Dynamic strength of the interaction between lung surfactant protein D (SP-D) and saccharide ligands
DEFF Research Database (Denmark)
Thormann, Esben; Dreyer, Jakob K; Simonsen, Adam C
2007-01-01
In order to investigate the dynamic strength of the interaction between lung surfactant protein D (SP-D) and different sugars, maltose, mannose, glucose, and galactose, we have used an atomic force microscope to monitor the interaction on a single molecule scale. The experiment is performed...
DEFF Research Database (Denmark)
Greisen, S R; Rasmussen, T K; Stengaard-Pedersen, K
2014-01-01
OBJECTIVES: Programmed death-1 (PD-1) is an immunoregulatory molecule functioning by down-regulating immune responses. PD-1 is present on follicular helper T cells (TFH) and is important in the formation of plasma cells. PD-1 exists in a bioactive soluble form (sPD-1) and is thought to be implica......OBJECTIVES: Programmed death-1 (PD-1) is an immunoregulatory molecule functioning by down-regulating immune responses. PD-1 is present on follicular helper T cells (TFH) and is important in the formation of plasma cells. PD-1 exists in a bioactive soluble form (sPD-1) and is thought...... Questionnaire (HAQ) score, immunoglobulin M rheumatoid factor (IgM-RF), anti-cyclic citrullinated peptide (anti-CCP) antibodies, C-reactive protein (CRP), interleukin-21 (IL-21), and total Sharp score (TSS). We also measured sPD-1 in plasma from healthy volunteers (HV) (n = 20) and in plasma and synovial fluid...
Kohler, Susanna
2016-06-01
Editors note:This week were in Boulder, Colorado at the47th meeting of the AAS Solar Physics Division (SPD). Follow along to catch some of the latest news from the field of solar physics!Yesterdayspress conference was titled Preparing for the 2017 Great American Eclipse. Four speakers highlighted both outreach and research projects that are planned for the eclipse that will cross the continental United States on August 21st next year.Eclipse from High AltitudeFirst up, Angela Des Jardins (Montana Space Grant Consortium) introduced us to the nationwide Eclipse Ballooning Project.An eclipse as seen from the ISS. Being up high gives you a very different perspective on eclipses! [NASA]The last total solar eclipse in the continental United States was in 1979, and people were told to stay inside and watch from their TVs! For the next total solar eclipse in the US, we want the opposite: for everyone to be outdoors and in the path of totality to watch (with eclipse glasses lets be safe)! This eclipse is a fantastic educational opportunity, and a way to reach an enormous audience.And what better way to experience the eclipse than to be involved? The Eclipse Ballooning Project is involving more than 50 student teams from 30 states to fly high-altitude balloons at 20 locations along the total eclipse path. These balloons will send live videos and images from the edge of space to the NASA website.Why? Being someplace high up provides an entirely different view for an eclipse! Instead of looking up to watch the Moon slide in front of the Sun, you can look down to watch the Moons shadow race across the Earths surface at thousands of miles per hour. This unique perspective is rare, and has certainly never been covered live. This will be an awesome addition to other coverage of the eclipse!At Maximum TotalityThe next speaker, Gordon Emslie, described the outreach efforts planned at his institution, Western Kentucky University (WKU). The location where the eclipse totality will
Kohler, Susanna
2016-06-01
Editors note: This week were in Boulder, Colorado at the 47th meeting of the AAS Solar Physics Division (SPD). Follow along to catch some of the latest news from the field of solar physics!The 2016 SPD meeting was launched this morning from the University of Colorado Boulder campus. Two of the hot topics at this years meeting include celebration of the recent move of the National Solar Observatorys headquarters to Boulder, and discussion of the future Daniel K. Inouye Solar Telescope (DKIST, formerly the Advanced Technology Solar Telescope, ATST). DKIST, planned for a 2019 completion in Hawaii, is the next big telescope on the horizon for solar physics.Todays press conference had an interesting focus: instruments providing new high-energy observations of the Sun. Representatives from four different instruments were here to talk about some of the latest X-ray solar observations.GRIPSThe GRIPS payload flew at 130,000 ft over Antarctica on a giant balloon in January 2016. [NASA/Albert Shih]First up, Albert Shih (NASA Goddard) described the Gamma-Ray Imager/Polarimeter for Solar flares, or GRIPS. GRIPS is a balloon-borne instrument designed to detect X-rays and gamma rays emitted during solar flares. Up to tens of a percent of the energy in solar flares is emitted in the form of accelerated particles, but the physics behind this process is not well understood. GRIPS observes where the highest-energy particles are accelerated, in an effort to learn more about the process.GRIPS was launched on 19 January, 2016 and flew for roughly 12 days gathering ~1 million seconds of data! The logistics of this instruments flight are especially interesting, since it was launched from Antarctica and carried by a balloon at a whopping elevation of 130,000 ft (to get high enough that the atmosphere doesnt absorb all the photons GRIPS is trying to observe). Though the data from the mission has been retrieved, the bulk of the hardware remains where it landed at the end of January. It must
SPD very front end electronics
International Nuclear Information System (INIS)
Luengo, S.; Gascon, D.; Comerma, A.; Garrido, L.; Riera, J.; Tortella, S.; Vilasis, X.
2006-01-01
The Scintillator Pad Detector (SPD) is part of the LHCb calorimetry system [D. Breton, The front-end electronics for LHCb calorimeters, Tenth International Conference on Calorimetry in Particle Physics, CALOR, Pasadena, 2002] that provides high-energy hadron, electron and photon candidates for the first level trigger. The SPD is designed to distinguish electrons from photons. It consists of a plastic scintillator layer, divided into about 6000 cells of different size to obtain better granularity near the beam [S. Amato, et al., LHCb technical design report, CERN/LHCC/2000-0036, 2000]. Charged particles will produce, and photons will not, ionization in the scintillator. This ionization generates a light pulse that is collected by a WaveLength Shifting (WLS) fiber that is coiled inside the scintillator cell. The light is transmitted through a clear fiber to the readout system that is placed at the periphery of the detector. Due to space constraints, and in order to reduce costs, these 6000 cells are divided in groups using a MAPMT [Z. Ajaltouni, et al., Nucl. Instr. and Meth. A 504 (2003) 9] of 64 channels that provides information to the VFE readout electronics. The SPD signal has rather large statistical fluctuations because of the low number (20-30) of photoelectrons per MIP. Therefore the signal is integrated over the whole bunch crossing length of 25 ns in order to have the maximum value. Since in average about 85% of the SPD signal is within 25 ns, 15% of a sample is subtracted from the following one using an operational amplifier. The SPD VFE readout system that will be presented consists of the following components. A specific ASIC [D. Gascon, et al., Discriminator ASIC for the VFE SPD of the LHCb Calorimeter, LHCB Technical Note, LHCB 2004-xx] integrates the signal, makes the signal-tail subtraction, and compares the level obtained to a programmable threshold (to distinguish electrons from photons). A FPGA programmes the ASIC threshold and the value for
The energy policy message of the Hamburg SPD party congress
International Nuclear Information System (INIS)
Heller, W.
