrahim; Gao, David Wenzhong; Ela, Erik

The electric power industry landscape is continually evolving. As emerging technologies such as wind and solar generating systems become more cost effective, traditional power system operating strategies will need to be re-evaluated. The presence of wind and solar generation (commonly referred to as variable generation or VG) can increase variability and uncertainty in the net-load profile. One mechanism to mitigate this issue is to schedule and dispatch additional operating reserves. These operating reserves aim to ensure that there is enough capacity online in the system to account for the increased variability and uncertainty occurring at finer temporal resolutions. A newmore » operating reserve strategy, referred to as flexibility reserve, has been introduced in some regions. A similar implementation is explored in this study, and its implications on power system operations are analyzed. Results show that flexibility reserve products can improve economic metrics, particularly in significantly reducing the number of scarcity pricing events, with minimal impacts on reliability metrics and production costs. Furthermore, the production costs increased due to increased VG curtailment - i.e. including the flexible ramping product in the commitment of excess thermal capacity that needed to remain online at the expense of VG output.« less

Stochastic Multi-Timescale Power System Operations With Variable Wind Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Hongyu; Krad, Ibrahim; Florita, Anthony

This paper describes a novel set of stochastic unit commitment and economic dispatch models that consider stochastic loads and variable generation at multiple operational timescales. The stochastic model includes four distinct stages: stochastic day-ahead security-constrained unit commitment (SCUC), stochastic real-time SCUC, stochastic real-time security-constrained economic dispatch (SCED), and deterministic automatic generation control (AGC). These sub-models are integrated together such that they are continually updated with decisions passed from one to another. The progressive hedging algorithm (PHA) is applied to solve the stochastic models to maintain the computational tractability of the proposed models. Comparative case studies with deterministic approaches are conductedmore » in low wind and high wind penetration scenarios to highlight the advantages of the proposed methodology, one with perfect forecasts and the other with current state-of-the-art but imperfect deterministic forecasts. The effectiveness of the proposed method is evaluated with sensitivity tests using both economic and reliability metrics to provide a broader view of its impact.« less

Neural network based control of Doubly Fed Induction Generator in wind power generation

NASA Astrophysics Data System (ADS)

Barbade, Swati A.; Kasliwal, Prabha

2012-07-01

To complement the other types of pollution-free generation wind energy is a viable option. Previously wind turbines were operated at constant speed. The evolution of technology related to wind systems industry leaded to the development of a generation of variable speed wind turbines that present many advantages compared to the fixed speed wind turbines. In this paper the phasor model of DFIG is used. This paper presents a study of a doubly fed induction generator driven by a wind turbine connected to the grid, and controlled by artificial neural network ANN controller. The behaviour of the system is shown with PI control, and then as controlled by ANN. The effectiveness of the artificial neural network controller is compared to that of a PI controller. The SIMULINK/MATLAB simulation for Doubly Fed Induction Generator and corresponding results and waveforms are displayed.

Resistance controllability and variability improvement in a TaO{sub x}-based resistive memory for multilevel storage application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prakash, A., E-mail: amitknp@postech.ac.kr, E-mail: amit.knp02@gmail.com, E-mail: hwanghs@postech.ac.kr; Song, J.; Hwang, H., E-mail: amitknp@postech.ac.kr, E-mail: amit.knp02@gmail.com, E-mail: hwanghs@postech.ac.kr

In order to obtain reliable multilevel cell (MLC) characteristics, resistance controllability between the different resistance levels is required especially in resistive random access memory (RRAM), which is prone to resistance variability mainly due to its intrinsic random nature of defect generation and filament formation. In this study, we have thoroughly investigated the multilevel resistance variability in a TaO{sub x}-based nanoscale (<30 nm) RRAM operated in MLC mode. It is found that the resistance variability not only depends on the conductive filament size but also is a strong function of oxygen vacancy concentration in it. Based on the gained insights through experimentalmore » observations and simulation, it is suggested that forming thinner but denser conductive filament may greatly improve the temporal resistance variability even at low operation current despite the inherent stochastic nature of resistance switching process.« less

Self-Regulated Learning and Ethnic/Racial Variables: Predicting Minority First-Generation College Students' Persistence

ERIC Educational Resources Information Center

Moore, John S., III.

2013-01-01

The purpose of this study was to investigate how self-regulated learning and ethnic/racial variables predict minority first-generation college student persistence and related constructs. Participants were drawn nationally from the U.S. Department of Education funded TRiO Student Support Services Programs. Additional participants from the Talent…

Semantic attributes based texture generation

NASA Astrophysics Data System (ADS)

Chi, Huifang; Gan, Yanhai; Qi, Lin; Dong, Junyu; Madessa, Amanuel Hirpa

2018-04-01

Semantic attributes are commonly used for texture description. They can be used to describe the information of a texture, such as patterns, textons, distributions, brightness, and so on. Generally speaking, semantic attributes are more concrete descriptors than perceptual features. Therefore, it is practical to generate texture images from semantic attributes. In this paper, we propose to generate high-quality texture images from semantic attributes. Over the last two decades, several works have been done on texture synthesis and generation. Most of them focusing on example-based texture synthesis and procedural texture generation. Semantic attributes based texture generation still deserves more devotion. Gan et al. proposed a useful joint model for perception driven texture generation. However, perceptual features are nonobjective spatial statistics used by humans to distinguish different textures in pre-attentive situations. To give more describing information about texture appearance, semantic attributes which are more in line with human description habits are desired. In this paper, we use sigmoid cross entropy loss in an auxiliary model to provide enough information for a generator. Consequently, the discriminator is released from the relatively intractable mission of figuring out the joint distribution of condition vectors and samples. To demonstrate the validity of our method, we compare our method to Gan et al.'s method on generating textures by designing experiments on PTD and DTD. All experimental results show that our model can generate textures from semantic attributes.

LineageSpecificSeqgen: generating sequence data with lineage-specific variation in the proportion of variable sites

PubMed Central

Grievink, Liat Shavit; Penny, David; Hendy, Mike D; Holland, Barbara R

2009-01-01

Correction to Shavit Grievink L, Penny D, Hendy MD, Holland BR: LineageSpecificSeqgen: generating sequence data with lineage-specific variation in the proportion of variable sites. BMC Evol Biol 2008, 8(1):317.

Ontology-Based Multiple Choice Question Generation

PubMed Central

Al-Yahya, Maha

2014-01-01

With recent advancements in Semantic Web technologies, a new trend in MCQ item generation has emerged through the use of ontologies. Ontologies are knowledge representation structures that formally describe entities in a domain and their relationships, thus enabling automated inference and reasoning. Ontology-based MCQ item generation is still in its infancy, but substantial research efforts are being made in the field. However, the applicability of these models for use in an educational setting has not been thoroughly evaluated. In this paper, we present an experimental evaluation of an ontology-based MCQ item generation system known as OntoQue. The evaluation was conducted using two different domain ontologies. The findings of this study show that ontology-based MCQ generation systems produce satisfactory MCQ items to a certain extent. However, the evaluation also revealed a number of shortcomings with current ontology-based MCQ item generation systems with regard to the educational significance of an automatically constructed MCQ item, the knowledge level it addresses, and its language structure. Furthermore, for the task to be successful in producing high-quality MCQ items for learning assessments, this study suggests a novel, holistic view that incorporates learning content, learning objectives, lexical knowledge, and scenarios into a single cohesive framework. PMID:24982937

Web-4D-QSAR: A web-based application to generate 4D-QSAR descriptors.

PubMed

Ataide Martins, João Paulo; Rougeth de Oliveira, Marco Antônio; Oliveira de Queiroz, Mário Sérgio

2018-06-05

A web-based application is developed to generate 4D-QSAR descriptors using the LQTA-QSAR methodology, based on molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package. The LQTAGrid module calculates the intermolecular interaction energies at each grid point, considering probes and all aligned conformations resulting from MD simulations. These interaction energies are the independent variables or descriptors employed in a QSAR analysis. A friendly front end web interface, built using the Django framework and Python programming language, integrates all steps of the LQTA-QSAR methodology in a way that is transparent to the user, and in the backend, GROMACS and LQTAGrid are executed to generate 4D-QSAR descriptors to be used later in the process of QSAR model building. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks.

PubMed

Pirbhulal, Sandeep; Zhang, Heye; Mukhopadhyay, Subhas Chandra; Li, Chunyue; Wang, Yumei; Li, Guanglin; Wu, Wanqing; Zhang, Yuan-Ting

2015-06-26

Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

A three-lead, programmable, and microcontroller-based electrocardiogram generator with frequency domain characteristics of heart rate variability.

PubMed

Wei, Ying-Chieh; Wei, Ying-Yu; Chang, Kai-Hsiung; Young, Ming-Shing

2012-04-01

The objective of this study is to design and develop a programmable electrocardiogram (ECG) generator with frequency domain characteristics of heart rate variability (HRV) which can be used to test the efficiency of ECG algorithms and to calibrate and maintain ECG equipment. We simplified and modified the three coupled ordinary differential equations in McSharry's model to a single differential equation to obtain the ECG signal. This system not only allows the signal amplitude, heart rate, QRS-complex slopes, and P- and T-wave position parameters to be adjusted, but can also be used to adjust the very low frequency, low frequency, and high frequency components of HRV frequency domain characteristics. The system can be tuned to function with HRV or not. When the HRV function is on, the average heart rate can be set to a value ranging from 20 to 122 beats per minute (BPM) with an adjustable variation of 1 BPM. When the HRV function is off, the heart rate can be set to a value ranging from 20 to 139 BPM with an adjustable variation of 1 BPM. The amplitude of the ECG signal can be set from 0.0 to 330 mV at a resolution of 0.005 mV. These parameters can be adjusted either via input through a keyboard or through a graphical user interface (GUI) control panel that was developed using LABVIEW. The GUI control panel depicts a preview of the ECG signal such that the user can adjust the parameters to establish a desired ECG morphology. A complete set of parameters can be stored in the flash memory of the system via a USB 2.0 interface. Our system can generate three different types of synthetic ECG signals for testing the efficiency of an ECG algorithm or calibrating and maintaining ECG equipment. © 2012 American Institute of Physics

A three-lead, programmable, and microcontroller-based electrocardiogram generator with frequency domain characteristics of heart rate variability

NASA Astrophysics Data System (ADS)

Wei, Ying-Chieh; Wei, Ying-Yu; Chang, Kai-Hsiung; Young, Ming-Shing

2012-04-01

The objective of this study is to design and develop a programmable electrocardiogram (ECG) generator with frequency domain characteristics of heart rate variability (HRV) which can be used to test the efficiency of ECG algorithms and to calibrate and maintain ECG equipment. We simplified and modified the three coupled ordinary differential equations in McSharry's model to a single differential equation to obtain the ECG signal. This system not only allows the signal amplitude, heart rate, QRS-complex slopes, and P- and T-wave position parameters to be adjusted, but can also be used to adjust the very low frequency, low frequency, and high frequency components of HRV frequency domain characteristics. The system can be tuned to function with HRV or not. When the HRV function is on, the average heart rate can be set to a value ranging from 20 to 122 beats per minute (BPM) with an adjustable variation of 1 BPM. When the HRV function is off, the heart rate can be set to a value ranging from 20 to 139 BPM with an adjustable variation of 1 BPM. The amplitude of the ECG signal can be set from 0.0 to 330 mV at a resolution of 0.005 mV. These parameters can be adjusted either via input through a keyboard or through a graphical user interface (GUI) control panel that was developed using LABVIEW. The GUI control panel depicts a preview of the ECG signal such that the user can adjust the parameters to establish a desired ECG morphology. A complete set of parameters can be stored in the flash memory of the system via a USB 2.0 interface. Our system can generate three different types of synthetic ECG signals for testing the efficiency of an ECG algorithm or calibrating and maintaining ECG equipment.

A Geostatistical Scaling Approach for the Generation of Non Gaussian Random Variables and Increments

NASA Astrophysics Data System (ADS)

Guadagnini, Alberto; Neuman, Shlomo P.; Riva, Monica; Panzeri, Marco

2016-04-01

We address manifestations of non-Gaussian statistical scaling displayed by many variables, Y, and their (spatial or temporal) increments. Evidence of such behavior includes symmetry of increment distributions at all separation distances (or lags) with sharp peaks and heavy tails which tend to decay asymptotically as lag increases. Variables reported to exhibit such distributions include quantities of direct relevance to hydrogeological sciences, e.g. porosity, log permeability, electrical resistivity, soil and sediment texture, sediment transport rate, rainfall, measured and simulated turbulent fluid velocity, and other. No model known to us captures all of the documented statistical scaling behaviors in a unique and consistent manner. We recently proposed a generalized sub-Gaussian model (GSG) which reconciles within a unique theoretical framework the probability distributions of a target variable and its increments. We presented an algorithm to generate unconditional random realizations of statistically isotropic or anisotropic GSG functions and illustrated it in two dimensions. In this context, we demonstrated the feasibility of estimating all key parameters of a GSG model underlying a single realization of Y by analyzing jointly spatial moments of Y data and corresponding increments. Here, we extend our GSG model to account for noisy measurements of Y at a discrete set of points in space (or time), present an algorithm to generate conditional realizations of corresponding isotropic or anisotropic random field, and explore them on one- and two-dimensional synthetic test cases.

Optimal Solar PV Arrays Integration for Distributed Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Omitaomu, Olufemi A; Li, Xueping

2012-01-01

Solar photovoltaic (PV) systems hold great potential for distributed energy generation by installing PV panels on rooftops of residential and commercial buildings. Yet challenges arise along with the variability and non-dispatchability of the PV systems that affect the stability of the grid and the economics of the PV system. This paper investigates the integration of PV arrays for distributed generation applications by identifying a combination of buildings that will maximize solar energy output and minimize system variability. Particularly, we propose mean-variance optimization models to choose suitable rooftops for PV integration based on Markowitz mean-variance portfolio selection model. We further introducemore » quantity and cardinality constraints to result in a mixed integer quadratic programming problem. Case studies based on real data are presented. An efficient frontier is obtained for sample data that allows decision makers to choose a desired solar energy generation level with a comfortable variability tolerance level. Sensitivity analysis is conducted to show the tradeoffs between solar PV energy generation potential and variability.« less

Parametric vs. non-parametric daily weather generator: validation and comparison

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin

2016-04-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30 years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series

Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis

PubMed Central

Dinalankara, Wikum; Bravo, Héctor Corrada

2015-01-01

Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings. PMID:26078586

Interannual rainfall variability and SOM-based circulation classification

NASA Astrophysics Data System (ADS)

Wolski, Piotr; Jack, Christopher; Tadross, Mark; van Aardenne, Lisa; Lennard, Christopher

2018-01-01

Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disaggregated SOM (7 × 9) of prognostic atmospheric variables, including specific humidity, air temperature and geostrophic winds, captures only 20-45% of interannual local rainfall variability, and that the residual variance contains a strong systematic component. Utilising a multivariate linear regression framework demonstrates that this residual variance can largely be explained using synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained

Model-based quality assessment and base-calling for second-generation sequencing data.

PubMed

Bravo, Héctor Corrada; Irizarry, Rafael A

2010-09-01

Second-generation sequencing (sec-gen) technology can sequence millions of short fragments of DNA in parallel, making it capable of assembling complex genomes for a small fraction of the price and time of previous technologies. In fact, a recently formed international consortium, the 1000 Genomes Project, plans to fully sequence the genomes of approximately 1200 people. The prospect of comparative analysis at the sequence level of a large number of samples across multiple populations may be achieved within the next five years. These data present unprecedented challenges in statistical analysis. For instance, analysis operates on millions of short nucleotide sequences, or reads-strings of A,C,G, or T's, between 30 and 100 characters long-which are the result of complex processing of noisy continuous fluorescence intensity measurements known as base-calling. The complexity of the base-calling discretization process results in reads of widely varying quality within and across sequence samples. This variation in processing quality results in infrequent but systematic errors that we have found to mislead downstream analysis of the discretized sequence read data. For instance, a central goal of the 1000 Genomes Project is to quantify across-sample variation at the single nucleotide level. At this resolution, small error rates in sequencing prove significant, especially for rare variants. Sec-gen sequencing is a relatively new technology for which potential biases and sources of obscuring variation are not yet fully understood. Therefore, modeling and quantifying the uncertainty inherent in the generation of sequence reads is of utmost importance. In this article, we present a simple model to capture uncertainty arising in the base-calling procedure of the Illumina/Solexa GA platform. Model parameters have a straightforward interpretation in terms of the chemistry of base-calling allowing for informative and easily interpretable metrics that capture the variability in

Accuracy of latent-variable estimation in Bayesian semi-supervised learning.

PubMed

Yamazaki, Keisuke

2015-09-01

Hierarchical probabilistic models, such as Gaussian mixture models, are widely used for unsupervised learning tasks. These models consist of observable and latent variables, which represent the observable data and the underlying data-generation process, respectively. Unsupervised learning tasks, such as cluster analysis, are regarded as estimations of latent variables based on the observable ones. The estimation of latent variables in semi-supervised learning, where some labels are observed, will be more precise than that in unsupervised, and one of the concerns is to clarify the effect of the labeled data. However, there has not been sufficient theoretical analysis of the accuracy of the estimation of latent variables. In a previous study, a distribution-based error function was formulated, and its asymptotic form was calculated for unsupervised learning with generative models. It has been shown that, for the estimation of latent variables, the Bayes method is more accurate than the maximum-likelihood method. The present paper reveals the asymptotic forms of the error function in Bayesian semi-supervised learning for both discriminative and generative models. The results show that the generative model, which uses all of the given data, performs better when the model is well specified. Copyright © 2015 Elsevier Ltd. All rights reserved.

Variable selection for confounder control, flexible modeling and Collaborative Targeted Minimum Loss-based Estimation in causal inference

PubMed Central

Schnitzer, Mireille E.; Lok, Judith J.; Gruber, Susan

2015-01-01

This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low-and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios. PMID:26226129

Variable Selection for Confounder Control, Flexible Modeling and Collaborative Targeted Minimum Loss-Based Estimation in Causal Inference.

PubMed

Schnitzer, Mireille E; Lok, Judith J; Gruber, Susan

2016-05-01

This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010 [27]) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low- and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios.

Exploring Relationships between Personal Variables, Programmatic Variables, and Self-Efficacy in School-Based Agricultural Education

ERIC Educational Resources Information Center

McKim, Aaron J.; Velez, Jonathan J.; Clement, Haley Q.

2017-01-01

The educational importance of teacher self-efficacy necessitates research into variables presumed to significantly influence teacher self-efficacy. In the current study, the role of personal and programmatic variables on the self-efficacy of school-based agriculture teachers was explored. Self-efficacy was measured in five aspects of the…

Task-Based Variability in Children's Singing Accuracy

ERIC Educational Resources Information Center

Nichols, Bryan E.

2013-01-01

The purpose of this study was to explore task-based variability in children's singing accuracy performance. The research questions were: Does children's singing accuracy vary based on the nature of the singing assessment employed? Is there a hierarchy of difficulty and discrimination ability among singing assessment tasks? What is the…

8760-Based Method for Representing Variable Generation Capacity Value in Capacity Expansion Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Frew, Bethany A

Capacity expansion models (CEMs) are widely used to evaluate the least-cost portfolio of electricity generators, transmission, and storage needed to reliably serve load over many years or decades. CEMs can be computationally complex and are often forced to estimate key parameters using simplified methods to achieve acceptable solve times or for other reasons. In this paper, we discuss one of these parameters -- capacity value (CV). We first provide a high-level motivation for and overview of CV. We next describe existing modeling simplifications and an alternate approach for estimating CV that utilizes hourly '8760' data of load and VG resources.more » We then apply this 8760 method to an established CEM, the National Renewable Energy Laboratory's (NREL's) Regional Energy Deployment System (ReEDS) model (Eurek et al. 2016). While this alternative approach for CV is not itself novel, it contributes to the broader CEM community by (1) demonstrating how a simplified 8760 hourly method, which can be easily implemented in other power sector models when data is available, more accurately captures CV trends than a statistical method within the ReEDS CEM, and (2) providing a flexible modeling framework from which other 8760-based system elements (e.g., demand response, storage, and transmission) can be added to further capture important dynamic interactions, such as curtailment.« less

A knowledge-base generating hierarchical fuzzy-neural controller.

PubMed

Kandadai, R M; Tien, J M

1997-01-01

We present an innovative fuzzy-neural architecture that is able to automatically generate a knowledge base, in an extractable form, for use in hierarchical knowledge-based controllers. The knowledge base is in the form of a linguistic rule base appropriate for a fuzzy inference system. First, we modify Berenji and Khedkar's (1992) GARIC architecture to enable it to automatically generate a knowledge base; a pseudosupervised learning scheme using reinforcement learning and error backpropagation is employed. Next, we further extend this architecture to a hierarchical controller that is able to generate its own knowledge base. Example applications are provided to underscore its viability.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

PubMed Central

Pirbhulal, Sandeep; Zhang, Heye; Mukhopadhyay, Subhas Chandra; Li, Chunyue; Wang, Yumei; Li, Guanglin; Wu, Wanqing; Zhang, Yuan-Ting

2015-01-01

Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption. PMID:26131666

An Efficient Variable Screening Method for Effective Surrogate Models for Reliability-Based Design Optimization

DTIC Science & Technology

2014-04-01

surrogate model generation is difficult for high -dimensional problems, due to the curse of dimensionality. Variable screening methods have been...a variable screening model was developed for the quasi-molecular treatment of ion-atom collision [16]. In engineering, a confidence interval of...for high -level radioactive waste [18]. Moreover, the design sensitivity method can be extended to the variable screening method because vital

A Peltier-based variable temperature source

NASA Astrophysics Data System (ADS)

Molki, Arman; Roof Baba, Abdul

2014-11-01

In this paper we propose a simple and cost-effective variable temperature source based on the Peltier effect using a commercially purchased thermoelectric cooler. The proposed setup can be used to quickly establish relatively accurate dry temperature reference points, which are necessary for many temperature applications such as thermocouple calibration.

BEAT: A Web-Based Boolean Expression Fault-Based Test Case Generation Tool

ERIC Educational Resources Information Center

Chen, T. Y.; Grant, D. D.; Lau, M. F.; Ng, S. P.; Vasa, V. R.

2006-01-01

BEAT is a Web-based system that generates fault-based test cases from Boolean expressions. It is based on the integration of our several fault-based test case selection strategies. The generated test cases are considered to be fault-based, because they are aiming at the detection of particular faults. For example, when the Boolean expression is in…

Validation of two (parametric vs non-parametric) daily weather generators

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Skalak, P.

2015-12-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed-like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30-years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series

Coal and Coal/Biomass-Based Power Generation

EPA Science Inventory

For Frank Princiotta's book, Global Climate Change--The Technology Challenge Coal is a key, growing component in power generation globally. It generates 50% of U.S. electricity, and criteria emissions from coal-based power generation are being reduced. However, CO2 emissions m...

Pulsed corona generation using a diode-based pulsed power generator

NASA Astrophysics Data System (ADS)

Pemen, A. J. M.; Grekhov, I. V.; van Heesch, E. J. M.; Yan, K.; Nair, S. A.; Korotkov, S. V.

2003-10-01

Pulsed plasma techniques serve a wide range of unconventional processes, such as gas and water processing, hydrogen production, and nanotechnology. Extending research on promising applications, such as pulsed corona processing, depends to a great extent on the availability of reliable, efficient and repetitive high-voltage pulsed power technology. Heavy-duty opening switches are the most critical components in high-voltage pulsed power systems with inductive energy storage. At the Ioffe Institute, an unconventional switching mechanism has been found, based on the fast recovery process in a diode. This article discusses the application of such a "drift-step-recovery-diode" for pulsed corona plasma generation. The principle of the diode-based nanosecond high-voltage generator will be discussed. The generator will be coupled to a corona reactor via a transmission-line transformer. The advantages of this concept, such as easy voltage transformation, load matching, switch protection and easy coupling with a dc bias voltage, will be discussed. The developed circuit is tested at both a resistive load and various corona reactors. Methods to optimize the energy transfer to a corona reactor have been evaluated. The impedance matching between the pulse generator and corona reactor can be significantly improved by using a dc bias voltage. At good matching, the corona energy increases and less energy reflects back to the generator. Matching can also be slightly improved by increasing the temperature in the corona reactor. More effective is to reduce the reactor pressure.

CONSTRAINTS ON VARIABLES IN SYNTAX.

ERIC Educational Resources Information Center

ROSS, JOHN ROBERT

IN ATTEMPTING TO DEFINE "SYNTACTIC VARIABLE," THE AUTHOR BASES HIS DISCUSSION ON THE ASSUMPTION THAT SYNTACTIC FACTS ARE A COLLECTION OF TWO TYPES OF RULES--CONTEXT-FREE PHRASE STRUCTURE RULES (GENERATING UNDERLYING OR DEEP PHRASE MARKERS) AND GRAMMATICAL TRANSFORMATIONS, WHICH MAP UNDERLYING PHRASE MARKERS ONTO SUPERFICIAL (OR SURFACE) PHRASE…

Diffractive optical variable image devices generated by maskless interferometric lithography for optical security

NASA Astrophysics Data System (ADS)

Cabral, Alexandre; Rebordão, José M.

2011-05-01

In optical security (protection against forgery and counterfeit of products and documents) the problem is not exact reproduction but the production of something sufficiently similar to the original. Currently, Diffractive Optically Variable Image Devices (DOVID), that create dynamic chromatic effects which may be easily recognized but are difficult to reproduce, are often used to protect important products and documents. Well known examples of DOVID for security are 3D or 2D/3D holograms in identity documents and credit cards. Others are composed of shapes with different types of microstructures yielding by diffraction to chromatic dynamic effects. A maskless interferometric lithography technique to generate DOVIDs for optical security is presented and compared to traditional techniques. The approach can be considered as a self-masking focused holography on planes tilted with respect to the reference optical axes of the system, and is based on the Scheimpflug and Hinge rules. No physical masks are needed to ensure optimum exposure of the photosensitive film. The system built to demonstrate the technique relies on the digital mirrors device MOEMS technology from Texas Instruments' Digital Light Processing. The technique is linear on the number of specified colors and does not depend either on the area of the device or the number of pixels, factors that drive the complexity of dot-matrix based systems. The results confirmed the technique innovation and capabilities in the creation of diffractive optical elements for security against counterfeiting and forgery.

Variable selection based cotton bollworm odor spectroscopic detection

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Gai, Shasha; Luo, Min; Zhao, Bo

2016-10-01

Aiming at rapid automatic pest detection based efficient and targeting pesticide application and shooting the trouble of reflectance spectral signal covered and attenuated by the solid plant, the possibility of near infrared spectroscopy (NIRS) detection on cotton bollworm odor is studied. Three cotton bollworm odor samples and 3 blank air gas samples were prepared. Different concentrations of cotton bollworm odor were prepared by mixing the above gas samples, resulting a calibration group of 62 samples and a validation group of 31 samples. Spectral collection system includes light source, optical fiber, sample chamber, spectrometer. Spectra were pretreated by baseline correction, modeled with partial least squares (PLS), and optimized by genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS). Minor counts differences are found among spectra of different cotton bollworm odor concentrations. PLS model of all the variables was built presenting RMSEV of 14 and RV2 of 0.89, its theory basis is insect volatilizes specific odor, including pheromone and allelochemics, which are used for intra-specific and inter-specific communication and could be detected by NIR spectroscopy. 28 sensitive variables are selected by GA, presenting the model performance of RMSEV of 14 and RV2 of 0.90. Comparably, 8 sensitive variables are selected by CARS, presenting the model performance of RMSEV of 13 and RV2 of 0.92. CARS model employs only 1.5% variables presenting smaller error than that of all variable. Odor gas based NIR technique shows the potential for cotton bollworm detection.

Skyrmion-based high-frequency signal generator

NASA Astrophysics Data System (ADS)

Luo, Shijiang; Zhang, Yue; Shen, Maokang; Ou-Yang, Jun; Yan, Baiqian; Yang, Xiaofei; Chen, Shi; Zhu, Benpeng; You, Long

2017-03-01

Many concepts for skyrmion-based devices have been proposed, and most of their possible applications are based on the motion of skyrmions driven by a dc current in an area with a constricted geometry. However, skyrmion motion driven by a pulsed current has not been investigated so far. In this work, we propose a skyrmion-based high-frequency signal generator based on the pulsed-current-driven circular motion of skyrmions in a square-shaped film by micromagnetic simulation. The results indicate that skyrmions can move in a closed curve with central symmetry. The trajectory and cycle period can be adjusted by tuning the size of the film, the current density, the Dzyaloshinskii-Moriya interaction constant, and the local in-plane magnetic anisotropy. The period can be tuned from several nanoseconds to tens of nanoseconds, which offers the possibility to prepare high-frequency signal generator based on skyrmions.

Generation of electromagnetic energy in a magnetic cumulation generator with the use of inductively coupled circuits with a variable coupling coefficient

NASA Astrophysics Data System (ADS)

Gilev, S. D.; Prokopiev, V. S.

2017-07-01

A method of generation of electromagnetic energy and magnetic flux in a magnetic cumulation generator is proposed. The method is based on dynamic variation of the circuit coupling coefficient. This circuit is compared with other available circuits of magnetic energy generation with the help of magnetic cumulation (classical magnetic cumulation generator, generator with transformer coupling, and generator with a dynamic transformer). It is demonstrated that the proposed method allows obtaining high values of magnetic energy. The proposed circuit is found to be more effective than the known transformer circuit. Experiments on electromagnetic energy generation are performed, which demonstrate the efficiency of the proposed method.

Continuous Variable Cluster State Generation over the Optical Spatial Mode Comb

DOE PAGES

Pooser, Raphael C.; Jing, Jietai

2014-10-20

One way quantum computing uses single qubit projective measurements performed on a cluster state (a highly entangled state of multiple qubits) in order to enact quantum gates. The model is promising due to its potential scalability; the cluster state may be produced at the beginning of the computation and operated on over time. Continuous variables (CV) offer another potential benefit in the form of deterministic entanglement generation. This determinism can lead to robust cluster states and scalable quantum computation. Recent demonstrations of CV cluster states have made great strides on the path to scalability utilizing either time or frequency multiplexingmore » in optical parametric oscillators (OPO) both above and below threshold. The techniques relied on a combination of entangling operators and beam splitter transformations. Here we show that an analogous transformation exists for amplifiers with Gaussian inputs states operating on multiple spatial modes. By judicious selection of local oscillators (LOs), the spatial mode distribution is analogous to the optical frequency comb consisting of axial modes in an OPO cavity. We outline an experimental system that generates cluster states across the spatial frequency comb which can also scale the amount of quantum noise reduction to potentially larger than in other systems.« less

Reducing Demand Charges and Onsite Generation Variability Using Behind-the-Meter Energy Storage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhattarai, Bishnu P.; Myers, Kurt S.; Bush, Jason W.

Electric utilities in the United States are increasingly employing demand charges and/or real-time pricing. This directive is bringing potential opportunities in deploying behindthe-meter energy storage (BMES) systems for various grid functionalities. This study quantifies techno-economic benefits of BMES in reducing demand charge and smoothing load/generation intermittencies, and determines how those benefits vary with onsite distributed photovoltaic. We proposed a two-stage control algorithm, whereby the first stage proactively determines costoptimal BMES configuration for reducing peak-demands and demand charges, and the second stage adaptively compensates intermittent generations and short load spikes that may otherwise increase the demand charges. The performance of themore » proposed algorithm is evaluated through a 24 hours time sweep simulation performed using data from smart microgrid testbed at Idaho National Laboratory (INL). The simulation results demonstrated that this research provides a simple but effective solution for peak shaving, demand charge reductions, and smoothing onsite PV variability.« less

Hydrogen-based power generation from bioethanol steam reforming

NASA Astrophysics Data System (ADS)

Tasnadi-Asztalos, Zs.; Cormos, C. C.; Agachi, P. S.

2015-12-01

This paper is evaluating two power generation concepts based on hydrogen produced from bioethanol steam reforming at industrial scale without and with carbon capture. The power generation from bioethanol conversion is based on two important steps: hydrogen production from bioethanol catalytic steam reforming and electricity generation using a hydrogen-fuelled gas turbine. As carbon capture method to be assessed in hydrogen-based power generation from bioethanol steam reforming, the gas-liquid absorption using methyl-di-ethanol-amine (MDEA) was used. Bioethanol is a renewable energy carrier mainly produced from biomass fermentation. Steam reforming of bioethanol (SRE) provides a promising method for hydrogen and power production from renewable resources. SRE is performed at high temperatures (e.g. 800-900°C) to reduce the reforming by-products (e.g. ethane, ethene). The power generation from hydrogen was done with M701G2 gas turbine (334 MW net power output). Hydrogen was obtained through catalytic steam reforming of bioethanol without and with carbon capture. For the evaluated plant concepts the following key performance indicators were assessed: fuel consumption, gross and net power outputs, net electrical efficiency, ancillary consumptions, carbon capture rate, specific CO2 emission etc. As the results show, the power generation based on bioethanol conversion has high energy efficiency and low carbon footprint.

Design Study: Rocket Based MHD Generator

NASA Technical Reports Server (NTRS)

1997-01-01

This report addresses the technical feasibility and design of a rocket based MHD generator using a sub-scale LOx/RP rocket motor. The design study was constrained by assuming the generator must function within the performance and structural limits of an existing magnet and by assuming realistic limits on (1) the axial electric field, (2) the Hall parameter, (3) current density, and (4) heat flux (given the criteria of heat sink operation). The major results of the work are summarized as follows: (1) A Faraday type of generator with rectangular cross section is designed to operate with a combustor pressure of 300 psi. Based on a magnetic field strength of 1.5 Tesla, the electrical power output from this generator is estimated to be 54.2 KW with potassium seed (weight fraction 3.74%) and 92 KW with cesium seed (weight fraction 9.66%). The former corresponds to a enthalpy extraction ratio of 2.36% while that for the latter is 4.16%; (2) A conceptual design of the Faraday MHD channel is proposed, based on a maximum operating time of 10 to 15 seconds. This concept utilizes a phenolic back wall for inserting the electrodes and inter-electrode insulators. Copper electrode and aluminum oxide insulator are suggested for this channel; and (3) A testing configuration for the sub-scale rocket based MHD system is proposed. An estimate of performance of an ideal rocket based MHD accelerator is performed. With a current density constraint of 5 Amps/cm(exp 2) and a conductivity of 30 Siemens/m, the push power density can be 250, 431, and 750 MW/m(sup 3) when the induced voltage uB have values of 5, 10, and 15 KV/m, respectively.

Identification of Important Process Variables for Fiber Spinning of Protein Nanotubes Generated from Waste Materials

DTIC Science & Technology

2012-01-11

nanotubes , which sold at the same current cost as carbon nanotubes , this would equate to a $788 million industry. In the USA, the potential to source eye...advantages over carbon nanotubes due to the ability to functionalized them 31. The nanotubes are a highly ordered, insoluble form of protein. Fibrils...1756 Identification of important process variables for fiber spinning of protein nanotubes generated from waste materials. Research Team (listed

Variable flexure-based fluid filter

DOEpatents

Brown, Steve B.; Colston, Jr., Billy W.; Marshall, Graham; Wolcott, Duane

2007-03-13

An apparatus and method for filtering particles from a fluid comprises a fluid inlet, a fluid outlet, a variable size passage between the fluid inlet and the fluid outlet, and means for adjusting the size of the variable size passage for filtering the particles from the fluid. An inlet fluid flow stream is introduced to a fixture with a variable size passage. The size of the variable size passage is set so that the fluid passes through the variable size passage but the particles do not pass through the variable size passage.

DNA-based random number generation in security circuitry.

PubMed

Gearheart, Christy M; Arazi, Benjamin; Rouchka, Eric C

2010-06-01

DNA-based circuit design is an area of research in which traditional silicon-based technologies are replaced by naturally occurring phenomena taken from biochemistry and molecular biology. This research focuses on further developing DNA-based methodologies to mimic digital data manipulation. While exhibiting fundamental principles, this work was done in conjunction with the vision that DNA-based circuitry, when the technology matures, will form the basis for a tamper-proof security module, revolutionizing the meaning and concept of tamper-proofing and possibly preventing it altogether based on accurate scientific observations. A paramount part of such a solution would be self-generation of random numbers. A novel prototype schema employs solid phase synthesis of oligonucleotides for random construction of DNA sequences; temporary storage and retrieval is achieved through plasmid vectors. A discussion of how to evaluate sequence randomness is included, as well as how these techniques are applied to a simulation of the random number generation circuitry. Simulation results show generated sequences successfully pass three selected NIST random number generation tests specified for security applications.

Data driven model generation based on computational intelligence

NASA Astrophysics Data System (ADS)

Gemmar, Peter; Gronz, Oliver; Faust, Christophe; Casper, Markus

2010-05-01

parameters with respect to a defined rating function and experimental data. To find A, we use for example a linear equation solver and RMSE-function. In practical process models, the number of Fuzzy sets and the according number of rules is fairly low. Nevertheless, creating the optimal model requires some experience. Therefore, we improved this development step by methods for automatic generation of Fuzzy sets, rules, and conclusions. Basically, the model achievement depends to a great extend on the selection of the conclusion variables. It is the aim that variables having most influence on the system reaction being considered and superfluous ones being neglected. At first, we use Kohonen maps, a specialized ANN, to identify relevant input variables from the large set of available system variables. A greedy algorithm selects a comprehensive set of dominant and uncorrelated variables. Next, the premise variables are analyzed with clustering methods (e.g. Fuzzy-C-means) and Fuzzy sets are then derived from cluster centers and outlines. The rule base is automatically constructed by permutation of the Fuzzy sets of the premise variables. Finally, the conclusion parameters are calculated and the total coverage of the input space is iteratively tested with experimental data, rarely firing rules are combined and coarse coverage of sensitive process states results in refined Fuzzy sets and rules. Results The described methods were implemented and integrated in a development system for process models. A series of models has already been built e.g. for rainfall-runoff modeling or for flood prediction (up to 72 hours) in river catchments. The models required significantly less development effort and showed advanced simulation results compared to conventional models. The models can be used operationally and simulation takes only some minutes on a standard PC e.g. for a gauge forecast (up to 72 hours) for the whole Mosel (Germany) river catchment.

Hydrogen-based power generation from bioethanol steam reforming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tasnadi-Asztalos, Zs., E-mail: tazsolt@chem.ubbcluj.ro; Cormos, C. C., E-mail: cormos@chem.ubbcluj.ro; Agachi, P. S.