2007-01-01
On October 26-28 this year, the Social Democratic (SPD) party congress was held in Hamburg; its new party platform, the so-called ''Hamburg Program,'' constitutes a landmark for the party. The Program's chapter on ''Sustainable Progress and Qualitative Growth'' refers to energy policy in the section about ''Turning Point in Energy Policy; Environmental Protection.'' Emphasis is given to the fact that energy, like air and water, is a basis of life of our civilization, and that the present ways of wasting energy and resources have no future. For this reason, the turnaround in energy policy initiated by the SPD must be advanced in the key issue of switching from non-renewable to renewable energy resources and from polluting to non-polluting resources. The ultimate goal is a solar age. As far as nuclear power is concerned, the Social Democratic Party finds that nuclear fission appeared to many as the big hope for energy available forever, but that these hopes cannot come true. To put it in a nutshell: The SPD is fast embarking on the road into a solar age. The party does see the growing world population and the rising energy requirement as well as the resulting challenges. However, its energy policy concept is too rigidly focused on Germany and the country's pioneering role. At the present time, nuclear power stands no chance in the SPD, although the Hamburg declaration includes a cautious reminder of the fact that, until 1986, the SPD was among the proponents of nuclear power. (orig.)
Nuclear energy - a challenge to the SPD
International Nuclear Information System (INIS)
Hauff, V.
1977-01-01
The author discusses the different aspects of the peaceful use of nuclear energy as a political issue from the point of view of the SPD (a political party in West Germany). In detail, he deals with the continuity of political work, concrete objectives, and the technical conference held by the SPD in April, 1978. (HK) [de
The ALICE Silicon Pixel Detector System (SPD)
Kluge, A; Antinori, Federico; Burns, M; Cali, I A; Campbell, M; Caselle, M; Ceresa, S; Dima, R; Elias, D; Fabris, D; Krivda, Marian; Librizzi, F; Manzari, Vito; Morel, M; Moretto, Sandra; Osmic, F; Pappalardo, G S; Pepato, Adriano; Pulvirenti, A; Riedler, P; Riggi, F; Santoro, R; Stefanini, G; Torcato De Matos, C; Turrisi, R; Tydesjo, H; Viesti, G; PH-EP
2007-01-01
The ALICE silicon pixel detector (SPD) comprises the two innermost layers of the ALICE inner tracker system. The SPD includes 120 detector modules (half-staves) each consisting of 10 ALICE pixel chips bump bonded to two silicon sensors and one multi-chip read-out module. Each pixel chip contains 8192 active cells, so that the total number of pixel cells in the SPD is ≈ 107. The on-detector read-out is based on a multi-chip-module containing 4 ASICs and an optical transceiver module. The constraints on material budget and detector module dimensions are very demanding.
Introduction to dynamic programming
Cooper, Leon; Rodin, E Y
1981-01-01
Introduction to Dynamic Programming provides information pertinent to the fundamental aspects of dynamic programming. This book considers problems that can be quantitatively formulated and deals with mathematical models of situations or phenomena that exists in the real world.Organized into 10 chapters, this book begins with an overview of the fundamental components of any mathematical optimization model. This text then presents the details of the application of dynamic programming to variational problems. Other chapters consider the application of dynamic programming to inventory theory, Mark
Dual Dynamic Programming - DDP
International Nuclear Information System (INIS)
Velasquez Bermudez, Jesus M
1998-01-01
Objections are presented to the mathematical formulation of the denominated Dual Dynamic programming-PDD that is the theoretical base of several computational model available for the optimal formulation of interconnected hydrothermal systems
Report of International NanoSPD Steering Committee and statistics on recent NanoSPD activities
International Nuclear Information System (INIS)
Valiev, R Z; Langdon, T G
2014-01-01
Abstract. The Université de Lorraine in Metz, France, is the selected site for the 6th International Conference on Nanomaterials by Severe Plastic Deformation (NanoSPD6) following a series of five earlier conferences. This introductory paper reports on several major developments in NanoSPD activities as well as on very recent NanoSPD citation data which confirm the continued growth and expansion of this important research area. Close attention is given to the topics of workshops, conferences and seminars organized during these last three years as well as on books and reviews published prior to the NanoSPD6 conference. A special concern of the committee is in introducing and discussing the appropriate terminology to be applied in this new field of materials science and engineering
Bender, Christian; Gärtner, Christian; Schweizer, Nikolaus
2017-01-01
We present a novel method for deriving tight Monte Carlo confidence intervals for solutions of stochastic dynamic programming equations. Taking some approximate solution to the equation as an input, we construct pathwise recursions with a known bias. Suitably coupling the recursions for lower and
NanoSPD activity in Ufa and International Cooperation
International Nuclear Information System (INIS)
Reshetnikova, N; Salakhova, M
2014-01-01
This report presents main achievements of R and D activities of the Institute of Physics of Advanced Materials of Ufa State Aviation Technical University (IPAM USATU, Ufa, Russia) with a special attention to innovative potential of nanostructured metals and alloys produced by the severe plastic deformation (SPD) techniques. Several examples of the first promising applications of bulk nanostructured materials (BNM) as well as potential competing technologies are considered and discussed. The authors would like to focus special emphasis on international cooperation in view of numerous emerging projects as well as different conferences and seminars that pave the way to close and fruitful cooperation, working visits and exchange of young scientists. The possibilities of international cooperation through various foundations and programs are considered
Remediation of spatial processing disorder (SPD).
Graydon, Kelley; Van Dun, Bram; Tomlin, Dani; Dowell, Richard; Rance, Gary
2018-05-01
To determine the efficacy of deficit-specific remediation for spatial processing disorder, quantify effects of remediation on functional listening, and determine if remediation is maintained. Participants had SPD, diagnosed using the Listening in Spatialised Noise-Sentences test. The LiSN and Learn software was provided as auditory training. Post-training, repeat LiSN-S testing was conducted. Questionnaires pre- and post-training acted as subjective measures of remediation. A late-outcome assessment established long-term effects of remediation. Sixteen children aged between 6;3 [years; months] and 10;0 completed between 20 and 146 training games. Post-training LiSN-S improved in measures containing spatial cues (p ≤ 0.001) by 2.0 SDs (3.6 dB) for DV90, 1.8 SDs for SV90 (3.2 dB), 1.4 SDs for spatial advantage (2.9 dB) and 1.6 SDs for total advantage (3.3 dB). Improvement was also found in the DV0 condition (1.4 dB or 0.5 SDs). Post-training changes were not significant in the talker advantage measure (1.0 dB or 0.4 SDs) or the SV0 condition (0.3 dB or 0.1 SDs). The late-outcome assessment demonstrated improvement was maintained. Subjective improvement post-remediation was observed using the parent questionnaire. Children with SPD had improved ability to utilise spatial cues following deficit-specific remediation, with the parent questionnaire sensitive to remediation. Effects of the remediation also appear to be sustained.
Signal Processing Device (SPD) for networked radiation monitoring system
International Nuclear Information System (INIS)
Dharmapurikar, A.; Bhattacharya, S.; Mukhopadhyay, P.K.; Sawhney, A.; Patil, R.K.
2010-01-01
A networked radiation and parameter monitoring system with three tier architecture is being developed. Signal Processing Device (SPD) is a second level sub-system node in the network. SPD is an embedded system which has multiple input channels and output communication interfaces. It acquires and processes data from first level parametric sensor devices, and sends to third level devices in response to request commands received from host. It also performs scheduled diagnostic operations and passes on the information to host. It supports inputs in the form of differential digital signals and analog voltage signals. SPD communicates with higher level devices over RS232/RS422/USB channels. The system has been designed with main requirements of minimal power consumption and harsh environment in radioactive plants. This paper discusses the hardware and software design details of SPD. (author)
Linking surfactant protein SP-D and IL-13
DEFF Research Database (Denmark)
Qaseem, Asif S; Sonar, Sanchaita; Mahajan, Lakshna
2012-01-01
of allergen-IgE interaction, histamine release by sensitised mast cells, downregulation of specific IgE production, suppression of pulmonary and peripheral eosinophilia, inhibition of mechanisms that cause airway remodelling, and induction of apoptosis in sensitised eosinophils. SP-D can also shift helper T......Surfactant protein D (SP-D) is an innate immune molecule that plays a protective role against lung infection, allergy, asthma and inflammation. In vivo experiments with murine models have shown that SP-D can protect against allergic challenge via a range of mechanisms including inhibition...... cell polarisation following in vivo allergenic challenge, from pathogenic Th2 to a protective Th1 cytokine response. Interestingly, SP-D gene deficient (-/-) mice show an IL-13 over-expressing phenotype. IL-13 has been shown to be involved in the development of asthma. Transgenic mice over...
Stochastic integer programming by dynamic programming
Lageweg, B.J.; Lenstra, J.K.; Rinnooy Kan, A.H.G.; Stougie, L.; Ermoliev, Yu.; Wets, R.J.B.
1988-01-01
Stochastic integer programming is a suitable tool for modeling hierarchical decision situations with combinatorial features. In continuation of our work on the design and analysis of heuristics for such problems, we now try to find optimal solutions. Dynamic programming techniques can be used to
Mun, Soo-Hyun
2011-12-31
This paper aimed to examine the debate over the fertility decline in the German Empire, focusing on the role of the SPD. During the German Empire, the fertility rate dramatically declined and the growing awareness of a continuous decline in the birth rate prompted a massive debate among politicians, doctors, sociologists, and feminist activists. The fertility decline was negatively evaluated and generated consciousness of crisis. However, it was not the only way to face this new phenomenon. Indeed, the use of birth control among the upper class was interpreted as a part of a modernizing process. As the same phenomenon reached the working class, it suddenly became a social problem and was attributed to the SPD. The debate over the fertility decline in imperial German society ridden with a fierce class conflict was developed into a weapon against the SPD. Contrary to the assumption of conservative politicians, the SPD had no clear-cut position on this issue. Except for a few politicians like Kautsky and the doctors who came into frequent contact with the workers, the "birth strike" was not listed as the main interest of the SPD. Even Clara Zetkin, the leader of the Social Democratic women's organization viewed it as a concern of the individual person which could not be incorporated in the party program. The women's organization of the SPD put priority on class conflict rather than issues specific to women. As a result, the debate over the birth rate decline within the SPD was not led by the women themselves. There could have been various means to stimulate the birth rate. Improvement in the welfare system, such as tax relief for large families, better housing conditions, and substantial maternity protection, could have been feasible solutions to the demographic crisis. However, Germany chose to respond to this crisis by imposing legal sanctions against birth control. In addition to paragraphs 218-220 of the German criminal law enacted in 1872 which prescribed penal
Introduction to stochastic dynamic programming
Ross, Sheldon M; Lukacs, E
1983-01-01
Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist-providing counterexamples where appropriate-and the
Dynamic Programming Foundations and Principles
Sniedovich, Moshe
2010-01-01
Focusing on the modeling and solution of deterministic multistage decision problems, this book looks at dynamic programming as a problem-solving optimization method. With over 400 useful references, this edition discusses the dynamic programming analysis of a problem, illustrates the rationale behind this analysis, and clarifies the theoretical grounds that justify the rationale. It also explains the meaning and role of the concept of state in dynamic programming, examines the purpose and function of the principle of optimality, and outlines solution strategies for problems defiant of conventi
Dynamic programming models and applications
Denardo, Eric V
2003-01-01
Introduction to sequential decision processes covers use of dynamic programming in studying models of resource allocation, methods for approximating solutions of control problems in continuous time, production control, more. 1982 edition.