This paper is evaluating two power generation concepts based on hydrogen produced from bioethanol steam reforming at industrial scale without and with carbon capture. The power generation from bioethanol conversion is based on two important steps: hydrogen production from bioethanol catalytic steam reforming and electricity generation using a hydrogen-fuelled gas turbine. As carbon capture method to be assessed in hydrogen-based power generation from bioethanol steam reforming, the gas-liquid absorption using methyl-di-ethanol-amine (MDEA) was used. Bioethanol is a renewable energy carrier mainly produced from biomass fermentation. Steam reforming of bioethanol (SRE) provides a promising method for hydrogen and power production frommore » renewable resources. SRE is performed at high temperatures (e.g. 800-900°C) to reduce the reforming by-products (e.g. ethane, ethene). The power generation from hydrogen was done with M701G2 gas turbine (334 MW net power output). Hydrogen was obtained through catalytic steam reforming of bioethanol without and with carbon capture. For the evaluated plant concepts the following key performance indicators were assessed: fuel consumption, gross and net power outputs, net electrical efficiency, ancillary consumptions, carbon capture rate, specific CO{sub 2} emission etc. As the results show, the power generation based on bioethanol conversion has high energy efficiency and low carbon footprint.« less

A multiple-alignment based primer design algorithm for genetically highly variable DNA targets

PubMed Central

2013-01-01

Background Primer design for highly variable DNA sequences is difficult, and experimental success requires attention to many interacting constraints. The advent of next-generation sequencing methods allows the investigation of rare variants otherwise hidden deep in large populations, but requires attention to population diversity and primer localization in relatively conserved regions, in addition to recognized constraints typically considered in primer design. Results Design constraints include degenerate sites to maximize population coverage, matching of melting temperatures, optimizing de novo sequence length, finding optimal bio-barcodes to allow efficient downstream analyses, and minimizing risk of dimerization. To facilitate primer design addressing these and other constraints, we created a novel computer program (PrimerDesign) that automates this complex procedure. We show its powers and limitations and give examples of successful designs for the analysis of HIV-1 populations. Conclusions PrimerDesign is useful for researchers who want to design DNA primers and probes for analyzing highly variable DNA populations. It can be used to design primers for PCR, RT-PCR, Sanger sequencing, next-generation sequencing, and other experimental protocols targeting highly variable DNA samples. PMID:23965160

Use of Partial Least Squares improves the efficacy of removing unwanted variability in differential expression analyses based on RNA-Seq data.

PubMed

Chakraborty, Sutirtha

2018-05-26

RNA-Seq technology has revolutionized the face of gene expression profiling by generating read count data measuring the transcript abundances for each queried gene on multiple experimental subjects. But on the downside, the underlying technical artefacts and hidden biological profiles of the samples generate a wide variety of latent effects that may potentially distort the actual transcript/gene expression signals. Standard normalization techniques fail to correct for these hidden variables and lead to flawed downstream analyses. In this work I demonstrate the use of Partial Least Squares (built as an R package 'SVAPLSseq') to correct for the traces of extraneous variability in RNA-Seq data. A novel and thorough comparative analysis of the PLS based method is presented along with some of the other popularly used approaches for latent variable correction in RNA-Seq. Overall, the method is found to achieve a substantially improved estimation of the hidden effect signatures in the RNA-Seq transcriptome expression landscape compared to other available techniques. Copyright © 2017. Published by Elsevier Inc.

Improvements to Fidelity, Generation and Implementation of Physics-Based Lithium-Ion Reduced-Order Models

NASA Astrophysics Data System (ADS)

Rodriguez Marco, Albert

Battery management systems (BMS) require computationally simple but highly accurate models of the battery cells they are monitoring and controlling. Historically, empirical equivalent-circuit models have been used, but increasingly researchers are focusing their attention on physics-based models due to their greater predictive capabilities. These models are of high intrinsic computational complexity and so must undergo some kind of order-reduction process to make their use by a BMS feasible: we favor methods based on a transfer-function approach of battery cell dynamics. In prior works, transfer functions have been found from full-order PDE models via two simplifying assumptions: (1) a linearization assumption--which is a fundamental necessity in order to make transfer functions--and (2) an assumption made out of expedience that decouples the electrolyte-potential and electrolyte-concentration PDEs in order to render an approach to solve for the transfer functions from the PDEs. This dissertation improves the fidelity of physics-based models by eliminating the need for the second assumption and, by linearizing nonlinear dynamics around different constant currents. Electrochemical transfer functions are infinite-order and cannot be expressed as a ratio of polynomials in the Laplace variable s. Thus, for practical use, these systems need to be approximated using reduced-order models that capture the most significant dynamics. This dissertation improves the generation of physics-based reduced-order models by introducing different realization algorithms, which produce a low-order model from the infinite-order electrochemical transfer functions. Physics-based reduced-order models are linear and describe cell dynamics if operated near the setpoint at which they have been generated. Hence, multiple physics-based reduced-order models need to be generated at different setpoints (i.e., state-of-charge, temperature and C-rate) in order to extend the cell operating range. This

Invited Article: Generation of one-million-mode continuous-variable cluster state by unlimited time-domain multiplexing

NASA Astrophysics Data System (ADS)

Yoshikawa, Jun-ichi; Yokoyama, Shota; Kaji, Toshiyuki; Sornphiphatphong, Chanond; Shiozawa, Yu; Makino, Kenzo; Furusawa, Akira

2016-09-01

In recent quantum optical continuous-variable experiments, the number of fully inseparable light modes has drastically increased by introducing a multiplexing scheme either in the time domain or in the frequency domain. Here, modifying the time-domain multiplexing experiment reported in the work of Yokoyama et al. [Nat. Photonics 7, 982 (2013)], we demonstrate the successive generation of fully inseparable light modes for more than one million modes. The resulting multi-mode state is useful as a dual-rail continuous variable cluster state. We circumvent the previous problem of optical phase drifts, which has limited the number of fully inseparable light modes to around ten thousands, by continuous feedback control of the optical system.

Virus-based piezoelectric energy generation

NASA Astrophysics Data System (ADS)

Lee, Byung Yang; Zhang, Jinxing; Zueger, Chris; Chung, Woo-Jae; Yoo, So Young; Wang, Eddie; Meyer, Joel; Ramesh, Ramamoorthy; Lee, Seung-Wuk

2012-06-01

Piezoelectric materials can convert mechanical energy into electrical energy, and piezoelectric devices made of a variety of inorganic materials and organic polymers have been demonstrated. However, synthesizing such materials often requires toxic starting compounds, harsh conditions and/or complex procedures. Previously, it was shown that hierarchically organized natural materials such as bones, collagen fibrils and peptide nanotubes can display piezoelectric properties. Here, we demonstrate that the piezoelectric and liquid-crystalline properties of M13 bacteriophage (phage) can be used to generate electrical energy. Using piezoresponse force microscopy, we characterize the structure-dependent piezoelectric properties of the phage at the molecular level. We then show that self-assembled thin films of phage can exhibit piezoelectric strengths of up to 7.8 pm V-1. We also demonstrate that it is possible to modulate the dipole strength of the phage, hence tuning the piezoelectric response, by genetically engineering the major coat proteins of the phage. Finally, we develop a phage-based piezoelectric generator that produces up to 6 nA of current and 400 mV of potential and use it to operate a liquid-crystal display. Because biotechnology techniques enable large-scale production of genetically modified phages, phage-based piezoelectric materials potentially offer a simple and environmentally friendly approach to piezoelectric energy generation.

Error Generation in CATS-Based Agents

NASA Technical Reports Server (NTRS)

Callantine, Todd

2003-01-01

This research presents a methodology for generating errors from a model of nominally preferred correct operator activities, given a particular operational context, and maintaining an explicit link to the erroneous contextual information to support analyses. It uses the Crew Activity Tracking System (CATS) model as the basis for error generation. This report describes how the process works, and how it may be useful for supporting agent-based system safety analyses. The report presents results obtained by applying the error-generation process and discusses implementation issues. The research is supported by the System-Wide Accident Prevention Element of the NASA Aviation Safety Program.

The Variability of Gender-Based Communication in Japanese Magazine Advertising.

ERIC Educational Resources Information Center

Maynard, Michael L.

1995-01-01

Analyzes Japanese magazine advertising text from an intracultural perspective based on gender. Uses content analysis to examine advertising text of eight gender-specific magazines. Reveals significant difference in the variability of message perception depending on target gender. Suggests the importance of recognizing intracultural variability,…

Electricity market design for generator revenue sufficiency with increased variable generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levin, Todd; Botterud, Audun

Here, we present a computationally efficient mixed-integer program (MIP) that determines optimal generator expansion decisions, and hourly unit commitment and dispatch in a power system. The impact of increasing wind power capacity on the optimal generation mix and generator profitability is analyzed for a test case that approximates the electricity market in Texas (ERCOT). We analyze three market policies that may support resource adequacy: Operating Reserve Demand Curves (ORDC), Fixed Reserve Scarcity Prices (FRSP) and fixed capacity payments (CP). Optimal expansion plans are comparable between the ORDC and FRSP implementations, while capacity payments may result in additional new capacity. Themore » FRSP policy leads to frequent reserves scarcity events and corresponding price spikes, while the ORDC implementation results in more continuous energy prices. Average energy prices decrease with increasing wind penetration under all policies, as do revenues for baseload and wind generators. Intermediate and peak load plants benefit from higher reserve prices and are less exposed to reduced energy prices. All else equal, an ORDC approach may be preferred to FRSP as it results in similar expansion and revenues with less extreme energy prices. A fixed CP leads to additional new flexible NGCT units, but lower profits for other technologies.« less

Electricity market design for generator revenue sufficiency with increased variable generation

DOE PAGES

Levin, Todd; Botterud, Audun

2015-10-01

Here, we present a computationally efficient mixed-integer program (MIP) that determines optimal generator expansion decisions, and hourly unit commitment and dispatch in a power system. The impact of increasing wind power capacity on the optimal generation mix and generator profitability is analyzed for a test case that approximates the electricity market in Texas (ERCOT). We analyze three market policies that may support resource adequacy: Operating Reserve Demand Curves (ORDC), Fixed Reserve Scarcity Prices (FRSP) and fixed capacity payments (CP). Optimal expansion plans are comparable between the ORDC and FRSP implementations, while capacity payments may result in additional new capacity. Themore » FRSP policy leads to frequent reserves scarcity events and corresponding price spikes, while the ORDC implementation results in more continuous energy prices. Average energy prices decrease with increasing wind penetration under all policies, as do revenues for baseload and wind generators. Intermediate and peak load plants benefit from higher reserve prices and are less exposed to reduced energy prices. All else equal, an ORDC approach may be preferred to FRSP as it results in similar expansion and revenues with less extreme energy prices. A fixed CP leads to additional new flexible NGCT units, but lower profits for other technologies.« less

Model Based Analysis and Test Generation for Flight Software

NASA Technical Reports Server (NTRS)

Pasareanu, Corina S.; Schumann, Johann M.; Mehlitz, Peter C.; Lowry, Mike R.; Karsai, Gabor; Nine, Harmon; Neema, Sandeep

2009-01-01

We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission.

A Tool for Model-Based Generation of Scenario-driven Electric Power Load Profiles

NASA Technical Reports Server (NTRS)

Rozek, Matthew L.; Donahue, Kenneth M.; Ingham, Michel D.; Kaderka, Justin D.

2015-01-01

Power consumption during all phases of spacecraft flight is of great interest to the aerospace community. As a result, significant analysis effort is exerted to understand the rates of electrical energy generation and consumption under many operational scenarios of the system. Previously, no standard tool existed for creating and maintaining a power equipment list (PEL) of spacecraft components that consume power, and no standard tool existed for generating power load profiles based on this PEL information during mission design phases. This paper presents the Scenario Power Load Analysis Tool (SPLAT) as a model-based systems engineering tool aiming to solve those problems. SPLAT is a plugin for MagicDraw (No Magic, Inc.) that aids in creating and maintaining a PEL, and also generates a power and temporal variable constraint set, in Maple language syntax, based on specified operational scenarios. The constraint set can be solved in Maple to show electric load profiles (i.e. power consumption from loads over time). SPLAT creates these load profiles from three modeled inputs: 1) a list of system components and their respective power modes, 2) a decomposition hierarchy of the system into these components, and 3) the specification of at least one scenario, which consists of temporal constraints on component power modes. In order to demonstrate how this information is represented in a system model, a notional example of a spacecraft planetary flyby is introduced. This example is also used to explain the overall functionality of SPLAT, and how this is used to generate electric power load profiles. Lastly, a cursory review of the usage of SPLAT on the Cold Atom Laboratory project is presented to show how the tool was used in an actual space hardware design application.

A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

PubMed

Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao

2014-10-07

In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

Corrugated Textile based Triboelectric Generator for Wearable Energy Harvesting

NASA Astrophysics Data System (ADS)

Choi, A. Young; Lee, Chang Jun; Park, Jiwon; Kim, Dogyun; Kim, Youn Tae

2017-03-01

Triboelectric energy harvesting has been applied to various fields, from large-scale power generation to small electronics. Triboelectric energy is generated when certain materials come into frictional contact, e.g., static electricity from rubbing a shoe on a carpet. In particular, textile-based triboelectric energy-harvesting technologies are one of the most promising approaches because they are not only flexible, light, and comfortable but also wearable. Most previous textile-based triboelectric generators (TEGs) generate energy by vertically pressing and rubbing something. However, we propose a corrugated textile-based triboelectric generator (CT-TEG) that can generate energy by stretching. Moreover, the CT-TEG is sewn into a corrugated structure that contains an effective air gap without additional spacers. The resulting CT-TEG can generate considerable energy from various deformations, not only by pressing and rubbing but also by stretching. The maximum output performances of the CT-TEG can reach up to 28.13 V and 2.71 μA with stretching and releasing motions. Additionally, we demonstrate the generation of sufficient energy from various activities of a human body to power about 54 LEDs. These results demonstrate the potential application of CT-TEGs for self-powered systems.

Simulation-Based Rule Generation Considering Readability

PubMed Central

Yahagi, H.; Shimizu, S.; Ogata, T.; Hara, T.; Ota, J.

2015-01-01

Rule generation method is proposed for an aircraft control problem in an airport. Designing appropriate rules for motion coordination of taxiing aircraft in the airport is important, which is conducted by ground control. However, previous studies did not consider readability of rules, which is important because it should be operated and maintained by humans. Therefore, in this study, using the indicator of readability, we propose a method of rule generation based on parallel algorithm discovery and orchestration (PADO). By applying our proposed method to the aircraft control problem, the proposed algorithm can generate more readable and more robust rules and is found to be superior to previous methods. PMID:27347501

Optoacoustic Monitoring of Physiologic Variables

PubMed Central

Esenaliev, Rinat O.

2017-01-01

Optoacoustic (photoacoustic) technique is a novel diagnostic platform that can be used for noninvasive measurements of physiologic variables, functional imaging, and hemodynamic monitoring. This technique is based on generation and time-resolved detection of optoacoustic (thermoelastic) waves generated in tissue by short optical pulses. This provides probing of tissues and individual blood vessels with high optical contrast and ultrasound spatial resolution. Because the optoacoustic waves carry information on tissue optical and thermophysical properties, detection, and analysis of the optoacoustic waves allow for measurements of physiologic variables with high accuracy and specificity. We proposed to use the optoacoustic technique for monitoring of a number of important physiologic variables including temperature, thermal coagulation, freezing, concentration of molecular dyes, nanoparticles, oxygenation, and hemoglobin concentration. In this review we present origin of contrast and high spatial resolution in these measurements performed with optoacoustic systems developed and built by our group. We summarize data obtained in vitro, in experimental animals, and in humans on monitoring of these physiologic variables. Our data indicate that the optoacoustic technology may be used for monitoring of cerebral blood oxygenation in patients with traumatic brain injury and in neonatal patients, central venous oxygenation monitoring, total hemoglobin concentration monitoring, hematoma detection and characterization, monitoring of temperature, and coagulation and freezing boundaries during thermotherapy. PMID:29311964

Optoacoustic Monitoring of Physiologic Variables.

PubMed

Esenaliev, Rinat O

2017-01-01

Optoacoustic (photoacoustic) technique is a novel diagnostic platform that can be used for noninvasive measurements of physiologic variables, functional imaging, and hemodynamic monitoring. This technique is based on generation and time-resolved detection of optoacoustic (thermoelastic) waves generated in tissue by short optical pulses. This provides probing of tissues and individual blood vessels with high optical contrast and ultrasound spatial resolution. Because the optoacoustic waves carry information on tissue optical and thermophysical properties, detection, and analysis of the optoacoustic waves allow for measurements of physiologic variables with high accuracy and specificity. We proposed to use the optoacoustic technique for monitoring of a number of important physiologic variables including temperature, thermal coagulation, freezing, concentration of molecular dyes, nanoparticles, oxygenation, and hemoglobin concentration. In this review we present origin of contrast and high spatial resolution in these measurements performed with optoacoustic systems developed and built by our group. We summarize data obtained in vitro , in experimental animals, and in humans on monitoring of these physiologic variables. Our data indicate that the optoacoustic technology may be used for monitoring of cerebral blood oxygenation in patients with traumatic brain injury and in neonatal patients, central venous oxygenation monitoring, total hemoglobin concentration monitoring, hematoma detection and characterization, monitoring of temperature, and coagulation and freezing boundaries during thermotherapy.

Mathematical modeling to predict residential solid waste generation.

PubMed

Benítez, Sara Ojeda; Lozano-Olvera, Gabriela; Morelos, Raúl Adalberto; Vega, Carolina Armijo de

2008-01-01

One of the challenges faced by waste management authorities is determining the amount of waste generated by households in order to establish waste management systems, as well as trying to charge rates compatible with the principle applied worldwide, and design a fair payment system for households according to the amount of residential solid waste (RSW) they generate. The goal of this research work was to establish mathematical models that correlate the generation of RSW per capita to the following variables: education, income per household, and number of residents. This work was based on data from a study on generation, quantification and composition of residential waste in a Mexican city in three stages. In order to define prediction models, five variables were identified and included in the model. For each waste sampling stage a different mathematical model was developed, in order to find the model that showed the best linear relation to predict residential solid waste generation. Later on, models to explore the combination of included variables and select those which showed a higher R(2) were established. The tests applied were normality, multicolinearity and heteroskedasticity. Another model, formulated with four variables, was generated and the Durban-Watson test was applied to it. Finally, a general mathematical model is proposed to predict residential waste generation, which accounts for 51% of the total.

Isolated Power Generation System Using Permanent Magnet Synchronous Generator with Improved Power Quality

NASA Astrophysics Data System (ADS)

Arya, Sabha Raj; Patel, Ashish; Giri, Ashutosh

2018-03-01

This paper deals wind energy based power generation system using Permanent Magnet Synchronous Generator (PMSG). It is controlled using advanced enhanced phase-lock loop for power quality features using distribution static compensator to eliminate the harmonics and to provide KVAR compensation as well as load balancing. It also manages rated potential at the point of common interface under linear and non-linear loads. In order to have better efficiency and reliable operation of PMSG driven by wind turbine, it is necessary to analyze the governing equation of wind based turbine and PMSG under fixed and variable wind speed. For handling power quality problems, power electronics based shunt connected custom power device is used in three wire system. The simulations in MATLAB/Simulink environment have been carried out in order to demonstrate this model and control approach used for the power quality enhancement. The performance results show the adequate performance of PMSG based power generation system and control algorithm.

Isolated Power Generation System Using Permanent Magnet Synchronous Generator with Improved Power Quality

NASA Astrophysics Data System (ADS)

Arya, Sabha Raj; Patel, Ashish; Giri, Ashutosh

2018-06-01

This paper deals wind energy based power generation system using Permanent Magnet Synchronous Generator (PMSG). It is controlled using advanced enhanced phase-lock loop for power quality features using distribution static compensator to eliminate the harmonics and to provide KVAR compensation as well as load balancing. It also manages rated potential at the point of common interface under linear and non-linear loads. In order to have better efficiency and reliable operation of PMSG driven by wind turbine, it is necessary to analyze the governing equation of wind based turbine and PMSG under fixed and variable wind speed. For handling power quality problems, power electronics based shunt connected custom power device is used in three wire system. The simulations in MATLAB/Simulink environment have been carried out in order to demonstrate this model and control approach used for the power quality enhancement. The performance results show the adequate performance of PMSG based power generation system and control algorithm.

Electric Grid Expansion Planning with High Levels of Variable Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hadley, Stanton W.; You, Shutang; Shankar, Mallikarjun

2016-02-01

Renewables are taking a large proportion of generation capacity in U.S. power grids. As their randomness has increasing influence on power system operation, it is necessary to consider their impact on system expansion planning. To this end, this project studies the generation and transmission expansion co-optimization problem of the US Eastern Interconnection (EI) power grid with a high wind power penetration rate. In this project, the generation and transmission expansion problem for the EI system is modeled as a mixed-integer programming (MIP) problem. This study analyzed a time series creation method to capture the diversity of load and wind powermore » across balancing regions in the EI system. The obtained time series can be easily introduced into the MIP co-optimization problem and then solved robustly through available MIP solvers. Simulation results show that the proposed time series generation method and the expansion co-optimization model and can improve the expansion result significantly after considering the diversity of wind and load across EI regions. The improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare. This study shows that modelling load and wind variations and diversities across balancing regions will produce significantly different expansion result compared with former studies. For example, if wind is modeled in more details (by increasing the number of wind output levels) so that more wind blocks are considered in expansion planning, transmission expansion will be larger and the expansion timing will be earlier. Regarding generation expansion, more wind scenarios will slightly reduce wind generation expansion in the EI system and increase the expansion of other generation such as gas. Also, adopting detailed wind scenarios will reveal that it may be uneconomic to expand transmission networks for transmitting a large amount of wind power through a long

Smart pitch control strategy for wind generation system using doubly fed induction generator

NASA Astrophysics Data System (ADS)

Raza, Syed Ahmed

A smart pitch control strategy for a variable speed doubly fed wind generation system is presented in this thesis. A complete dynamic model of DFIG system is developed. The model consists of the generator, wind turbine, aerodynamic and the converter system. The strategy proposed includes the use of adaptive neural network to generate optimized controller gains for pitch control. This involves the generation of controller parameters of pitch controller making use of differential evolution intelligent technique. Training of the back propagation neural network has been carried out for the development of an adaptive neural network. This tunes the weights of the network according to the system states in a variable wind speed environment. Four cases have been taken to test the pitch controller which includes step and sinusoidal changes in wind speeds. The step change is composed of both step up and step down changes in wind speeds. The last case makes use of scaled wind data collected from the wind turbine installed at King Fahd University beach front. Simulation studies show that the differential evolution based adaptive neural network is capable of generating the appropriate control to deliver the maximum possible aerodynamic power available from wind to the generator in an efficient manner by minimizing the transients.

Virus-based piezoelectric energy generation.

PubMed

Lee, Byung Yang; Zhang, Jinxing; Zueger, Chris; Chung, Woo-Jae; Yoo, So Young; Wang, Eddie; Meyer, Joel; Ramesh, Ramamoorthy; Lee, Seung-Wuk

2012-05-13

Piezoelectric materials can convert mechanical energy into electrical energy, and piezoelectric devices made of a variety of inorganic materials and organic polymers have been demonstrated. However, synthesizing such materials often requires toxic starting compounds, harsh conditions and/or complex procedures. Previously, it was shown that hierarchically organized natural materials such as bones, collagen fibrils and peptide nanotubes can display piezoelectric properties. Here, we demonstrate that the piezoelectric and liquid-crystalline properties of M13 bacteriophage (phage) can be used to generate electrical energy. Using piezoresponse force microscopy, we characterize the structure-dependent piezoelectric properties of the phage at the molecular level. We then show that self-assembled thin films of phage can exhibit piezoelectric strengths of up to 7.8 pm V(-1). We also demonstrate that it is possible to modulate the dipole strength of the phage, hence tuning the piezoelectric response, by genetically engineering the major coat proteins of the phage. Finally, we develop a phage-based piezoelectric generator that produces up to 6 nA of current and 400 mV of potential and use it to operate a liquid-crystal display. Because biotechnology techniques enable large-scale production of genetically modified phages, phage-based piezoelectric materials potentially offer a simple and environmentally friendly approach to piezoelectric energy generation.

Infant breathing rate counter based on variable resistor for pneumonia

NASA Astrophysics Data System (ADS)

Sakti, Novi Angga; Hardiyanto, Ardy Dwi; La Febry Andira R., C.; Camelya, Kesa; Widiyanti, Prihartini

2016-03-01

Pneumonia is one of the leading causes of death in new born baby in Indonesia. According to WHO in 2002, breathing rate is very important index to be the symptom of pneumonia. In the Community Health Center, the nurses count with a stopwatch for exactly one minute. Miscalculation in Community Health Center occurs because of long time concentration and focus on two object at once. This calculation errors can cause the baby who should be admitted to the hospital only be attended at home. Therefore, an accurate breathing rate counter at Community Health Center level is necessary. In this work, resistance change of variable resistor is made to be breathing rate counter. Resistance change in voltage divider can produce voltage change. If the variable resistance moves periodically, the voltage will change periodically too. The voltage change counted by software in the microcontroller. For the every mm shift at the variable resistor produce average 0.96 voltage change. The software can count the number of wave generated by shifting resistor.

Predictive Inference Using Latent Variables with Covariates*

PubMed Central

Schofield, Lynne Steuerle; Junker, Brian; Taylor, Lowell J.; Black, Dan A.

2014-01-01

Plausible Values (PVs) are a standard multiple imputation tool for analysis of large education survey data that measures latent proficiency variables. When latent proficiency is the dependent variable, we reconsider the standard institutionally-generated PV methodology and find it applies with greater generality than shown previously. When latent proficiency is an independent variable, we show that the standard institutional PV methodology produces biased inference because the institutional conditioning model places restrictions on the form of the secondary analysts’ model. We offer an alternative approach that avoids these biases based on the mixed effects structural equations (MESE) model of Schofield (2008). PMID:25231627

The Hebrewer: A Web-Based Inflection Generator

ERIC Educational Resources Information Center

Foster, James Q.; Harrell, Lane Foster; Raizen, Esther

2004-01-01

This paper reports on the grammatical and programmatical production aspects of the "Hebrewer," a cross-platform web-based reference work in the form of a Hebrew inflection generator. The Hebrewer, a Java applet/servlet combination, is currently capable of generating 2,500 nouns in full declension and 500 verbs in full conjugation,…

Characterizing the Optical Variability of Bright Blazars: Variability-based Selection of Fermi Active Galactic Nuclei

NASA Astrophysics Data System (ADS)

Ruan, John J.; Anderson, Scott F.; MacLeod, Chelsea L.; Becker, Andrew C.; Burnett, T. H.; Davenport, James R. A.; Ivezić, Željko; Kochanek, Christopher S.; Plotkin, Richard M.; Sesar, Branimir; Stuart, J. Scott

2012-11-01

We investigate the use of optical photometric variability to select and identify blazars in large-scale time-domain surveys, in part to aid in the identification of blazar counterparts to the ~30% of γ-ray sources in the Fermi 2FGL catalog still lacking reliable associations. Using data from the optical LINEAR asteroid survey, we characterize the optical variability of blazars by fitting a damped random walk model to individual light curves with two main model parameters, the characteristic timescales of variability τ, and driving amplitudes on short timescales \\hat{\\sigma }. Imposing cuts on minimum τ and \\hat{\\sigma } allows for blazar selection with high efficiency E and completeness C. To test the efficacy of this approach, we apply this method to optically variable LINEAR objects that fall within the several-arcminute error ellipses of γ-ray sources in the Fermi 2FGL catalog. Despite the extreme stellar contamination at the shallow depth of the LINEAR survey, we are able to recover previously associated optical counterparts to Fermi active galactic nuclei with E >= 88% and C = 88% in Fermi 95% confidence error ellipses having semimajor axis r < 8'. We find that the suggested radio counterpart to Fermi source 2FGL J1649.6+5238 has optical variability consistent with other γ-ray blazars and is likely to be the γ-ray source. Our results suggest that the variability of the non-thermal jet emission in blazars is stochastic in nature, with unique variability properties due to the effects of relativistic beaming. After correcting for beaming, we estimate that the characteristic timescale of blazar variability is ~3 years in the rest frame of the jet, in contrast with the ~320 day disk flux timescale observed in quasars. The variability-based selection method presented will be useful for blazar identification in time-domain optical surveys and is also a probe of jet physics.

Optimal Interpolation scheme to generate reference crop evapotranspiration

NASA Astrophysics Data System (ADS)

Tomas-Burguera, Miquel; Beguería, Santiago; Vicente-Serrano, Sergio; Maneta, Marco

2018-05-01

We used an Optimal Interpolation (OI) scheme to generate a reference crop evapotranspiration (ETo) grid, forcing meteorological variables, and their respective error variance in the Iberian Peninsula for the period 1989-2011. To perform the OI we used observational data from the Spanish Meteorological Agency (AEMET) and outputs from a physically-based climate model. To compute ETo we used five OI schemes to generate grids for the five observed climate variables necessary to compute ETo using the FAO-recommended form of the Penman-Monteith equation (FAO-PM). The granularity of the resulting grids are less sensitive to variations in the density and distribution of the observational network than those generated by other interpolation methods. This is because our implementation of the OI method uses a physically-based climate model as prior background information about the spatial distribution of the climatic variables, which is critical for under-observed regions. This provides temporal consistency in the spatial variability of the climatic fields. We also show that increases in the density and improvements in the distribution of the observational network reduces substantially the uncertainty of the climatic and ETo estimates. Finally, a sensitivity analysis of observational uncertainties and network densification suggests the existence of a trade-off between quantity and quality of observations.

Corrugated Textile based Triboelectric Generator for Wearable Energy Harvesting

PubMed Central

Choi, A Young; Lee, Chang Jun; Park, Jiwon; Kim, Dogyun; Kim, Youn Tae

2017-01-01

Triboelectric energy harvesting has been applied to various fields, from large-scale power generation to small electronics. Triboelectric energy is generated when certain materials come into frictional contact, e.g., static electricity from rubbing a shoe on a carpet. In particular, textile-based triboelectric energy-harvesting technologies are one of the most promising approaches because they are not only flexible, light, and comfortable but also wearable. Most previous textile-based triboelectric generators (TEGs) generate energy by vertically pressing and rubbing something. However, we propose a corrugated textile-based triboelectric generator (CT-TEG) that can generate energy by stretching. Moreover, the CT-TEG is sewn into a corrugated structure that contains an effective air gap without additional spacers. The resulting CT-TEG can generate considerable energy from various deformations, not only by pressing and rubbing but also by stretching. The maximum output performances of the CT-TEG can reach up to 28.13 V and 2.71 μA with stretching and releasing motions. Additionally, we demonstrate the generation of sufficient energy from various activities of a human body to power about 54 LEDs. These results demonstrate the potential application of CT-TEGs for self-powered systems. PMID:28349928

Optimal Test Design with Rule-Based Item Generation

ERIC Educational Resources Information Center

Geerlings, Hanneke; van der Linden, Wim J.; Glas, Cees A. W.

2013-01-01

Optimal test-design methods are applied to rule-based item generation. Three different cases of automated test design are presented: (a) test assembly from a pool of pregenerated, calibrated items; (b) test generation on the fly from a pool of calibrated item families; and (c) test generation on the fly directly from calibrated features defining…

Electrowetting-Based Variable-Focus Lens for Miniature Systems

NASA Astrophysics Data System (ADS)

Hendriks, B. H. W.; Kuiper, S.; van As, M. A. J.; et al.

The meniscus between two immiscible liquids of different refractive indices can be used as a lens. A change in curvature of this meniscus by electrostatic control of the solid/liquid interfacial tension leads to a change in focal distance. It is demonstrated that two liquids in a tube form a self-centred variable-focus lens. The optical properties of this lens were investigated experimentally. We designed and constructed a miniature camera module based on this variable lens suitable for mobile applications. Furthermore, the liquid lens was applied in a Blu-ray Disc optical recording system to enable dual layer disc reading/writing.

Simulated Annealing Based Hybrid Forecast for Improving Daily Municipal Solid Waste Generation Prediction

PubMed Central

Song, Jingwei; He, Jiaying; Zhu, Menghua; Tan, Debao; Zhang, Yu; Ye, Song; Shen, Dingtao; Zou, Pengfei

2014-01-01

A simulated annealing (SA) based variable weighted forecast model is proposed to combine and weigh local chaotic model, artificial neural network (ANN), and partial least square support vector machine (PLS-SVM) to build a more accurate forecast model. The hybrid model was built and multistep ahead prediction ability was tested based on daily MSW generation data from Seattle, Washington, the United States. The hybrid forecast model was proved to produce more accurate and reliable results and to degrade less in longer predictions than three individual models. The average one-week step ahead prediction has been raised from 11.21% (chaotic model), 12.93% (ANN), and 12.94% (PLS-SVM) to 9.38%. Five-week average has been raised from 13.02% (chaotic model), 15.69% (ANN), and 15.92% (PLS-SVM) to 11.27%. PMID:25301508

Text generation from Taiwanese Sign Language using a PST-based language model for augmentative communication.

PubMed

Wu, Chung-Hsien; Chiu, Yu-Hsien; Guo, Chi-Shiang

2004-12-01

This paper proposes a novel approach to the generation of Chinese sentences from ill-formed Taiwanese Sign Language (TSL) for people with hearing impairments. First, a sign icon-based virtual keyboard is constructed to provide a visualized interface to retrieve sign icons from a sign database. A proposed language model (LM), based on a predictive sentence template (PST) tree, integrates a statistical variable n-gram LM and linguistic constraints to deal with the translation problem from ill-formed sign sequences to grammatical written sentences. The PST tree trained by a corpus collected from the deaf schools was used to model the correspondence between signed and written Chinese. In addition, a set of phrase formation rules, based on trigger pair category, was derived for sentence pattern expansion. These approaches improved the efficiency of text generation and the accuracy of word prediction and, therefore, improved the input rate. For the assessment of practical communication aids, a reading-comprehension training program with ten profoundly deaf students was undertaken in a deaf school in Tainan, Taiwan. Evaluation results show that the literacy aptitude test and subjective satisfactory level are significantly improved.

Estimating evaporative vapor generation from automobiles based on parking activities.

PubMed

Dong, Xinyi; Tschantz, Michael; Fu, Joshua S

2015-07-01

A new approach is proposed to quantify the evaporative vapor generation based on real parking activity data. As compared to the existing methods, two improvements are applied in this new approach to reduce the uncertainties: First, evaporative vapor generation from diurnal parking events is usually calculated based on estimated average parking duration for the whole fleet, while in this study, vapor generation rate is calculated based on parking activities distribution. Second, rather than using the daily temperature gradient, this study uses hourly temperature observations to derive the hourly incremental vapor generation rates. The parking distribution and hourly incremental vapor generation rates are then adopted with Wade-Reddy's equation to estimate the weighted average evaporative generation. We find that hourly incremental rates can better describe the temporal variations of vapor generation, and the weighted vapor generation rate is 5-8% less than calculation without considering parking activity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Variable cycle control model for intersection based on multi-source information

NASA Astrophysics Data System (ADS)

Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

2018-05-01

In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

Control of variable speed variable pitch wind turbine based on a disturbance observer

NASA Astrophysics Data System (ADS)

Ren, Haijun; Lei, Xin

2017-11-01

In this paper, a novel sliding mode controller based on disturbance observer (DOB) to optimize the efficiency of variable speed variable pitch (VSVP) wind turbine is developed and analyzed. Due to the highly nonlinearity of the VSVP system, the model is linearly processed to obtain the state space model of the system. Then, a conventional sliding mode controller is designed and a DOB is added to estimate wind speed. The proposed control strategy can successfully deal with the random nature of wind speed, the nonlinearity of VSVP system, the uncertainty of parameters and external disturbance. Via adding the observer to the sliding mode controller, it can greatly reduce the chattering produced by the sliding mode switching gain. The simulation results show that the proposed control system has the effectiveness and robustness.

Peak flow regression equations For small, ungaged streams in Maine: Comparing map-based to field-based variables

USGS Publications Warehouse

Lombard, Pamela J.; Hodgkins, Glenn A.

2015-01-01

Regression equations to estimate peak streamflows with 1- to 500-year recurrence intervals (annual exceedance probabilities from 99 to 0.2 percent, respectively) were developed for small, ungaged streams in Maine. Equations presented here are the best available equations for estimating peak flows at ungaged basins in Maine with drainage areas from 0.3 to 12 square miles (mi2). Previously developed equations continue to be the best available equations for estimating peak flows for basin areas greater than 12 mi2. New equations presented here are based on streamflow records at 40 U.S. Geological Survey streamgages with a minimum of 10 years of recorded peak flows between 1963 and 2012. Ordinary least-squares regression techniques were used to determine the best explanatory variables for the regression equations. Traditional map-based explanatory variables were compared to variables requiring field measurements. Two field-based variables—culvert rust lines and bankfull channel widths—either were not commonly found or did not explain enough of the variability in the peak flows to warrant inclusion in the equations. The best explanatory variables were drainage area and percent basin wetlands; values for these variables were determined with a geographic information system. Generalized least-squares regression was used with these two variables to determine the equation coefficients and estimates of accuracy for the final equations.

Variability in ADHD care in community-based pediatrics.

PubMed

Epstein, Jeffery N; Kelleher, Kelly J; Baum, Rebecca; Brinkman, William B; Peugh, James; Gardner, William; Lichtenstein, Phil; Langberg, Joshua

2014-12-01

Although many efforts have been made to improve the quality of care delivered to children with attention-deficit/hyperactivity disorder (ADHD) in community-based pediatric settings, little is known about typical ADHD care in these settings other than rates garnered through pediatrician self-report. Rates of evidence-based ADHD care and sources of variability (practice-level, pediatrician-level, patient-level) were determined by chart reviews of a random sample of 1594 patient charts across 188 pediatricians at 50 different practices. In addition, the associations of Medicaid-status and practice setting (ie, urban, suburban, and rural) with the quality of ADHD care were examined. Parent- and teacher-rating scales were used during ADHD assessment with approximately half of patients. The use of Diagnostic and Statistical Manual of Mental Disorders criteria was documented in 70.4% of patients. The vast majority (93.4%) of patients with ADHD were receiving medication and only 13.0% were receiving psychosocial treatment. Parent- and teacher-ratings were rarely collected to monitor treatment response or side effects. Further, fewer than half (47.4%) of children prescribed medication had contact with their pediatrician within the first month of prescribing. Most variability in pediatrician-delivered ADHD care was accounted for at the patient level; however, pediatricians and practices also accounted for significant variability on specific ADHD care behaviors. There is great need to improve the quality of ADHD care received by children in community-based pediatric settings. Improvements will likely require systematic interventions at the practice and policy levels to promote change. Copyright © 2014 by the American Academy of Pediatrics.