1978-10-01
8 Track Bushing Research, . . . . . . . . . . . * . . . 8 Advanced frack Concept Development ..... . . . . . 9 TECHNICAL DISCUSSION...machine design effort was conducted. The design which was developed has separate servocontrolled hydraulic actuators to apply radial...back bending-but, in the order and magnitude of the way the torsional stress is incurred in service. This suggests a programable, hydraulically actuated
Directory of Open Access Journals (Sweden)
Mühlfeld Christian
2007-10-01
Full Text Available Abstract Background Surfactant protein D (SP-D deficient mice develop emphysema-like pathology associated with focal accumulations of foamy alveolar macrophages, an excess of surfactant phospholipids in the alveolar space and both hypertrophy and hyperplasia of alveolar type II cells. These findings are associated with a chronic inflammatory state. Treatment of SP-D deficient mice with a truncated recombinant fragment of human SP-D (rfhSP-D has been shown to decrease the lipidosis and alveolar macrophage accumulation as well as production of proinflammatory chemokines. The aim of this study was to investigate if rfhSP-D treatment reduces the structural abnormalities in parenchymal architecture and type II cells characteristic of SP-D deficiency. Methods SP-D knock-out mice, aged 3 weeks, 6 weeks and 9 weeks were treated with rfhSP-D for 9, 6 and 3 weeks, respectively. All mice were sacrificed at age 12 weeks and compared to both PBS treated SP-D deficient and wild-type groups. Lung structure was quantified by design-based stereology at the light and electron microscopic level. Emphasis was put on quantification of emphysema, type II cell changes and intracellular surfactant. Data were analysed with two sided non-parametric Mann-Whitney U-test. Main Results After 3 weeks of treatment, alveolar number was higher and mean alveolar size was smaller compared to saline-treated SP-D knock-out controls. There was no significant difference concerning these indices of pulmonary emphysema within rfhSP-D treated groups. Type II cell number and size were smaller as a consequence of treatment. The total volume of lamellar bodies per type II cell and per lung was smaller after 6 weeks of treatment. Conclusion Treatment of SP-D deficient mice with rfhSP-D leads to a reduction in the degree of emphysema and a correction of type II cell hyperplasia and hypertrophy. This supports the concept that rfhSP-D might become a therapeutic option in diseases that are
Grain refinement through severe plastic deformation (SPD) processing
International Nuclear Information System (INIS)
Izairi, N.; Vevecka - Priftaj, A.
2012-01-01
There is considerable current interest in processing metallic samples through procedures involving the imposition of severe plastic deformation (SPD). These procedures lead to very significant grain refinement to the submicrometer or even the nanometer level, resulting in advanced physical properties. Among various SPD processes, Equal Channel Angular Pressing, High pressure Torsion and Accumulated Roll Bonding have been widely used for many metals and alloys. In the present work, we present an overview of the most used methods of SPD for grain refinement and the production of bulk nano structured materials with enhancement in their mechanical and functional properties. In order to examine the potential for using ECAP to refine the grain size and improve the mechanical properties, two commercial 5754 Al alloy and AA 3004 , were selected for study. Processing by ECAP gives a reduction in the grain size and an increase in the microhardness. (Author)
Secure Dynamic Program Repartitioning
DEFF Research Database (Denmark)
Hansen, Rene Rydhoff; Probst, Christian
2005-01-01
Secure program partitioning has been introduced as a language-based technique to allow the distribution of data and computation across mutualy untrusted hosts, while at the same time guaranteeing the protection of confidential data. Programs that have been annotated with security types......, but the partitioning compiler becomes a part of the network and can recompile applications, thus alowing hosts to enter or leave the framework. We contend that this setting is superior to static partitioning, since it allows redistribution of data and computations. This is especialy beneficial if the new host alows...... data and computations to better fulfil the trust requirements of the users. Erasure Policies ensure that the original host of the redistributed data or computation does not store the data any longer....
DEFF Research Database (Denmark)
Sørensen, Grith Lykke; Hoegh, Silje V; Leth-Larsen, Rikke
2009-01-01
-D compared to Met11 SP-D. Multimerization has proven important for enhancement of microbial phagocytosis. In the present study defined multimeric forms of Met11Thr SP-D were isolated from human amniotic fluid. Implementation of ManNAc-affinity chromatography allowed high recovery of natural trimeric SP......-D multimers. Trimeric SP-D subunits also showed greater binding to endogenous lipoproteins: LDL, oxLDL, and HDL, than multimeric SP-D. In conclusion, purified trimeric and multimeric SP-D represent separate and only partly interconvertible molecular populations with distinct biochemical properties....
Charter of the Sandia National Laboratories Sandia Postdoctoral Development (SPD) Association.
Energy Technology Data Exchange (ETDEWEB)
McBride, Amber Alane Fisher; McBride, Amber Alane Fisher; Rodgers, Theron; Dong, Wen; Juan, Pierre-Alexandre; Barkholtz, Heather; Alley, William Morgan; Wolk, Benjamin Matthew; Vane, Zachary Phillips; Priye, Aashish; Ball, Cameron Scott; McBride, Amber Alane Fisher
2017-03-01
The SNL SPD Association represents all personnel that are classified as Postdoctoral Appointees at Sandia National Laboratories. The purpose of the SNL SPD Association is to address the needs and concerns of Postdoctoral Appointees within Sandia National Laboratories.
Energy Technology Data Exchange (ETDEWEB)
McBride, Amber Alane Fisher; McBride, Amber Alane Fisher; Rodgers, Theron; Dong, Wen; Juan, Pierre-Alexandre; Barkholtz, Heather; Alley, William Morgan; Wolk, Benjamin Matthew; Vane, Zachary Phillips; Priye, Aashish; Ball, Cameron Scott
2017-03-01
The purpose of this document is to define the rules of governance for the Sandia Postdoctoral Development (SPD) Association. This includes election procedures for filling vacancies on the SPD board, an all-purpose voting procedure, and definitions for the roles and responsibilities of each SPD board member. The voting procedures can also be used to amend the by-laws, as well as to create, dissolve, or consolidate vacant SPD board positions.
Serum-surfactant SP-D correlates inversely to lung function in cystic fibrosis
DEFF Research Database (Denmark)
Olesen, Hanne Vebert; Holmskov, Uffe; Schiøtz, Peter Oluf
2010-01-01
BACKGROUND: Cystic fibrosis (CF) affects the lungs causing infections and inflammation. Surfactant protein D (SP-D) is an innate defense lectin primarily secreted in the lungs. We investigated the influence of the SP-D Met11Thr polymorphism on CF lung function; and serum SP-D as a marker for CF...
Incidence of sleep pattern disturbance (SPD) in a hemodialysis sample.
Strangio, D; Locking-Cusolito, H
1999-01-01
Personal experience suggests that sleep pattern disturbance (SPD) is a serious problem for the patients we serve. The purpose of this study was to identify the scope of sleep problems among all willing patients in a medium-sized hemodialysis unit in a university teaching centre. This descriptive study examined SPD through the use of a sleep diary that subjects were asked to complete each morning for a week. Subjects were asked to describe sleep latency, sleep quantity, number of arousals, whether they awoke feeling rested, factors that interfered with sleep the night before, and sleep inducers employed the night before. They were also asked to record their dialysis schedule. Each subject's chart was reviewed with respect to medications and evidence of other medical problems that interfered with sleep. Findings were benchmarked with results from the literature. Information regarding facilitators and barriers to sleep has provided some basis for an interdisciplinary plan of care to address this distressing problem.
Radiation hardness on very front-end for SPD
International Nuclear Information System (INIS)
Cano, Xavier; Graciani, Ricardo; Gascon, David; Garrido, Lluis; Bota, Sebastia; Herms, Atila; Comerma, Albert; Riera, Jordi
2005-01-01
The calorimeter front-end electronics of the LHCb experiment will be located in a region, which is not protected from radiation. Therefore, all the electronics must be qualified to stand some defined radiation levels. The procedure, measurements and results of an irradiation test for every component of the very front-end SPD detector, which is part of the LHCb calorimeter are presented here. All the tested components, except a custom made ASIC, are commercially available
DEFF Research Database (Denmark)
Knudsen, Lars; Ochs, Katharina; Boxler, Laura
2013-01-01
Surfactant protein D (SP-D) is part of the innate immune system involved in lung homeostasis. SP-D knockout mice show accumulations of foamy alveolar macrophages, alveolar lipoproteinosis and pulmonary emphysema. Three single nucleotide polymorphisms (SNPs) have been described in the coding...
DEFF Research Database (Denmark)
Wueseke, Oliver; Bunkenborg, Jakob; Hein, Marco Y
2014-01-01
mostly as a monomer but also forms complexes with the PP2A-regulatory proteins RSA-1 and RSA-2, which are required for microtubule organization at centrosomes. These results suggest that the interactions between SPD-2, SPD-5, and PLK-1 do not result in formation of cytoplasmic complexes, but instead...
Fluid dynamics computer programs for NERVA turbopump
Brunner, J. J.
1972-01-01
During the design of the NERVA turbopump, numerous computer programs were developed for the analyses of fluid dynamic problems within the machine. Program descriptions, example cases, users instructions, and listings for the majority of these programs are presented.
Neutrophil programming dynamics and its disease relevance.
Ran, Taojing; Geng, Shuo; Li, Liwu
2017-11-01
Neutrophils are traditionally considered as first responders to infection and provide antimicrobial host defense. However, recent advances indicate that neutrophils are also critically involved in the modulation of host immune environments by dynamically adopting distinct functional states. Functionally diverse neutrophil subsets are increasingly recognized as critical components mediating host pathophysiology. Despite its emerging significance, molecular mechanisms as well as functional relevance of dynamically programmed neutrophils remain to be better defined. The increasing complexity of neutrophil functions may require integrative studies that address programming dynamics of neutrophils and their pathophysiological relevance. This review aims to provide an update on the emerging topics of neutrophil programming dynamics as well as their functional relevance in diseases.
SP-D as a biomarker for COPD in the Lebanese population
DEFF Research Database (Denmark)
Akiki, Zeina; Fakih, Dalia; Jounblat, Rania
2014-01-01
Background: Surfactant protein D (SP-D), a promising systemic biomarker of chronic obstructive pulmonary disease (COPD) was never evaluated in the Lebanese population. Objective: The validity of serum SP-D as a biomarker for COPD, in comparison with C-reactive protein (CRP) and fibrinogen was inv...
Rule of Thumb and Dynamic Programming
Lettau, M.; Uhlig, H.F.H.V.S.
1995-01-01
This paper studies the relationships between learning about rules of thumb (represented by classifier systems) and dynamic programming. Building on a result about Markovian stochastic approximation algorithms, we characterize all decision functions that can be asymptotically obtained through
Dynamic Programming: An Introduction by Example
Zietz, Joachim
2007-01-01
The author introduces some basic dynamic programming techniques, using examples, with the help of the computer algebra system "Maple". The emphasis is on building confidence and intuition for the solution of dynamic problems in economics. To integrate the material better, the same examples are used to introduce different techniques. One covers the…
Guidelines for dynamic international programs
International Nuclear Information System (INIS)
Gold, M.A.
1993-01-01
Matters of global concern-deforestation, global warming, biodiversity loss, sustainable development, fuelwood crises, watershed destruction, and large-scale flooding-frequently involve forests and natural resources. In the future, university students will enter a global setting that more than ever depends on a strong knowledge of international issues. USA land-grant universities are attempting to prepare students for this challenge by improving their international programs including forestry. To improve university programs, several factors will need to be addressed and are discussed, with examples, in this article: commitment of the faculty; program specialization; geographic specialization; reward systems for international contributions; international collaboration; recycled dollars within the university; active teaching programs; research; extention and outreach; language training; international faculty; travel grants; twinning relationships with sister institutions; selective in pursuit of international development assistance; and study centers. 6 refs
Evaluating Dynamic Analysis Techniques for Program Comprehension
Cornelissen, S.G.M.
2009-01-01
Program comprehension is an essential part of software development and software maintenance, as software must be sufficiently understood before it can be properly modified. One of the common approaches in getting to understand a program is the study of its execution, also known as dynamic analysis.
Hybrid Differential Dynamic Programming with Stochastic Search
Aziz, Jonathan; Parker, Jeffrey; Englander, Jacob
2016-01-01
Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASAs Dawn mission. The Dawn trajectory was designed with the DDP-based Static Dynamic Optimal Control algorithm used in the Mystic software. Another recently developed method, Hybrid Differential Dynamic Programming (HDDP) is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.