The Reliability of Randomly Generated Math Curriculum-Based Measurements

ERIC Educational Resources Information Center

Strait, Gerald G.; Smith, Bradley H.; Pender, Carolyn; Malone, Patrick S.; Roberts, Jarod; Hall, John D.

2015-01-01

"Curriculum-Based Measurement" (CBM) is a direct method of academic assessment used to screen and evaluate students' skills and monitor their responses to academic instruction and intervention. Interventioncentral.org offers a math worksheet generator at no cost that creates randomly generated "math curriculum-based measures"…

Supervised Learning Based Hypothesis Generation from Biomedical Literature.

PubMed

Sang, Shengtian; Yang, Zhihao; Li, Zongyao; Lin, Hongfei

2015-01-01

Nowadays, the amount of biomedical literatures is growing at an explosive speed, and there is much useful knowledge undiscovered in this literature. Researchers can form biomedical hypotheses through mining these works. In this paper, we propose a supervised learning based approach to generate hypotheses from biomedical literature. This approach splits the traditional processing of hypothesis generation with classic ABC model into AB model and BC model which are constructed with supervised learning method. Compared with the concept cooccurrence and grammar engineering-based approaches like SemRep, machine learning based models usually can achieve better performance in information extraction (IE) from texts. Then through combining the two models, the approach reconstructs the ABC model and generates biomedical hypotheses from literature. The experimental results on the three classic Swanson hypotheses show that our approach outperforms SemRep system.

Variable disparity-motion estimation based fast three-view video coding

NASA Astrophysics Data System (ADS)

Bae, Kyung-Hoon; Kim, Seung-Cheol; Hwang, Yong Seok; Kim, Eun-Soo

2009-02-01

In this paper, variable disparity-motion estimation (VDME) based 3-view video coding is proposed. In the encoding, key-frame coding (KFC) based motion estimation and variable disparity estimation (VDE) for effectively fast three-view video encoding are processed. These proposed algorithms enhance the performance of 3-D video encoding/decoding system in terms of accuracy of disparity estimation and computational overhead. From some experiments, stereo sequences of 'Pot Plant' and 'IVO', it is shown that the proposed algorithm's PSNRs is 37.66 and 40.55 dB, and the processing time is 0.139 and 0.124 sec/frame, respectively.

Analyst-to-Analyst Variability in Simulation-Based Prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glickman, Matthew R.; Romero, Vicente J.

This report describes findings from the culminating experiment of the LDRD project entitled, "Analyst-to-Analyst Variability in Simulation-Based Prediction". For this experiment, volunteer participants solving a given test problem in engineering and statistics were interviewed at different points in their solution process. These interviews are used to trace differing solutions to differing solution processes, and differing processes to differences in reasoning, assumptions, and judgments. The issue that the experiment was designed to illuminate -- our paucity of understanding of the ways in which humans themselves have an impact on predictions derived from complex computational simulations -- is a challenging and openmore » one. Although solution of the test problem by analyst participants in this experiment has taken much more time than originally anticipated, and is continuing past the end of this LDRD, this project has provided a rare opportunity to explore analyst-to-analyst variability in significant depth, from which we derive evidence-based insights to guide further explorations in this important area.« less

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses

PubMed Central

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-01-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. PMID:24462600

The probable source of certain spurious frequencies found in the output of a variable speed generating system using slip recovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlin, P W

1989-06-01

As part of US Department of Energy-sponsored research on wind energy, a Mod-O wind turbine was used to drive a variable-speed, wound-rotor, induction generator. Energy resulting from the slip frequency voltage in the generator rotor was rectified to dc, inverted back to utility frequency ac, and injected into the power line. Spurious changing frequencies displayed in the generator output by a spectrum analyzer are caused by ripple on the dc link. No resonances of any of these moving frequencies were seen in spite of the presence of a bank of power factor correcting capacitors. 5 figs.

Contouring variability of human- and deformable-generated contours in radiotherapy for prostate cancer

NASA Astrophysics Data System (ADS)

Gardner, Stephen J.; Wen, Ning; Kim, Jinkoo; Liu, Chang; Pradhan, Deepak; Aref, Ibrahim; Cattaneo, Richard, II; Vance, Sean; Movsas, Benjamin; Chetty, Indrin J.; Elshaikh, Mohamed A.

2015-06-01

This study was designed to evaluate contouring variability of human-and deformable-generated contours on planning CT (PCT) and CBCT for ten patients with low-or intermediate-risk prostate cancer. For each patient in this study, five radiation oncologists contoured the prostate, bladder, and rectum, on one PCT dataset and five CBCT datasets. Consensus contours were generated using the STAPLE method in the CERR software package. Observer contours were compared to consensus contour, and contour metrics (Dice coefficient, Hausdorff distance, Contour Distance, Center-of-Mass [COM] Deviation) were calculated. In addition, the first day CBCT was registered to subsequent CBCT fractions (CBCTn: CBCT2-CBCT5) via B-spline Deformable Image Registration (DIR). Contours were transferred from CBCT1 to CBCTn via the deformation field, and contour metrics were calculated through comparison with consensus contours generated from human contour set. The average contour metrics for prostate contours on PCT and CBCT were as follows: Dice coefficient—0.892 (PCT), 0.872 (CBCT-Human), 0.824 (CBCT-Deformed); Hausdorff distance—4.75 mm (PCT), 5.22 mm (CBCT-Human), 5.94 mm (CBCT-Deformed); Contour Distance (overall contour)—1.41 mm (PCT), 1.66 mm (CBCT-Human), 2.30 mm (CBCT-Deformed); COM Deviation—2.01 mm (PCT), 2.78 mm (CBCT-Human), 3.45 mm (CBCT-Deformed). For human contours on PCT and CBCT, the difference in average Dice coefficient between PCT and CBCT (approx. 2%) and Hausdorff distance (approx. 0.5 mm) was small compared to the variation between observers for each patient (standard deviation in Dice coefficient of 5% and Hausdorff distance of 2.0 mm). However, additional contouring variation was found for the deformable-generated contours (approximately 5.0% decrease in Dice coefficient and 0.7 mm increase in Hausdorff distance relative to human-generated contours on CBCT). Though deformable contours provide a reasonable starting point for contouring on

Variability Analysis based on POSS1/POSS2 Photometry

NASA Astrophysics Data System (ADS)

Mickaelian, Areg M.; Sarkissian, Alain; Sinamyan, Parandzem K.

2012-04-01

We introduce accurate magnitudes as combined calculations from catalogues based on accurate measurements of POSS1- and POSS2-epoch plates. The photometric accuracy of various catalogues was established, and statistical weights for each of them have been calculated. To achieve the best possible magnitudes, we used weighted averaging of data from APM, MAPS, USNO-A2.0, USNO-B1.0 (for POSS1-epoch), and USNO-B1.0 and GSC 2.3.2 (for POSS2-epoch) catalogues. The r.m.s. accuracy of magnitudes achieved for POSS1 is 0.184 in B and 0.173 mag in R, or 0.138 in B and 0.128 in R for POSS2. By adopting those new magnitudes we examined the First Byurakan Survey (FBS) of blue stellar objects for variability, and uncovered 336 probable and possible variables among 1103 objects with POSS2-POSS1 >= 3σ of the errors, including 161 highly probable variables. We have developed methods to control and exclude accidental errors for any survey. We compared and combined our results with those given in Northern Sky Variability Survey (NSVS) database, and obtained firm candidates for variability. By such an approach it will be possible to conduct investigations of variability for large numbers of objects.

Handwriting generates variable visual input to facilitate symbol learning

PubMed Central

Li, Julia X.; James, Karin H.

2015-01-01

Recent research has demonstrated that handwriting practice facilitates letter categorization in young children. The present experiments investigated why handwriting practice facilitates visual categorization by comparing two hypotheses: That handwriting exerts its facilitative effect because of the visual-motor production of forms, resulting in a direct link between motor and perceptual systems, or because handwriting produces variable visual instances of a named category in the environment that then changes neural systems. We addressed these issues by measuring performance of 5 year-old children on a categorization task involving novel, Greek symbols across 6 different types of learning conditions: three involving visual-motor practice (copying typed symbols independently, tracing typed symbols, tracing handwritten symbols) and three involving visual-auditory practice (seeing and saying typed symbols of a single typed font, of variable typed fonts, and of handwritten examples). We could therefore compare visual-motor production with visual perception both of variable and similar forms. Comparisons across the six conditions (N=72) demonstrated that all conditions that involved studying highly variable instances of a symbol facilitated symbol categorization relative to conditions where similar instances of a symbol were learned, regardless of visual-motor production. Therefore, learning perceptually variable instances of a category enhanced performance, suggesting that handwriting facilitates symbol understanding by virtue of its environmental output: supporting the notion of developmental change though brain-body-environment interactions. PMID:26726913

Dual-loop self-optimizing robust control of wind power generation with Doubly-Fed Induction Generator.

PubMed

Chen, Quan; Li, Yaoyu; Seem, John E

2015-09-01

This paper presents a self-optimizing robust control scheme that can maximize the power generation for a variable speed wind turbine with Doubly-Fed Induction Generator (DFIG) operated in Region 2. A dual-loop control structure is proposed to synergize the conversion from aerodynamic power to rotor power and the conversion from rotor power to the electrical power. The outer loop is an Extremum Seeking Control (ESC) based generator torque regulation via the electric power feedback. The ESC can search for the optimal generator torque constant to maximize the rotor power without wind measurement or accurate knowledge of power map. The inner loop is a vector-control based scheme that can both regulate the generator torque requested by the ESC and also maximize the conversion from the rotor power to grid power. An ℋ(∞) controller is synthesized for maximizing, with performance specifications defined based upon the spectrum of the rotor power obtained by the ESC. Also, the controller is designed to be robust against the variations of some generator parameters. The proposed control strategy is validated via simulation study based on the synergy of several software packages including the TurbSim and FAST developed by NREL, Simulink and SimPowerSystems. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Preserving Differential Privacy in Degree-Correlation based Graph Generation

PubMed Central

Wang, Yue; Wu, Xintao

2014-01-01

Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as cluster coefficient often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we study the problem of enforcing edge differential privacy in graph generation. The idea is to enforce differential privacy on graph model parameters learned from the original network and then generate the graphs for releasing using the graph model with the private parameters. In particular, we develop a differential privacy preserving graph generator based on the dK-graph generation model. We first derive from the original graph various parameters (i.e., degree correlations) used in the dK-graph model, then enforce edge differential privacy on the learned parameters, and finally use the dK-graph model with the perturbed parameters to generate graphs. For the 2K-graph model, we enforce the edge differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We conduct experiments on four real networks and compare the performance of our private dK-graph models with the stochastic Kronecker graph generation model in terms of utility and privacy tradeoff. Empirical evaluations show the developed private dK-graph generation models significantly outperform the approach based on the stochastic Kronecker generation model. PMID:24723987

Approaches for controlling air pollutants and their environmental impacts generated from coal-based electricity generation in China.

PubMed

Xu, Changqing; Hong, Jinglan; Ren, Yixin; Wang, Qingsong; Yuan, Xueliang

2015-08-01

This study aims at qualifying air pollutants and environmental impacts generated from coal-based power plants and providing useful information for decision makers on the management of coal-based power plants in China. Results showed that approximately 9.03, 54.95, 62.08, and 12.12% of the national carbon dioxide, sulfur dioxide, nitrogen oxides, and particulate matter emissions, respectively, in 2011were generated from coal-based electricity generation. The air pollutants were mainly generated from east China because of the well-developed economy and energy-intensive industries in the region. Coal-washing technology can simply and significantly reduce the environmental burden because of the relativity low content of coal gangue and sulfur in washed coal. Optimizing the efficiency of raw materials and energy consumption is additional key factor to reduce the potential environmental impacts. In addition, improving the efficiency of air pollutants (e.g., dust, mercury, sulfur dioxide, nitrogen oxides) control system and implementing the strict requirements on air pollutants for power plants are important ways for reducing the potential environmental impacts of coal-based electricity generation in China.

Intra-generational Redistribution under Public Pension Planning Based on Generation-based Funding Scheme

NASA Astrophysics Data System (ADS)

Banjo, Daisuke; Tamura, Hiroyuki; Murata, Tadahiko

In this paper, we propose a method of determining the pension in the generation-based funding scheme. In this proposal, we include two types of pensions in the scheme. One is the payment-amount related pension and the other is the payment-frequency related pension. We set the ratio of the total amount of payment-amount related pension to the total amount of both pensions, and simulate income gaps and the relationship between contributions and benefits for each individual when the proposed method is applied.

Spatial and temporal variability of runoff and streamflow generation within and among headwater catchments: a combined hydrometric and stable isotope approach

NASA Astrophysics Data System (ADS)

Singh, N. K.; Emanuel, R. E.; McGlynn, B. L.

2012-12-01

The combined influence of topography and vegetation on runoff generation and streamflow in headwater catchments remains unclear. We aim to understand how spatial, hydrological and climate variables affect runoff generation and streamflow at hillslope and watershed scales at the Coweeta Hydrologic Laboratory (CHL) in the southern Appalachian Mountains by analyzing stable isotopes of hydrogen (2H) and oxygen (18O) coupled with measurements of hydrological variables (stream discharge, soil moisture, shallow groundwater) and landscape variables (upslope accumulated area, vegetation density slope, and aspect). We investigated four small catchments, two of which contained broadleaf deciduous vegetation and two of which contained evergreen coniferous vegetation. Beginning in June 2011, we collected monthly water samples at 25 m intervals along each stream, monthly samples from 24 shallow groundwater wells, and weekly to monthly samples from 10 rain gauges distributed across CHL. Water samples were analyzed for 2H and 18O using cavity ring-down spectroscopy. During the same time period we recorded shallow groundwater stage at 30 min intervals from each well, and beginning in fall 2011 we collected volumetric soil moisture data at 30 min intervals from multiple depths at 16 landscape positions. Results show high spatial and temporal variability in δ2H and δ18O within and among streams, but in general we found isotopic enrichment with increasing contributing area along each stream. We used a combination of hydrometric observations and geospatial analyses to understand why stream isotope patterns varied during the year and among watersheds, and we used complementary measurements of δ2H and δ18O from other pools within the watersheds to understand the movement and mixing of precipitation that precedes runoff formation. This combination of high resolution stable isotope data and hydrometric observations facilitates a clearer understanding of spatial controls on streamflow

On-chip continuous-variable quantum entanglement

NASA Astrophysics Data System (ADS)

Masada, Genta; Furusawa, Akira

2016-09-01

Entanglement is an essential feature of quantum theory and the core of the majority of quantum information science and technologies. Quantum computing is one of the most important fruits of quantum entanglement and requires not only a bipartite entangled state but also more complicated multipartite entanglement. In previous experimental works to demonstrate various entanglement-based quantum information processing, light has been extensively used. Experiments utilizing such a complicated state need highly complex optical circuits to propagate optical beams and a high level of spatial interference between different light beams to generate quantum entanglement or to efficiently perform balanced homodyne measurement. Current experiments have been performed in conventional free-space optics with large numbers of optical components and a relatively large-sized optical setup. Therefore, they are limited in stability and scalability. Integrated photonics offer new tools and additional capabilities for manipulating light in quantum information technology. Owing to integrated waveguide circuits, it is possible to stabilize and miniaturize complex optical circuits and achieve high interference of light beams. The integrated circuits have been firstly developed for discrete-variable systems and then applied to continuous-variable systems. In this article, we review the currently developed scheme for generation and verification of continuous-variable quantum entanglement such as Einstein-Podolsky-Rosen beams using a photonic chip where waveguide circuits are integrated. This includes balanced homodyne measurement of a squeezed state of light. As a simple example, we also review an experiment for generating discrete-variable quantum entanglement using integrated waveguide circuits.

Handwriting generates variable visual output to facilitate symbol learning.

PubMed

Li, Julia X; James, Karin H

2016-03-01

Recent research has demonstrated that handwriting practice facilitates letter categorization in young children. The present experiments investigated why handwriting practice facilitates visual categorization by comparing 2 hypotheses: that handwriting exerts its facilitative effect because of the visual-motor production of forms, resulting in a direct link between motor and perceptual systems, or because handwriting produces variable visual instances of a named category in the environment that then changes neural systems. We addressed these issues by measuring performance of 5-year-old children on a categorization task involving novel, Greek symbols across 6 different types of learning conditions: 3 involving visual-motor practice (copying typed symbols independently, tracing typed symbols, tracing handwritten symbols) and 3 involving visual-auditory practice (seeing and saying typed symbols of a single typed font, of variable typed fonts, and of handwritten examples). We could therefore compare visual-motor production with visual perception both of variable and similar forms. Comparisons across the 6 conditions (N = 72) demonstrated that all conditions that involved studying highly variable instances of a symbol facilitated symbol categorization relative to conditions where similar instances of a symbol were learned, regardless of visual-motor production. Therefore, learning perceptually variable instances of a category enhanced performance, suggesting that handwriting facilitates symbol understanding by virtue of its environmental output: supporting the notion of developmental change though brain-body-environment interactions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Clustering-based Feature Learning on Variable Stars

NASA Astrophysics Data System (ADS)

Mackenzie, Cristóbal; Pichara, Karim; Protopapas, Pavlos

2016-04-01

The success of automatic classification of variable stars depends strongly on the lightcurve representation. Usually, lightcurves are represented as a vector of many descriptors designed by astronomers called features. These descriptors are expensive in terms of computing, require substantial research effort to develop, and do not guarantee a good classification. Today, lightcurve representation is not entirely automatic; algorithms must be designed and manually tuned up for every survey. The amounts of data that will be generated in the future mean astronomers must develop scalable and automated analysis pipelines. In this work we present a feature learning algorithm designed for variable objects. Our method works by extracting a large number of lightcurve subsequences from a given set, which are then clustered to find common local patterns in the time series. Representatives of these common patterns are then used to transform lightcurves of a labeled set into a new representation that can be used to train a classifier. The proposed algorithm learns the features from both labeled and unlabeled lightcurves, overcoming the bias using only labeled data. We test our method on data sets from the Massive Compact Halo Object survey and the Optical Gravitational Lensing Experiment; the results show that our classification performance is as good as and in some cases better than the performance achieved using traditional statistical features, while the computational cost is significantly lower. With these promising results, we believe that our method constitutes a significant step toward the automation of the lightcurve classification pipeline.

Relating Solar Resource Variability to Cloud Type

NASA Astrophysics Data System (ADS)

Hinkelman, L. M.; Sengupta, M.

2012-12-01

Power production from renewable energy (RE) resources is rapidly increasing. Generation of renewable energy is quite variable since the solar and wind resources that form the inputs are, themselves, inherently variable. There is thus a need to understand the impact of renewable generation on the transmission grid. Such studies require estimates of high temporal and spatial resolution power output under various scenarios, which can be created from corresponding solar resource data. Satellite-based solar resource estimates are the best source of long-term solar irradiance data for the typically large areas covered by transmission studies. As satellite-based resource datasets are generally available at lower temporal and spatial resolution than required, there is, in turn, a need to downscale these resource data. Downscaling in both space and time requires information about solar irradiance variability, which is primarily a function of cloud types and properties. In this study, we analyze the relationship between solar resource variability and satellite-based cloud properties. One-minute resolution surface irradiance data were obtained from a number of stations operated by the National Oceanic and Atmospheric Administration (NOAA) under the Surface Radiation (SURFRAD) and Integrated Surface Irradiance Study (ISIS) networks as well as from NREL's Solar Radiation Research Laboratory (SRRL) in Golden, Colorado. Individual sites were selected so that a range of meteorological conditions would be represented. Cloud information at a nominal 4 km resolution and half hour intervals was derived from NOAA's Geostationary Operation Environmental Satellite (GOES) series of satellites. Cloud class information from the GOES data set was then used to select and composite irradiance data from the measurement sites. The irradiance variability for each cloud classification was characterized using general statistics of the fluxes themselves and their variability in time, as represented

Variables Affecting Student Motivation Based on Academic Publications

ERIC Educational Resources Information Center

Yilmaz, Ercan; Sahin, Mehmet; Turgut, Mehmet

2017-01-01

In this study, the variables having impact on the student motivation have been analyzed based on the articles, conference papers, master's theses and doctoral dissertations published in the years 2000-2017. A total of 165 research papers were selected for the research material and the data were collected through qualitative research techniques…

A stochastical event-based continuous time step rainfall generator based on Poisson rectangular pulse and microcanonical random cascade models

NASA Astrophysics Data System (ADS)

Pohle, Ina; Niebisch, Michael; Zha, Tingting; Schümberg, Sabine; Müller, Hannes; Maurer, Thomas; Hinz, Christoph

2017-04-01

weights, which we implemented through sigmoid functions. Secondly, the branching of the first and last box is constrained to preserve the rainfall event durations generated by the Poisson rectangular pulse model. The event-based continuous time step rainfall generator has been developed and tested using 10 min and hourly rainfall data of four stations in North-Eastern Germany. The model performs well in comparison to observed rainfall in terms of event durations and mean event intensities as well as wet spell and dry spell durations. It is currently being tested using data from other stations across Germany and in different climate zones. Furthermore, the rainfall event generator is being applied in modelling approaches aimed at understanding the impact of rainfall variability on hydrological processes. Reference Olsson, J.: Evaluation of a scaling cascade model for temporal rainfall disaggregation, Hydrology and Earth System Sciences, 2, 19.30

A PLL-based resampling technique for vibration analysis in variable-speed wind turbines with PMSG: A bearing fault case

NASA Astrophysics Data System (ADS)

Pezzani, Carlos M.; Bossio, José M.; Castellino, Ariel M.; Bossio, Guillermo R.; De Angelo, Cristian H.

2017-02-01

Condition monitoring in permanent magnet synchronous machines has gained interest due to the increasing use in applications such as electric traction and power generation. Particularly in wind power generation, non-invasive condition monitoring techniques are of great importance. Usually, in such applications the access to the generator is complex and costly, while unexpected breakdowns results in high repair costs. This paper presents a technique which allows using vibration analysis for bearing fault detection in permanent magnet synchronous generators used in wind turbines. Given that in wind power applications the generator rotational speed may vary during normal operation, it is necessary to use special sampling techniques to apply spectral analysis of mechanical vibrations. In this work, a resampling technique based on order tracking without measuring the rotor position is proposed. To synchronize sampling with rotor position, an estimation of the rotor position obtained from the angle of the voltage vector is proposed. This angle is obtained from a phase-locked loop synchronized with the generator voltages. The proposed strategy is validated by laboratory experimental results obtained from a permanent magnet synchronous generator. Results with single point defects in the outer race of a bearing under variable speed and load conditions are presented.

Gaussian Mixture Model of Heart Rate Variability

PubMed Central

Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

2012-01-01

Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

Means and extremes: building variability into community-level climate change experiments.

PubMed

Thompson, Ross M; Beardall, John; Beringer, Jason; Grace, Mike; Sardina, Paula

2013-06-01

Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of 'generations' based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new 'generation' of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. © 2013 John Wiley & Sons Ltd/CNRS.

Array-based Hierarchical Mesh Generation in Parallel

DOE PAGES

Ray, Navamita; Grindeanu, Iulian; Zhao, Xinglin; ...

2015-11-03

In this paper, we describe an array-based hierarchical mesh generation capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial mesh that can be used for a number of purposes such as multi-level methods to generating large meshes. The capability is developed under the parallel mesh framework “Mesh Oriented dAtaBase” a.k.a MOAB. We describe the underlying data structures and algorithms to generate such hierarchies and present numerical results for computational efficiency and mesh quality. Inmore » conclusion, we also present results to demonstrate the applicability of the developed capability to a multigrid finite-element solver.« less

An Investigation of Factors That Influence the Hypothesis Generation Ability of Students in School- Based Agricultural Education Programs When Troubleshooting Small Gasoline Engines

ERIC Educational Resources Information Center

Blackburn, J. Joey; Robinson, J. Shane

2017-01-01

The purpose of this study was to determine if selected factors influenced the ability of students in school-based agricultural education programs to generate a correct hypothesis when troubleshooting small gasoline engines. Variables of interest included students' cognitive style, age, GPA, and content knowledge in small gasoline engines. Kirton's…

Imaging quality analysis of computer-generated holograms using the point-based method and slice-based method

NASA Astrophysics Data System (ADS)

Zhang, Zhen; Chen, Siqing; Zheng, Huadong; Sun, Tao; Yu, Yingjie; Gao, Hongyue; Asundi, Anand K.

2017-06-01

Computer holography has made a notably progress in recent years. The point-based method and slice-based method are chief calculation algorithms for generating holograms in holographic display. Although both two methods are validated numerically and optically, the differences of the imaging quality of these methods have not been specifically analyzed. In this paper, we analyze the imaging quality of computer-generated phase holograms generated by point-based Fresnel zone plates (PB-FZP), point-based Fresnel diffraction algorithm (PB-FDA) and slice-based Fresnel diffraction algorithm (SB-FDA). The calculation formula and hologram generation with three methods are demonstrated. In order to suppress the speckle noise, sequential phase-only holograms are generated in our work. The results of reconstructed images numerically and experimentally are also exhibited. By comparing the imaging quality, the merits and drawbacks with three methods are analyzed. Conclusions are given by us finally.

Space-based laser-driven MHD generator: Feasibility study

NASA Technical Reports Server (NTRS)

Choi, S. H.

1986-01-01

The feasibility of a laser-driven MHD generator, as a candidate receiver for a space-based laser power transmission system, was investigated. On the basis of reasonable parameters obtained in the literature, a model of the laser-driven MHD generator was developed with the assumptions of a steady, turbulent, two-dimensional flow. These assumptions were based on the continuous and steady generation of plasmas by the exposure of the continuous wave laser beam thus inducing a steady back pressure that enables the medium to flow steadily. The model considered here took the turbulent nature of plasmas into account in the two-dimensional geometry of the generator. For these conditions with the plasma parameters defining the thermal conductivity, viscosity, electrical conductivity for the plasma flow, a generator efficiency of 53.3% was calculated. If turbulent effects and nonequilibrium ionization are taken into account, the efficiency is 43.2%. The study shows that the laser-driven MHD system has potential as a laser power receiver for space applications because of its high energy conversion efficiency, high energy density and relatively simple mechanism as compared to other energy conversion cycles.

MEMS-Based Power Generation Techniques for Implantable Biosensing Applications

PubMed Central

Lueke, Jonathan; Moussa, Walied A.

2011-01-01

Implantable biosensing is attractive for both medical monitoring and diagnostic applications. It is possible to monitor phenomena such as physical loads on joints or implants, vital signs, or osseointegration in vivo and in real time. Microelectromechanical (MEMS)-based generation techniques can allow for the autonomous operation of implantable biosensors by generating electrical power to replace or supplement existing battery-based power systems. By supplementing existing battery-based power systems for implantable biosensors, the operational lifetime of the sensor is increased. In addition, the potential for a greater amount of available power allows additional components to be added to the biosensing module, such as computational and wireless and components, improving functionality and performance of the biosensor. Photovoltaic, thermovoltaic, micro fuel cell, electrostatic, electromagnetic, and piezoelectric based generation schemes are evaluated in this paper for applicability for implantable biosensing. MEMS-based generation techniques that harvest ambient energy, such as vibration, are much better suited for implantable biosensing applications than fuel-based approaches, producing up to milliwatts of electrical power. High power density MEMS-based approaches, such as piezoelectric and electromagnetic schemes, allow for supplemental and replacement power schemes for biosensing applications to improve device capabilities and performance. In addition, this may allow for the biosensor to be further miniaturized, reducing the need for relatively large batteries with respect to device size. This would cause the implanted biosensor to be less invasive, increasing the quality of care received by the patient. PMID:22319362

MEMS-based power generation techniques for implantable biosensing applications.

PubMed

Lueke, Jonathan; Moussa, Walied A

2011-01-01

Implantable biosensing is attractive for both medical monitoring and diagnostic applications. It is possible to monitor phenomena such as physical loads on joints or implants, vital signs, or osseointegration in vivo and in real time. Microelectromechanical (MEMS)-based generation techniques can allow for the autonomous operation of implantable biosensors by generating electrical power to replace or supplement existing battery-based power systems. By supplementing existing battery-based power systems for implantable biosensors, the operational lifetime of the sensor is increased. In addition, the potential for a greater amount of available power allows additional components to be added to the biosensing module, such as computational and wireless and components, improving functionality and performance of the biosensor. Photovoltaic, thermovoltaic, micro fuel cell, electrostatic, electromagnetic, and piezoelectric based generation schemes are evaluated in this paper for applicability for implantable biosensing. MEMS-based generation techniques that harvest ambient energy, such as vibration, are much better suited for implantable biosensing applications than fuel-based approaches, producing up to milliwatts of electrical power. High power density MEMS-based approaches, such as piezoelectric and electromagnetic schemes, allow for supplemental and replacement power schemes for biosensing applications to improve device capabilities and performance. In addition, this may allow for the biosensor to be further miniaturized, reducing the need for relatively large batteries with respect to device size. This would cause the implanted biosensor to be less invasive, increasing the quality of care received by the patient.

Analysis of blocking probability for OFDM-based variable bandwidth optical network

NASA Astrophysics Data System (ADS)

Gong, Lei; Zhang, Jie; Zhao, Yongli; Lin, Xuefeng; Wu, Yuyao; Gu, Wanyi

2011-12-01

Orthogonal Frequency Division Multiplexing (OFDM) has recently been proposed as a modulation technique. For optical networks, because of its good spectral efficiency, flexibility, and tolerance to impairments, optical OFDM is much more flexible compared to traditional WDM systems, enabling elastic bandwidth transmissions, and optical networking is the future trend of development. In OFDM-based optical network the research of blocking rate has very important significance for network assessment. Current research for WDM network is basically based on a fixed bandwidth, in order to accommodate the future business and the fast-changing development of optical network, our study is based on variable bandwidth OFDM-based optical networks. We apply the mathematical analysis and theoretical derivation, based on the existing theory and algorithms, research blocking probability of the variable bandwidth of optical network, and then we will build a model for blocking probability.

Operation ranges and dynamic capabilities of variable-speed pumped-storage hydropower

NASA Astrophysics Data System (ADS)

Mercier, Thomas; Olivier, Mathieu; Dejaeger, Emmanuel

2017-04-01

The development of renewable and intermittent power generation creates incentives for the development of both energy storage solutions and more flexible power generation assets. Pumped-storage hydropower (PSH) is the most established and mature energy storage technology, but recent developments in power electronics have created a renewed interest by providing PSH units with a variable-speed feature, thereby increasing their flexibility. This paper reviews technical considerations related to variable-speed PSH in link with the provision of primary frequency control, also referred to as frequency containment reserves (FCRs). Based on the detailed characteristics of a scale model pump-turbine, the variable-speed operation ranges in pump and turbine modes are precisely assessed and the implications for the provision of FCRs are highlighted. Modelling and control for power system studies are discussed, both for fixed- and variable-speed machines and simulation results are provided to illustrate the high dynamic capabilities of variable-speed PSH.

Three-Dimensional Flow of an Oldroyd-B Fluid with Variable Thermal Conductivity and Heat Generation/Absorption

PubMed Central

Shehzad, Sabir Ali; Alsaedi, Ahmed; Hayat, Tasawar; Alhuthali, M. Shahab

2013-01-01

This paper looks at the series solutions of three dimensional boundary layer flow. An Oldroyd-B fluid with variable thermal conductivity is considered. The flow is induced due to stretching of a surface. Analysis has been carried out in the presence of heat generation/absorption. Homotopy analysis is implemented in developing the series solutions to the governing flow and energy equations. Graphs are presented and discussed for various parameters of interest. Comparison of present study with the existing limiting solution is shown and examined. PMID:24223780

Empirical Analysis of the Variability of Wind Generation in India: Implications for Grid Integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phadke, Amol; Abhyankar, NIkit; Rao, Poorvi

We analyze variability in load and wind generation in India to assess its implications for grid integration of large scale wind projects using actual wind generation and load data from two states in India, Karnataka and Tamil Nadu. We compare the largest variations in load and net load (load ?wind, i.e., load after integrating wind) that the generation fleet has to meet. In Tamil Nadu, where wind capacity is about 53percent of the peak demand, we find that the additional variation added due to wind over the current variation in load is modest; if wind penetration reaches 15percent and 30percentmore » by energy, the additional hourly variation is less than 0.5percent and 4.5percent of the peak demand respectively for 99percent of the time. For wind penetration of 15percent by energy, Tamil Nadu system is found to be capable of meeting the additional ramping requirement for 98.8percent of the time. Potential higher uncertainty in net load compared to load is found to have limited impact on ramping capability requirements of the system if coal plants can me ramped down to 50percent of their capacity. Load and wind aggregation in Tamil Nadu and Karnataka is found to lower the variation by at least 20percent indicating the benefits geographic diversification. These findings suggest modest additional flexible capacity requirements and costs for absorbing variation in wind power and indicate that the potential capacity support (if wind does not generate enough during peak periods) may be the issue that has more bearing on the economics of integrating wind« less

Research on ionospheric tomography based on variable pixel height

NASA Astrophysics Data System (ADS)

Zheng, Dunyong; Li, Peiqing; He, Jie; Hu, Wusheng; Li, Chaokui

2016-05-01

A novel ionospheric tomography technique based on variable pixel height was developed for the tomographic reconstruction of the ionospheric electron density distribution. The method considers the height of each pixel as an unknown variable, which is retrieved during the inversion process together with the electron density values. In contrast to conventional computerized ionospheric tomography (CIT), which parameterizes the model with a fixed pixel height, the variable-pixel-height computerized ionospheric tomography (VHCIT) model applies a disturbance to the height of each pixel. In comparison with conventional CIT models, the VHCIT technique achieved superior results in a numerical simulation. A careful validation of the reliability and superiority of VHCIT was performed. According to the results of the statistical analysis of the average root mean square errors, the proposed model offers an improvement by 15% compared with conventional CIT models.

Intraocular lens based on double-liquid variable-focus lens.

PubMed

Peng, Runling; Li, Yifan; Hu, Shuilan; Wei, Maowei; Chen, Jiabi

2014-01-10

In this work, the crystalline lens in the Gullstrand-Le Grand human eye model is replaced by a double-liquid variable-focus lens, the structure data of which are based on theoretical analysis and experimental results. When the pseudoaphakic eye is built in Zemax, aspherical surfaces are introduced to the double-liquid variable-focus lens to reduce the axial spherical aberration existent in the system. After optimization, the zoom range of the pseudoaphakic eye greatly exceeds that of normal human eyes, and the spot size on an image plane basically reaches the normal human eye's limit of resolution.

Osmosis-Based Pressure Generation: Dynamics and Application

PubMed Central

Li, Suyi; Billeh, Yazan N.; Wang, K. W.; Mayer, Michael

2014-01-01

This paper describes osmotically-driven pressure generation in a membrane-bound compartment while taking into account volume expansion, solute dilution, surface area to volume ratio, membrane hydraulic permeability, and changes in osmotic gradient, bulk modulus, and degree of membrane fouling. The emphasis lies on the dynamics of pressure generation; these dynamics have not previously been described in detail. Experimental results are compared to and supported by numerical simulations, which we make accessible as an open source tool. This approach reveals unintuitive results about the quantitative dependence of the speed of pressure generation on the relevant and interdependent parameters that will be encountered in most osmotically-driven pressure generators. For instance, restricting the volume expansion of a compartment allows it to generate its first 5 kPa of pressure seven times faster than without a restraint. In addition, this dynamics study shows that plants are near-ideal osmotic pressure generators, as they are composed of many small compartments with large surface area to volume ratios and strong cell wall reinforcements. Finally, we demonstrate two applications of an osmosis-based pressure generator: actuation of a soft robot and continuous volume delivery over long periods of time. Both applications do not need an external power source but rather take advantage of the energy released upon watering the pressure generators. PMID:24614529

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses.

PubMed

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-06-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.

Operational Characteristics of an SCR-Based Pulse Generating Circuit

DTIC Science & Technology

2014-12-01

of OUTC can further be explained by the RC time constants involved in the charging and discharging of OUTC during each pulse . When the SCR is...CHARACTERISTICS OF AN SCR-BASED PULSE GENERATING CIRCUIT by Wing Chien Christopher Chang December 2014 Thesis Advisor: Gamani Karunasiri Co...COVERED December 20 14 Master ’s Thesis 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS OPERATIONAL CHARACTERISTICS OF AN SCR-BASED PULSE GENERATING CIRCUIT 6

Effect of material constants on power output in piezoelectric vibration-based generators.

PubMed

Takeda, Hiroaki; Mihara, Kensuke; Yoshimura, Tomohiro; Hoshina, Takuya; Tsurumi, Takaaki

2011-09-01

A possible power output estimation based on material constants in piezoelectric vibration-based generators is proposed. A modified equivalent circuit model of the generator was built and was validated by the measurement results in the generator fabricated using potassium sodium niobate-based and lead zirconate titanate (PZT) ceramics. Subsequently, generators with the same structure using other PZT-based and bismuth-layered structure ferroelectrics ceramics were fabricated and tested. The power outputs of these generators were expressed as a linear functions of the term composed of electromechanical coupling coefficients k(sys)(2) and mechanical quality factors Q*(m) of the generator. The relationship between device constants (k(sys)(2) and Q*(m)) and material constants (k(31)(2) and Q(m)) was clarified. Estimation of the power output using material constants is demonstrated and the appropriate piezoelectric material for the generator is suggested.

Capacitor regenerative braking system of electric wheelchair for senior citizen based on variable frequency chopper control.

PubMed

Takahashi, Yoshiaki; Seki, Hirokazu

2009-01-01

This paper proposes a novel regenerative braking control system of electric wheelchairs for senior citizen. "Electric powered wheelchair", which generates the driving force by electric motors according to the human operation, is expected to be widely used as a mobility support system for elderly people. This study focuses on the braking control to realize the safety and smooth stopping motion using the regenerative braking control technique based on fuzzy algorithm. The ride quality improvement and energy recycling can be expected by the proposed control system with stopping distance estimation and variable frequency control on the step-up/down chopper type of capacitor regenerative circuit. Some driving experiments confirm the effectiveness of the proposed control system.

A field programmable gate array-based reconfigurable smart-sensor network for wireless monitoring of new generation computer numerically controlled machines.

PubMed

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; Romero-Troncoso, Rene de Jesus

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node.

Entropy generation in Gaussian quantum transformations: applying the replica method to continuous-variable quantum information theory

NASA Astrophysics Data System (ADS)

Gagatsos, Christos N.; Karanikas, Alexandros I.; Kordas, Georgios; Cerf, Nicolas J.

2016-02-01

In spite of their simple description in terms of rotations or symplectic transformations in phase space, quadratic Hamiltonians such as those modelling the most common Gaussian operations on bosonic modes remain poorly understood in terms of entropy production. For instance, determining the quantum entropy generated by a Bogoliubov transformation is notably a hard problem, with generally no known analytical solution, while it is vital to the characterisation of quantum communication via bosonic channels. Here we overcome this difficulty by adapting the replica method, a tool borrowed from statistical physics and quantum field theory. We exhibit a first application of this method to continuous-variable quantum information theory, where it enables accessing entropies in an optical parametric amplifier. As an illustration, we determine the entropy generated by amplifying a binary superposition of the vacuum and a Fock state, which yields a surprisingly simple, yet unknown analytical expression.

Design keys for paper-based concentration gradient generators.

PubMed

Schaumburg, Federico; Urteaga, Raúl; Kler, Pablo A; Berli, Claudio L A

2018-08-03

The generation of concentration gradients is an essential operation for several analytical processes implemented on microfluidic paper-based analytical devices. The dynamic gradient formation is based on the transverse dispersion of chemical species across co-flowing streams. In paper channels, this transverse flux of molecules is dominated by mechanical dispersion, which is substantially different than molecular diffusion, which is the mechanism acting in conventional microchannels. Therefore, the design of gradient generators on paper requires strategies different from those used in traditional microfluidics. This work considers the foundations of transverse dispersion in porous substrates to investigate the optimal design of microfluidic paper-based concentration gradient generators (μPGGs) by computer simulations. A set of novel and versatile μPGGs were designed in the format of numerical prototypes, and virtual experiments were run to explore the ranges of operation and the overall performance of such devices. Then physical prototypes were fabricated and experimentally tested in our lab. Finally, some basic rules for the design of optimized μPGGs are proposed. Apart from improving the efficiency of mixers, diluters and μPGGs, the results of this investigation are relevant to attain highly controlled concentration fields on paper-based devices. Copyright © 2018 Elsevier B.V. All rights reserved.

Generation of a novel phase-space-based cylindrical dose kernel for IMRT optimization.

PubMed

Zhong, Hualiang; Chetty, Indrin J

2012-05-01

Improving dose calculation accuracy is crucial in intensity-modulated radiation therapy (IMRT). We have developed a method for generating a phase-space-based dose kernel for IMRT planning of lung cancer patients. Particle transport in the linear accelerator treatment head of a 21EX, 6 MV photon beam (Varian Medical Systems, Palo Alto, CA) was simulated using the EGSnrc/BEAMnrc code system. The phase space information was recorded under the secondary jaws. Each particle in the phase space file was associated with a beamlet whose index was calculated and saved in the particle's LATCH variable. The DOSXYZnrc code was modified to accumulate the energy deposited by each particle based on its beamlet index. Furthermore, the central axis of each beamlet was calculated from the orientation of all the particles in this beamlet. A cylinder was then defined around the central axis so that only the energy deposited within the cylinder was counted. A look-up table was established for each cylinder during the tallying process. The efficiency and accuracy of the cylindrical beamlet energy deposition approach was evaluated using a treatment plan developed on a simulated lung phantom. Profile and percentage depth doses computed in a water phantom for an open, square field size were within 1.5% of measurements. Dose optimized with the cylindrical dose kernel was found to be within 0.6% of that computed with the nontruncated 3D kernel. The cylindrical truncation reduced optimization time by approximately 80%. A method for generating a phase-space-based dose kernel, using a truncated cylinder for scoring dose, in beamlet-based optimization of lung treatment planning was developed and found to be in good agreement with the standard, nontruncated scoring approach. Compared to previous techniques, our method significantly reduces computational time and memory requirements, which may be useful for Monte-Carlo-based 4D IMRT or IMAT treatment planning.

Model Based Document and Report Generation for Systems Engineering

NASA Technical Reports Server (NTRS)

Delp, Christopher; Lam, Doris; Fosse, Elyse; Lee, Cin-Young

2013-01-01

As Model Based Systems Engineering (MBSE) practices gain adoption, various approaches have been developed in order to simplify and automate the process of generating documents from models. Essentially, all of these techniques can be unified around the concept of producing different views of the model according to the needs of the intended audience. In this paper, we will describe a technique developed at JPL of applying SysML Viewpoints and Views to generate documents and reports. An architecture of model-based view and document generation will be presented, and the necessary extensions to SysML with associated rationale will be explained. A survey of examples will highlight a variety of views that can be generated, and will provide some insight into how collaboration and integration is enabled. We will also describe the basic architecture for the enterprise applications that support this approach.

Model based document and report generation for systems engineering

NASA Astrophysics Data System (ADS)

Delp, C.; Lam, D.; Fosse, E.; Lee, Cin-Young

As Model Based Systems Engineering (MBSE) practices gain adoption, various approaches have been developed in order to simplify and automate the process of generating documents from models. Essentially, all of these techniques can be unified around the concept of producing different views of the model according to the needs of the intended audience. In this paper, we will describe a technique developed at JPL of applying SysML Viewpoints and Views to generate documents and reports. An architecture of model-based view and document generation will be presented, and the necessary extensions to SysML with associated rationale will be explained. A survey of examples will highlight a variety of views that can be generated, and will provide some insight into how collaboration and integration is enabled. We will also describe the basic architecture for the enterprise applications that support this approach.

A Research on the Generative Learning Model Supported by Context-Based Learning

ERIC Educational Resources Information Center

Ulusoy, Fatma Merve; Onen, Aysem Seda

2014-01-01

This study is based on the generative learning model which involves context-based learning. Using the generative learning model, we taught the topic of Halogens. This topic is covered in the grade 10 chemistry curriculum using activities which are designed in accordance with the generative learning model supported by context-based learning. The…

Investigating Factorial Invariance of Latent Variables Across Populations When Manifest Variables Are Missing Completely

PubMed Central

Widaman, Keith F.; Grimm, Kevin J.; Early, Dawnté R.; Robins, Richard W.; Conger, Rand D.

2013-01-01

Difficulties arise in multiple-group evaluations of factorial invariance if particular manifest variables are missing completely in certain groups. Ad hoc analytic alternatives can be used in such situations (e.g., deleting manifest variables), but some common approaches, such as multiple imputation, are not viable. At least 3 solutions to this problem are viable: analyzing differing sets of variables across groups, using pattern mixture approaches, and a new method using random number generation. The latter solution, proposed in this article, is to generate pseudo-random normal deviates for all observations for manifest variables that are missing completely in a given sample and then to specify multiple-group models in a way that respects the random nature of these values. An empirical example is presented in detail comparing the 3 approaches. The proposed solution can enable quantitative comparisons at the latent variable level between groups using programs that require the same number of manifest variables in each group. PMID:24019738

Cooperative Coevolution with Formula-Based Variable Grouping for Large-Scale Global Optimization.

PubMed

Wang, Yuping; Liu, Haiyan; Wei, Fei; Zong, Tingting; Li, Xiaodong

2017-08-09

For a large-scale global optimization (LSGO) problem, divide-and-conquer is usually considered an effective strategy to decompose the problem into smaller subproblems, each of which can then be solved individually. Among these decomposition methods, variable grouping is shown to be promising in recent years. Existing variable grouping methods usually assume the problem to be black-box (i.e., assuming that an analytical model of the objective function is unknown), and they attempt to learn appropriate variable grouping that would allow for a better decomposition of the problem. In such cases, these variable grouping methods do not make a direct use of the formula of the objective function. However, it can be argued that many real-world problems are white-box problems, that is, the formulas of objective functions are often known a priori. These formulas of the objective functions provide rich information which can then be used to design an effective variable group method. In this article, a formula-based grouping strategy (FBG) for white-box problems is first proposed. It groups variables directly via the formula of an objective function which usually consists of a finite number of operations (i.e., four arithmetic operations "[Formula: see text]", "[Formula: see text]", "[Formula: see text]", "[Formula: see text]" and composite operations of basic elementary functions). In FBG, the operations are classified into two classes: one resulting in nonseparable variables, and the other resulting in separable variables. In FBG, variables can be automatically grouped into a suitable number of non-interacting subcomponents, with variables in each subcomponent being interdependent. FBG can easily be applied to any white-box problem and can be integrated into a cooperative coevolution framework. Based on FBG, a novel cooperative coevolution algorithm with formula-based variable grouping (so-called CCF) is proposed in this article for decomposing a large-scale white-box problem

Soft sensor modeling based on variable partition ensemble method for nonlinear batch processes

NASA Astrophysics Data System (ADS)

Wang, Li; Chen, Xiangguang; Yang, Kai; Jin, Huaiping

2017-01-01

Batch processes are always characterized by nonlinear and system uncertain properties, therefore, the conventional single model may be ill-suited. A local learning strategy soft sensor based on variable partition ensemble method is developed for the quality prediction of nonlinear and non-Gaussian batch processes. A set of input variable sets are obtained by bootstrapping and PMI criterion. Then, multiple local GPR models are developed based on each local input variable set. When a new test data is coming, the posterior probability of each best performance local model is estimated based on Bayesian inference and used to combine these local GPR models to get the final prediction result. The proposed soft sensor is demonstrated by applying to an industrial fed-batch chlortetracycline fermentation process.

Variability of Snow Ablation: Consequences for Runoff Generation at the Process Scale and Lessons for Large Cold Regions Catchments

NASA Astrophysics Data System (ADS)

Pomeroy, J. W.; Carey, S. K.; Granger, R. J.; Hedstrom, N. R.; Janowicz, R.; Pietroniro, A.; Quinton, W. L.

2002-12-01

The supply of water to large northern catchments such as the Mackenzie and Yukon Rivers is dominated by snowmelt runoff from first order mountain catchments. In order to understand the timing, peak and duration of the snowmelt freshet at larger scale it is important to appreciate the spatial and temporal variability of snowmelt and runoff processes at the source. For this reason a comprehensive hydrology study of a Yukon River headwaters catchment, Wolf Creek Research Basin, near Whitehorse, has focussed on the spatial variability of snow ablation and snowmelt runoff generation and the consequences for the water balance in a mountain tundra zone. In northern mountain tundra, surface energetics vary with receipt of solar radiation, shrub vegetation cover and initial snow accumulation. Therefore the timing of snowmelt is controlled by aspect, in that south facing slopes become snow-free 4-5 weeks before the north facing. Runoff generation differs widely between the slopes; there is normally no spring runoff generated from the south facing slope as all meltwater evaporates or infiltrates. On the north facing slope, snowmelt provides substantial runoff to hillside macropores which rapidly route water to the stream channel. Macropore distribution is associated with organic terrain and discontinuous permafrost, which in turn result from the summer surface energetics. Therefore the influence of small-scale snow redistribution and energetics as controlled by topography must be accounted for when calculating contributing areas to larger scale catchments, and estimating the effectiveness of snowfall in generating streamflow. This concept is quite distinct from the drainage controlled contributing area that has been found useful in temperate-zone hydrology.

Physiologically Based Pharmacokinetic (PBPK) Modeling of Interstrain Variability in Trichloroethylene Metabolism in the Mouse

PubMed Central

Campbell, Jerry L.; Clewell, Harvey J.; Zhou, Yi-Hui; Wright, Fred A.; Guyton, Kathryn Z.

2014-01-01

Background: Quantitative estimation of toxicokinetic variability in the human population is a persistent challenge in risk assessment of environmental chemicals. Traditionally, interindividual differences in the population are accounted for by default assumptions or, in rare cases, are based on human toxicokinetic data. Objectives: We evaluated the utility of genetically diverse mouse strains for estimating toxicokinetic population variability for risk assessment, using trichloroethylene (TCE) metabolism as a case study. Methods: We used data on oxidative and glutathione conjugation metabolism of TCE in 16 inbred and 1 hybrid mouse strains to calibrate and extend existing physiologically based pharmacokinetic (PBPK) models. We added one-compartment models for glutathione metabolites and a two-compartment model for dichloroacetic acid (DCA). We used a Bayesian population analysis of interstrain variability to quantify variability in TCE metabolism. Results: Concentration–time profiles for TCE metabolism to oxidative and glutathione conjugation metabolites varied across strains. Median predictions for the metabolic flux through oxidation were less variable (5-fold range) than that through glutathione conjugation (10-fold range). For oxidative metabolites, median predictions of trichloroacetic acid production were less variable (2-fold range) than DCA production (5-fold range), although the uncertainty bounds for DCA exceeded the predicted variability. Conclusions: Population PBPK modeling of genetically diverse mouse strains can provide useful quantitative estimates of toxicokinetic population variability. When extrapolated to lower doses more relevant to environmental exposures, mouse population-derived variability estimates for TCE metabolism closely matched population variability estimates previously derived from human toxicokinetic studies with TCE, highlighting the utility of mouse interstrain metabolism studies for addressing toxicokinetic variability

Simple Process-Based Simulators for Generating Spatial Patterns of Habitat Loss and Fragmentation: A Review and Introduction to the G-RaFFe Model

PubMed Central

Pe'er, Guy; Zurita, Gustavo A.; Schober, Lucia; Bellocq, Maria I.; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model “G-RaFFe” generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non

Simple process-based simulators for generating spatial patterns of habitat loss and fragmentation: a review and introduction to the G-RaFFe model.

PubMed

Pe'er, Guy; Zurita, Gustavo A; Schober, Lucia; Bellocq, Maria I; Strer, Maximilian; Müller, Michael; Pütz, Sandro

2013-01-01

Landscape simulators are widely applied in landscape ecology for generating landscape patterns. These models can be divided into two categories: pattern-based models that generate spatial patterns irrespective of the processes that shape them, and process-based models that attempt to generate patterns based on the processes that shape them. The latter often tend toward complexity in an attempt to obtain high predictive precision, but are rarely used for generic or theoretical purposes. Here we show that a simple process-based simulator can generate a variety of spatial patterns including realistic ones, typifying landscapes fragmented by anthropogenic activities. The model "G-RaFFe" generates roads and fields to reproduce the processes in which forests are converted into arable lands. For a selected level of habitat cover, three factors dominate its outcomes: the number of roads (accessibility), maximum field size (accounting for land ownership patterns), and maximum field disconnection (which enables field to be detached from roads). We compared the performance of G-RaFFe to three other models: Simmap (neutral model), Qrule (fractal-based) and Dinamica EGO (with 4 model versions differing in complexity). A PCA-based analysis indicated G-RaFFe and Dinamica version 4 (most complex) to perform best in matching realistic spatial patterns, but an alternative analysis which considers model variability identified G-RaFFe and Qrule as performing best. We also found model performance to be affected by habitat cover and the actual land-uses, the latter reflecting on land ownership patterns. We suggest that simple process-based generators such as G-RaFFe can be used to generate spatial patterns as templates for theoretical analyses, as well as for gaining better understanding of the relation between spatial processes and patterns. We suggest caution in applying neutral or fractal-based approaches, since spatial patterns that typify anthropogenic landscapes are often non

Variable Cycle Intake for Reverse Core Engine

NASA Technical Reports Server (NTRS)

Chandler, Jesse M (Inventor); Staubach, Joseph B (Inventor); Suciu, Gabriel L (Inventor)

2016-01-01

A gas generator for a reverse core engine propulsion system has a variable cycle intake for the gas generator, which variable cycle intake includes a duct system. The duct system is configured for being selectively disposed in a first position and a second position, wherein free stream air is fed to the gas generator when in the first position, and fan stream air is fed to the gas generator when in the second position.

SVAw - a web-based application tool for automated surrogate variable analysis of gene expression studies

PubMed Central

2013-01-01

Background Surrogate variable analysis (SVA) is a powerful method to identify, estimate, and utilize the components of gene expression heterogeneity due to unknown and/or unmeasured technical, genetic, environmental, or demographic factors. These sources of heterogeneity are common in gene expression studies, and failing to incorporate them into the analysis can obscure results. Using SVA increases the biological accuracy and reproducibility of gene expression studies by identifying these sources of heterogeneity and correctly accounting for them in the analysis. Results Here we have developed a web application called SVAw (Surrogate variable analysis Web app) that provides a user friendly interface for SVA analyses of genome-wide expression studies. The software has been developed based on open source bioconductor SVA package. In our software, we have extended the SVA program functionality in three aspects: (i) the SVAw performs a fully automated and user friendly analysis workflow; (ii) It calculates probe/gene Statistics for both pre and post SVA analysis and provides a table of results for the regression of gene expression on the primary variable of interest before and after correcting for surrogate variables; and (iii) it generates a comprehensive report file, including graphical comparison of the outcome for the user. Conclusions SVAw is a web server freely accessible solution for the surrogate variant analysis of high-throughput datasets and facilitates removing all unwanted and unknown sources of variation. It is freely available for use at http://psychiatry.igm.jhmi.edu/sva. The executable packages for both web and standalone application and the instruction for installation can be downloaded from our web site. PMID:23497726

Encouraging the next generation into land-based industries.

PubMed

Rowarth, Js

2008-12-01

Members of the Y-Generation (born between approximately 1978 and 1994) have expectations of careers, rewards and 'work-life balance' that are very different from those of previous generations. This paper discusses these differences, how the land-based industries can position in order to offer 'the career path of choice', and how doing so will be of benefit not only to employers but also to New Zealand.

Assessment of economic status in trauma registries: A new algorithm for generating population-specific clustering-based models of economic status for time-constrained low-resource settings.

PubMed

Eyler, Lauren; Hubbard, Alan; Juillard, Catherine

2016-10-01

Low and middle-income countries (LMICs) and the world's poor bear a disproportionate share of the global burden of injury. Data regarding disparities in injury are vital to inform injury prevention and trauma systems strengthening interventions targeted towards vulnerable populations, but are limited in LMICs. We aim to facilitate injury disparities research by generating a standardized methodology for assessing economic status in resource-limited country trauma registries where complex metrics such as income, expenditures, and wealth index are infeasible to assess. To address this need, we developed a cluster analysis-based algorithm for generating simple population-specific metrics of economic status using nationally representative Demographic and Health Surveys (DHS) household assets data. For a limited number of variables, g, our algorithm performs weighted k-medoids clustering of the population using all combinations of g asset variables and selects the combination of variables and number of clusters that maximize average silhouette width (ASW). In simulated datasets containing both randomly distributed variables and "true" population clusters defined by correlated categorical variables, the algorithm selected the correct variable combination and appropriate cluster numbers unless variable correlation was very weak. When used with 2011 Cameroonian DHS data, our algorithm identified twenty economic clusters with ASW 0.80, indicating well-defined population clusters. This economic model for assessing health disparities will be used in the new Cameroonian six-hospital centralized trauma registry. By describing our standardized methodology and algorithm for generating economic clustering models, we aim to facilitate measurement of health disparities in other trauma registries in resource-limited countries. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Gaussian-based routines to impute categorical variables in health surveys.

PubMed

Yucel, Recai M; He, Yulei; Zaslavsky, Alan M

2011-12-20

The multivariate normal (MVN) distribution is arguably the most popular parametric model used in imputation and is available in most software packages (e.g., SAS PROC MI, R package norm). When it is applied to categorical variables as an approximation, practitioners often either apply simple rounding techniques for ordinal variables or create a distinct 'missing' category and/or disregard the nominal variable from the imputation phase. All of these practices can potentially lead to biased and/or uninterpretable inferences. In this work, we develop a new rounding methodology calibrated to preserve observed distributions to multiply impute missing categorical covariates. The major attractiveness of this method is its flexibility to use any 'working' imputation software, particularly those based on MVN, allowing practitioners to obtain usable imputations with small biases. A simulation study demonstrates the clear advantage of the proposed method in rounding ordinal variables and, in some scenarios, its plausibility in imputing nominal variables. We illustrate our methods on a widely used National Survey of Children with Special Health Care Needs where incomplete values on race posed a valid threat on inferences pertaining to disparities. Copyright © 2011 John Wiley & Sons, Ltd.

A tandem-based compact dual-energy gamma generator.

PubMed

Persaud, A; Kwan, J W; Leitner, M; Leung, K-N; Ludewigt, B; Tanaka, N; Waldron, W; Wilde, S; Antolak, A J; Morse, D H; Raber, T

2010-02-01

A dual-energy tandem-type gamma generator has been developed at E. O. Lawrence Berkeley National Laboratory and Sandia National Laboratories. The tandem accelerator geometry allows higher energy nuclear reactions to be reached, thereby allowing more flexible generation of MeV-energy gammas for active interrogation applications. Both positively charged ions and atoms of hydrogen are created from negative ions via a gas stripper. In this paper, we show first results of the working tandem-based gamma generator and that a gas stripper can be utilized in a compact source design. Preliminary results of monoenergetic gamma production are shown.

Multi-Layer Artificial Neural Networks Based MPPT-Pitch Angle Control of a Tidal Stream Generator

PubMed Central

Bouallègue, Soufiene; Garrido, Aitor J.; Haggège, Joseph

2018-01-01

Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG) systems aim to provide clean and reliable electrical power. However, the power captured from tidal currents is highly disturbed due to the swell effect and the periodicity of the tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN) is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT) generated from the ANN block. In case of strong tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances. PMID:29695127

Multi-Layer Artificial Neural Networks Based MPPT-Pitch Angle Control of a Tidal Stream Generator.

PubMed

Ghefiri, Khaoula; Bouallègue, Soufiene; Garrido, Izaskun; Garrido, Aitor J; Haggège, Joseph

2018-04-24

Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG) systems aim to provide clean and reliable electrical power. However, the power captured from tidal currents is highly disturbed due to the swell effect and the periodicity of the tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN) is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT) generated from the ANN block. In case of strong tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances.

System efficiency of a tap transformer based grid connection topology applied on a direct driven generator for wind power.

PubMed

Apelfröjd, Senad; Eriksson, Sandra

2014-01-01

Results from experiments on a tap transformer based grid connection system for a variable speed vertical axis wind turbine are presented. The tap transformer based system topology consists of a passive diode rectifier, DC-link, IGBT inverter, LCL-filter, and tap transformer. Full range variable speed operation is enabled by using the different step-up ratios of a tap transformer. Simulations using MATLAB/Simulink have been performed in order to study the behavior of the system. A full experimental set up of the system has been used in the laboratory study, where a clone of the on-site generator was driven by an induction motor and the system was connected to a resistive load to better evaluate the performance. Furthermore, the system is run and evaluated for realistic wind speeds and variable speed operation. For a more complete picture of the system performance, a case study using real site Weibull parameters is done, comparing different tap selection options. The results show high system efficiency at nominal power and an increase in overall power output for full tap operation in comparison with the base case, a standard transformer. In addition, the loss distribution at different wind speeds is shown, which highlights the dominant losses at low and high wind speeds. Finally, means for further increasing the overall system efficiency are proposed.

System Efficiency of a Tap Transformer Based Grid Connection Topology Applied on a Direct Driven Generator for Wind Power

PubMed Central

2014-01-01

Results from experiments on a tap transformer based grid connection system for a variable speed vertical axis wind turbine are presented. The tap transformer based system topology consists of a passive diode rectifier, DC-link, IGBT inverter, LCL-filter, and tap transformer. Full range variable speed operation is enabled by using the different step-up ratios of a tap transformer. Simulations using MATLAB/Simulink have been performed in order to study the behavior of the system. A full experimental set up of the system has been used in the laboratory study, where a clone of the on-site generator was driven by an induction motor and the system was connected to a resistive load to better evaluate the performance. Furthermore, the system is run and evaluated for realistic wind speeds and variable speed operation. For a more complete picture of the system performance, a case study using real site Weibull parameters is done, comparing different tap selection options. The results show high system efficiency at nominal power and an increase in overall power output for full tap operation in comparison with the base case, a standard transformer. In addition, the loss distribution at different wind speeds is shown, which highlights the dominant losses at low and high wind speeds. Finally, means for further increasing the overall system efficiency are proposed. PMID:25258733

Seasonal variability of the Canary Current: A numerical study

NASA Astrophysics Data System (ADS)

Mason, Evan; Colas, Francois; Molemaker, Jeroen; Shchepetkin, Alexander F.; Troupin, Charles; McWilliams, James C.; Sangrã, Pablo

2011-06-01

A high-resolution numerical model study of the Canary Basin in the northeast subtropical Atlantic Ocean is presented. A long-term climatological solution from the Regional Oceanic Modeling System (ROMS) reveals mesoscale variability associated with the Azores and Canary Current systems, the northwest African coastal upwelling, and the Canary Island archipelago. The primary result concerns the Canary Current (CanC) which, in the solution, transports ˜3 Sv southward in line with observations. The simulated CanC has a well-defined path with pronounced seasonal variability. This variability is shown to be mediated by the westward passage of two large annually excited counterrotating anomalous structures that originate at the African coast. The anomalies have a sea surface expression, permitting their validation using altimetry and travel at the phase speed of baroclinic planetary (Rossby) waves. The role of nearshore wind stress curl variability as a generating mechanism for the anomalies is confirmed through a sensitivity experiment forced by low-resolution winds. The resulting circulation is weak in comparison to the base run, but the propagating anomalies are still discernible, so we cannot discount a further role in their generation being played by annual reversals of the large-scale boundary flow that are known to occur along the African margin. An additional sensitivity experiment, where the Azores Current is removed by closing the Strait of Gibraltar presents the same anomalies and CanC behavior as the base run, suggesting that the CanC is rather insensitive to upstream variability from the Azores Current.

Variability sensitivity of dynamic texture based recognition in clinical CT data

NASA Astrophysics Data System (ADS)

Kwitt, Roland; Razzaque, Sharif; Lowell, Jeffrey; Aylward, Stephen

2014-03-01

Dynamic texture recognition using a database of template models has recently shown promising results for the task of localizing anatomical structures in Ultrasound video. In order to understand its clinical value, it is imperative to study the sensitivity with respect to inter-patient variability as well as sensitivity to acquisition parameters such as Ultrasound probe angle. Fully addressing patient and acquisition variability issues, however, would require a large database of clinical Ultrasound from many patients, acquired in a multitude of controlled conditions, e.g., using a tracked transducer. Since such data is not readily attainable, we advocate an alternative evaluation strategy using abdominal CT data as a surrogate. In this paper, we describe how to replicate Ultrasound variabilities by extracting subvolumes from CT and interpreting the image material as an ordered sequence of video frames. Utilizing this technique, and based on a database of abdominal CT from 45 patients, we report recognition results on an organ (kidney) recognition task, where we try to discriminate kidney subvolumes/videos from a collection of randomly sampled negative instances. We demonstrate that (1) dynamic texture recognition is relatively insensitive to inter-patient variation while (2) viewing angle variability needs to be accounted for in the template database. Since naively extending the template database to counteract variability issues can lead to impractical database sizes, we propose an alternative strategy based on automated identification of a small set of representative models.

Correlated resistive/capacitive state variability in solid TiO2 based memory devices

NASA Astrophysics Data System (ADS)

Li, Qingjiang; Salaoru, Iulia; Khiat, Ali; Xu, Hui; Prodromakis, Themistoklis

2017-05-01

In this work, we experimentally demonstrated the correlated resistive/capacitive switching and state variability in practical TiO2 based memory devices. Based on filamentary functional mechanism, we argue that the impedance state variability stems from the randomly distributed defects inside the oxide bulk. Finally, our assumption was verified via a current percolation circuit model, by taking into account of random defects distribution and coexistence of memristor and memcapacitor.

A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

PubMed Central

Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; de Jesus Romero-Troncoso, Rene

2010-01-01

Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node. PMID:22163602

HLA-E coding and 3' untranslated region variability determined by next-generation sequencing in two West-African population samples.

PubMed

Castelli, Erick C; Mendes-Junior, Celso T; Sabbagh, Audrey; Porto, Iane O P; Garcia, André; Ramalho, Jaqueline; Lima, Thálitta H A; Massaro, Juliana D; Dias, Fabrício C; Collares, Cristhianna V A; Jamonneau, Vincent; Bucheton, Bruno; Camara, Mamadou; Donadi, Eduardo A

2015-12-01

HLA-E is a non-classical Human Leucocyte Antigen class I gene with immunomodulatory properties. Whereas HLA-E expression usually occurs at low levels, it is widely distributed amongst human tissues, has the ability to bind self and non-self antigens and to interact with NK cells and T lymphocytes, being important for immunosurveillance and also for fighting against infections. HLA-E is usually the most conserved locus among all class I genes. However, most of the previous studies evaluating HLA-E variability sequenced only a few exons or genotyped known polymorphisms. Here we report a strategy to evaluate HLA-E variability by next-generation sequencing (NGS) that might be used to other HLA loci and present the HLA-E haplotype diversity considering the segment encoding the entire HLA-E mRNA (including 5'UTR, introns and the 3'UTR) in two African population samples, Susu from Guinea-Conakry and Lobi from Burkina Faso. Our results indicate that (a) the HLA-E gene is indeed conserved, encoding mainly two different protein molecules; (b) Africans do present several unknown HLA-E alleles presenting synonymous mutations; (c) the HLA-E 3'UTR is quite polymorphic and (d) haplotypes in the HLA-E 3'UTR are in close association with HLA-E coding alleles. NGS has proved to be an important tool on data generation for future studies evaluating variability in non-classical MHC genes. Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

The Impact of Engagement in Street-based Income Generation Activities on Stimulant Drug Use Cessation among People who Inject Drugs

PubMed Central

Ti, Lianping; Richardson, Lindsey; DeBeck, Kora; Nguyen, Paul; Montaner, Julio; Wood, Evan; Kerr, Thomas

2014-01-01

Background Despite the growing prevalence of illicit stimulant drug use internationally, and the widespread involvement of people who inject drugs (IDU) within street-based drug markets, little is known about the impact of different types of street-based income generation activities on the cessation of stimulant use among IDU. Methods Data were derived from an open prospective cohort of IDU in Vancouver, Canada. We used Kaplan-Meier methods and Cox proportional hazards regression to examine the effect of different types of street-based income generation activities (e.g., sex work, drug dealing, and scavenging) on time to cessation of stimulant use. Results Between December, 2005 and November, 2012, 887 IDU who use stimulant drugs (cocaine, crack cocaine, or crystal methamphetamine) were prospectively followed-up for a median duration of 47 months. In Kaplan-Meier analyses, compared to those who did not engage in street-based income generation activities, participants who reported sex work, drug dealing, scavenging, or more than one of these activities were significantly less likely to report stimulant drug use cessation (all p<0.001). When considered as time-updated variables and adjusted for potential confounders in a multivariable model, each type of street-based income generation activity remained significantly associated with a slower time to stimulant drug cessation (all p<0.005). Conclusions Our findings highlight the urgent need for strategies to address stimulant dependence, including novel pharmacotherapies. Also important, structural interventions, such as low-threshold employment opportunities, availability of supportive housing, legal reforms regarding drug use, and evidence-based approaches that reduce harm among IDU are urgently required. PMID:24909853

The impact of engagement in street-based income generation activities on stimulant drug use cessation among people who inject drugs.

PubMed

Ti, Lianping; Richardson, Lindsey; DeBeck, Kora; Nguyen, Paul; Montaner, Julio; Wood, Evan; Kerr, Thomas

2014-08-01

Despite the growing prevalence of illicit stimulant drug use internationally, and the widespread involvement of people who inject drugs (IDU) within street-based drug markets, little is known about the impact of different types of street-based income generation activities on the cessation of stimulant use among IDU. Data were derived from an open prospective cohort of IDU in Vancouver, Canada. We used Kaplan-Meier methods and Cox proportional hazards regression to examine the effect of different types of street-based income generation activities (e.g., sex work, drug dealing, and scavenging) on time to cessation of stimulant use. Between December, 2005 and November, 2012, 887 IDU who use stimulant drugs (cocaine, crack cocaine, or crystal methamphetamine) were prospectively followed-up for a median duration of 47 months. In Kaplan-Meier analyses, compared to those who did not engage in street-based income generation activities, participants who reported sex work, drug dealing, scavenging, or more than one of these activities were significantly less likely to report stimulant drug use cessation (all p<0.001). When considered as time-updated variables and adjusted for potential confounders in a multivariable model, each type of street-based income generation activity remained significantly associated with a slower time to stimulant drug cessation (all p<0.005). Our findings highlight the urgent need for strategies to address stimulant dependence, including novel pharmacotherapies. Also important, structural interventions, such as low-threshold employment opportunities, availability of supportive housing, legal reforms regarding drug use, and evidence-based approaches that reduce harm among IDU are urgently required. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Parsing with logical variables (logic-based programming systems)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finin, T.W.; Stone Palmer, M.

1983-01-01

Logic based programming systems have enjoyed an increasing popularity in applied AI work in the last few years. One of the contributions to computational linguistics made by the logic programming paradigm has been the definite clause grammar. In comparing DCGS with previous parsing mechanisms such as ATNS, certain clear advantages are seen. The authors feel that the most important of these advantages are due to the use of logical variables with unification as the fundamental operation on them. To illustrate the power of the logical variable, they have implemented an experimental atn system which treats atn registers as logical variablesmore » and provides a unification operation over them. They aim to simultaneously encourage the use of the powerful mechanisms available in DCGS and demonstrate that some of these techniques can be captured without reference to a resolution theorem prover. 14 references.« less

Modeling thrombin generation: plasma composition based approach.

PubMed

Brummel-Ziedins, Kathleen E; Everse, Stephen J; Mann, Kenneth G; Orfeo, Thomas

2014-01-01

Thrombin has multiple functions in blood coagulation and its regulation is central to maintaining the balance between hemorrhage and thrombosis. Empirical and computational methods that capture thrombin generation can provide advancements to current clinical screening of the hemostatic balance at the level of the individual. In any individual, procoagulant and anticoagulant factor levels together act to generate a unique coagulation phenotype (net balance) that is reflective of the sum of its developmental, environmental, genetic, nutritional and pharmacological influences. Defining such thrombin phenotypes may provide a means to track disease progression pre-crisis. In this review we briefly describe thrombin function, methods for assessing thrombin dynamics as a phenotypic marker, computationally derived thrombin phenotypes versus determined clinical phenotypes, the boundaries of normal range thrombin generation using plasma composition based approaches and the feasibility of these approaches for predicting risk.

Flexible Energy Scheduling Tool for Integrating Variable Generation | Grid

Science.gov Websites

, security-constrained economic dispatch, and automatic generation control programs. DOWNLOAD PAPER Electric commitment, security-constrained economic dispatch, and automatic generation control sub-models. Each sub resolutions and operating strategies can be explored. FESTIV produces not only economic metrics but also

Measurement-based quantum communication with resource states generated by entanglement purification

NASA Astrophysics Data System (ADS)

Wallnöfer, J.; Dür, W.

2017-01-01

We investigate measurement-based quantum communication with noisy resource states that are generated by entanglement purification. We consider the transmission of encoded information via noisy quantum channels using a measurement-based implementation of encoding, error correction, and decoding. We show that such an approach offers advantages over direct transmission, gate-based error correction, and measurement-based schemes with direct generation of resource states. We analyze the noise structure of resource states generated by entanglement purification and show that a local error model, i.e., noise acting independently on all qubits of the resource state, is a good approximation in general, and provides an exact description for Greenberger-Horne-Zeilinger states. The latter are resources for a measurement-based implementation of error-correction codes for bit-flip or phase-flip errors. This provides an approach to link the recently found very high thresholds for fault-tolerant measurement-based quantum information processing based on local error models for resource states with error thresholds for gate-based computational models.

A Window Into Clinical Next-Generation Sequencing-Based Oncology Testing Practices.

PubMed

Nagarajan, Rakesh; Bartley, Angela N; Bridge, Julia A; Jennings, Lawrence J; Kamel-Reid, Suzanne; Kim, Annette; Lazar, Alexander J; Lindeman, Neal I; Moncur, Joel; Rai, Alex J; Routbort, Mark J; Vasalos, Patricia; Merker, Jason D

2017-12-01

- Detection of acquired variants in cancer is a paradigm of precision medicine, yet little has been reported about clinical laboratory practices across a broad range of laboratories. - To use College of American Pathologists proficiency testing survey results to report on the results from surveys on next-generation sequencing-based oncology testing practices. - College of American Pathologists proficiency testing survey results from more than 250 laboratories currently performing molecular oncology testing were used to determine laboratory trends in next-generation sequencing-based oncology testing. - These presented data provide key information about the number of laboratories that currently offer or are planning to offer next-generation sequencing-based oncology testing. Furthermore, we present data from 60 laboratories performing next-generation sequencing-based oncology testing regarding specimen requirements and assay characteristics. The findings indicate that most laboratories are performing tumor-only targeted sequencing to detect single-nucleotide variants and small insertions and deletions, using desktop sequencers and predesigned commercial kits. Despite these trends, a diversity of approaches to testing exists. - This information should be useful to further inform a variety of topics, including national discussions involving clinical laboratory quality systems, regulation and oversight of next-generation sequencing-based oncology testing, and precision oncology efforts in a data-driven manner.

Variable disparity estimation based intermediate view reconstruction in dynamic flow allocation over EPON-based access networks

NASA Astrophysics Data System (ADS)

Bae, Kyung-Hoon; Lee, Jungjoon; Kim, Eun-Soo

2008-06-01

In this paper, a variable disparity estimation (VDE)-based intermediate view reconstruction (IVR) in dynamic flow allocation (DFA) over an Ethernet passive optical network (EPON)-based access network is proposed. In the proposed system, the stereoscopic images are estimated by a variable block-matching algorithm (VBMA), and they are transmitted to the receiver through DFA over EPON. This scheme improves a priority-based access network by converting it to a flow-based access network with a new access mechanism and scheduling algorithm, and then 16-view images are synthesized by the IVR using VDE. Some experimental results indicate that the proposed system improves the peak-signal-to-noise ratio (PSNR) to as high as 4.86 dB and reduces the processing time to 3.52 s. Additionally, the network service provider can provide upper limits of transmission delays by the flow. The modeling and simulation results, including mathematical analyses, from this scheme are also provided.