Dynamic programming for QFD in PES optimization
Energy Technology Data Exchange (ETDEWEB)
Sorrentino, R. [Mediterranean Univ. of Reggio Calabria, Reggio Calabria (Italy). Dept. of Computer Science and Electrical Technology
2008-07-01
Quality function deployment (QFD) is a method for linking the needs of the customer with design, development, engineering, manufacturing, and service functions. In the electric power industry, QFD is used to help designers concentrate on the most important technical attributes to develop better electrical services. Most optimization approaches used in QFD analysis have been based on integer or linear programming. These approaches perform well in certain circumstances, but there are problems that hinder their practical use. This paper proposed an approach to optimize Power and Energy Systems (PES). A dynamic programming approach was used along with an extended House of Quality to gather information. Dynamic programming was used to allocate the limited resources to the technical attributes. The approach integrated dynamic programming into the electrical service design process. The dynamic programming approach did not require the full relationship curve between technical attributes and customer satisfaction, or the relationship between technical attributes and cost. It only used a group of discrete points containing information about customer satisfaction, technical attributes, and the cost to find the optimal product design. Therefore, it required less time and resources than other approaches. At the end of the optimization process, the value of each technical attribute, the related cost, and the overall customer satisfaction were obtained at the same time. It was concluded that compared with other optimization methods, the dynamic programming method requires less information and the optimal results are more relevant. 21 refs., 2 tabs., 2 figs.
Directory of Open Access Journals (Sweden)
Pal-Val P.
2015-12-01
Full Text Available The effect of annealing on dynamic Young’s modulus, E, of ultrafine-grained (UFG copper obtained by combined severe plastic deformation (SPD is investigated. It is established that Young’s modulus in the SPD-prepared samples exceeds that in the coarse-grained fully annealed (CGFA samples by 10 to 20 %. Isothermal annealing at elevated temperatures between 90 and 630°С leads to a sharp decrease of Young’s modulus for annealing temperatures above 210°С. After annealing at 410°С, the value of E reaches its minimal value that is 35 % lower than E in CGFA samples (total change in E is about 47 % of the initial value. Further annealing at higher temperatures leads to an increase in Young’s modulus. It is shown, that the unusual behavior of Young’s modulus is caused by formation of the axial texture in the SPD-treated samples which then is replaced by the texture during the post-SPD heat treatment.
DEFF Research Database (Denmark)
Fleck, Oliver; Fahnøe, Ulrik; Løvschal, Katrine Vyff
2017-01-01
In fission yeast, the small, intrinsically disordered protein S-phase delaying protein 1 (Spd1) blocks DNA replication and causes checkpoint activation at least in part, by inhibiting the enzyme ribonucleotide reductase, which is responsible for the synthesis of DNA. The CRL4(Cdt2) E3 ubiquitin...... ligase mediates degradation of Spd1 and the related protein Spd2 at S phase of the cell cycle. We have generated a conditional allele of CRL4(Cdt2), by expressing the highly unstable substrate-recruiting protein Cdt2 from a repressible promoter. Unlike Spd1, Spd2 does not regulate deoxynucleotide...... triphosphate (dNTP) pools; yet we find that Spd1 and Spd2 together inhibit DNA replication upon Cdt2 depletion. To directly test whether this block of replication was solely due to insufficient dNTP levels, we established a deoxy-nucleotide salvage pathway in fission yeast by expressing the human nucleoside...
Lung Surfactant Protein D (SP-D) Response and Regulation During Acute and Chronic Lung Injury
DEFF Research Database (Denmark)
Gaunsbaek, Maria Quisgaard; Rasmussen, Karina Juhl; Beers, Michael F.
2013-01-01
in three murine models of lung injury, using a validated ELISA technology for estimation of SP-D levels. METHODS: Mice were exposed to lipopolysaccharide, bleomycin, or Pneumocystis carinii (Pc) and sacrificed at different time points. RESULTS: In lipopolysaccharide-challenged mice, the level of SP...... injury, with a sustained increment during chronic inflammation compared with acute inflammation. A quick upregulation of SP-D in serum in response to acute airway inflammation supports the notion that SP-D translocates from the airways into the vascular system, in favor of being synthesized systemically....... The study also confirms the concept of using increased SP-D serum levels as a biomarker of especially chronic airway inflammation....
Human surfactant protein D: SP-D contains a C-type lectin carbohydrate recognition domain.
Rust, K; Grosso, L; Zhang, V; Chang, D; Persson, A; Longmore, W; Cai, G Z; Crouch, E
1991-10-01
Lung surfactant protein D (SP-D) shows calcium-dependent binding to specific saccharides, and is similar in domain structure to certain members of the calcium-dependent (C-type) lectin family. Using a degenerate oligomeric probe corresponding to a conserved peptide sequence derived from the amino-terminus of the putative carbohydrate binding domain of rat and bovine SP-D, we screened a human lung cDNA library and isolated a 1.4-kb cDNA for the human protein. The relationship of the cDNA to SP-D was established by several techniques including amino-terminal microsequencing of SP-D-derived peptides, and immunoprecipitation of translation products of transcribed mRNA with monospecific antibodies to SP-D. In addition, antibodies to a synthetic peptide derived from a predicted unique epitope within the carbohydrate recognition domain of SP-D specifically reacted with SP-D. DNA sequencing demonstrated a noncollagenous carboxy-terminal domain that is highly homologous with the carboxy-terminal globular domain of previously described C-type lectins. This domain contains all of the so-called "invariant residues," including four conserved cysteine residues, and shows high homology with the mannose-binding subfamily of C-type lectins. Sequencing also demonstrated an amino-terminal collagenous domain that contains an uninterrupted sequence of 59 Gly-X-Y triplets and that also contains the only identified consensus for asparagine-linked oligosaccharides. The studies demonstrate that SP-D is a member of the C-type lectin family, and confirm predicted structural similarities to conglutinin, SP-D, and the serum mannose binding proteins.