On the accuracy and reproducibility of a novel probabilistic atlas-based generation for calculation of head attenuation maps on integrated PET/MR scanners.

PubMed

Chen, Kevin T; Izquierdo-Garcia, David; Poynton, Clare B; Chonde, Daniel B; Catana, Ciprian

2017-03-01

To propose an MR-based method for generating continuous-valued head attenuation maps and to assess its accuracy and reproducibility. Demonstrating that novel MR-based photon attenuation correction methods are both accurate and reproducible is essential prior to using them routinely in research and clinical studies on integrated PET/MR scanners. Continuous-valued linear attenuation coefficient maps ("μ-maps") were generated by combining atlases that provided the prior probability of voxel positions belonging to a certain tissue class (air, soft tissue, or bone) and an MR intensity-based likelihood classifier to produce posterior probability maps of tissue classes. These probabilities were used as weights to generate the μ-maps. The accuracy of this probabilistic atlas-based continuous-valued μ-map ("PAC-map") generation method was assessed by calculating the voxel-wise absolute relative change (RC) between the MR-based and scaled CT-based attenuation-corrected PET images. To assess reproducibility, we performed pair-wise comparisons of the RC values obtained from the PET images reconstructed using the μ-maps generated from the data acquired at three time points. The proposed method produced continuous-valued μ-maps that qualitatively reflected the variable anatomy in patients with brain tumor and agreed well with the scaled CT-based μ-maps. The absolute RC comparing the resulting PET volumes was 1.76 ± 2.33 %, quantitatively demonstrating that the method is accurate. Additionally, we also showed that the method is highly reproducible, the mean RC value for the PET images reconstructed using the μ-maps obtained at the three visits being 0.65 ± 0.95 %. Accurate and highly reproducible continuous-valued head μ-maps can be generated from MR data using a probabilistic atlas-based approach.

Two-stage stochastic unit commitment model including non-generation resources with conditional value-at-risk constraints

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Yuping; Zheng, Qipeng P.; Wang, Jianhui

2014-11-01

tThis paper presents a two-stage stochastic unit commitment (UC) model, which integrates non-generation resources such as demand response (DR) and energy storage (ES) while including riskconstraints to balance between cost and system reliability due to the fluctuation of variable genera-tion such as wind and solar power. This paper uses conditional value-at-risk (CVaR) measures to modelrisks associated with the decisions in a stochastic environment. In contrast to chance-constrained modelsrequiring extra binary variables, risk constraints based on CVaR only involve linear constraints and con-tinuous variables, making it more computationally attractive. The proposed models with risk constraintsare able to avoid over-conservative solutions butmore » still ensure system reliability represented by loss ofloads. Then numerical experiments are conducted to study the effects of non-generation resources ongenerator schedules and the difference of total expected generation costs with risk consideration. Sen-sitivity analysis based on reliability parameters is also performed to test the decision preferences ofconfidence levels and load-shedding loss allowances on generation cost reduction.« less

Exploring changes in the spatial distribution of stream baseflow generation during a seasonal recession

USGS Publications Warehouse

Payn, R.A.; Gooseff, M.N.; McGlynn, B.L.; Bencala, K.E.; Wondzell, S.M.

2012-01-01

Relating watershed structure to streamflow generation is a primary focus of hydrology. However, comparisons of longitudinal variability in stream discharge with adjacent valley structure have been rare, resulting in poor understanding of the distribution of the hydrologic mechanisms that cause variability in streamflow generation along valleys. This study explores detailed surveys of stream base flow across a gauged, 23 km2 mountain watershed. Research objectives were (1) to relate spatial variability in base flow to fundamental elements of watershed structure, primarily topographic contributing area, and (2) to assess temporal changes in the spatial patterns of those relationships during a seasonal base flow recession. We analyzed spatiotemporal variability in base flow using (1) summer hydrographs at the study watershed outlet and 5 subwatershed outlets and (2) longitudinal series of discharge measurements every ~100 m along the streams of the 3 largest subwatersheds (1200 to 2600 m in valley length), repeated 2 to 3 times during base flow recession. Reaches within valley segments of 300 to 1200 m in length tended to demonstrate similar streamflow generation characteristics. Locations of transitions between these segments were consistent throughout the recession, and tended to be collocated with abrupt longitudinal transitions in valley slope or hillslope-riparian characteristics. Both within and among subwatersheds, correlation between the spatial distributions of streamflow and topographic contributing area decreased during the recession, suggesting a general decrease in the influence of topography on stream base flow contributions. As topographic controls on base flow evidently decreased, multiple aspects of subsurface structure were likely to have gained influence.

Adaptive Practice: Next Generation Evidence-Based Practice in Digital Environments.

PubMed

Kennedy, Margaret Ann

2016-01-01

Evidence-based practice in nursing is considered foundational to safe, competent care. To date, rigid traditional perceptions of what constitutes 'evidence' have constrained the recognition and use of practice-based evidence and the exploitation of novel forms of evidence from data rich environments. Advancements such as the conceptualization of clinical intelligence, the prevalence of increasingly sophisticated digital health information systems, and the advancement of the Big Data phenomenon have converged to generate a new contemporary context. In today's dynamic data-rich environments, clinicians have new sources of valid evidence, and need a new paradigm supporting clinical practice that is adaptive to information generated by diverse electronic sources. This opinion paper presents adaptive practice as the next generation of evidence-based practice in contemporary evidence-rich environments and provides recommendations for the next phase of evolution.

Piezo-Potential Generation in Capacitive Flexible Sensors Based on GaN Horizontal Wires.

PubMed

El Kacimi, Amine; Pauliac-Vaujour, Emmanuelle; Delléa, Olivier; Eymery, Joël

2018-06-12

We report an example of the realization of a flexible capacitive piezoelectric sensor based on the assembly of horizontal c¯-polar long Gallium nitride (GaN) wires grown by metal organic vapour phase epitaxy (MOVPE) with the Boostream ® technique spreading wires on a moving liquid before their transfer on large areas. The measured signal (<0.6 V) obtained by a punctual compression/release of the device shows a large variability attributed to the dimensions of the wires and their in-plane orientations. The cause of this variability and the general operating mechanisms of this flexible capacitive device are explained by finite element modelling simulations. This method allows considering the full device composed of a metal/dielectric/wires/dielectric/metal stacking. We first clarify the mechanisms involved in the piezo-potential generation by mapping the charge and piezo-potential in a single wire and studying the time-dependent evolution of this phenomenon. GaN wires have equivalent dipoles that generate a tension between metallic electrodes only when they have a non-zero in-plane projection. This is obtained in practice by the conical shape occurring spontaneously during the MOVPE growth. The optimal aspect ratio in terms of length and conicity (for the usual MOVPE wire diameter) is determined for a bending mechanical loading. It is suggested to use 60⁻120 µm long wires (i.e., growth time less than 1 h). To study further the role of these dipoles, we consider model systems with in-plane 1D and 2D regular arrays of horizontal wires. It is shown that a strong electrostatic coupling and screening occur between neighbouring horizontal wires depending on polarity and shape. This effect, highlighted here only from calculations, should be taken into account to improve device performance.

Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. I: Spike Generating Models on Converging Motifs

PubMed Central

Bi, Zedong; Zhou, Changsong

2016-01-01

In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons and synapses as well as the randomness of connection details, spike trains typically exhibit variability such as spatial randomness and temporal stochasticity, resulting in variability of synaptic changes under plasticity, which we call efficacy variability. How the variability of spike trains influences the efficacy variability of synapses remains unclear. In this paper, we try to understand this influence under pair-wise additive spike-timing dependent plasticity (STDP) when the mean strength of plastic synapses into a neuron is bounded (synaptic homeostasis). Specifically, we systematically study, analytically and numerically, how four aspects of statistical features, i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations, as well as their interactions influence the efficacy variability in converging motifs (simple networks in which one neuron receives from many other neurons). Neurons (including the post-synaptic neuron) in a converging motif generate spikes according to statistical models with tunable parameters. In this way, we can explicitly control the statistics of the spike patterns, and investigate their influence onto the efficacy variability, without worrying about the feedback from synaptic changes onto the dynamics of the post-synaptic neuron. We separate efficacy variability into two parts: the drift part (DriftV) induced by the heterogeneity of change rates of different synapses, and the diffusion part (DiffV) induced by weight diffusion caused by stochasticity of spike trains. Our main findings are: (1) synchronous firing and burstiness tend to increase DiffV, (2) heterogeneity of rates induces DriftV when potentiation and depression in STDP are not balanced, and (3) heterogeneity of cross-correlations induces DriftV together with heterogeneity of rates. We anticipate our work

Method of operating a thermoelectric generator

DOEpatents

Reynolds, Michael G; Cowgill, Joshua D

2013-11-05

A method for operating a thermoelectric generator supplying a variable-load component includes commanding the variable-load component to operate at a first output and determining a first load current and a first load voltage to the variable-load component while operating at the commanded first output. The method also includes commanding the variable-load component to operate at a second output and determining a second load current and a second load voltage to the variable-load component while operating at the commanded second output. The method includes calculating a maximum power output of the thermoelectric generator from the determined first load current and voltage and the determined second load current and voltage, and commanding the variable-load component to operate at a third output. The commanded third output is configured to draw the calculated maximum power output from the thermoelectric generator.

Unsupervised classification of variable stars

NASA Astrophysics Data System (ADS)

Valenzuela, Lucas; Pichara, Karim

2018-03-01

During the past 10 years, a considerable amount of effort has been made to develop algorithms for automatic classification of variable stars. That has been primarily achieved by applying machine learning methods to photometric data sets where objects are represented as light curves. Classifiers require training sets to learn the underlying patterns that allow the separation among classes. Unfortunately, building training sets is an expensive process that demands a lot of human efforts. Every time data come from new surveys; the only available training instances are the ones that have a cross-match with previously labelled objects, consequently generating insufficient training sets compared with the large amounts of unlabelled sources. In this work, we present an algorithm that performs unsupervised classification of variable stars, relying only on the similarity among light curves. We tackle the unsupervised classification problem by proposing an untraditional approach. Instead of trying to match classes of stars with clusters found by a clustering algorithm, we propose a query-based method where astronomers can find groups of variable stars ranked by similarity. We also develop a fast similarity function specific for light curves, based on a novel data structure that allows scaling the search over the entire data set of unlabelled objects. Experiments show that our unsupervised model achieves high accuracy in the classification of different types of variable stars and that the proposed algorithm scales up to massive amounts of light curves.

A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

PubMed

Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

2017-01-01

Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

Dispersed solar thermal generation employing parabolic dish-electric transport with field modulated generator systems

NASA Technical Reports Server (NTRS)

Ramakumar, R.; Bahrami, K.

1981-01-01

This paper discusses the application of field modulated generator systems (FMGS) to dispersed solar-thermal-electric generation from a parabolic dish field with electric transport. Each solar generation unit is rated at 15 kWe and the power generated by an array of such units is electrically collected for insertion into an existing utility grid. Such an approach appears to be most suitable when the heat engine rotational speeds are high (greater than 6000 r/min) and, in particular, if they are operated in the variable speed mode and if utility-grade a.c. is required for direct insertion into the grid without an intermediate electric energy storage and reconversion system. Predictions of overall efficiencies based on conservative efficiency figures for the FMGS are in the range of 25 per cent and should be encouraging to those involved in the development of cost-effective dispersed solar thermal power systems.

Auto Code Generation for Simulink-Based Attitude Determination Control System

NASA Technical Reports Server (NTRS)

MolinaFraticelli, Jose Carlos

2012-01-01

This paper details the work done to auto generate C code from a Simulink-Based Attitude Determination Control System (ADCS) to be used in target platforms. NASA Marshall Engineers have developed an ADCS Simulink simulation to be used as a component for the flight software of a satellite. This generated code can be used for carrying out Hardware in the loop testing of components for a satellite in a convenient manner with easily tunable parameters. Due to the nature of the embedded hardware components such as microcontrollers, this simulation code cannot be used directly, as it is, on the target platform and must first be converted into C code; this process is known as auto code generation. In order to generate C code from this simulation; it must be modified to follow specific standards set in place by the auto code generation process. Some of these modifications include changing certain simulation models into their atomic representations which can bring new complications into the simulation. The execution order of these models can change based on these modifications. Great care must be taken in order to maintain a working simulation that can also be used for auto code generation. After modifying the ADCS simulation for the auto code generation process, it is shown that the difference between the output data of the former and that of the latter is between acceptable bounds. Thus, it can be said that the process is a success since all the output requirements are met. Based on these results, it can be argued that this generated C code can be effectively used by any desired platform as long as it follows the specific memory requirements established in the Simulink Model.

Changes in the Economic Value of Variable Generation at High Penetration Levels: A Pilot Case Study of California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mills, Andrew; Wiser, Ryan

2012-05-18

We estimate the long-run economic value of variable renewable generation with increasing penetration using a unique investment and dispatch model that captures long-run investment decisions while also incorporating detailed operational constraints and hourly time resolution over a full year. High time resolution and the incorporation of operational constraints are important for estimating the economic value of variable generation, as is the use of a modeling framework that accommodates new investment decisions. The model is herein applied with a case study that is loosely based on California in 2030. Increasing amounts of wind, photovoltaics (PV), and concentrating solar power (CSP) with and without thermal energy storage (TES) are added one at a time. The marginal economic value of these renewable energy sources is estimated and then decomposed into capacity value, energy value, day-ahead forecast error cost, and ancillary services. The marginal economic value, as defined here, is primarily based on the combination of avoided capital investment cost and avoided variable fuel and operations and maintenance costs from other power plants in the power system. Though the model only captures a subset of the benefits and costs of renewable energy, it nonetheless provides unique insights into how the value of that subset changes with technology and penetration level. Specifically, in this case study implementation of the model, the marginal economic value of all three solar options is found to exceed the value of a flat-block of power (as well as wind energy) by \\more » $$20--30/MWh at low penetration levels, largely due to the high capacity value of solar at low penetration. Because the value of CSP per unit of energy is found to be high with or without thermal energy storage at low penetration, we find little apparent incremental value to thermal storage at low solar penetration in the present case study analysis. The marginal economic value of PV and CSP without

Generation of remote adaptive torsional shear waves with an octagonal phased array to enhance displacements and reduce variability of shear wave speeds: comparison with quasi-plane shear wavefronts.

PubMed

Ouared, Abderrahmane; Montagnon, Emmanuel; Cloutier, Guy

2015-10-21

A method based on adaptive torsional shear waves (ATSW) is proposed to overcome the strong attenuation of shear waves generated by a radiation force in dynamic elastography. During the inward propagation of ATSW, the magnitude of displacements is enhanced due to the convergence of shear waves and constructive interferences. The proposed method consists in generating ATSW fields from the combination of quasi-plane shear wavefronts by considering a linear superposition of displacement maps. Adaptive torsional shear waves were experimentally generated in homogeneous and heterogeneous tissue mimicking phantoms, and compared to quasi-plane shear wave propagations. Results demonstrated that displacement magnitudes by ATSW could be up to 3 times higher than those obtained with quasi-plane shear waves, that the variability of shear wave speeds was reduced, and that the signal-to-noise ratio of displacements was improved. It was also observed that ATSW could cause mechanical inclusions to resonate in heterogeneous phantoms, which further increased the displacement contrast between the inclusion and the surrounding medium. This method opens a way for the development of new noninvasive tissue characterization strategies based on ATSW in the framework of our previously reported shear wave induced resonance elastography (SWIRE) method proposed for breast cancer diagnosis.

Measuring spatial variability in soil characteristics

DOEpatents

Hoskinson, Reed L.; Svoboda, John M.; Sawyer, J. Wayne; Hess, John R.; Hess, J. Richard

2002-01-01

The present invention provides systems and methods for measuring a load force associated with pulling a farm implement through soil that is used to generate a spatially variable map that represents the spatial variability of the physical characteristics of the soil. An instrumented hitch pin configured to measure a load force is provided that measures the load force generated by a farm implement when the farm implement is connected with a tractor and pulled through or across soil. Each time a load force is measured, a global positioning system identifies the location of the measurement. This data is stored and analyzed to generate a spatially variable map of the soil. This map is representative of the physical characteristics of the soil, which are inferred from the magnitude of the load force.

The influence of an uncertain force environment on reshaping trial-to-trial motor variability.

PubMed

Izawa, Jun; Yoshioka, Toshinori; Osu, Rieko

2014-09-10

Motor memory is updated to generate ideal movements in a novel environment. When the environment changes every trial randomly, how does the brain incorporate this uncertainty into motor memory? To investigate how the brain adapts to an uncertain environment, we considered a reach adaptation protocol where individuals practiced moving in a force field where a noise was injected. After they had adapted, we measured the trial-to-trial variability in the temporal profiles of the produced hand force. We found that the motor variability was significantly magnified by the adaptation to the random force field. Temporal profiles of the motor variance were significantly dissociable between two different types of random force fields experienced. A model-based analysis suggests that the variability is generated by noise in the gains of the internal model. It further suggests that the trial-to-trial motor variability magnified by the adaptation in a random force field is generated by the uncertainty of the internal model formed in the brain as a result of the adaptation.

a Spiral-Based Downscaling Method for Generating 30 M Time Series Image Data

NASA Astrophysics Data System (ADS)

Liu, B.; Chen, J.; Xing, H.; Wu, H.; Zhang, J.

2017-09-01

The spatial detail and updating frequency of land cover data are important factors influencing land surface dynamic monitoring applications in high spatial resolution scale. However, the fragmentized patches and seasonal variable of some land cover types (e. g. small crop field, wetland) make it labor-intensive and difficult in the generation of land cover data. Utilizing the high spatial resolution multi-temporal image data is a possible solution. Unfortunately, the spatial and temporal resolution of available remote sensing data like Landsat or MODIS datasets can hardly satisfy the minimum mapping unit and frequency of current land cover mapping / updating at the same time. The generation of high resolution time series may be a compromise to cover the shortage in land cover updating process. One of popular way is to downscale multi-temporal MODIS data with other high spatial resolution auxiliary data like Landsat. But the usual manner of downscaling pixel based on a window may lead to the underdetermined problem in heterogeneous area, result in the uncertainty of some high spatial resolution pixels. Therefore, the downscaled multi-temporal data can hardly reach high spatial resolution as Landsat data. A spiral based method was introduced to downscale low spatial and high temporal resolution image data to high spatial and high temporal resolution image data. By the way of searching the similar pixels around the adjacent region based on the spiral, the pixel set was made up in the adjacent region pixel by pixel. The underdetermined problem is prevented to a large extent from solving the linear system when adopting the pixel set constructed. With the help of ordinary least squares, the method inverted the endmember values of linear system. The high spatial resolution image was reconstructed on the basis of high spatial resolution class map and the endmember values band by band. Then, the high spatial resolution time series was formed with these high spatial

Generating partially correlated noise—A comparison of methods

PubMed Central

Hartmann, William M.; Cho, Yun Jin

2011-01-01

There are three standard methods for generating two channels of partially correlated noise: the two-generator method, the three-generator method, and the symmetric-generator method. These methods allow an experimenter to specify a target cross correlation between the two channels, but actual generated noises show statistical variability around the target value. Numerical experiments were done to compare the variability for those methods as a function of the number of degrees of freedom. The results of the experiments quantify the stimulus uncertainty in diverse binaural psychoacoustical experiments: incoherence detection, perceived auditory source width, envelopment, noise localization∕lateralization, and the masking level difference. The numerical experiments found that when the elemental generators have unequal powers, the different methods all have similar variability. When the powers are constrained to be equal, the symmetric-generator method has much smaller variability than the other two. PMID:21786899

Ground-based full-sky imaging polarimeter based on liquid crystal variable retarders.

PubMed

Zhang, Ying; Zhao, Huijie; Song, Ping; Shi, Shaoguang; Xu, Wujian; Liang, Xiao

2014-04-07

A ground-based full-sky imaging polarimeter based on liquid crystal variable retarders (LCVRs) is proposed in this paper. Our proposed method can be used to realize the rapid detection of the skylight polarization information with hemisphere field-of-view for the visual band. The characteristics of the incidence angle of light on the LCVR are investigated, based on the electrically controlled birefringence. Then, the imaging polarimeter with hemisphere field-of-view is designed. Furthermore, the polarization calibration method with the field-of-view multiplexing and piecewise linear fitting is proposed, based on the rotation symmetry of the polarimeter. The polarization calibration of the polarimeter is implemented with the hemisphere field-of-view. This imaging polarimeter is investigated by the experiment of detecting the skylight image. The consistency between the obtained experimental distribution of polarization angle with that due to Rayleigh scattering model is 90%, which confirms the effectivity of our proposed imaging polarimeter.

Major and trace element modeling of mid-ocean ridge mantle melting from the garnet to the plagioclase stability fields: Generating local and global compositional variability

NASA Astrophysics Data System (ADS)

Brown, S. M.; Behn, M. D.; Grove, T. L.

2017-12-01

We present results of a combined petrologic - geochemical (major and trace element) - geodynamical forward model for mantle melting and subsequent melt modification. The model advances Behn & Grove (2015), and is calibrated using experimental petrology. Our model allows for melting in the plagioclase, spinel, and garnet fields with a flexible retained melt fraction (from pure batch to pure fractional), tracks residual mantle composition, and includes melting with water, variable melt productivity, and mantle mode calculations. This approach is valuable for understanding oceanic crustal accretion, which involves mantle melting and melt modification by migration and aggregation. These igneous processes result in mid-ocean ridge basalts that vary in composition at the local (segment) and global scale. The important variables are geophysical and geochemical and include mantle composition, potential temperature, mantle flow, and spreading rate. Accordingly, our model allows us to systematically quantify the importance of each of these external variables. In addition to discriminating melt generation effects, we are able to discriminate the effects of different melt modification processes (inefficient pooling, melt-rock reaction, and fractional crystallization) in generating both local, segment-scale and global-scale compositional variability. We quantify the influence of a specific igneous process on the generation of oceanic crust as a function of variations in the external variables. We also find that it is unlikely that garnet lherzolite melting produces a signature in either major or trace element compositions formed from aggregated melts, because when melting does occur in the garnet field at high mantle temperature, it contributes a relatively small, uniform fraction (< 10%) of the pooled melt compositions at all spreading rates. Additionally, while increasing water content and/or temperature promote garnet melting, they also increase melt extent, pushing the

Ground-based total ozone column measurements and their diurnal variability

NASA Astrophysics Data System (ADS)

Silva, Abel A.

2013-07-01

Brewer spectrophotometers were set up in three tropical sites of South America (in the Bolivian Altiplano and seashore and biomass burning areas of Brazil) to measure the total ozone column (TOC). Only TOC measurements with uncertainties ≤1% (1σ) were considered. Typically, the standard deviation for the diurnal sets of measurements was predominantly ≤1% for two of these sites. The average variability in TOC ranged from 6.3 Dobson units (DU) to 16.8 DU, and the largest variability reached 54.3 DU. Comparisons between ground-based and satellite (Total Ozone Mapping Spectrometer (TOMS)) data showed good agreement with coefficients of determination ≤0.83. However, the quality of the ground-based measurements was affected by the weather condition, especially for one of the sites. Visual observation of the sky from the ground during the measurements with one of the Brewers added to the satellite data of reflectivity and aerosol index supports that statement.

Research on grid connection control technology of double fed wind generator

NASA Astrophysics Data System (ADS)

Ling, Li

2017-01-01

The composition and working principle of variable speed constant frequency doubly fed wind power generation system is discussed in this thesis. On the basis of theoretical analysis and control on the modeling, the doubly fed wind power generation simulation control system is designed based on a TMS320F2407 digital signal processor (DSP), and has done a large amount of experimental research, which mainly include, variable speed constant frequency, constant pressure, Grid connected control experiment. The running results show that the design of simulation control system is reasonable and can meet the need of experimental research.

Ratio index variables or ANCOVA? Fisher's cats revisited.

PubMed

Tu, Yu-Kang; Law, Graham R; Ellison, George T H; Gilthorpe, Mark S

2010-01-01

Over 60 years ago Ronald Fisher demonstrated a number of potential pitfalls with statistical analyses using ratio variables. Nonetheless, these pitfalls are largely overlooked in contemporary clinical and epidemiological research, which routinely uses ratio variables in statistical analyses. This article aims to demonstrate how very different findings can be generated as a result of less than perfect correlations among the data used to generate ratio variables. These imperfect correlations result from measurement error and random biological variation. While the former can often be reduced by improvements in measurement, random biological variation is difficult to estimate and eliminate in observational studies. Moreover, wherever the underlying biological relationships among epidemiological variables are unclear, and hence the choice of statistical model is also unclear, the different findings generated by different analytical strategies can lead to contradictory conclusions. Caution is therefore required when interpreting analyses of ratio variables whenever the underlying biological relationships among the variables involved are unspecified or unclear. (c) 2009 John Wiley & Sons, Ltd.

Seabed mapping and characterization of sediment variability using the usSEABED data base

USGS Publications Warehouse

Goff, J.A.; Jenkins, C.J.; Jeffress, Williams S.

2008-01-01

We present a methodology for statistical analysis of randomly located marine sediment point data, and apply it to the US continental shelf portions of usSEABED mean grain size records. The usSEABED database, like many modern, large environmental datasets, is heterogeneous and interdisciplinary. We statistically test the database as a source of mean grain size data, and from it provide a first examination of regional seafloor sediment variability across the entire US continental shelf. Data derived from laboratory analyses ("extracted") and from word-based descriptions ("parsed") are treated separately, and they are compared statistically and deterministically. Data records are selected for spatial analysis by their location within sample regions: polygonal areas defined in ArcGIS chosen by geography, water depth, and data sufficiency. We derive isotropic, binned semivariograms from the data, and invert these for estimates of noise variance, field variance, and decorrelation distance. The highly erratic nature of the semivariograms is a result both of the random locations of the data and of the high level of data uncertainty (noise). This decorrelates the data covariance matrix for the inversion, and largely prevents robust estimation of the fractal dimension. Our comparison of the extracted and parsed mean grain size data demonstrates important differences between the two. In particular, extracted measurements generally produce finer mean grain sizes, lower noise variance, and lower field variance than parsed values. Such relationships can be used to derive a regionally dependent conversion factor between the two. Our analysis of sample regions on the US continental shelf revealed considerable geographic variability in the estimated statistical parameters of field variance and decorrelation distance. Some regional relationships are evident, and overall there is a tendency for field variance to be higher where the average mean grain size is finer grained

Costs of solar and wind power variability for reducing CO2 emissions.

PubMed

Lueken, Colleen; Cohen, Gilbert E; Apt, Jay

2012-09-04

We compare the power output from a year of electricity generation data from one solar thermal plant, two solar photovoltaic (PV) arrays, and twenty Electric Reliability Council of Texas (ERCOT) wind farms. The analysis shows that solar PV electricity generation is approximately one hundred times more variable at frequencies on the order of 10(-3) Hz than solar thermal electricity generation, and the variability of wind generation lies between that of solar PV and solar thermal. We calculate the cost of variability of the different solar power sources and wind by using the costs of ancillary services and the energy required to compensate for its variability and intermittency, and the cost of variability per unit of displaced CO(2) emissions. We show the costs of variability are highly dependent on both technology type and capacity factor. California emissions data were used to calculate the cost of variability per unit of displaced CO(2) emissions. Variability cost is greatest for solar PV generation at $8-11 per MWh. The cost of variability for solar thermal generation is $5 per MWh, while that of wind generation in ERCOT was found to be on average $4 per MWh. Variability adds ~$15/tonne CO(2) to the cost of abatement for solar thermal power, $25 for wind, and $33-$40 for PV.

Age-Based Methods to Explore Time-Related Variables in Occupational Epidemiology Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Janice P. Watkins, Edward L. Frome, Donna L. Cragle

2005-08-31

Although age is recognized as the strongest predictor of mortality in chronic disease epidemiology, a calendar-based approach is often employed when evaluating time-related variables. An age-based analysis file, created by determining the value of each time-dependent variable for each age that a cohort member is followed, provides a clear definition of age at exposure and allows development of diverse analytic models. To demonstrate methods, the relationship between cancer mortality and external radiation was analyzed with Poisson regression for 14,095 Oak Ridge National Laboratory workers. Based on previous analysis of this cohort, a model with ten-year lagged cumulative radiation doses partitionedmore » by receipt before (dose-young) or after (dose-old) age 45 was examined. Dose-response estimates were similar to calendar-year-based results with elevated risk for dose-old, but not when film badge readings were weekly before 1957. Complementary results showed increasing risk with older hire ages and earlier birth cohorts, since workers hired after age 45 were born before 1915, and dose-young and dose-old were distributed differently by birth cohorts. Risks were generally higher for smokingrelated than non-smoking-related cancers. It was difficult to single out specific variables associated with elevated cancer mortality because of: (1) birth cohort differences in hire age and mortality experience completeness, and (2) time-period differences in working conditions, dose potential, and exposure assessment. This research demonstrated the utility and versatility of the age-based approach.« less

Perspectives in flow-based microfluidic gradient generators for characterizing bacterial chemotaxis

PubMed Central

Wolfram, Christopher J.; Rubloff, Gary W.; Luo, Xiaolong

2016-01-01

Chemotaxis is a phenomenon which enables cells to sense concentrations of certain chemical species in their microenvironment and move towards chemically favorable regions. Recent advances in microbiology have engineered the chemotactic properties of bacteria to perform novel functions, but traditional methods of characterizing chemotaxis do not fully capture the associated cell motion, making it difficult to infer mechanisms that link the motion to the microbiology which induces it. Microfluidics offers a potential solution in the form of gradient generators. Many of the gradient generators studied to date for this application are flow-based, where a chemical species diffuses across the laminar flow interface between two solutions moving through a microchannel. Despite significant research efforts, flow-based gradient generators have achieved mixed success at accurately capturing the highly subtle chemotactic responses exhibited by bacteria. Here we present an analysis encompassing previously published versions of flow-based gradient generators, the theories that govern their gradient-generating properties, and new, more practical considerations that result from experimental factors. We conclude that flow-based gradient generators present a challenge inherent to their design in that the residence time and gradient decay must be finely balanced, and that this significantly narrows the window for reliable observation and quantification of chemotactic motion. This challenge is compounded by the effects of shear on an ellipsoidal bacterium that causes it to preferentially align with the direction of flow and subsequently suppresses the cross-flow chemotactic response. These problems suggest that a static, non-flowing gradient generator may be a more suitable platform for chemotaxis studies in the long run, despite posing greater difficulties in design and fabrication. PMID:27917249

Perspectives in flow-based microfluidic gradient generators for characterizing bacterial chemotaxis.

PubMed

Wolfram, Christopher J; Rubloff, Gary W; Luo, Xiaolong

2016-11-01

Chemotaxis is a phenomenon which enables cells to sense concentrations of certain chemical species in their microenvironment and move towards chemically favorable regions. Recent advances in microbiology have engineered the chemotactic properties of bacteria to perform novel functions, but traditional methods of characterizing chemotaxis do not fully capture the associated cell motion, making it difficult to infer mechanisms that link the motion to the microbiology which induces it. Microfluidics offers a potential solution in the form of gradient generators. Many of the gradient generators studied to date for this application are flow-based, where a chemical species diffuses across the laminar flow interface between two solutions moving through a microchannel. Despite significant research efforts, flow-based gradient generators have achieved mixed success at accurately capturing the highly subtle chemotactic responses exhibited by bacteria. Here we present an analysis encompassing previously published versions of flow-based gradient generators, the theories that govern their gradient-generating properties, and new, more practical considerations that result from experimental factors. We conclude that flow-based gradient generators present a challenge inherent to their design in that the residence time and gradient decay must be finely balanced, and that this significantly narrows the window for reliable observation and quantification of chemotactic motion. This challenge is compounded by the effects of shear on an ellipsoidal bacterium that causes it to preferentially align with the direction of flow and subsequently suppresses the cross-flow chemotactic response. These problems suggest that a static, non-flowing gradient generator may be a more suitable platform for chemotaxis studies in the long run, despite posing greater difficulties in design and fabrication.

A fast chaos-based image encryption scheme with a dynamic state variables selection mechanism

NASA Astrophysics Data System (ADS)

Chen, Jun-xin; Zhu, Zhi-liang; Fu, Chong; Yu, Hai; Zhang, Li-bo

2015-03-01

In recent years, a variety of chaos-based image cryptosystems have been investigated to meet the increasing demand for real-time secure image transmission. Most of them are based on permutation-diffusion architecture, in which permutation and diffusion are two independent procedures with fixed control parameters. This property results in two flaws. (1) At least two chaotic state variables are required for encrypting one plain pixel, in permutation and diffusion stages respectively. Chaotic state variables produced with high computation complexity are not sufficiently used. (2) The key stream solely depends on the secret key, and hence the cryptosystem is vulnerable against known/chosen-plaintext attacks. In this paper, a fast chaos-based image encryption scheme with a dynamic state variables selection mechanism is proposed to enhance the security and promote the efficiency of chaos-based image cryptosystems. Experimental simulations and extensive cryptanalysis have been carried out and the results prove the superior security and high efficiency of the scheme.

Power Smoothing of a Variable-Speed Wind Turbine Generator in Association With the Rotor-Speed-Dependent Gain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Yeonhee; Kang, Moses; Muljadi, Eduard

This paper proposes a power-smoothing scheme for a variable-speed wind turbine generator (WTG) that can smooth out the WTG's fluctuating power caused by varying wind speeds, and thereby keep the system frequency within a narrow range. The proposed scheme employs an additional loop based on the system frequency deviation that operates in conjunction with the maximum power point tracking (MPPT) control loop. Unlike the conventional, fixed-gain scheme, its control gain is modified with the rotor speed. In the proposed scheme, the control gain is determined by considering the ratio of the output of the additional loop to that of themore » MPPT loop. To improve the contribution of the scheme toward maintaining the frequency while ensuring the stable operation of WTGs, in the low rotor speed region, the ratio is set to be proportional to the rotor speed; in the high rotor speed region, the ratio remains constant. The performance of the proposed scheme is investigated under varying wind conditions for the IEEE 14-bus system. The simulation results demonstrate that the scheme successfully operates regardless of the output power fluctuation of a WTG by adjusting the gain with the rotor speed, and thereby improves the frequency-regulating capability of a WTG.« less

MLP based LOGSIG transfer function for solar generation monitoring

NASA Astrophysics Data System (ADS)

Hashim, Fakroul Ridzuan; Din, Muhammad Faiz Md; Ahmad, Shahril; Arif, Farah Khairunnisa; Rizman, Zairi Ismael

2018-02-01

Solar panel is one of the renewable energy that can reduce the environmental pollution and have a wide potential of application. The exact solar prediction model will give a big impact on the management of solar power plants and the design of solar energy systems. This paper attempts to use Multilayer Perceptron (MLP) neural network based transfer function. The MLP network can be used to calculate the temperature module (TM) in Malaysia. This can be done by simulating the collected data of four weather variables which are the ambient temperature (TA), local wind speed (VW), solar radiation flux (GT) and the relative humidity (RH) as the input into the neural network. The transfer function will be applied to the 14 types of training. Finally, an equation from the best training algorithm will be deduced to calculate the temperature module based on the input of weather variables in Malaysia.

Generating partially correlated noise--a comparison of methods.

PubMed

Hartmann, William M; Cho, Yun Jin

2011-07-01

There are three standard methods for generating two channels of partially correlated noise: the two-generator method, the three-generator method, and the symmetric-generator method. These methods allow an experimenter to specify a target cross correlation between the two channels, but actual generated noises show statistical variability around the target value. Numerical experiments were done to compare the variability for those methods as a function of the number of degrees of freedom. The results of the experiments quantify the stimulus uncertainty in diverse binaural psychoacoustical experiments: incoherence detection, perceived auditory source width, envelopment, noise localization/lateralization, and the masking level difference. The numerical experiments found that when the elemental generators have unequal powers, the different methods all have similar variability. When the powers are constrained to be equal, the symmetric-generator method has much smaller variability than the other two. © 2011 Acoustical Society of America

Improvement of SET variability in TaO x based resistive RAM devices

NASA Astrophysics Data System (ADS)

Schönhals, Alexander; Waser, Rainer; Wouters, Dirk J.

2017-11-01

Improvement or at least control of variability is one of the key challenges for Redox based resistive switching memory technology. In this paper, we investigate the impact of a serial resistor as a voltage divider on the SET variability in Pt/Ta2O5/Ta/Pt nano crossbar devices. A partial RESET in a competing complementary switching (CS) mode is identified as a possible failure mechanism of bipolar switching SET in our devices. Due to a voltage divider effect, serial resistance value shows unequal impact on switching voltages of both modes which allows for a selective suppression of the CS mode. The impact of voltage divider on SET variability is demonstrated. A combination of appropriate write voltage and serial resistance allows for a significant improvement of the SET variability.

Sparsity-based fast CGH generation using layer-based approach for 3D point cloud model

NASA Astrophysics Data System (ADS)

Kim, Hak Gu; Jeong, Hyunwook; Ro, Yong Man

2017-03-01

Computer generated hologram (CGH) is becoming increasingly important for a 3-D display in various applications including virtual reality. In the CGH, holographic fringe patterns are generated by numerically calculating them on computer simulation systems. However, a heavy computational cost is required to calculate the complex amplitude on CGH plane for all points of 3D objects. This paper proposes a new fast CGH generation based on the sparsity of CGH for 3D point cloud model. The aim of the proposed method is to significantly reduce computational complexity while maintaining the quality of the holographic fringe patterns. To that end, we present a new layer-based approach for calculating the complex amplitude distribution on the CGH plane by using sparse FFT (sFFT). We observe the CGH of a layer of 3D objects is sparse so that dominant CGH is rapidly generated from a small set of signals by sFFT. Experimental results have shown that the proposed method is one order of magnitude faster than recently reported fast CGH generation.

Generating Variable and Random Schedules of Reinforcement Using Microsoft Excel Macros

ERIC Educational Resources Information Center

Bancroft, Stacie L.; Bourret, Jason C.