Usefulness of serum KL-6 and SP-D in the diagnosis of radiation pneumonitis
International Nuclear Information System (INIS)
Saika, Yoshinori; Doi, Kenji; Misaki, Toshimasa; Tatsumi, Tomoaki; Komori, Tsuyoshi; Narabayashi, Isamu
2004-01-01
The objective of this study was to investigate the usefulness of serum KL-6 and SP-D in the diagnosis of radiation pneumonitis. We measured serum KL-6 and SP-D in patients undergoing radiation therapy of the chest, primarily for lung cancer, in the Department of Radiology, Osaka Medical College and compared the results with the findings on plain chest X-ray films and thoracic computed tomography conducted at the same time. The sensitivity of serum KL-6 and SP-D for diagnosing radiation pneumonitis were 68.2% and 70.0%, respectively, the specificity were 86.6% and 80.0%, and the accuracy were 82.0% and 77.8%. Examination of the relationship between lesion extent and activity and serum KL-6 showed that serum KL-6 values were higher when the lesion extended beyond the irradiation field than when the lesion was confined to within the irradiation field and that the value tended to be lower for old lesions than for active lesions. In patients with radiation pneumonitis in whom serum KL-6 and SP-D could be measured over time, KL-6 tended to increase after the lesion was discovered by imaging, whereas SP-D increased prior to this in many cases. Examination of the comparison between before radiotherapy and just after radiotherapy in the patients with radiation pneumonitis showed that SP-D had a consistent tendency to increase. Both serum KL-6 and SP-D had a satisfactory degree of sensitivity and specificity for diagnosing radiation pneumonitis. Serum KL-6 correlated with the extent and activity of the lesions. The results suggested that serum SP-D may be helpful for the early detection of radiation pneumonitis. (author)
Dynamic analysis program for frame structure
International Nuclear Information System (INIS)
Ando, Kozo; Chiba, Toshio
1975-01-01
A general purpose computer program named ISTRAN/FD (Isub(HI) STRucture ANalysis/Frame structure, Dynamic analysis) has been developed for dynamic analysis of three-dimensional frame structures. This program has functions of free vibration analysis, seismic response analysis, graphic display by plotter and CRT, etc. This paper introduces ISTRAN/FD; examples of its application are shown with various problems : idealization of the cantilever, dynamic analysis of the main tower of the suspension bridge, three-dimensional vibration in the plate girder bridge, seismic response in the boiler steel structure, and dynamic properties of the underground LNG tank. In this last example, solid elements, in addition to beam elements, are especially used for the analysis. (auth.)
Planar multibody dynamics formulation, programming and applications
Nikravesh, Parviz E
2007-01-01
Introduction Multibody Mechanical Systems Types of Analyses Methods of Formulation Computer Programming Application Examples Unit System Remarks Preliminaries Reference Axes Scalars and Vectors Matrices Vector, Array, and Matrix Differentiation Equations and Expressions Remarks Problems Fundamentals of Kinematics A Particle Kinematics of a Rigid Body Definitions Remarks Problems Fundamentals of Dynamics Newton's Laws of Motion Dynamics of a Body Force Elements Applied Forces Reaction Force Remarks Problems Point-Coordinates: Kinematics Multipoint
Configuring Airspace Sectors with Approximate Dynamic Programming
Bloem, Michael; Gupta, Pramod
2010-01-01
In response to changing traffic and staffing conditions, supervisors dynamically configure airspace sectors by assigning them to control positions. A finite horizon airspace sector configuration problem models this supervisor decision. The problem is to select an airspace configuration at each time step while considering a workload cost, a reconfiguration cost, and a constraint on the number of control positions at each time step. Three algorithms for this problem are proposed and evaluated: a myopic heuristic, an exact dynamic programming algorithm, and a rollouts approximate dynamic programming algorithm. On problem instances from current operations with only dozens of possible configurations, an exact dynamic programming solution gives the optimal cost value. The rollouts algorithm achieves costs within 2% of optimal for these instances, on average. For larger problem instances that are representative of future operations and have thousands of possible configurations, excessive computation time prohibits the use of exact dynamic programming. On such problem instances, the rollouts algorithm reduces the cost achieved by the heuristic by more than 15% on average with an acceptable computation time.
The Dynamic Geometrisation of Computer Programming
Sinclair, Nathalie; Patterson, Margaret
2018-01-01
The goal of this paper is to explore dynamic geometry environments (DGE) as a type of computer programming language. Using projects created by secondary students in one particular DGE, we analyse the extent to which the various aspects of computational thinking--including both ways of doing things and particular concepts--were evident in their…
A Dynamic Programming Approach to Constrained Portfolios
DEFF Research Database (Denmark)
Kraft, Holger; Steffensen, Mogens
2013-01-01
This paper studies constrained portfolio problems that may involve constraints on the probability or the expected size of a shortfall of wealth or consumption. Our first contribution is that we solve the problems by dynamic programming, which is in contrast to the existing literature that applies...
Quantum optical device accelerating dynamic programming
Grigoriev, D.; Kazakov, A.; Vakulenko, S.
2005-01-01
In this paper we discuss analogue computers based on quantum optical systems accelerating dynamic programming for some computational problems. These computers, at least in principle, can be realized by actually existing devices. We estimate an acceleration in resolving of some NP-hard problems that can be obtained in such a way versus deterministic computers
Microsoft Dynamics NAV 7 programming cookbook
Raul, Rakesh
2013-01-01
Written in the style of a cookbook. Microsoft Dynamics NAV 7 Programming Cookbook is full of recipes to help you get the job done.If you are a junior / entry-level NAV developer then the first half of the book is designed primarily for you. You may or may not have any experience programming. It focuses on the basics of NAV programming.If you are a mid-level NAV developer, you will find these chapters explain how to think outside of the NAV box when building solutions. There are also recipes that senior developers will find useful.
Efficient dynamic optimization of logic programs
Laird, Phil
1992-01-01
A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.
Stochastic control theory dynamic programming principle
Nisio, Makiko
2015-01-01
This book offers a systematic introduction to the optimal stochastic control theory via the dynamic programming principle, which is a powerful tool to analyze control problems. First we consider completely observable control problems with finite horizons. Using a time discretization we construct a nonlinear semigroup related to the dynamic programming principle (DPP), whose generator provides the Hamilton–Jacobi–Bellman (HJB) equation, and we characterize the value function via the nonlinear semigroup, besides the viscosity solution theory. When we control not only the dynamics of a system but also the terminal time of its evolution, control-stopping problems arise. This problem is treated in the same frameworks, via the nonlinear semigroup. Its results are applicable to the American option price problem. Zero-sum two-player time-homogeneous stochastic differential games and viscosity solutions of the Isaacs equations arising from such games are studied via a nonlinear semigroup related to DPP (the min-ma...
An enzyme-linked immunosorbent assay (ELISA) for quantification of mouse surfactant protein D (SP-D)
DEFF Research Database (Denmark)
Hansen, Soren; Schmidt, Vivi; Steffensen, Maria Abildgaard
2008-01-01
characterized and validated for use in sandwich enzyme-linked immunosorbent assay (ELISA). Based on two of these, we established an ELISA that allows for measurements of mouse SP-D in various body fluids. The final ELISA was optimized and calibrated with a standard of purified recombinant mouse SP-D, which......Surfactant protein D (SP-D) is a pattern recognition molecule of the collectin family of C-type lectins. It is found in the airways and at mucosal surfaces. SP-D is part of the innate immune system where it neutralizes and leads to elimination of microorganisms. It regulates the functions of other...... innate immune cells, such as macrophages and neutrophils. It also modulates the adaptive immune response by interacting with antigen-presenting cells and T cells. Monoclonal anti-mouse-SP-D antibodies were raised from SP-D deficient mice using recombinant SP-D as antigen. Ten monoclonal antibodies were...