2008-01-01

Variable reinforcement schedules are used to arrange the availability of reinforcement following varying response ratios or intervals of time. Random reinforcement schedules are subtypes of variable reinforcement schedules that can be used to arrange the availability of reinforcement at a constant probability across number of responses or time.…

Connecting Lines of Research on Task Model Variables, Automatic Item Generation, and Learning Progressions in Game-Based Assessment

ERIC Educational Resources Information Center

Graf, Edith Aurora

2014-01-01

In "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games," Almond, Kim, Velasquez, and Shute have prepared a thought-provoking piece contrasting the roles of task model variables in a traditional assessment of mathematics word problems to their roles in "Newton's Playground," a game designed…

Wind Velocity and Position Sensor-less Operation for PMSG Wind Generator

NASA Astrophysics Data System (ADS)

Senjyu, Tomonobu; Tamaki, Satoshi; Urasaki, Naomitsu; Uezato, Katsumi; Funabashi, Toshihisa; Fujita, Hideki

Electric power generation using non-conventional sources is receiving considerable attention throughout the world. Wind energy is one of the available non-conventional energy sources. Electrical power generation using wind energy is possible in two ways, viz. constant speed operation and variable speed operation using power electronic converters. Variable speed power generation is attractive, because maximum electric power can be generated at all wind velocities. However, this system requires a rotor speed sensor, for vector control purpose, which increases the cost of the system. To alleviate the need of rotor speed sensor in vector control, we propose a new sensor-less control of PMSG (Permanent Magnet Synchronous Generator) based on the flux linkage. We can estimate the rotor position using the estimated flux linkage. We use a first-order lag compensator to obtain the flux linkage. Furthermore‚we estimate wind velocity and rotation speed using a observer. The effectiveness of the proposed method is demonstrated thorough simulation results.

A technique for generating phase-space-based Monte Carlo beamlets in radiotherapy applications.

PubMed

Bush, K; Popescu, I A; Zavgorodni, S

2008-09-21

As radiotherapy treatment planning moves toward Monte Carlo (MC) based dose calculation methods, the MC beamlet is becoming an increasingly common optimization entity. At present, methods used to produce MC beamlets have utilized a particle source model (PSM) approach. In this work we outline the implementation of a phase-space-based approach to MC beamlet generation that is expected to provide greater accuracy in beamlet dose distributions. In this approach a standard BEAMnrc phase space is sorted and divided into beamlets with particles labeled using the inheritable particle history variable. This is achieved with the use of an efficient sorting algorithm, capable of sorting a phase space of any size into the required number of beamlets in only two passes. Sorting a phase space of five million particles can be achieved in less than 8 s on a single-core 2.2 GHz CPU. The beamlets can then be transported separately into a patient CT dataset, producing separate dose distributions (doselets). Methods for doselet normalization and conversion of dose to absolute units of Gy for use in intensity modulated radiation therapy (IMRT) plan optimization are also described.

Addressing sub-scan variability of tundra snow properties in ground-based Ku- and X-band scatterometer observations

NASA Astrophysics Data System (ADS)

King, J. M.; Kasurak, A.; Kelly, R. E.; Duguay, C. R.; Derksen, C.; Rutter, N.; Sandells, M.; Watts, T.

2012-12-01

these measurements, continuous surfaces were generated to represent the observed snow target. Two snow pits were also completed within the field of view, quantifying vertical variability in density, permittivity, temperature, grain size, and stratigraphy. A new post-processing method is applied to divide the previously aggregated scatterometer observations into smaller sub-sets, which are then co-located with the physical snow observations. Sub-scan backscatter coefficients and their relationship to tundra snowpack parameters are then explored. The results presented here provide quantitative methods relevant to the radar observation science of snow and, therefore, to potential future space-borne missions such as the Cold Regions Hydrology High-resolution Observatory (CoReH2O), a candidate European Space Agency Earth Explorer mission. Moreover, this paper provides guidelines for future studies exploring ground-based scatterometer observations of tundra snow.

The guitar chord-generating algorithm based on complex network

NASA Astrophysics Data System (ADS)

Ren, Tao; Wang, Yi-fan; Du, Dan; Liu, Miao-miao; Siddiqi, Awais

2016-02-01

This paper aims to generate chords for popular songs automatically based on complex network. Firstly, according to the characteristics of guitar tablature, six chord networks of popular songs by six pop singers are constructed and the properties of all networks are concluded. By analyzing the diverse chord networks, the accompaniment regulations and features are shown, with which the chords can be generated automatically. Secondly, in terms of the characteristics of popular songs, a two-tiered network containing a verse network and a chorus network is constructed. With this network, the verse and chorus can be composed respectively with the random walk algorithm. Thirdly, the musical motif is considered for generating chords, with which the bad chord progressions can be revised. This method can make the accompaniments sound more melodious. Finally, a popular song is chosen for generating chords and the new generated accompaniment sounds better than those done by the composers.

Autonomously generating operations sequences for a Mars Rover using AI-based planning

NASA Technical Reports Server (NTRS)

Sherwood, Rob; Mishkin, Andrew; Estlin, Tara; Chien, Steve; Backes, Paul; Cooper, Brian; Maxwell, Scott; Rabideau, Gregg

2001-01-01

This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from highlevel science and engineering activities. This prototype is based on ASPEN, the Automated Scheduling and Planning Environment. This Artificial Intelligence (AI) based planning and scheduling system will automatically generate a command sequence that will execute within resource constraints and satisfy flight rules.

Fault-tolerant measurement-based quantum computing with continuous-variable cluster states.

PubMed

Menicucci, Nicolas C

2014-03-28

A long-standing open question about Gaussian continuous-variable cluster states is whether they enable fault-tolerant measurement-based quantum computation. The answer is yes. Initial squeezing in the cluster above a threshold value of 20.5 dB ensures that errors from finite squeezing acting on encoded qubits are below the fault-tolerance threshold of known qubit-based error-correcting codes. By concatenating with one of these codes and using ancilla-based error correction, fault-tolerant measurement-based quantum computation of theoretically indefinite length is possible with finitely squeezed cluster states.

Certifying Auto-Generated Flight Code

NASA Technical Reports Server (NTRS)

Denney, Ewen

2008-01-01

Model-based design and automated code generation are being used increasingly at NASA. Many NASA projects now use MathWorks Simulink and Real-Time Workshop for at least some of their modeling and code development. However, there are substantial obstacles to more widespread adoption of code generators in safety-critical domains. Since code generators are typically not qualified, there is no guarantee that their output is correct, and consequently the generated code still needs to be fully tested and certified. Moreover, the regeneration of code can require complete recertification, which offsets many of the advantages of using a generator. Indeed, manual review of autocode can be more challenging than for hand-written code. Since the direct V&V of code generators is too laborious and complicated due to their complex (and often proprietary) nature, we have developed a generator plug-in to support the certification of the auto-generated code. Specifically, the AutoCert tool supports certification by formally verifying that the generated code is free of different safety violations, by constructing an independently verifiable certificate, and by explaining its analysis in a textual form suitable for code reviews. The generated documentation also contains substantial tracing information, allowing users to trace between model, code, documentation, and V&V artifacts. This enables missions to obtain assurance about the safety and reliability of the code without excessive manual V&V effort and, as a consequence, eases the acceptance of code generators in safety-critical contexts. The generation of explicit certificates and textual reports is particularly well-suited to supporting independent V&V. The primary contribution of this approach is the combination of human-friendly documentation with formal analysis. The key technical idea is to exploit the idiomatic nature of auto-generated code in order to automatically infer logical annotations. The annotation inference algorithm

Solar energy thermally powered electrical generating system

NASA Technical Reports Server (NTRS)

Owens, William R. (Inventor)

1989-01-01

A thermally powered electrical generating system for use in a space vehicle is disclosed. The rate of storage in a thermal energy storage medium is controlled by varying the rate of generation and dissipation of electrical energy in a thermally powered electrical generating system which is powered from heat stored in the thermal energy storage medium without exceeding a maximum quantity of heat. A control system (10) varies the rate at which electrical energy is generated by the electrical generating system and the rate at which electrical energy is consumed by a variable parasitic electrical load to cause storage of an amount of thermal energy in the thermal energy storage system at the end of a period of insolation which is sufficient to satisfy the scheduled demand for electrical power to be generated during the next period of eclipse. The control system is based upon Kalman filter theory.

Characteristics of tuberculosis patients who generate secondary cases.

PubMed

Rodrigo, T; Caylà, J A; García de Olalla, P; Galdós-Tangüis, H; Jansà, J M; Miranda, P; Brugal, T

1997-08-01

To determine the characteristics of smear positive tuberculosis (TB) patients who generate secondary TB cases. Those smear positive TB patients detected by the Barcelona Tuberculosis Program between 1990-1993, and for whom contact studies had been performed, were studied. We analyzed the predictive role of the variables: age, sex, intravenous drug use (IVDU), the presence of the acquired immune deficiency syndrome (AIDS), human immunodeficiency virus (HIV) infection, radiology pattern, district of residence, history of imprisonment, alcoholism, smoking, history of TB, treatment compliance and the number of secondary cases generated. Statistical analysis was based on the logistic regression model, calculating the odds ratios (OR) with 95% confidence intervals (CI). Of the 1079 patients studied, 78 (7.2%) had generated only one secondary case, and 30 (2.8%) two or more. The variables associated with generating two or more secondary cases were: IVDU (P < 0.001; OR = 4.06; CI: 1.80-9.15), cavitary radiology pattern (P = 0.002; OR = 3.69; CI: 1.62-8.43), and age (P = 0.016; OR = 0.98; CI: 0.96-0.99). When we examined those who had generated one or more secondary cases, the following variables were significant: IVDU (P = 0.043; OR = 1.75; CI: 1.02-3.02), cavitary radiology pattern (P < 0.001; OR = 3.07; CI: 1.98-4.77) and age (P < 0.001; OR = 0.98; CI: 0.97-0.99). The study of the contacts of smear positive TB patients allows us to detect an important number of secondary cases. Young adults, those with cavitary radiology pattern, and IVDU are more likely to generate secondary cases.

Knowledge-based reasoning in the Paladin tactical decision generation system

NASA Technical Reports Server (NTRS)

Chappell, Alan R.

1993-01-01

A real-time tactical decision generation system for air combat engagements, Paladin, has been developed. A pilot's job in air combat includes tasks that are largely symbolic. These symbolic tasks are generally performed through the application of experience and training (i.e. knowledge) gathered over years of flying a fighter aircraft. Two such tasks, situation assessment and throttle control, are identified and broken out in Paladin to be handled by specialized knowledge based systems. Knowledge pertaining to these tasks is encoded into rule-bases to provide the foundation for decisions. Paladin uses a custom built inference engine and a partitioned rule-base structure to give these symbolic results in real-time. This paper provides an overview of knowledge-based reasoning systems as a subset of rule-based systems. The knowledge used by Paladin in generating results as well as the system design for real-time execution is discussed.

Power Smoothing and MPPT for Grid-connected Wind Power Generation with Doubly Fed Induction Generator

NASA Astrophysics Data System (ADS)

Kai, Takaaki; Tanaka, Yuji; Kaneda, Hirotoshi; Kobayashi, Daichi; Tanaka, Akio

Recently, doubly fed induction generator (DFIG) and synchronous generator are mostly applied for wind power generation, and variable speed control and power factor control are executed for high efficiently for wind energy capture and high quality for power system voltage. In variable speed control, a wind speed or a generator speed is used for maximum power point tracking. However, performances of a wind generation power fluctuation due to wind speed variation have not yet investigated for those controls. The authors discuss power smoothing by those controls for the DFIG inter-connected to 6.6kV distribution line. The performances are verified using power system simulation software PSCAD/EMTDC for actual wind speed data and are examined from an approximate equation of wind generation power fluctuation for wind speed variation.

Generation of 103 fs mode-locked pulses by a gain linewidth-variable Nd,Y:CaF2 disordered crystal.

PubMed

Qin, Z P; Xie, G Q; Ma, J; Ge, W Y; Yuan, P; Qian, L J; Su, L B; Jiang, D P; Ma, F K; Zhang, Q; Cao, Y X; Xu, J

2014-04-01

We have demonstrated a diode-pumped passively mode-locked femtosecond Nd,Y:CaF2 disordered crystal laser for the first time to our knowledge. By choosing appropriate Y-doping concentration, a broad fluorescence linewidth of 31 nm has been obtained from the gain linewidth-variable Nd,Y:CaF2 crystal. With the Nd,Y:CaF2 disordered crystal as gain medium, the mode-locked laser generated pulses with pulse duration as short as 103 fs, average output power of 89 mW, and repetition rate of 100 MHz. To our best knowledge, this is the shortest pulse generated from Nd-doped crystal lasers so far. The research results show that the Nd,Y:CaF2 disordered crystal will be a potential alternative as gain medium of repetitive chirped pulse amplification for high-peak-power lasers.

Differentially Variable Component Analysis (dVCA): Identifying Multiple Evoked Components using Trial-to-Trial Variability

NASA Technical Reports Server (NTRS)

Knuth, Kevin H.; Shah, Ankoor S.; Truccolo, Wilson; Ding, Ming-Zhou; Bressler, Steven L.; Schroeder, Charles E.

2003-01-01

Electric potentials and magnetic fields generated by ensembles of synchronously active neurons in response to external stimuli provide information essential to understanding the processes underlying cognitive and sensorimotor activity. Interpreting recordings of these potentials and fields is difficult as each detector records signals simultaneously generated by various regions throughout the brain. We introduce the differentially Variable Component Analysis (dVCA) algorithm, which relies on trial-to-trial variability in response amplitude and latency to identify multiple components. Using simulations we evaluate the importance of response variability to component identification, the robustness of dVCA to noise, and its ability to characterize single-trial data. Finally, we evaluate the technique using visually evoked field potentials recorded at incremental depths across the layers of cortical area VI, in an awake, behaving macaque monkey.

Fuzzy variable impedance control based on stiffness identification for human-robot cooperation

NASA Astrophysics Data System (ADS)

Mao, Dachao; Yang, Wenlong; Du, Zhijiang

2017-06-01

This paper presents a dynamic fuzzy variable impedance control algorithm for human-robot cooperation. In order to estimate the intention of human for co-manipulation, a fuzzy inference system is set up to adjust the impedance parameter. Aiming at regulating the output fuzzy universe based on the human arm’s stiffness, an online stiffness identification method is developed. A drag interaction task is conducted on a 5-DOF robot with variable impedance control. Experimental results demonstrate that the proposed algorithm is superior.

Assess and Predict Automatic Generation Control Performances for Thermal Power Generation Units Based on Modeling Techniques

NASA Astrophysics Data System (ADS)

Zhao, Yan; Yang, Zijiang; Gao, Song; Liu, Jinbiao

2018-02-01

Automatic generation control(AGC) is a key technology to maintain real time power generation and load balance, and to ensure the quality of power supply. Power grids require each power generation unit to have a satisfactory AGC performance, being specified in two detailed rules. The two rules provide a set of indices to measure the AGC performance of power generation unit. However, the commonly-used method to calculate these indices is based on particular data samples from AGC responses and will lead to incorrect results in practice. This paper proposes a new method to estimate the AGC performance indices via system identification techniques. In addition, a nonlinear regression model between performance indices and load command is built in order to predict the AGC performance indices. The effectiveness of the proposed method is validated through industrial case studies.

Design Optimization of Gas Generator Hybrid Propulsion Boosters

NASA Technical Reports Server (NTRS)

Weldon, Vincent; Phillips, Dwight; Fink, Larry

1990-01-01

A methodology used in support of a study for NASA/MSFC to optimize the design of gas generator hybrid propulsion booster for uprating the National Space Transportation System (NSTS) is presented. The objective was to compare alternative configurations for this booster approach, optimizing each candidate concept on different bases, in order to develop data for a trade table on which a final decision was based. The methodology is capable of processing a large number of independent and dependent variables, adjusting the overall subsystems characteristics to arrive at a best compromise integrated design to meet various specific optimization criteria subject to selected constraints. For each system considered, a detailed weight statement was generated along with preliminary cost and reliability estimates.

On the design of henon and logistic map-based random number generator

NASA Astrophysics Data System (ADS)

Magfirawaty; Suryadi, M. T.; Ramli, Kalamullah

2017-10-01

The key sequence is one of the main elements in the cryptosystem. True Random Number Generators (TRNG) method is one of the approaches to generating the key sequence. The randomness source of the TRNG divided into three main groups, i.e. electrical noise based, jitter based and chaos based. The chaos based utilizes a non-linear dynamic system (continuous time or discrete time) as an entropy source. In this study, a new design of TRNG based on discrete time chaotic system is proposed, which is then simulated in LabVIEW. The principle of the design consists of combining 2D and 1D chaotic systems. A mathematical model is implemented for numerical simulations. We used comparator process as a harvester method to obtain the series of random bits. Without any post processing, the proposed design generated random bit sequence with high entropy value and passed all NIST 800.22 statistical tests.

Impact of region contouring variability on image-based focal therapy evaluation

NASA Astrophysics Data System (ADS)

Gibson, Eli; Donaldson, Ian A.; Shah, Taimur T.; Hu, Yipeng; Ahmed, Hashim U.; Barratt, Dean C.

2016-03-01

Motivation: Focal therapy is an emerging low-morbidity treatment option for low-intermediate risk prostate cancer; however, challenges remain in accurately delivering treatment to specified targets and determining treatment success. Registered multi-parametric magnetic resonance imaging (MPMRI) acquired before and after treatment can support focal therapy evaluation and optimization; however, contouring variability, when defining the prostate, the clinical target volume (CTV) and the ablation region in images, reduces the precision of quantitative image-based focal therapy evaluation metrics. To inform the interpretation and clarify the limitations of such metrics, we investigated inter-observer contouring variability and its impact on four metrics. Methods: Pre-therapy and 2-week-post-therapy standard-of-care MPMRI were acquired from 5 focal cryotherapy patients. Two clinicians independently contoured, on each slice, the prostate (pre- and post-treatment) and the dominant index lesion CTV (pre-treatment) in the T2-weighted MRI, and the ablated region (post-treatment) in the dynamic-contrast- enhanced MRI. For each combination of clinician contours, post-treatment images were registered to pre-treatment images using a 3D biomechanical-model-based registration of prostate surfaces, and four metrics were computed: the proportion of the target tissue region that was ablated and the target:ablated region volume ratio for each of two targets (the CTV and an expanded planning target volume). Variance components analysis was used to measure the contribution of each type of contour to the variance in the therapy evaluation metrics. Conclusions: 14-23% of evaluation metric variance was attributable to contouring variability (including 6-12% from ablation region contouring); reducing this variability could improve the precision of focal therapy evaluation metrics.

Kernel-Based Measure of Variable Importance for Genetic Association Studies.

PubMed

Gallego, Vicente; Luz Calle, M; Oller, Ramon

2017-06-17

The identification of genetic variants that are associated with disease risk is an important goal of genetic association studies. Standard approaches perform univariate analysis where each genetic variant, usually Single Nucleotide Polymorphisms (SNPs), is tested for association with disease status. Though many genetic variants have been identified and validated so far using this univariate approach, for most complex diseases a large part of their genetic component is still unknown, the so called missing heritability. We propose a Kernel-based measure of variable importance (KVI) that provides the contribution of a SNP, or a group of SNPs, to the joint genetic effect of a set of genetic variants. KVI can be used for ranking genetic markers individually, sets of markers that form blocks of linkage disequilibrium or sets of genetic variants that lie in a gene or a genetic pathway. We prove that, unlike the univariate analysis, KVI captures the relationship with other genetic variants in the analysis, even when measured at the individual level for each genetic variable separately. This is specially relevant and powerful for detecting genetic interactions. We illustrate the results with data from an Alzheimer's disease study and show through simulations that the rankings based on KVI improve those rankings based on two measures of importance provided by the Random Forest. We also prove with a simulation study that KVI is very powerful for detecting genetic interactions.

Robustness of observation-based decadal sea level variability in the Indo-Pacific Ocean

NASA Astrophysics Data System (ADS)

Nidheesh, A. G.; Lengaigne, M.; Vialard, J.; Izumo, T.; Unnikrishnan, A. S.; Meyssignac, B.; Hamlington, B.; de Boyer Montegut, C.

2017-07-01

We examine the consistency of Indo-Pacific decadal sea level variability in 10 gridded, observation-based sea level products for the 1960-2010 period. Decadal sea level variations are robust in the Pacific, with more than 50% of variance explained by decadal modulation of two flavors of El Niño-Southern Oscillation (classical ENSO and Modoki). Amplitude of decadal sea level variability is weaker in the Indian Ocean than in the Pacific. All data sets indicate a transmission of decadal sea level signals from the western Pacific to the northwest Australian coast through the Indonesian throughflow. The southern tropical Indian Ocean sea level variability is associated with decadal modulations of ENSO in reconstructions but not in reanalyses or in situ data set. The Pacific-independent Indian Ocean decadal sea level variability is not robust but tends to be maximum in the southwestern tropical Indian Ocean. The inconsistency of Indian Ocean decadal variability across the sea level products calls for caution in making definitive conclusions on decadal sea level variability in this basin.

Optical testing of aspheres based on photochromic computer-generated holograms

NASA Astrophysics Data System (ADS)

Pariani, Giorgio; Bianco, Andrea; Bertarelli, Chiara; Spanó, Paolo; Molinari, Emilio

2010-07-01

Aspherical optics are widely used in modern optical telescopes and instrumentation because of their ability to reduce aberrations with a simple optical system. Testing their optical quality through null interferometry is not trivial as reference optics are not available. Computer-Generated Holograms (CGHs) are efficient devices that allow to generate a well-defined optical wavefront. We developed rewritable Computer Generated Holograms for the interferometric test of aspheres based on photochromic layers. These photochromic holograms are cost-effective and the method of production does not need any post exposure process.

Raster Scan Computer Image Generation (CIG) System Based On Refresh Memory

NASA Astrophysics Data System (ADS)

Dichter, W.; Doris, K.; Conkling, C.

1982-06-01

A full color, Computer Image Generation (CIG) raster visual system has been developed which provides a high level of training sophistication by utilizing advanced semiconductor technology and innovative hardware and firmware techniques. Double buffered refresh memory and efficient algorithms eliminate the problem of conventional raster line ordering by allowing the generated image to be stored in a random fashion. Modular design techniques and simplified architecture provide significant advantages in reduced system cost, standardization of parts, and high reliability. The major system components are a general purpose computer to perform interfacing and data base functions; a geometric processor to define the instantaneous scene image; a display generator to convert the image to a video signal; an illumination control unit which provides final image processing; and a CRT monitor for display of the completed image. Additional optional enhancements include texture generators, increased edge and occultation capability, curved surface shading, and data base extensions.

Review on Variable Emissivity Materials and Devices Based on Smart Chromism

NASA Astrophysics Data System (ADS)

Lang, FengPei; Wang, Hao; Zhang, ShengJun; Liu, JingBing; Yan, Hui

2018-01-01

Variable emissivity material (VEM) can dynamically vary its emissivity and infrared radiation under certain conditions, which may find potential applications in infrared stealth/camouflage, solar thermal collector, spacecraft thermal control, and smart energy-saving windows. In this paper, the variable emissivity materials and devices based on electrochromism and thermochromism are introduced. The basic principle and present status of the research in these fields are overviewed. Four kinds of representative VEMs are extensively summarized, which are tungsten trioxides (WO3), conducting polymers (CPs), perovskite oxides (A_{1-{x}}B_{{x}}MO3), and vanadium dioxide (VO2). Finally, specific issues confronted with electrochromic and thermochromic materials and devices are prospected.

TermGenie - a web-application for pattern-based ontology class generation.

PubMed

Dietze, Heiko; Berardini, Tanya Z; Foulger, Rebecca E; Hill, David P; Lomax, Jane; Osumi-Sutherland, David; Roncaglia, Paola; Mungall, Christopher J

2014-01-01

Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

Adaptive Critic-based Neurofuzzy Controller for the Steam Generator Water Level

NASA Astrophysics Data System (ADS)

Fakhrazari, Amin; Boroushaki, Mehrdad

2008-06-01

In this paper, an adaptive critic-based neurofuzzy controller is presented for water level regulation of nuclear steam generators. The problem has been of great concern for many years as the steam generator is a highly nonlinear system showing inverse response dynamics especially at low operating power levels. Fuzzy critic-based learning is a reinforcement learning method based on dynamic programming. The only information available for the critic agent is the system feedback which is interpreted as the last action the controller has performed in the previous state. The signal produced by the critic agent is used alongside the backpropagation of error algorithm to tune online conclusion parts of the fuzzy inference rules. The critic agent here has a proportional-derivative structure and the fuzzy rule base has nine rules. The proposed controller shows satisfactory transient responses, disturbance rejection and robustness to model uncertainty. Its simple design procedure and structure, nominates it as one of the suitable controller designs for the steam generator water level control in nuclear power plant industry.

Variable Asymmetric Chains in Transition Metal Oxyfluorides: Structure-Second-Harmonic-Generation Property Relationships.

PubMed

Ahmed, Belal; Jo, Hongil; Oh, Seung-Jin; Ok, Kang Min

2018-05-15

Four novel transition metal oxyfluorides, [Zn(pz) 3 ][MoO 2 F 4 ]·0.1H 2 O (1), [Zn(pz) 2 F 2 ][Zn(pz) 3 ] 2 [WO 2 F 4 ] 2 (2), [Cd(pz) 4 ][Cd(pz) 4 (H 2 O)][MoO 2 F 4 ] 2 ·0.625H 2 O (3), and [Zn(mpz) 3 ] 2 [MoO 2 F 4 ] 2 (4) (pz = pyrazole; mpz = 3-methyl pyrazole) have been synthesized. Compounds 1 and 4 contain helical chains. Compound 2 accommodates zigzag chains, and compound 3 has quasi-one-dimensional linear chains. The variable chain structures are found to be attributable to the different structure-directing anionic groups and hydrogen bonding interactions. Compound 4 crystallized in the noncentrosymmetric (NCS) polar space group, Pna2 1 , is nonphase-matchable (Type I), and reveals a moderate second-harmonic-generation (SHG) efficiency (10 × α-SiO 2 ). The observed SHG efficiency of compound 4 is due to the small net polarization occurring from the arrangement of ZnN 3 F 2 trigonal bipyramids. Spectroscopic and thermal characterizations along with calculations for the title materials are reported.

A New Targeted CFTR Mutation Panel Based on Next-Generation Sequencing Technology.

PubMed

Lucarelli, Marco; Porcaro, Luigi; Biffignandi, Alice; Costantino, Lucy; Giannone, Valentina; Alberti, Luisella; Bruno, Sabina Maria; Corbetta, Carlo; Torresani, Erminio; Colombo, Carla; Seia, Manuela

2017-09-01

Searching for mutations in the cystic fibrosis transmembrane conductance regulator gene (CFTR) is a key step in the diagnosis of and neonatal and carrier screening for cystic fibrosis (CF), and it has implications for prognosis and personalized therapy. The large number of mutations and genetic and phenotypic variability make this search a complex task. Herein, we developed, validated, and tested a laboratory assay for an extended search for mutations in CFTR using a next-generation sequencing-based method, with a panel of 188 CFTR mutations customized for the Italian population. Overall, 1426 dried blood spots from neonatal screening, 402 genomic DNA samples from various origins, and 1138 genomic DNA samples from patients with CF were analyzed. The assay showed excellent analytical and diagnostic operative characteristics. We identified and experimentally validated 159 (of 188) CFTR mutations. The assay achieved detection rates of 95.0% and 95.6% in two large-scale case series of CF patients from central and northern Italy, respectively. These detection rates are among the highest reported so far with a genetic test for CF based on a mutation panel. This assay appears to be well suited for diagnostics, neonatal and carrier screening, and assisted reproduction, and it represents a considerable advantage in CF genetic counseling. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Novel layered clustering-based approach for generating ensemble of classifiers.

PubMed

Rahman, Ashfaqur; Verma, Brijesh

2011-05-01

This paper introduces a novel concept for creating an ensemble of classifiers. The concept is based on generating an ensemble of classifiers through clustering of data at multiple layers. The ensemble classifier model generates a set of alternative clustering of a dataset at different layers by randomly initializing the clustering parameters and trains a set of base classifiers on the patterns at different clusters in different layers. A test pattern is classified by first finding the appropriate cluster at each layer and then using the corresponding base classifier. The decisions obtained at different layers are fused into a final verdict using majority voting. As the base classifiers are trained on overlapping patterns at different layers, the proposed approach achieves diversity among the individual classifiers. Identification of difficult-to-classify patterns through clustering as well as achievement of diversity through layering leads to better classification results as evidenced from the experimental results.

Ring system-based chemical graph generation for de novo molecular design

NASA Astrophysics Data System (ADS)

Miyao, Tomoyuki; Kaneko, Hiromasa; Funatsu, Kimito

2016-05-01

Generating chemical graphs in silico by combining building blocks is important and fundamental in virtual combinatorial chemistry. A premise in this area is that generated structures should be irredundant as well as exhaustive. In this study, we develop structure generation algorithms regarding combining ring systems as well as atom fragments. The proposed algorithms consist of three parts. First, chemical structures are generated through a canonical construction path. During structure generation, ring systems can be treated as reduced graphs having fewer vertices than those in the original ones. Second, diversified structures are generated by a simple rule-based generation algorithm. Third, the number of structures to be generated can be estimated with adequate accuracy without actual exhaustive generation. The proposed algorithms were implemented in structure generator Molgilla. As a practical application, Molgilla generated chemical structures mimicking rosiglitazone in terms of a two dimensional pharmacophore pattern. The strength of the algorithms lies in simplicity and flexibility. Therefore, they may be applied to various computer programs regarding structure generation by combining building blocks.

Climate variability has a stabilizing effect on the coexistence of prairie grasses

PubMed Central

Adler, Peter B.; HilleRisLambers, Janneke; Kyriakidis, Phaedon C.; Guan, Qingfeng; Levine, Jonathan M.

2006-01-01

How expected increases in climate variability will affect species diversity depends on the role of such variability in regulating the coexistence of competing species. Despite theory linking temporal environmental fluctuations with the maintenance of diversity, the importance of climate variability for stabilizing coexistence remains unknown because of a lack of appropriate long-term observations. Here, we analyze three decades of demographic data from a Kansas prairie to demonstrate that interannual climate variability promotes the coexistence of three common grass species. Specifically, we show that (i) the dynamics of the three species satisfy all requirements of “storage effect” theory based on recruitment variability with overlapping generations, (ii) climate variables are correlated with interannual variation in species performance, and (iii) temporal variability increases low-density growth rates, buffering these species against competitive exclusion. Given that environmental fluctuations are ubiquitous in natural systems, our results suggest that coexistence based on the storage effect may be underappreciated and could provide an important alternative to recent neutral theories of diversity. Field evidence for positive effects of variability on coexistence also emphasizes the need to consider changes in both climate means and variances when forecasting the effects of global change on species diversity. PMID:16908862

A two-stage flow-based intrusion detection model for next-generation networks.

PubMed

Umer, Muhammad Fahad; Sher, Muhammad; Bi, Yaxin

2018-01-01

The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results.

A two-stage flow-based intrusion detection model for next-generation networks

PubMed Central

2018-01-01

The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results. PMID:29329294

Method to implement the CCD timing generator based on FPGA

NASA Astrophysics Data System (ADS)

Li, Binhua; Song, Qian; He, Chun; Jin, Jianhui; He, Lin

2010-07-01

With the advance of the PFPA technology, the design methodology of digital systems is changing. In recent years we develop a method to implement the CCD timing generator based on FPGA and VHDL. This paper presents the principles and implementation skills of the method. Taking a developed camera as an example, we introduce the structure, input and output clocks/signals of a timing generator implemented in the camera. The generator is composed of a top module and a bottom module. The bottom one is made up of 4 sub-modules which correspond to 4 different operation modes. The modules are implemented by 5 VHDL programs. Frame charts of the architecture of these programs are shown in the paper. We also describe implementation steps of the timing generator in Quartus II, and the interconnections between the generator and a Nios soft core processor which is the controller of this generator. Some test results are presented in the end.

Forces and moments generated by the human arm: Variability and control

PubMed Central

Xu, Y; Terekhov, AV; Latash, ML; Zatsiorsky, VM

2012-01-01

This is an exploratory study of the accurate endpoint force vector production by the human arm in isometric conditions. We formulated three common-sense hypotheses and falsified them in the experiment. The subjects (n=10) exerted static forces on the handle in eight directions in a horizontal plane for 25 seconds. The forces were of 4 magnitude levels (10 %, 20%, 30% and 40% of individual MVC). The torsion moment on the handle (grasp moment) was not specified in the instruction. The two force components and the grasp moment were recorded, and the shoulder, elbow, and wrist joint torques were computed. The following main facts were observed: (a) While the grasp moment was not prescribed by the instruction, it was always produced. The moment magnitude and direction depended on the instructed force magnitude and direction. (b) The within-trial angular variability of the exerted force vector (angular precision) did not depend on the target force magnitude (a small negative correlation was observed). (c) Across the target force directions, the variability of the exerted force magnitude and directional variability exhibited opposite trends: In the directions where the variability of force magnitude was maximal, the directional variability was minimal and vice versa. (d) The time profiles of joint torques in the trials were always positively correlated, even for the force directions where flexion torque was produced at one joint and extension torque was produced at the other joint. (e) The correlations between the grasp moment and the wrist torque were negative across the tasks and positive within the individual trials. (f) In static serial kinematic chains, the pattern of the joint torques distribution could not be explained by an optimization cost function additive with respect to the torques. Plans for several future experiments have been suggested. PMID:23080084

Realistic facial animation generation based on facial expression mapping

NASA Astrophysics Data System (ADS)

Yu, Hui; Garrod, Oliver; Jack, Rachael; Schyns, Philippe

2014-01-01

Facial expressions reflect internal emotional states of a character or in response to social communications. Though much effort has been taken to generate realistic facial expressions, it still remains a challenging topic due to human being's sensitivity to subtle facial movements. In this paper, we present a method for facial animation generation, which reflects true facial muscle movements with high fidelity. An intermediate model space is introduced to transfer captured static AU peak frames based on FACS to the conformed target face. And then dynamic parameters derived using a psychophysics method is integrated to generate facial animation, which is assumed to represent natural correlation of multiple AUs. Finally, the animation sequence in the intermediate model space is mapped to the target face to produce final animation.

Climate Change Impact Assessment in Pacific North West Using Copula based Coupling of Temperature and Precipitation variables

NASA Astrophysics Data System (ADS)

Qin, Y.; Rana, A.; Moradkhani, H.

2014-12-01

The multi downscaled-scenario products allow us to better assess the uncertainty of the changes/variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions (PDFs), of both the climatic variables, might help better understand the interdependence of the two, and thus in-turn help in accessing the future with confidence. Using the joint distribution of temperature and precipitation is also of significant importance in hydrological applications and climate change studies. In the present study, we have used multi-modelled statistically downscaled-scenario ensemble of precipitation and temperature variables using 2 different statistically downscaled climate dataset. The datasets used are, 10 Global Climate Models (GCMs) downscaled products from CMIP5 daily dataset, namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, leading to 2 ensemble time series from 20 GCM products. Thereafter the ensemble PDFs of both precipitation and temperature is evaluated for summer, winter, and yearly periods for all the 10 sub-basins across Columbia River Basin (CRB). Eventually, Copula is applied to establish the joint distribution of two variables enabling users to model the joint behavior of the variables with any level of correlation and dependency. Moreover, the probabilistic distribution helps remove the limitations on marginal distributions of variables in question. The joint distribution is then used to estimate the change trends of the joint precipitation and temperature in the current and future, along with estimation of the probabilities of the given change. Results have indicated towards varied change trends of the joint distribution of, summer, winter, and yearly time scale, respectively in all 10 sub-basins. Probabilities of changes, as estimated

Quantum random number generator based on quantum nature of vacuum fluctuations

NASA Astrophysics Data System (ADS)

Ivanova, A. E.; Chivilikhin, S. A.; Gleim, A. V.

2017-11-01

Quantum random number generator (QRNG) allows obtaining true random bit sequences. In QRNG based on quantum nature of vacuum, optical beam splitter with two inputs and two outputs is normally used. We compare mathematical descriptions of spatial beam splitter and fiber Y-splitter in the quantum model for QRNG, based on homodyne detection. These descriptions were identical, that allows to use fiber Y-splitters in practical QRNG schemes, simplifying the setup. Also we receive relations between the input radiation and the resulting differential current in homodyne detector. We experimentally demonstrate possibility of true random bits generation by using QRNG based on homodyne detection with Y-splitter.

Sleep Quality Estimation based on Chaos Analysis for Heart Rate Variability

NASA Astrophysics Data System (ADS)

Fukuda, Toshio; Wakuda, Yuki; Hasegawa, Yasuhisa; Arai, Fumihito; Kawaguchi, Mitsuo; Noda, Akiko

In this paper, we propose an algorithm to estimate sleep quality based on a heart rate variability using chaos analysis. Polysomnography(PSG) is a conventional and reliable system to diagnose sleep disorder and to evaluate its severity and therapeatic effect, by estimating sleep quality based on multiple channels. However, a recording process requires a lot of time and a controlled environment for measurement and then an analyzing process of PSG data is hard work because the huge sensed data should be manually evaluated. On the other hand, it is focused that some people make a mistake or cause an accident due to lost of regular sleep and of homeostasis these days. Therefore a simple home system for checking own sleep is required and then the estimation algorithm for the system should be developed. Therefore we propose an algorithm to estimate sleep quality based only on a heart rate variability which can be measured by a simple sensor such as a pressure sensor and an infrared sensor in an uncontrolled environment, by experimentally finding the relationship between chaos indices and sleep quality. The system including the estimation algorithm can inform patterns and quality of own daily sleep to a user, and then the user can previously arranges his life schedule, pays more attention based on sleep results and consult with a doctor.

Continuously-Variable Positive-Mesh Power Transmission

NASA Technical Reports Server (NTRS)

Johnson, J. L.

1982-01-01

Proposed transmission with continuously-variable speed ratio couples two mechanical trigonometric-function generators. Transmission is expected to handle higher loads than conventional variable-pulley drives; and, unlike variable pulley, positive traction through entire drive train with no reliance on friction to transmit power. Able to vary speed continuously through zero and into reverse. Possible applications in instrumentation where drive-train slippage cannot be tolerated.

Generating temporal model using climate variables for the prediction of dengue cases in Subang Jaya, Malaysia

PubMed Central

Dom, Nazri Che; Hassan, A Abu; Latif, Z Abd; Ismail, Rodziah

2013-01-01

Objective To develop a forecasting model for the incidence of dengue cases in Subang Jaya using time series analysis. Methods The model was performed using the Autoregressive Integrated Moving Average (ARIMA) based on data collected from 2005 to 2010. The fitted model was then used to predict dengue incidence for the year 2010 by extrapolating dengue patterns using three different approaches (i.e. 52, 13 and 4 weeks ahead). Finally cross correlation between dengue incidence and climate variable was computed over a range of lags in order to identify significant variables to be included as external regressor. Results The result of this study revealed that the ARIMA (2,0,0) (0,0,1)52 model developed, closely described the trends of dengue incidence and confirmed the existence of dengue fever cases in Subang Jaya for the year 2005 to 2010. The prediction per period of 4 weeks ahead for ARIMA (2,0,0)(0,0,1)52 was found to be best fit and consistent with the observed dengue incidence based on the training data from 2005 to 2010 (Root Mean Square Error=0.61). The predictive power of ARIMA (2,0,0) (0,0,1)52 is enhanced by the inclusion of climate variables as external regressor to forecast the dengue cases for the year 2010. Conclusions The ARIMA model with weekly variation is a useful tool for disease control and prevention program as it is able to effectively predict the number of dengue cases in Malaysia.

A canonical neural mechanism for behavioral variability

NASA Astrophysics Data System (ADS)

Darshan, Ran; Wood, William E.; Peters, Susan; Leblois, Arthur; Hansel, David

2017-05-01

The ability to generate variable movements is essential for learning and adjusting complex behaviours. This variability has been linked to the temporal irregularity of neuronal activity in the central nervous system. However, how neuronal irregularity actually translates into behavioural variability is unclear. Here we combine modelling, electrophysiological and behavioural studies to address this issue. We demonstrate that a model circuit comprising topographically organized and strongly recurrent neural networks can autonomously generate irregular motor behaviours. Simultaneous recordings of neurons in singing finches reveal that neural correlations increase across the circuit driving song variability, in agreement with the model predictions. Analysing behavioural data, we find remarkable similarities in the babbling statistics of 5-6-month-old human infants and juveniles from three songbird species and show that our model naturally accounts for these `universal' statistics.

Regional frameworks applied to hydrology: can landscape-based frameworks capture the hydrologic variability?

Treesearch

R. McManamay; D. Orth; C. Dolloff; E. Frimpong

2011-01-01

Regional frameworks have been used extensively in recent years to aid in broad-scale management. Widely used landscape-based regional frameworks, such as hydrologic landscape regions (HLRs) and physiographic provinces, may provide predictive tools of hydrologic variability. However, hydrologic-based regional frameworks, created using only streamflow data, are also...

Experimental nonlocality-based randomness generation with nonprojective measurements

NASA Astrophysics Data System (ADS)

Gómez, S.; Mattar, A.; Gómez, E. S.; Cavalcanti, D.; Farías, O. Jiménez; Acín, A.; Lima, G.

2018-04-01

We report on an optical setup generating more than one bit of randomness from one entangled bit (i.e., a maximally entangled state of two qubits). The amount of randomness is certified through the observation of Bell nonlocal correlations. To attain this result we implemented a high-purity entanglement source and a nonprojective three-outcome measurement. Our implementation achieves a gain of 27% of randomness as compared with the standard methods using projective measurements. Additionally, we estimate the amount of randomness certified in a one-sided device-independent scenario, through the observation of Einstein-Podolsky-Rosen steering. Our results prove that nonprojective quantum measurements allow extending the limits for nonlocality-based certified randomness generation using current technology.

Flexible Control of Safety Margins for Action Based on Environmental Variability.

PubMed

Hadjiosif, Alkis M; Smith, Maurice A

2015-06-17

To reduce the risk of slip, grip force (GF) control includes a safety margin above the force level ordinarily sufficient for the expected load force (LF) dynamics. The current view is that this safety margin is based on the expected LF dynamics, amounting to a static safety factor like that often used in engineering design. More efficient control could be achieved, however, if the motor system reduces the safety margin when LF variability is low and increases it when this variability is high. Here we show that this is indeed the case by demonstrating that the human motor system sizes the GF safety margin in proportion to an internal estimate of LF variability to maintain a fixed statistical confidence against slip. In contrast to current models of GF control that neglect the variability of LF dynamics, we demonstrate that GF is threefold more sensitive to the SD than the expected value of LF dynamics, in line with the maintenance of a 3-sigma confidence level. We then show that a computational model of GF control that includes a variability-driven safety margin predicts highly asymmetric GF adaptation between increases versus decreases in load. We find clear experimental evidence for this asymmetry and show that it explains previously reported differences in how rapidly GFs and manipulatory forces adapt. This model further predicts bizarre nonmonotonic shapes for GF learning curves, which are faithfully borne out in our experimental data. Our findings establish a new role for environmental variability in the control of action. Copyright © 2015 the authors 0270-6474/15/359106-16$15.00/0.

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Quantum simulation of quantum field theory using continuous variables

DOE PAGES

Marshall, Kevin; Pooser, Raphael C.; Siopsis, George; ...

2015-12-14

Much progress has been made in the field of quantum computing using continuous variables over the last couple of years. This includes the generation of extremely large entangled cluster states (10,000 modes, in fact) as well as a fault tolerant architecture. This has lead to the point that continuous-variable quantum computing can indeed be thought of as a viable alternative for universal quantum computing. With that in mind, we present a new algorithm for continuous-variable quantum computers which gives an exponential speedup over the best known classical methods. Specifically, this relates to efficiently calculating the scattering amplitudes in scalar bosonicmore » quantum field theory, a problem that is known to be hard using a classical computer. Thus, we give an experimental implementation based on cluster states that is feasible with today's technology.« less

Quantum simulation of quantum field theory using continuous variables

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marshall, Kevin; Pooser, Raphael C.; Siopsis, George

Much progress has been made in the field of quantum computing using continuous variables over the last couple of years. This includes the generation of extremely large entangled cluster states (10,000 modes, in fact) as well as a fault tolerant architecture. This has lead to the point that continuous-variable quantum computing can indeed be thought of as a viable alternative for universal quantum computing. With that in mind, we present a new algorithm for continuous-variable quantum computers which gives an exponential speedup over the best known classical methods. Specifically, this relates to efficiently calculating the scattering amplitudes in scalar bosonicmore » quantum field theory, a problem that is known to be hard using a classical computer. Thus, we give an experimental implementation based on cluster states that is feasible with today's technology.« less

A grid spacing control technique for algebraic grid generation methods

NASA Technical Reports Server (NTRS)

Smith, R. E.; Kudlinski, R. A.; Everton, E. L.

1982-01-01

A technique which controls the spacing of grid points in algebraically defined coordinate transformations is described. The technique is based on the generation of control functions which map a uniformly distributed computational grid onto parametric variables defining the physical grid. The control functions are smoothed cubic splines. Sets of control points are input for each coordinate directions to outline the control functions. Smoothed cubic spline functions are then generated to approximate the input data. The technique works best in an interactive graphics environment where control inputs and grid displays are nearly instantaneous. The technique is illustrated with the two-boundary grid generation algorithm.

Robust optimization-based DC optimal power flow for managing wind generation uncertainty

NASA Astrophysics Data System (ADS)

Boonchuay, Chanwit; Tomsovic, Kevin; Li, Fangxing; Ongsakul, Weerakorn

2012-11-01

Integrating wind generation into the wider grid causes a number of challenges to traditional power system operation. Given the relatively large wind forecast errors, congestion management tools based on optimal power flow (OPF) need to be improved. In this paper, a robust optimization (RO)-based DCOPF is proposed to determine the optimal generation dispatch and locational marginal prices (LMPs) for a day-ahead competitive electricity market considering the risk of dispatch cost variation. The basic concept is to use the dispatch to hedge against the possibility of reduced or increased wind generation. The proposed RO-based DCOPF is compared with a stochastic non-linear programming (SNP) approach on a modified PJM 5-bus system. Primary test results show that the proposed DCOPF model can provide lower dispatch cost than the SNP approach.

Throughfall and its spatial variability beneath xerophytic shrub canopies within water-limited arid desert ecosystems

NASA Astrophysics Data System (ADS)

Zhang, Ya-feng; Wang, Xin-ping; Hu, Rui; Pan, Yan-xia

2016-08-01

Throughfall is known to be a critical component of the hydrological and biogeochemical cycles of forested ecosystems with inherently temporal and spatial variability. Yet little is understood concerning the throughfall variability of shrubs and the associated controlling factors in arid desert ecosystems. Here we systematically investigated the variability of throughfall of two morphological distinct xerophytic shrubs (Caragana korshinskii and Artemisia ordosica) within a re-vegetated arid desert ecosystem, and evaluated the effects of shrub structure and rainfall characteristics on throughfall based on heavily gauged throughfall measurements at the event scale. We found that morphological differences were not sufficient to generate significant difference (P < 0.05) in throughfall between two studied shrub species under the same rainfall and meteorological conditions in our study area, with a throughfall percentage of 69.7% for C. korshinskii and 64.3% for A. ordosica. We also observed a highly variable patchy pattern of throughfall beneath individual shrub canopies, but the spatial patterns appeared to be stable among rainfall events based on time stability analysis. Throughfall linearly increased with the increasing distance from the shrub base for both shrubs, and radial direction beneath shrub canopies had a pronounced impact on throughfall. Throughfall variability, expressed as the coefficient of variation (CV) of throughfall, tended to decline with the increase in rainfall amount, intensity and duration, and stabilized passing a certain threshold. Our findings highlight the great variability of throughfall beneath the canopies of xerophytic shrubs and the time stability of throughfall pattern among rainfall events. The spatially heterogeneous and temporally stable throughfall is expected to generate a dynamic patchy distribution of soil moisture beneath shrub canopies within arid desert ecosystems.

Design optimization of gas generator hybrid propulsion boosters

NASA Technical Reports Server (NTRS)

Weldon, Vincent; Phillips, Dwight U.; Fink, Lawrence E.

1990-01-01

A methodology used in support of a contract study for NASA/MSFC to optimize the design of gas generator hybrid propulsion booster for uprating the National Space Transportation System (NSTS) is presented. The objective was to compare alternative configurations for this booster approach, optimizing each candidate concept on different bases, in order to develop data for a trade table on which a final decision was based. The methodology is capable of processing a large number of independent and dependent variables, adjusting the overall subsystems characteristics to arrive at a best compromise integrated design to meet various specified optimization criteria subject to selected constraints. For each system considered, a detailed weight statement was generated along with preliminary cost and reliability estimates.

Topology optimization based design of unilateral NMR for generating a remote homogeneous field.

PubMed

Wang, Qi; Gao, Renjing; Liu, Shutian

2017-06-01

This paper presents a topology optimization based design method for the design of unilateral nuclear magnetic resonance (NMR), with which a remote homogeneous field can be obtained. The topology optimization is actualized by seeking out the optimal layout of ferromagnetic materials within a given design domain. The design objective is defined as generating a sensitive magnetic field with optimal homogeneity and maximal field strength within a required region of interest (ROI). The sensitivity of the objective function with respect to the design variables is derived and the method for solving the optimization problem is presented. A design example is provided to illustrate the utility of the design method, specifically the ability to improve the quality of the magnetic field over the required ROI by determining the optimal structural topology for the ferromagnetic poles. Both in simulations and experiments, the sensitive region of the magnetic field achieves about 2 times larger than that of the reference design, validating validates the feasibility of the design method. Copyright © 2017. Published by Elsevier Inc.

A Model-Based Method for Content Validation of Automatically Generated Test Items

ERIC Educational Resources Information Center

Zhang, Xinxin; Gierl, Mark

2016-01-01

The purpose of this study is to describe a methodology to recover the item model used to generate multiple-choice test items with a novel graph theory approach. Beginning with the generated test items and working backward to recover the original item model provides a model-based method for validating the content used to automatically generate test…

An artificially generated atmosphere near a lunar base

NASA Technical Reports Server (NTRS)

Burns, Jack O.; Fernini, Ilias; Sulkanen, Martin; Duric, Nebojsa; Taylor, G. Jeffrey; Johnson, Stewart W.

1992-01-01

We discuss the formation of an artificial atmosphere generated by vigorous lunar base activity in this paper. We developed an analytical, steady-state model for a lunar atmosphere based upon previous investigations of the Moon's atmosphere from Apollo. Constant gas-injection rates, ballistic trajectories, and a Maxwellian particle distribution for an oxygen-like gas are assumed. Even for the extreme case of continuous He-3 mining of the lunar regolith, we find that the lunar atmosphere would not significantly degrade astronomical observations beyond about 10 km from the mining operation.

Seasonal forecasts in the Sahel region: the use of rainfall-based predictive variables

NASA Astrophysics Data System (ADS)

Lodoun, Tiganadaba; Sanon, Moussa; Giannini, Alessandra; Traoré, Pierre Sibiry; Somé, Léopold; Rasolodimby, Jeanne Millogo

2014-08-01

In the Sahel region, seasonal predictions are crucial to alleviate the impacts of climate variability on populations' livelihoods. Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May-July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920-2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. A total of nine climatic zones were identified in each of which, based on rainfall records from May to July, we derived linear discriminant functions to correctly predict the nature of a potential onset date of the rainy season (real or false) and that of the rainy season (dry or wet) in at least three cases out of five. These functions should contribute to alleviating the negative impacts of climate variability in the different climatic zones of Burkina Faso.

Dual gait generative models for human motion estimation from a single camera.

PubMed

Zhang, Xin; Fan, Guoliang

2010-08-01

This paper presents a general gait representation framework for video-based human motion estimation. Specifically, we want to estimate the kinematics of an unknown gait from image sequences taken by a single camera. This approach involves two generative models, called the kinematic gait generative model (KGGM) and the visual gait generative model (VGGM), which represent the kinematics and appearances of a gait by a few latent variables, respectively. The concept of gait manifold is proposed to capture the gait variability among different individuals by which KGGM and VGGM can be integrated together, so that a new gait with unknown kinematics can be inferred from gait appearances via KGGM and VGGM. Moreover, a new particle-filtering algorithm is proposed for dynamic gait estimation, which is embedded with a segmental jump-diffusion Markov Chain Monte Carlo scheme to accommodate the gait variability in a long observed sequence. The proposed algorithm is trained from the Carnegie Mellon University (CMU) Mocap data and tested on the Brown University HumanEva data with promising results.

Enhanced Requirements for Assessment in a Competency-Based, Time-Variable Medical Education System.

PubMed

Gruppen, Larry D; Ten Cate, Olle; Lingard, Lorelei A; Teunissen, Pim W; Kogan, Jennifer R

2018-03-01

Competency-based, time-variable medical education has reshaped the perceptions and practices of teachers, curriculum designers, faculty developers, clinician educators, and program administrators. This increasingly popular approach highlights the fact that learning among different individuals varies in duration, foundation, and goal. Time variability places particular demands on the assessment data that are so necessary for making decisions about learner progress. These decisions may be formative (e.g., feedback for improvement) or summative (e.g., decisions about advancing a student). This article identifies challenges to collecting assessment data and to making assessment decisions in a time-variable system. These challenges include managing assessment data, defining and making valid assessment decisions, innovating in assessment, and modeling the considerable complexity of assessment in real-world settings and richly interconnected social systems. There are hopeful signs of creativity in assessment both from researchers and practitioners, but the transition from a traditional to a competency-based medical education system will likely continue to create much controversy and offer opportunities for originality and innovation in assessment.

Digital relief generation from 3D models

NASA Astrophysics Data System (ADS)

Wang, Meili; Sun, Yu; Zhang, Hongming; Qian, Kun; Chang, Jian; He, Dongjian

2016-09-01

It is difficult to extend image-based relief generation to high-relief generation, as the images contain insufficient height information. To generate reliefs from three-dimensional (3D) models, it is necessary to extract the height fields from the model, but this can only generate bas-reliefs. To overcome this problem, an efficient method is proposed to generate bas-reliefs and high-reliefs directly from 3D meshes. To produce relief features that are visually appropriate, the 3D meshes are first scaled. 3D unsharp masking is used to enhance the visual features in the 3D mesh, and average smoothing and Laplacian smoothing are implemented to achieve better smoothing results. A nonlinear variable scaling scheme is then employed to generate the final bas-reliefs and high-reliefs. Using the proposed method, relief models can be generated from arbitrary viewing positions with different gestures and combinations of multiple 3D models. The generated relief models can be printed by 3D printers. The proposed method provides a means of generating both high-reliefs and bas-reliefs in an efficient and effective way under the appropriate scaling factors.

The sixth generation robot in space

NASA Technical Reports Server (NTRS)

Butcher, A.; Das, A.; Reddy, Y. V.; Singh, H.

1990-01-01

The knowledge based simulator developed in the artificial intelligence laboratory has become a working test bed for experimenting with intelligent reasoning architectures. With this simulator, recently, small experiments have been done with an aim to simulate robot behavior to avoid colliding paths. An automatic extension of such experiments to intelligently planning robots in space demands advanced reasoning architectures. One such architecture for general purpose problem solving is explored. The robot, seen as a knowledge base machine, goes via predesigned abstraction mechanism for problem understanding and response generation. The three phases in one such abstraction scheme are: abstraction for representation, abstraction for evaluation, and abstraction for resolution. Such abstractions require multimodality. This multimodality requires the use of intensional variables to deal with beliefs in the system. Abstraction mechanisms help in synthesizing possible propagating lattices for such beliefs. The machine controller enters into a sixth generation paradigm.

Variable aperture-based ptychographical iterative engine method

NASA Astrophysics Data System (ADS)

Sun, Aihui; Kong, Yan; Meng, Xin; He, Xiaoliang; Du, Ruijun; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-02-01

A variable aperture-based ptychographical iterative engine (vaPIE) is demonstrated both numerically and experimentally to reconstruct the sample phase and amplitude rapidly. By adjusting the size of a tiny aperture under the illumination of a parallel light beam to change the illumination on the sample step by step and recording the corresponding diffraction patterns sequentially, both the sample phase and amplitude can be faithfully reconstructed with a modified ptychographical iterative engine (PIE) algorithm. Since many fewer diffraction patterns are required than in common PIE and the shape, the size, and the position of the aperture need not to be known exactly, this proposed vaPIE method remarkably reduces the data acquisition time and makes PIE less dependent on the mechanical accuracy of the translation stage; therefore, the proposed technique can be potentially applied for various scientific researches.

Location and Size Planning of Distributed Photovoltaic Generation in Distribution network System Based on K-means Clustering Analysis

NASA Astrophysics Data System (ADS)

Lu, Siqi; Wang, Xiaorong; Wu, Junyong

2018-01-01

The paper presents a method to generate the planning scenarios, which is based on K-means clustering analysis algorithm driven by data, for the location and size planning of distributed photovoltaic (PV) units in the network. Taken the power losses of the network, the installation and maintenance costs of distributed PV, the profit of distributed PV and the voltage offset as objectives and the locations and sizes of distributed PV as decision variables, Pareto optimal front is obtained through the self-adaptive genetic algorithm (GA) and solutions are ranked by a method called technique for order preference by similarity to an ideal solution (TOPSIS). Finally, select the planning schemes at the top of the ranking list based on different planning emphasis after the analysis in detail. The proposed method is applied to a 10-kV distribution network in Gansu Province, China and the results are discussed.

Evidence-based health policy: three generations of reform in Mexico.

PubMed

Frenk, Julio; Sepúlveda, Jaime; Gómez-Dantés, Octavio; Knaul, Felicia

2003-11-15

The Mexican health system has evolved through three generations of reform. The creation of the Ministry of Health and the main social security agency in 1943 marked the first generation of health reforms. In the late 1970s, a second generation of reforms was launched around the primary health-care model. Third-generation reforms favour systemic changes to reorganise the system through the horizontal integration of basic functions-stewardship, financing, and provision. The stability of leadership in the health sector is emphasised as a key element that allowed for reform during the past 60 years. Furthermore, there has been a transition in the second generation of reforms to a model that is increasingly based on evidence; this has been intensified and extended in the third generation of reforms. We also examine policy developments that will provide social protection in health for all. These developments could be of interest for countries seeking to provide their citizens with universal access to health care that incorporates equity, quality, and financial protection.

Tethered balloon-based measurements of meteorological variables and aerosols

NASA Technical Reports Server (NTRS)

Sentell, R. J.; Storey, R. W.; Chang, J. J. C.; Jacobsen, S. J.

1976-01-01

Tethered balloon based measurements of the vertical distributions of temperature, humidity, wind speed, and aerosol concentrations were taken over a 4-hour period beginning at sunrise on June 29, 1976, at Wallops Island, Virginia. Twelve consecutive profiles of each variable were obtained from ground to about 500 meters. These measurements were in conjuction with a noise propagation study on remotely arrayed acoustic range (ROMAAR) at Wallops Flight Center. An organized listing of these vertical soundings is presented. The tethered balloon system configuration utilized for these measurements is described.

Communication systems, transceivers, and methods for generating data based on channel characteristics

DOEpatents

Forman, Michael A; Young, Derek

2012-09-18

Examples of methods for generating data based on a communications channel are described. In one such example, a processing unit may generate a first vector representation based in part on at least two characteristics of a communications channel. A constellation having at least two dimensions may be addressed with the first vector representation to identify a first symbol associated with the first vector representation. The constellation represents a plurality of regions, each region associated with a respective symbol. The symbol may be used to generate data, which may stored in an electronic storage medium and used as a cryptographic key or a spreading code or hopping sequence in a modulation technique.

Generation of Potent T-cell Immunotherapy for Cancer using DAP12-based, Multichain, Chimeric Immunoreceptors

PubMed Central

Wang, Enxiu; Wang, Liang-Chuan; Tsai, Ching-Yi; Bhoj, Vijay; Gershenson, Zack; Moon, Edmund; Newick, Kheng; Sun, Jing; Lo, Albert; Baradet, Timothy; Feldman, Michael D.; Barrett, David; Puré, Ellen; Albelda, Steven; Milone, Michael C.

2015-01-01

Chimeric antigen receptors (CAR) bearing an antigen-binding domain linked in cis to the cytoplasmic domains of CD3ζ and costimulatory receptors have provided a potent method for engineering T-cell cytotoxicity towards B-cell leukemia and lymphoma. However, resistance to immunotherapy due to loss of T-cell effector function remains a significant barrier, especially in solid malignancies. We describe an alternative chimeric immunoreceptor design in which we have fused a single-chain variable fragment for antigen recognition to the transmembrane and cytoplasmic domains of KIR2DS2, a stimulatory killer immunoglobulin-like receptor (KIR). We show that this simple, KIR-based CAR (KIR-CAR) triggers robust antigen-specific proliferation and effector function in vitro when introduced into human T cells with DAP12, an immunotyrosine-based activation motifs (ITAM)-containing adaptor. T cells modified to express a KIR-CAR and DAP12 exhibit superior antitumor activity compared to standard first and second generation CD3ζ-based CARs in a xenograft model of mesothelioma highly resistant to immunotherapy. The enhanced antitumor activity is associated with improved retention of chimeric immunoreceptor expression and improved effector function of isolated tumor-infiltrating lymphocytes. These results support the exploration of KIR-CARs for adoptive T-cell immunotherapy, particularly in immunotherapy-resistant solid tumors. PMID:25941351

Natural wind variability triggered drop in German redispatch volume and costs from 2015 to 2016.

PubMed

Wohland, Jan; Reyers, Mark; Märker, Carolin; Witthaut, Dirk

2018-01-01

Avoiding dangerous climate change necessitates the decarbonization of electricity systems within the next few decades. In Germany, this decarbonization is based on an increased exploitation of variable renewable electricity sources such as wind and solar power. While system security has remained constantly high, the integration of renewables causes additional costs. In 2015, the costs of grid management saw an all time high of about € 1 billion. Despite the addition of renewable capacity, these costs dropped substantially in 2016. We thus investigate the effect of natural climate variability on grid management costs in this study. We show that the decline is triggered by natural wind variability focusing on redispatch as a main cost driver. In particular, we find that 2016 was a weak year in terms of wind generation averages and the occurrence of westerly circulation weather types. Moreover, we show that a simple model based on the wind generation time series is skillful in detecting redispatch events on timescales of weeks and beyond. As a consequence, alterations in annual redispatch costs in the order of hundreds of millions of euros need to be understood and communicated as a normal feature of the current system due to natural wind variability.

Natural wind variability triggered drop in German redispatch volume and costs from 2015 to 2016

PubMed Central

Reyers, Mark; Märker, Carolin; Witthaut, Dirk

2018-01-01

Avoiding dangerous climate change necessitates the decarbonization of electricity systems within the next few decades. In Germany, this decarbonization is based on an increased exploitation of variable renewable electricity sources such as wind and solar power. While system security has remained constantly high, the integration of renewables causes additional costs. In 2015, the costs of grid management saw an all time high of about € 1 billion. Despite the addition of renewable capacity, these costs dropped substantially in 2016. We thus investigate the effect of natural climate variability on grid management costs in this study. We show that the decline is triggered by natural wind variability focusing on redispatch as a main cost driver. In particular, we find that 2016 was a weak year in terms of wind generation averages and the occurrence of westerly circulation weather types. Moreover, we show that a simple model based on the wind generation time series is skillful in detecting redispatch events on timescales of weeks and beyond. As a consequence, alterations in annual redispatch costs in the order of hundreds of millions of euros need to be understood and communicated as a normal feature of the current system due to natural wind variability. PMID:29329349

A Model of Generating Visual Place Cells Based on Environment Perception and Similar Measure.

PubMed

Zhou, Yang; Wu, Dewei

2016-01-01

It is an important content to generate visual place cells (VPCs) in the field of bioinspired navigation. By analyzing the firing characteristic of biological place cells and the existing methods for generating VPCs, a model of generating visual place cells based on environment perception and similar measure is abstracted in this paper. VPCs' generation process is divided into three phases, including environment perception, similar measure, and recruiting of a new place cell. According to this process, a specific method for generating VPCs is presented. External reference landmarks are obtained based on local invariant characteristics of image and a similar measure function is designed based on Euclidean distance and Gaussian function. Simulation validates the proposed method is available. The firing characteristic of the generated VPCs is similar to that of biological place cells, and VPCs' firing fields can be adjusted flexibly by changing the adjustment factor of firing field (AFFF) and firing rate's threshold (FRT).

A Model of Generating Visual Place Cells Based on Environment Perception and Similar Measure

PubMed Central

2016-01-01

It is an important content to generate visual place cells (VPCs) in the field of bioinspired navigation. By analyzing the firing characteristic of biological place cells and the existing methods for generating VPCs, a model of generating visual place cells based on environment perception and similar measure is abstracted in this paper. VPCs' generation process is divided into three phases, including environment perception, similar measure, and recruiting of a new place cell. According to this process, a specific method for generating VPCs is presented. External reference landmarks are obtained based on local invariant characteristics of image and a similar measure function is designed based on Euclidean distance and Gaussian function. Simulation validates the proposed method is available. The firing characteristic of the generated VPCs is similar to that of biological place cells, and VPCs' firing fields can be adjusted flexibly by changing the adjustment factor of firing field (AFFF) and firing rate's threshold (FRT). PMID:27597859

How to differentiate collective variables in free energy codes: Computer-algebra code generation and automatic differentiation

NASA Astrophysics Data System (ADS)

Giorgino, Toni

2018-07-01

The proper choice of collective variables (CVs) is central to biased-sampling free energy reconstruction methods in molecular dynamics simulations. The PLUMED 2 library, for instance, provides several sophisticated CV choices, implemented in a C++ framework; however, developing new CVs is still time consuming due to the need to provide code for the analytical derivatives of all functions with respect to atomic coordinates. We present two solutions to this problem, namely (a) symbolic differentiation and code generation, and (b) automatic code differentiation, in both cases leveraging open-source libraries (SymPy and Stan Math, respectively). The two approaches are demonstrated and discussed in detail implementing a realistic example CV, the local radius of curvature of a polymer. Users may use the code as a template to streamline the implementation of their own CVs using high-level constructs and automatic gradient computation.

A canonical neural mechanism for behavioral variability

PubMed Central

Darshan, Ran; Wood, William E.; Peters, Susan; Leblois, Arthur; Hansel, David

2017-01-01

The ability to generate variable movements is essential for learning and adjusting complex behaviours. This variability has been linked to the temporal irregularity of neuronal activity in the central nervous system. However, how neuronal irregularity actually translates into behavioural variability is unclear. Here we combine modelling, electrophysiological and behavioural studies to address this issue. We demonstrate that a model circuit comprising topographically organized and strongly recurrent neural networks can autonomously generate irregular motor behaviours. Simultaneous recordings of neurons in singing finches reveal that neural correlations increase across the circuit driving song variability, in agreement with the model predictions. Analysing behavioural data, we find remarkable similarities in the babbling statistics of 5–6-month-old human infants and juveniles from three songbird species and show that our model naturally accounts for these ‘universal' statistics. PMID:28530225

Relationship between operational variables, fundamental physics and foamed cement properties in lab and field generated foamed cement slurries

DOE PAGES

Glosser, D.; Kutchko, B.; Benge, G.; ...

2016-03-21

Foamed cement is a critical component for wellbore stability. The mechanical performance of a foamed cement depends on its microstructure, which in turn depends on the preparation method and attendant operational variables. Determination of cement stability for field use is based on laboratory testing protocols governed by API Recommended Practice 10B-4 (API RP 10B-4, 2015). However, laboratory and field operational variables contrast considerably in terms of scale, as well as slurry mixing and foaming processes. Here in this paper, laboratory and field operational processes are characterized within a physics-based framework. It is shown that the “atomization energy” imparted by themore » high pressure injection of nitrogen gas into the field mixed foamed cement slurry is – by a significant margin – the highest energy process, and has a major impact on the void system in the cement slurry. There is no analog for this high energy exchange in current laboratory cement preparation and testing protocols. Quantifying the energy exchanges across the laboratory and field processes provides a basis for understanding relative impacts of these variables on cement structure, and can ultimately lead to the development of practices to improve cement testing and performance.« less

Novel pseudo-random number generator based on quantum random walks.

PubMed

Yang, Yu-Guang; Zhao, Qian-Qian

2016-02-04

In this paper, we investigate the potential application of quantum computation for constructing pseudo-random number generators (PRNGs) and further construct a novel PRNG based on quantum random walks (QRWs), a famous quantum computation model. The PRNG merely relies on the equations used in the QRWs, and thus the generation algorithm is simple and the computation speed is fast. The proposed PRNG is subjected to statistical tests such as NIST and successfully passed the test. Compared with the representative PRNG based on quantum chaotic maps (QCM), the present QRWs-based PRNG has some advantages such as better statistical complexity and recurrence. For example, the normalized Shannon entropy and the statistical complexity of the QRWs-based PRNG are 0.999699456771172 and 1.799961178212329e-04 respectively given the number of 8 bits-words, say, 16Mbits. By contrast, the corresponding values of the QCM-based PRNG are 0.999448131481064 and 3.701210794388818e-04 respectively. Thus the statistical complexity and the normalized entropy of the QRWs-based PRNG are closer to 0 and 1 respectively than those of the QCM-based PRNG when the number of words of the analyzed sequence increases. It provides a new clue to construct PRNGs and also extends the applications of quantum computation.

Novel pseudo-random number generator based on quantum random walks

PubMed Central

Yang, Yu-Guang; Zhao, Qian-Qian

2016-01-01

In this paper, we investigate the potential application of quantum computation for constructing pseudo-random number generators (PRNGs) and further construct a novel PRNG based on quantum random walks (QRWs), a famous quantum computation model. The PRNG merely relies on the equations used in the QRWs, and thus the generation algorithm is simple and the computation speed is fast. The proposed PRNG is subjected to statistical tests such as NIST and successfully passed the test. Compared with the representative PRNG based on quantum chaotic maps (QCM), the present QRWs-based PRNG has some advantages such as better statistical complexity and recurrence. For example, the normalized Shannon entropy and the statistical complexity of the QRWs-based PRNG are 0.999699456771172 and 1.799961178212329e-04 respectively given the number of 8 bits-words, say, 16Mbits. By contrast, the corresponding values of the QCM-based PRNG are 0.999448131481064 and 3.701210794388818e-04 respectively. Thus the statistical complexity and the normalized entropy of the QRWs-based PRNG are closer to 0 and 1 respectively than those of the QCM-based PRNG when the number of words of the analyzed sequence increases. It provides a new clue to construct PRNGs and also extends the applications of quantum computation. PMID:26842402

The Formula Design and Performance Study of Gas Generators based on 5-Aminotetrazole

NASA Astrophysics Data System (ADS)

Han, Z. Y.; Zhang, Y. P.; Du, Z. M.; Li, Z. Y.; Yao, Q.; Yang, Y. Z.

2018-01-01

Up to now, the research studies about 5-aminotetrazole (5-AT) gas generators are still not complete. In this work, ten gas generators based on 5-AT with different ordinary oxidants were designed. At the same time, ten gas generators based on azodicarbonamide (ADC), a current gas-generating material, were also designed, which serves as a contrast to formulas of 5-AT. The oxidants of all formulas are the same in proportion. The specific volume, gas production rate, and combustion temperature of these gas generators were measured and calculated. In conclusion, 5-AT/KClO4/Fe2O3/MnO2 formula has high specific volume, acceptable combustion temperature (1466.07 K), and large gas production (maximum pressures can reach 1.79 MPa). It is a kind of gas generator with potential value of development such as using in inflating airbags of automobiles.

Internal Catchment Process Simulation in a Snow-Dominated Basin: Performance Evaluation with Spatiotemporally Variable Runoff Generation and Groundwater Dynamics

NASA Astrophysics Data System (ADS)

Kuras, P. K.; Weiler, M.; Alila, Y.; Spittlehouse, D.; Winkler, R.

2006-12-01

Hydrologic models have been increasingly used in forest hydrology to overcome the limitations of paired watershed experiments, where vegetative recovery and natural variability obscure the inferences and conclusions that can be drawn from such studies. Models, however, are also plagued by uncertainty stemming from a limited understanding of hydrological processes in forested catchments and parameter equifinality is a common concern. This has created the necessity to improve our understanding of how hydrological systems work, through the development of hydrological measures, analyses and models that address the question: are we getting the right answers for the right reasons? Hence, physically-based, spatially-distributed hydrologic models should be validated with high-quality experimental data describing multiple concurrent internal catchment processes under a range of hydrologic regimes. The distributed hydrology soil vegetation model (DHSVM) frequently used in forest management applications is an example of a process-based model used to address the aforementioned circumstances, and this study takes a novel approach at collectively examining the ability of a pre-calibrated model application to realistically simulate outlet flows along with the spatial-temporal variation of internal catchment processes including: continuous groundwater dynamics at 9 locations, stream and road network flow at 67 locations for six individual days throughout the freshet, and pre-melt season snow distribution. Model efficiency was improved over prior evaluations due to continuous efforts in improving the quality of meteorological data in the watershed. Road and stream network flows were very well simulated for a range of hydrological conditions, and the spatial distribution of the pre-melt season snowpack was in general agreement with observed values. The model was effective in simulating the spatial variability of subsurface flow generation, except at locations where strong stream

Variables that Correlate with Faculty Use of Research-Based Instructional Strategies

NASA Astrophysics Data System (ADS)

Henderson, Charles; Dancy, Melissa H.; Niewiadomska-Bugaj, Magdalena

2010-10-01

During the Fall of 2008 a web survey, designed to collect information about pedagogical knowledge and practices, was completed by a representative sample of 722 physics faculty across the United States (a 50.3% response rate). This paper examines how 20 predictor variables correlate with faculty knowledge about and use of research-based instructional strategies (RBIS). Profiles were developed for each of four faculty levels of knowledge about and use of RBIS. Logistic regression analysis was used to identify a subset of the variables that could predict group membership. Five significant predictor variables were identified. High levels of knowledge and use of RBIS were associated with the following characteristics: attendee of the physics and astronomy new faculty workshop, attendee of at least one talk or workshop related to teaching in the last two years, satisfaction with meeting instructional goals, regular reader of one or more journals related to teaching, and being female. High research productivity and large class sizes were not found to be barriers to use of at least some RBIS.

[Hydrologic variability and sensitivity based on Hurst coefficient and Bartels statistic].

PubMed

Lei, Xu; Xie, Ping; Wu, Zi Yi; Sang, Yan Fang; Zhao, Jiang Yan; Li, Bin Bin

2018-04-01

Due to the global climate change and frequent human activities in recent years, the pure stochastic components of hydrological sequence is mixed with one or several of the variation ingredients, including jump, trend, period and dependency. It is urgently needed to clarify which indices should be used to quantify the degree of their variability. In this study, we defined the hydrological variability based on Hurst coefficient and Bartels statistic, and used Monte Carlo statistical tests to test and analyze their sensitivity to different variants. When the hydrological sequence had jump or trend variation, both Hurst coefficient and Bartels statistic could reflect the variation, with the Hurst coefficient being more sensitive to weak jump or trend variation. When the sequence had period, only the Bartels statistic could detect the mutation of the sequence. When the sequence had a dependency, both the Hurst coefficient and the Bartels statistics could reflect the variation, with the latter could detect weaker dependent variations. For the four variations, both the Hurst variability and Bartels variability increased with the increases of variation range. Thus, they could be used to measure the variation intensity of the hydrological sequence. We analyzed the temperature series of different weather stations in the Lancang River basin. Results showed that the temperature of all stations showed the upward trend or jump, indicating that the entire basin had experienced warming in recent years and the temperature variability in the upper and lower reaches was much higher. This case study showed the practicability of the proposed method.

Managing Wind-based Electricity Generation and Storage

NASA Astrophysics Data System (ADS)

Zhou, Yangfang

Among the many issues that profoundly affect the world economy every day, energy is one of the most prominent. Countries such as the U.S. strive to reduce reliance on the import of fossil fuels, and to meet increasing electricity demand without harming the environment. Two of the most promising solutions for the energy issue are to rely on renewable energy, and to develop efficient electricity storage. Renewable energy---such as wind energy and solar energy---is free, abundant, and most importantly, does not exacerbate the global warming problem. However, most renewable energy is inherently intermittent and variable, and thus can benefit greatly from coupling with electricity storage, such as grid-level industrial batteries. Grid storage can also help match the supply and demand of an entire electricity market. In addition, electricity storage such as car batteries can help reduce dependence on oil, as it can enable the development of Plug-in Hybrid Electric Vehicles, and Battery Electric Vehicles. This thesis focuses on understanding how to manage renewable energy and electricity storage properly together, and electricity storage alone. In Chapter 2, I study how to manage renewable energy, specifically wind energy. Managing wind energy is conceptually straightforward: generate and sell as much electricity as possible when prices are positive, and do nothing otherwise. However, this leads to curtailment when wind energy exceeds the transmission capacity, and possible revenue dilution when current prices are low but are expected to increase in the future. Electricity storage is being considered as a means to alleviate these problems, and also enables buying electricity from the market for later resale. But the presence of storage complicates the management of electricity generation from wind, and the value of storage for a wind-based generator is not entirely understood. I demonstrate that for such a combined generation and storage system the optimal policy does not

A Correlation-Based Transition Model using Local Variables. Part 1; Model Formation

NASA Technical Reports Server (NTRS)

Menter, F. R.; Langtry, R. B.; Likki, S. R.; Suzen, Y. B.; Huang, P. G.; Volker, S.

2006-01-01

A new correlation-based transition model has been developed, which is based strictly on local variables. As a result, the transition model is compatible with modern computational fluid dynamics (CFD) approaches, such as unstructured grids and massive parallel execution. The model is based on two transport equations, one for intermittency and one for the transition onset criteria in terms of momentum thickness Reynolds number. The proposed transport equations do not attempt to model the physics of the transition process (unlike, e.g., turbulence models) but from a framework for the implementation of correlation-based models into general-purpose CFD methods.

Realistic generation of natural phenomena based on video synthesis

NASA Astrophysics Data System (ADS)

Wang, Changbo; Quan, Hongyan; Li, Chenhui; Xiao, Zhao; Chen, Xiao; Li, Peng; Shen, Liuwei

2009-10-01

Research on the generation of natural phenomena has many applications in special effects of movie, battlefield simulation and virtual reality, etc. Based on video synthesis technique, a new approach is proposed for the synthesis of natural phenomena, including flowing water and fire flame. From the fire and flow video, the seamless video of arbitrary length is generated. Then, the interaction between wind and fire flame is achieved through the skeleton of flame. Later, the flow is also synthesized by extending the video textures using an edge resample method. Finally, we can integrate the synthesized natural phenomena into a virtual scene.

Pseudo-random bit generator based on lag time series

NASA Astrophysics Data System (ADS)

García-Martínez, M.; Campos-Cantón, E.

2014-12-01

In this paper, we present a pseudo-random bit generator (PRBG) based on two lag time series of the logistic map using positive and negative values in the bifurcation parameter. In order to hidden the map used to build the pseudo-random series we have used a delay in the generation of time series. These new series when they are mapped xn against xn+1 present a cloud of points unrelated to the logistic map. Finally, the pseudo-random sequences have been tested with the suite of NIST giving satisfactory results for use in stream ciphers.

Uncertainty and Variability in Physiologically-Based Pharmacokinetic (PBPK) Models: Key Issues and Case Studies (Final Report)

EPA Science Inventory

EPA announced the availability of the final report, Uncertainty and Variability in Physiologically-Based Pharmacokinetic (PBPK) Models: Key Issues and Case Studies. This report summarizes some of the recent progress in characterizing uncertainty and variability in physi...

Deep Learning-Based Data Forgery Detection in Automatic Generation Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Fengli; Li, Qinghua

Automatic Generation Control (AGC) is a key control system in the power grid. It is used to calculate the Area Control Error (ACE) based on frequency and tie-line power flow between balancing areas, and then adjust power generation to maintain the power system frequency in an acceptable range. However, attackers might inject malicious frequency or tie-line power flow measurements to mislead AGC to do false generation correction which will harm the power grid operation. Such attacks are hard to be detected since they do not violate physical power system models. In this work, we propose algorithms based on Neural Networkmore » and Fourier Transform to detect data forgery attacks in AGC. Different from the few previous work that rely on accurate load prediction to detect data forgery, our solution only uses the ACE data already available in existing AGC systems. In particular, our solution learns the normal patterns of ACE time series and detects abnormal patterns caused by artificial attacks. Evaluations on the real ACE dataset show that our methods have high detection accuracy.« less

Partitioning neuronal variability

PubMed Central

Goris, Robbe L.T.; Movshon, J. Anthony; Simoncelli, Eero P.

2014-01-01

Responses of sensory neurons differ across repeated measurements. This variability is usually treated as stochasticity arising within neurons or neural circuits. However, some portion of the variability arises from fluctuations in excitability due to factors that are not purely sensory, such as arousal, attention, and adaptation. To isolate these fluctuations, we developed a model in which spikes are generated by a Poisson process whose rate is the product of a drive that is sensory in origin, and a gain summarizing stimulus-independent modulatory influences on excitability. This model provides an accurate account of response distributions of visual neurons in macaque LGN, V1, V2, and MT, revealing that variability originates in large part from excitability fluctuations which are correlated over time and between neurons, and which increase in strength along the visual pathway. The model provides a parsimonious explanation for observed systematic dependencies of response variability and covariability on firing rate. PMID:24777419

Ontology-based automatic generation of computerized cognitive exercises.

PubMed

Leonardi, Giorgio; Panzarasa, Silvia; Quaglini, Silvana

2011-01-01

Computer-based approaches can add great value to the traditional paper-based approaches for cognitive rehabilitation. The management of a big amount of stimuli and the use of multimedia features permits to improve the patient's involvement and to reuse and recombine them to create new exercises, whose difficulty level should be adapted to the patient's performance. This work proposes an ontological organization of the stimuli, to support the automatic generation of new exercises, tailored on the patient's preferences and skills, and its integration into a commercial cognitive rehabilitation tool. The possibilities offered by this approach are presented with the help of real examples.

First neutron generation in the BINP accelerator based neutron source.

PubMed

Bayanov, B; Burdakov, A; Chudaev, V; Ivanov, A; Konstantinov, S; Kuznetsov, A; Makarov, A; Malyshkin, G; Mekler, K; Sorokin, I; Sulyaev, Yu; Taskaev, S

2009-07-01

Pilot innovative facility for neutron capture therapy was built at Budker Institute of Nuclear Physics, Novosibirsk. This facility is based on a compact vacuum insulation tandem accelerator designed to produce proton current up to 10 mA. Epithermal neutrons are proposed to be generated by 1.915 MeV protons bombarding a lithium target using (7)Li(p,n)(7)Be threshold reaction. The results of the first experiments on neutron generation are reported and discussed.

Brownian motion properties of optoelectronic random bit generators based on laser chaos.

PubMed

Li, Pu; Yi, Xiaogang; Liu, Xianglian; Wang, Yuncai; Wang, Yongge

2016-07-11

The nondeterministic property of the optoelectronic random bit generator (RBG) based on laser chaos are experimentally analyzed from two aspects of the central limit theorem and law of iterated logarithm. The random bits are extracted from an optical feedback chaotic laser diode using a multi-bit extraction technique in the electrical domain. Our experimental results demonstrate that the generated random bits have no statistical distance from the Brownian motion, besides that they can pass the state-of-the-art industry-benchmark statistical test suite (NIST SP800-22). All of them give a mathematically provable evidence that the ultrafast random bit generator based on laser chaos can be used as a nondeterministic random bit source.

Variable aperture-based ptychographical iterative engine method.

PubMed

Sun, Aihui; Kong, Yan; Meng, Xin; He, Xiaoliang; Du, Ruijun; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-02-01

A variable aperture-based ptychographical iterative engine (vaPIE) is demonstrated both numerically and experimentally to reconstruct the sample phase and amplitude rapidly. By adjusting the size of a tiny aperture under the illumination of a parallel light beam to change the illumination on the sample step by step and recording the corresponding diffraction patterns sequentially, both the sample phase and amplitude can be faithfully reconstructed with a modified ptychographical iterative engine (PIE) algorithm. Since many fewer diffraction patterns are required than in common PIE and the shape, the size, and the position of the aperture need not to be known exactly, this proposed vaPIE method remarkably reduces the data acquisition time and makes PIE less dependent on the mechanical accuracy of the translation stage; therefore, the proposed technique can be potentially applied for various scientific researches. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Consequences of neglecting the interannual variability of the solar resource: A case study of photovoltaic power among the Hawaiian Islands

DOE PAGES

Bryce, Richard; Losada Carreno, Ignacio; Kumler, Andrew; ...

2018-04-05

The interannual variability of the solar irradiance and meteorological conditions are often ignored in favor of single-year data sets for modeling power generation and evaluating the economic value of photovoltaic (PV) power systems. Yet interannual variability significantly impacts the generation from one year to another of renewable power systems such as wind and PV. Consequently, the interannual variability of power generation corresponds to the interannual variability of capital returns on investment. The penetration of PV systems within the Hawaiian Electric Companies' portfolio has rapidly accelerated in recent years and is expected to continue to increase given the state's energy objectivesmore » laid out by the Hawaii Clean Energy Initiative. We use the National Solar Radiation Database (1998-2015) to characterize the interannual variability of the solar irradiance and meteorological conditions across the State of Hawaii. These data sets are passed to the National Renewable Energy Laboratory's System Advisory Model (SAM) to calculate an 18-year PV power generation data set to characterize the variability of PV power generation. We calculate the interannual coefficient of variability (COV) for annual average global horizontal irradiance (GHI) on the order of 2% and COV for annual capacity factor on the order of 3% across the Hawaiian archipelago. Regarding the interannual variability of seasonal trends, we calculate the COV for monthly average GHI values on the order of 5% and COV for monthly capacity factor on the order of 10%. We model residential-scale and utility-scale PV systems and calculate the economic returns of each system via the payback period and the net present value. We demonstrate that studies based on single-year data sets for economic evaluations reach conclusions that deviate from the true values realized by accounting for interannual variability.« less

Consequences of neglecting the interannual variability of the solar resource: A case study of photovoltaic power among the Hawaiian Islands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bryce, Richard; Losada Carreno, Ignacio; Kumler, Andrew

The interannual variability of the solar irradiance and meteorological conditions are often ignored in favor of single-year data sets for modeling power generation and evaluating the economic value of photovoltaic (PV) power systems. Yet interannual variability significantly impacts the generation from one year to another of renewable power systems such as wind and PV. Consequently, the interannual variability of power generation corresponds to the interannual variability of capital returns on investment. The penetration of PV systems within the Hawaiian Electric Companies' portfolio has rapidly accelerated in recent years and is expected to continue to increase given the state's energy objectivesmore » laid out by the Hawaii Clean Energy Initiative. We use the National Solar Radiation Database (1998-2015) to characterize the interannual variability of the solar irradiance and meteorological conditions across the State of Hawaii. These data sets are passed to the National Renewable Energy Laboratory's System Advisory Model (SAM) to calculate an 18-year PV power generation data set to characterize the variability of PV power generation. We calculate the interannual coefficient of variability (COV) for annual average global horizontal irradiance (GHI) on the order of 2% and COV for annual capacity factor on the order of 3% across the Hawaiian archipelago. Regarding the interannual variability of seasonal trends, we calculate the COV for monthly average GHI values on the order of 5% and COV for monthly capacity factor on the order of 10%. We model residential-scale and utility-scale PV systems and calculate the economic returns of each system via the payback period and the net present value. We demonstrate that studies based on single-year data sets for economic evaluations reach conclusions that deviate from the true values realized by accounting for interannual variability.« less

Analysis on flood generation processes by means of a continuous simulation model

NASA Astrophysics Data System (ADS)

Fiorentino, M.; Gioia, A.; Iacobellis, V.; Manfreda, S.

2006-03-01

In the present research, we exploited a continuous hydrological simulation to investigate on key variables responsible of flood peak formation. With this purpose, a distributed hydrological model (DREAM) is used in cascade with a rainfall generator (IRP-Iterated Random Pulse) to simulate a large number of extreme events providing insight into the main controls of flood generation mechanisms. Investigated variables are those used in theoretically derived probability distribution of floods based on the concept of partial contributing area (e.g. Iacobellis and Fiorentino, 2000). The continuous simulation model is used to investigate on the hydrological losses occurring during extreme events, the variability of the source area contributing to the flood peak and its lag-time. Results suggest interesting simplification for the theoretical probability distribution of floods according to the different climatic and geomorfologic environments. The study is applied to two basins located in Southern Italy with different climatic characteristics.

Quantum mechanical energy-based screening of combinatorially generated library of tautomers. TauTGen: a tautomer generator program.

PubMed

Harańczyk, Maciej; Gutowski, Maciej

2007-01-01

We describe a procedure of finding low-energy tautomers of a molecule. The procedure consists of (i) combinatorial generation of a library of tautomers, (ii) screening based on the results of geometry optimization of initial structures performed at the density functional level of theory, and (iii) final refinement of geometry for the top hits at the second-order Möller-Plesset level of theory followed by single-point energy calculations at the coupled cluster level of theory with single, double, and perturbative triple excitations. The library of initial structures of various tautomers is generated with TauTGen, a tautomer generator program. The procedure proved to be successful for these molecular systems for which common chemical knowledge had not been sufficient to predict the most stable structures.

Grey Comprehensive Evaluation of Biomass Power Generation Project Based on Group Judgement

NASA Astrophysics Data System (ADS)

Xia, Huicong; Niu, Dongxiao

2017-06-01

The comprehensive evaluation of benefit is an important task needed to be carried out at all stages of biomass power generation projects. This paper proposed an improved grey comprehensive evaluation method based on triangle whiten function. To improve the objectivity of weight calculation result of only reference comparison judgment method, this paper introduced group judgment to the weighting process. In the process of grey comprehensive evaluation, this paper invited a number of experts to estimate the benefit level of projects, and optimized the basic estimations based on the minimum variance principle to improve the accuracy of evaluation result. Taking a biomass power generation project as an example, the grey comprehensive evaluation result showed that the benefit level of this project was good. This example demonstrates the feasibility of grey comprehensive evaluation method based on group judgment for benefit evaluation of biomass power generation project.

Schwarz-Christoffel Conformal Mapping based Grid Generation for Global Oceanic Circulation Models

NASA Astrophysics Data System (ADS)

Xu, Shiming

2015-04-01

We propose new grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithm are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the conventional grid design problem of pole relocation, it also addresses more advanced issues of computational efficiency and the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily 10 utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling when complex land-ocean distribution is present.

Forecasting generation of urban solid waste in developing countries--a case study in Mexico.

PubMed

Buenrostro, O; Bocco, G; Vence, J

2001-01-01

Based on a study of the composition of urban solid waste (USW) and of socioeconomic variables in Morelia, Mexico, generation rates were estimated. In addition, the generation of residential solid waste (RSW) and nonresidential solid waste (NRSW) was forecasted by means of a multiple linear regression (MLR) analysis. For residential sources, the independent variables analyzed were monthly wages, persons per dwelling, age, and educational level of the heads of the household. For nonresidential sources, variables analyzed were number of employees, area of facilities, number of working days, and working hours per day. The forecasted values for residential waste were similar to those observed. This approach may be applied to areas in which available data are scarce, and in which there is an urgent need for the planning of adequate management of USW.

An Infrastructure for UML-Based Code Generation Tools

NASA Astrophysics Data System (ADS)

Wehrmeister, Marco A.; Freitas, Edison P.; Pereira, Carlos E.

The use of Model-Driven Engineering (MDE) techniques in the domain of distributed embedded real-time systems are gain importance in order to cope with the increasing design complexity of such systems. This paper discusses an infrastructure created to build GenERTiCA, a flexible tool that supports a MDE approach, which uses aspect-oriented concepts to handle non-functional requirements from embedded and real-time systems domain. GenERTiCA generates source code from UML models, and also performs weaving of aspects, which have been specified within the UML model. Additionally, this paper discusses the Distributed Embedded Real-Time Compact Specification (DERCS), a PIM created to support UML-based code generation tools. Some heuristics to transform UML models into DERCS, which have been implemented in GenERTiCA, are also discussed.

Impact of Subsurface Temperature Variability on Meteorological Variability: An AGCM Study

NASA Astrophysics Data System (ADS)

Mahanama, S. P.; Koster, R. D.; Liu, P.

2006-05-01

Anomalous atmospheric conditions can lead to surface temperature anomalies, which in turn can lead to temperature anomalies deep in the soil. The deep soil temperature (and the associated ground heat content) has significant memory -- the dissipation of a temperature anomaly may take weeks to months -- and thus deep soil temperature may contribute to the low frequency variability of energy and water variables elsewhere in the system. The memory may even provide some skill to subseasonal and seasonal forecasts. This study uses two long-term AGCM experiments to isolate the contribution of deep soil temperature variability to variability elsewhere in the climate system. The first experiment consists of a standard ensemble of AMIP-type simulations, simulations in which the deep soil temperature variable is allowed to interact with the rest of the system. In the second experiment, the coupling of the deep soil temperature to the rest of the climate system is disabled -- at each grid cell, the local climatological seasonal cycle of deep soil temperature (as determined from the first experiment) is prescribed. By comparing the variability of various atmospheric quantities as generated in the two experiments, we isolate the contribution of interactive deep soil temperature to that variability. The results show that interactive deep soil temperature contributes significantly to surface temperature variability. Interactive deep soil temperature, however, reduces the variability of the hydrological cycle (evaporation and precipitation), largely because it allows for a negative feedback between evaporation and temperature.

Electromagnetic fields from mobile phone base station - variability analysis.

PubMed

Bienkowski, Pawel; Zubrzak, Bartlomiej

2015-09-01

The article describes the character of electromagnetic field (EMF) in mobile phone base station (BS) surroundings and its variability in time with an emphasis on the measurement difficulties related to its pulse and multi-frequency nature. Work also presents long-term monitoring measurements performed recently in different locations in Poland - small city with dispersed building development and in major polish city - dense urban area. Authors tried to determine the trends in changing of EMF spectrum analyzing daily changes of measured EMF levels in those locations. Research was performed using selective electromagnetic meters and also EMF meter with spectrum analysis.

A GPU-Based Implementation of the Firefly Algorithm for Variable Selection in Multivariate Calibration Problems

PubMed Central

de Paula, Lauro C. M.; Soares, Anderson S.; de Lima, Telma W.; Delbem, Alexandre C. B.; Coelho, Clarimar J.; Filho, Arlindo R. G.

2014-01-01

Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation. PMID:25493625

A GPU-Based Implementation of the Firefly Algorithm for Variable Selection in Multivariate Calibration Problems.

PubMed

de Paula, Lauro C M; Soares, Anderson S; de Lima, Telma W; Delbem, Alexandre C B; Coelho, Clarimar J; Filho, Arlindo R G

2014-01-01

Several variable selection algorithms in multivariate calibration can be accelerated using Graphics Processing Units (GPU). Among these algorithms, the Firefly Algorithm (FA) is a recent proposed metaheuristic that may be used for variable selection. This paper presents a GPU-based FA (FA-MLR) with multiobjective formulation for variable selection in multivariate calibration problems and compares it with some traditional sequential algorithms in the literature. The advantage of the proposed implementation is demonstrated in an example involving a relatively large number of variables. The results showed that the FA-MLR, in comparison with the traditional algorithms is a more suitable choice and a relevant contribution for the variable selection problem. Additionally, the results also demonstrated that the FA-MLR performed in a GPU can be five times faster than its sequential implementation.

Heart rate variability based on risk stratification for type 2 diabetes mellitus.

PubMed

Silva-E-Oliveira, Julia; Amélio, Pâmela Marina; Abranches, Isabela Lopes Laguardia; Damasceno, Dênis Derly; Furtado, Fabianne

2017-01-01

To evaluate heart rate variability among adults with different risk levels for type 2 diabetes mellitus. The risk for type 2 diabetes mellitus was assessed in 130 participants (89 females) based on the questionnaire Finnish Diabetes Risk Score and was classified as low risk (n=26), slightly elevated risk (n=41), moderate risk (n=27) and high risk (n=32). To measure heart rate variability, a heart-rate monitor Polar S810i® was employed to obtain RR series for each individual, at rest, for 5 minutes, followed by analysis of linear and nonlinear indexes. The groups at higher risk of type 2 diabetes mellitus had significantly lower linear and nonlinear heart rate variability indexes. The individuals at high risk for type 2 diabetes mellitus have lower heart rate variability. Avaliar a variabilidade da frequência cardíaca em adultos com diferentes níveis de risco para diabetes mellitus tipo 2. O grau de risco para diabetes mellitus tipo 2 de 130 participantes (41 homens) foi avaliado pelo questionário Finnish Diabetes Risk Score. Os participantes foram classificados em baixo risco (n=26), risco levemente elevado (n=41), risco moderado (n=27) e alto risco (n=32). Para medir a variabilidade da frequência cardíaca, utilizou-se o frequencímetro Polar S810i® para obter séries de intervalo RR para cada indivíduo, em repouso, durante 5 minutos; posteriormente, realizou-se análise por meio de índices lineares e não-lineares. O grupo com maior risco para diabetes mellitus tipo 2 teve uma diminuição significante nos índices lineares e não-lineares da variabilidade da frequência cardíaca. Os resultados apontam que indivíduos com risco alto para diabetes mellitus tipo 2 tem menor variabilidade da frequência cardíaca. To evaluate heart rate variability among adults with different risk levels for type 2 diabetes mellitus. The risk for type 2 diabetes mellitus was assessed in 130 participants (89 females) based on the questionnaire Finnish Diabetes Risk Score

Interactive algebraic grid-generation technique

NASA Technical Reports Server (NTRS)

Smith, R. E.; Wiese, M. R.

1986-01-01

An algebraic grid generation technique and use of an associated interactive computer program are described. The technique, called the two boundary technique, is based on Hermite cubic interpolation between two fixed, nonintersecting boundaries. The boundaries are referred to as the bottom and top, and they are defined by two ordered sets of points. Left and right side boundaries which intersect the bottom and top boundaries may also be specified by two ordered sets of points. when side boundaries are specified, linear blending functions are used to conform interior interpolation to the side boundaries. Spacing between physical grid coordinates is determined as a function of boundary data and uniformly space computational coordinates. Control functions relating computational coordinates to parametric intermediate variables that affect the distance between grid points are embedded in the interpolation formulas. A versatile control function technique with smooth-cubic-spline functions is presented. The technique works best in an interactive graphics environment where computational displays and user responses are quickly exchanged. An interactive computer program based on the technique and called TBGG (two boundary grid generation) is also described.

Incorporating abundance information and guiding variable selection for climate-based ensemble forecasting of species' distributional shifts.

PubMed

Tanner, Evan P; Papeş, Monica; Elmore, R Dwayne; Fuhlendorf, Samuel D; Davis, Craig A

2017-01-01

Ecological niche models (ENMs) have increasingly been used to estimate the potential effects of climate change on species' distributions worldwide. Recently, predictions of species abundance have also been obtained with such models, though knowledge about the climatic variables affecting species abundance is often lacking. To address this, we used a well-studied guild (temperate North American quail) and the Maxent modeling algorithm to compare model performance of three variable selection approaches: correlation/variable contribution (CVC), biological (i.e., variables known to affect species abundance), and random. We then applied the best approach to forecast potential distributions, under future climatic conditions, and analyze future potential distributions in light of available abundance data and presence-only occurrence data. To estimate species' distributional shifts we generated ensemble forecasts using four global circulation models, four representative concentration pathways, and two time periods (2050 and 2070). Furthermore, we present distributional shifts where 75%, 90%, and 100% of our ensemble models agreed. The CVC variable selection approach outperformed our biological approach for four of the six species. Model projections indicated species-specific effects of climate change on future distributions of temperate North American quail. The Gambel's quail (Callipepla gambelii) was the only species predicted to gain area in climatic suitability across all three scenarios of ensemble model agreement. Conversely, the scaled quail (Callipepla squamata) was the only species predicted to lose area in climatic suitability across all three scenarios of ensemble model agreement. Our models projected future loss of areas for the northern bobwhite (Colinus virginianus) and scaled quail in portions of their distributions which are currently areas of high abundance. Climatic variables that influence local abundance may not always scale up to influence species

Two-dimensional carbon-based nanocomposites for photocatalytic energy generation and environmental remediation applications.

PubMed

Kumar, Suneel; Kumar, Ashish; Bahuguna, Ashish; Sharma, Vipul; Krishnan, Venkata

2017-01-01

In the pursuit towards the use of sunlight as a sustainable source for energy generation and environmental remediation, photocatalytic water splitting and photocatalytic pollutant degradation have recently gained significant importance. Research in this field is aimed at solving the global energy crisis and environmental issues in an ecologically-friendly way by using two of the most abundant natural resources, namely sunlight and water. Over the past few years, carbon-based nanocomposites, particularly graphene and graphitic carbon nitride, have attracted much attention as interesting materials in this field. Due to their unique chemical and physical properties, carbon-based nanocomposites have made a substantial contribution towards the generation of clean, renewable and viable forms of energy from light-based water splitting and pollutant removal. This review article provides a comprehensive overview of the recent research progress in the field of energy generation and environmental remediation using two-dimensional carbon-based nanocomposites. It begins with a brief introduction to the field, basic principles of photocatalytic water splitting for energy generation and environmental remediation, followed by the properties of carbon-based nanocomposites. Then, the development of various graphene-based nanocomposites for the above-mentioned applications is presented, wherein graphene plays different roles, including electron acceptor/transporter, cocatalyst, photocatalyst and photosensitizer. Subsequently, the development of different graphitic carbon nitride-based nanocomposites as photocatalysts for energy and environmental applications is discussed in detail. This review concludes by highlighting the advantages and challenges involved in the use of two-dimensional carbon-based nanocomposites for photocatalysis. Finally, the future perspectives of research in this field are also briefly mentioned.

Two-dimensional carbon-based nanocomposites for photocatalytic energy generation and environmental remediation applications

PubMed Central

Kumar, Suneel; Kumar, Ashish; Bahuguna, Ashish; Sharma, Vipul

2017-01-01

In the pursuit towards the use of sunlight as a sustainable source for energy generation and environmental remediation, photocatalytic water splitting and photocatalytic pollutant degradation have recently gained significant importance. Research in this field is aimed at solving the global energy crisis and environmental issues in an ecologically-friendly way by using two of the most abundant natural resources, namely sunlight and water. Over the past few years, carbon-based nanocomposites, particularly graphene and graphitic carbon nitride, have attracted much attention as interesting materials in this field. Due to their unique chemical and physical properties, carbon-based nanocomposites have made a substantial contribution towards the generation of clean, renewable and viable forms of energy from light-based water splitting and pollutant removal. This review article provides a comprehensive overview of the recent research progress in the field of energy generation and environmental remediation using two-dimensional carbon-based nanocomposites. It begins with a brief introduction to the field, basic principles of photocatalytic water splitting for energy generation and environmental remediation, followed by the properties of carbon-based nanocomposites. Then, the development of various graphene-based nanocomposites for the above-mentioned applications is presented, wherein graphene plays different roles, including electron acceptor/transporter, cocatalyst, photocatalyst and photosensitizer. Subsequently, the development of different graphitic carbon nitride-based nanocomposites as photocatalysts for energy and environmental applications is discussed in detail. This review concludes by highlighting the advantages and challenges involved in the use of two-dimensional carbon-based nanocomposites for photocatalysis. Finally, the future perspectives of research in this field are also briefly mentioned. PMID:28884063

MOSFET-based high voltage short pulse generator for ultrasonic transducer excitation

NASA Astrophysics Data System (ADS)

Hidayat, Darmawan; Setianto, Syafei, Nendi Suhendi; Wibawa, Bambang Mukti

2018-02-01

This paper presents the generation of a high-voltage short pulse for the excitation of high frequency ultrasonic transducers. This is highly required in the purpose of various ultrasonic-based evaluations, particularly when high resolution measurement is necessary. A high voltage (+760 V) DC voltage source was pulsated by an ultrafast switching MOSFET which was driven by a pulse generator circuit consisting of an astable multivibrator, a one-shot multivibrator with Schmitt trigger input and a high current MOSFET driver. The generated pulses excited a 200-kHz and a 1-MHz ultrasonic transducers and tested in the transmission mode propagation to evaluate the performances of the generated pulse. The test results showed the generator were able to produce negative spike pulses up to -760 V voltage with the shortest time-width of 107.1 nanosecond. The transmission-received ultrasonic waves show frequency oscillation at 200 and 961 kHz and their amplitudes varied with the voltage of excitation pulse. These results conclude that the developed pulse generator is applicable to excite transducer for the generation of high frequency ultrasonic waves.

Toward DNA-based Security Circuitry: First Step - Random Number Generation.

PubMed

Bogard, Christy M; Arazi, Benjamin; Rouchka, Eric C

2008-08-10

DNA-based circuit design is an area of research in which traditional silicon-based technologies are replaced by naturally occurring phenomena taken from biochemistry and molecular biology. Our team investigates the implications of DNA-based circuit design in serving security applications. As an initial step we develop a random number generation circuitry. A novel prototype schema employs solid-phase synthesis of oligonucleotides for random construction of DNA sequences. Temporary storage and retrieval is achieved through plasmid vectors.

Embedded system based on PWM control of hydrogen generator with SEPIC converter

NASA Astrophysics Data System (ADS)

Fall, Cheikh; Setiawan, Eko; Habibi, Muhammad Afnan; Hodaka, Ichijo

2017-09-01

The objective of this paper is to design and to produce a micro electrical plant system based on fuel cell for teaching material-embedded systems in technical vocational training center. Based on this, the student can experience generating hydrogen by fuel cells, controlling the rate of hydrogen generation by the duty ration of single-ended primary-inductor converter(SEPIC), drawing the curve rate of hydrogen to duty ratio, generating electrical power by using hydrogen, and calculating the fuel cell efficiency when it is used as electrical energy generator. This project is of great importance insofar as students will need to acquire several skills to be able to realize it such as continuous DC DC conversion and the scientific concept behind the converter, the regulation of systems with integral proportional controllers, the installation of photovoltaic cells, the use of high-tech sensors, microcontroller programming, object-oriented programming, mastery of the fuel cell syste

Knowledge-Based Planning Model for Courses of Action Generation,

DTIC Science & Technology

1986-04-07

AO-AIS 608 KNOWLEDGE-BASED PLANNING MODEL FOR COURSES OF ACTION mJI OENERATION(U) ARMY MAR COLL CARLISLE BARRACKS PA USI FE D R COLLINS ET AL. 97APR...agencies. This document may not be released for open publication until it has been cleared by the appropriate military service or government agency. 00 DTIC...I ELECTE KNOWLEDGE-BASED PLANNING MODEL C AUG 5~ FOR COURSES OF ACTION GENERATION DD BY COLONEL D. R. COLLINS LIEUTENANT COLONEL(P) T. A. BAUCUM

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

DOE PAGES

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie; ...

2016-10-18

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and

Bio-inspired Optimal Locomotion Reconfigurability of Quadruped Rovers using Central Pattern Generators

NASA Astrophysics Data System (ADS)

Bohra, Murtaza

Legged rovers are often considered as viable solutions for traversing unknown terrain. This work addresses the optimal locomotion reconfigurability of quadruped rovers, which consists of obtaining optimal locomotion modes, and transitioning between them. A 2D sagittal plane rover model is considered based on a domestic cat. Using a Genetic Algorithm, the gait, pose and control variables that minimize torque or maximize speed are found separately. The optimization approach takes into account the elimination of leg impact, while considering the entire variable spectrum. The optimal solutions are consistent with other works on gait optimization, and are similar to gaits found in quadruped animals as well. An online model-free gait planning framework is also implemented, that is based on Central Pattern Generators is implemented. It is used to generate joint and control trajectories for any arbitrarily varying speed profile, and shown to regulate locomotion transition and speed modulation, both endogenously and continuously.

A Framework for Effective Assessment of Model-based Projections of Biodiversity to Inform the Next Generation of Global Conservation Targets

NASA Astrophysics Data System (ADS)

Myers, B.; Beard, T. D.; Weiskopf, S. R.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.; Casey, K.; Lenton, T. M.; Leidner, A. K.; Ruane, A. C.; Ferrier, S.; Serbin, S.; Matsuda, H.; Shiklomanov, A. N.; Rosa, I.

2017-12-01

Biodiversity and ecosystems services underpin political targets for the conservation of biodiversity; however, previous incarnations of these biodiversity-related targets have not relied on integrated model based projections of possible outcomes based on climate and land use change. Although a few global biodiversity models are available, most biodiversity models lie along a continuum of geography and components of biodiversity. Model-based projections of the future of global biodiversity are critical to support policymakers in the development of informed global conservation targets, but the scientific community lacks a clear strategy for integrating diverse data streams in developing, and evaluating the performance of, such biodiversity models. Therefore, in this paper, we propose a framework for ongoing testing and refinement of model-based projections of biodiversity trends and change, by linking a broad variety of biodiversity models with data streams generated by advances in remote sensing, coupled with new and emerging in-situ observation technologies to inform development of essential biodiversity variables, future global biodiversity targets, and indicators. Our two main objectives are to (1) develop a framework for model testing and refining projections of a broad range of biodiversity models, focusing on global models, through the integration of diverse data streams and (2) identify the realistic outputs that can be developed and determine coupled approaches using remote sensing and new and emerging in-situ observations (e.g., metagenomics) to better inform the next generation of global biodiversity targets.

Pollen-based reconstruction of Holocene climate variability in the Eifel region evaluated with stable isotopes

NASA Astrophysics Data System (ADS)

Kühl, Norbert; Moschen, Robert; Wagner, Stefanie

2010-05-01

Pollen as well as stable isotopes have great potential as climate proxy data. While variability in these proxy data is frequently assumed to reflect climate variability, other factors than climate, including human impact and statistical noise, can often not be excluded as primary cause for the observed variability. Multiproxy studies offer the opportunity to test different drivers by providing different lines of evidence for environmental change such as climate variability and human impact. In this multiproxy study we use pollen and peat humification to evaluate to which extent stable oxygen and carbon isotope series from the peat bog "Dürres Maar" reflect human impact rather than climate variability. For times before strong anthropogenic vegetation change, isotope series from Dürres Maar were used to validate quantitative reconstructions based on pollen. Our study site is the kettle hole peat bog "Dürres Maar" in the Eifel low mountain range, Germany (450m asl), which grew 12m during the last 10,000 years. Pollen was analysed with a sum of at least 1000 terrestrial pollen grains throughout the profile to minimize statistical effects on the reconstructions. A recently developed probabilistic indicator taxa method ("pdf-method") was used for the quantitative climate estimates (January and July temperature) based on pollen. For isotope analysis, attention was given to use monospecific Sphagnum leaves whenever possible, reducing the potential of a species effect and any potential artefact that can originate from selective degradation of different morphological parts of Sphagnum plants (Moschen et al., 2009). Pollen at "Dürres Maar" reflect the variable and partly strong human impact on vegetation during the last 4000 years. Stable isotope time series were apparently not influenced by human impact at this site. This highlights the potential of stable isotope investigations from peat for climatic interpretation, because stable isotope series from lacustrine

Knowledge Base for Automatic Generation of Online IMS LD Compliant Course Structures

ERIC Educational Resources Information Center

Pacurar, Ecaterina Giacomini; Trigano, Philippe; Alupoaie, Sorin

2006-01-01

Our article presents a pedagogical scenarios-based web application that allows the automatic generation and development of pedagogical websites. These pedagogical scenarios are represented in the IMS Learning Design standard. Our application is a web portal helping teachers to dynamically generate web course structures, to edit pedagogical content…

DietPal: A Web-Based Dietary Menu-Generating and Management System

PubMed Central

Abdullah, Siti Norulhuda; Shahar, Suzana; Abdul-Hamid, Helmi; Khairudin, Nurkahirizan; Yusoff, Mohamed; Ghazali, Rafidah; Mohd-Yusoff, Nooraini; Shafii, Nik Shanita; Abdul-Manaf, Zaharah

2004-01-01

Background Attempts in current health care practice to make health care more accessible, effective, and efficient through the use of information technology could include implementation of computer-based dietary menu generation. While several of such systems already exist, their focus is mainly to assist healthy individuals calculate their calorie intake and to help monitor the selection of menus based upon a prespecified calorie value. Although these prove to be helpful in some ways, they are not suitable for monitoring, planning, and managing patients' dietary needs and requirements. This paper presents a Web-based application that simulates the process of menu suggestions according to a standard practice employed by dietitians. Objective To model the workflow of dietitians and to develop, based on this workflow, a Web-based system for dietary menu generation and management. The system is aimed to be used by dietitians or by medical professionals of health centers in rural areas where there are no designated qualified dietitians. Methods First, a user-needs study was conducted among dietitians in Malaysia. The first survey of 93 dietitians (with 52 responding) was an assessment of information needed for dietary management and evaluation of compliance towards a dietary regime. The second study consisted of ethnographic observation and semi-structured interviews with 14 dietitians in order to identify the workflow of a menu-suggestion process. We subsequently designed and developed a Web-based dietary menu generation and management system called DietPal. DietPal has the capability of automatically calculating the nutrient and calorie intake of each patient based on the dietary recall as well as generating suitable diet and menu plans according to the calorie and nutrient requirement of the patient, calculated from anthropometric measurements. The system also allows reusing stored or predefined menus for other patients with similar health and nutrient requirements

DietPal: a Web-based dietary menu-generating and management system.

PubMed

Noah, Shahrul A; Abdullah, Siti Norulhuda; Shahar, Suzana; Abdul-Hamid, Helmi; Khairudin, Nurkahirizan; Yusoff, Mohamed; Ghazali, Rafidah; Mohd-Yusoff, Nooraini; Shafii, Nik Shanita; Abdul-Manaf, Zaharah

2004-01-30

Attempts in current health care practice to make health care more accessible, effective, and efficient through the use of information technology could include implementation of computer-based dietary menu generation. While several of such systems already exist, their focus is mainly to assist healthy individuals calculate their calorie intake and to help monitor the selection of menus based upon a prespecified calorie value. Although these prove to be helpful in some ways, they are not suitable for monitoring, planning, and managing patients' dietary needs and requirements. This paper presents a Web-based application that simulates the process of menu suggestions according to a standard practice employed by dietitians. To model the workflow of dietitians and to develop, based on this workflow, a Web-based system for dietary menu generation and management. The system is aimed to be used by dietitians or by medical professionals of health centers in rural areas where there are no designated qualified dietitians. First, a user-needs study was conducted among dietitians in Malaysia. The first survey of 93 dietitians (with 52 responding) was an assessment of information needed for dietary management and evaluation of compliance towards a dietary regime. The second study consisted of ethnographic observation and semi-structured interviews with 14 dietitians in order to identify the workflow of a menu-suggestion process. We subsequently designed and developed a Web-based dietary menu generation and management system called DietPal. DietPal has the capability of automatically calculating the nutrient and calorie intake of each patient based on the dietary recall as well as generating suitable diet and menu plans according to the calorie and nutrient requirement of the patient, calculated from anthropometric measurements. The system also allows reusing stored or predefined menus for other patients with similar health and nutrient requirements. We modeled the workflow of