Sugioka, Kenji; Hamill, Danielle R; Lowry, Joshua B; McNeely, Marie E; Enrick, Molly; Richter, Alyssa C; Kiebler, Lauren E; Priess, James R; Bowerman, Bruce
2017-01-01
The centriole/basal body is a eukaryotic organelle that plays essential roles in cell division and signaling. Among five known core centriole proteins, SPD-2/Cep192 is the first recruited to the site of daughter centriole formation and regulates the centriolar localization of the other components in C. elegans and in humans. However, the molecular basis for SPD-2 centriolar localization remains unknown. Here, we describe a new centriole component, the coiled-coil protein SAS-7, as a regulator of centriole duplication, assembly and elongation. Intriguingly, our genetic data suggest that SAS-7 is required for daughter centrioles to become competent for duplication, and for mother centrioles to maintain this competence. We also show that SAS-7 binds SPD-2 and regulates SPD-2 centriolar recruitment, while SAS-7 centriolar localization is SPD-2-independent. Furthermore, pericentriolar material (PCM) formation is abnormal in sas-7 mutants, and the PCM-dependent induction of cell polarity that defines the anterior-posterior body axis frequently fails. We conclude that SAS-7 functions at the earliest step in centriole duplication yet identified and plays important roles in the orchestration of centriole and PCM assembly. DOI: http://dx.doi.org/10.7554/eLife.20353.001 PMID:28092264
LIU, Tongzhu; SHEN, Aizong; HU, Xiaojian; TONG, Guixian; GU, Wei
2017-01-01
Background: We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. Methods: We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. Results: For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Conclusion: Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers. PMID:28828316
Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei
2017-06-01
We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers.
Markdown Optimization via Approximate Dynamic Programming
Directory of Open Access Journals (Sweden)
Cos?gun
2013-02-01
Full Text Available We consider the markdown optimization problem faced by the leading apparel retail chain. Because of substitution among products the markdown policy of one product affects the sales of other products. Therefore, markdown policies for product groups having a significant crossprice elasticity among each other should be jointly determined. Since the state space of the problem is very huge, we use Approximate Dynamic Programming. Finally, we provide insights on the behavior of how each product price affects the markdown policy.
Joint Chance-Constrained Dynamic Programming
Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J. Bob
2012-01-01
This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.
Sandia Dynamic Materials Program Strategic Plan.
Energy Technology Data Exchange (ETDEWEB)
Flicker, Dawn Gustine [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Benage, John F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Desjarlais, Michael P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Knudson, Marcus D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Leifeste, Gordon T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lemke, Raymond W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Mattsson, Thomas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wise, Jack L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-05-01
Materials in nuclear and conventional weapons can reach multi-megabar pressures and 1000s of degree temperatures on timescales ranging from microseconds to nanoseconds. Understanding the response of complex materials under these conditions is important for designing and assessing changes to nuclear weapons. In the next few decades, a major concern will be evaluating the behavior of aging materials and remanufactured components. The science to enable the program to underwrite decisions quickly and confidently on use, remanufacturing, and replacement of these materials will be critical to NNSA’s new Stockpile Responsiveness Program. Material response is also important for assessing the risks posed by adversaries or proliferants. Dynamic materials research, which refers to the use of high-speed experiments to produce extreme conditions in matter, is an important part of NNSA’s Stockpile Stewardship Program.
Dynamic programming algorithms for biological sequence comparison.
Pearson, W R; Miller, W
1992-01-01
Efficient dynamic programming algorithms are available for a broad class of protein and DNA sequence comparison problems. These algorithms require computer time proportional to the product of the lengths of the two sequences being compared [O(N2)] but require memory space proportional only to the sum of these lengths [O(N)]. Although the requirement for O(N2) time limits use of the algorithms to the largest computers when searching protein and DNA sequence databases, many other applications of these algorithms, such as calculation of distances for evolutionary trees and comparison of a new sequence to a library of sequence profiles, are well within the capabilities of desktop computers. In particular, the results of library searches with rapid searching programs, such as FASTA or BLAST, should be confirmed by performing a rigorous optimal alignment. Whereas rapid methods do not overlook significant sequence similarities, FASTA limits the number of gaps that can be inserted into an alignment, so that a rigorous alignment may extend the alignment substantially in some cases. BLAST does not allow gaps in the local regions that it reports; a calculation that allows gaps is very likely to extend the alignment substantially. Although a Monte Carlo evaluation of the statistical significance of a similarity score with a rigorous algorithm is much slower than the heuristic approach used by the RDF2 program, the dynamic programming approach should take less than 1 hr on a 386-based PC or desktop Unix workstation. For descriptive purposes, we have limited our discussion to methods for calculating similarity scores and distances that use gap penalties of the form g = rk. Nevertheless, programs for the more general case (g = q+rk) are readily available. Versions of these programs that run either on Unix workstations, IBM-PC class computers, or the Macintosh can be obtained from either of the authors.
DEFF Research Database (Denmark)
Fakih, Dalia; Pilecki, Bartosz; Schlosser, Anders
2015-01-01
SP-D is a pulmonary collectin important in lung immunity. SP-D-deficient mice (Sftpd(-/-)) are reported to be susceptible to ovalbumin (OVA)- and fungal allergen-induced pulmonary inflammation, while treatment with exogenous SP-D has therapeutic effects in such disease models. β-glucans are a div...
Common genetic variants of surfactant protein-D (SP-D are associated with type 2 diabetes.
Directory of Open Access Journals (Sweden)
Neus Pueyo
Full Text Available CONTEXT: Surfactant protein-D (SP-D is a primordial component of the innate immune system intrinsically linked to metabolic pathways. We aimed to study the association of single nucleotide polymorphisms (SNPs affecting SP-D with insulin resistance and type 2 diabetes (T2D. RESEARCH DESIGN AND METHODS: We evaluated a common genetic variant located in the SP-D coding region (rs721917, Met(31Thr in a sample of T2D patients and non-diabetic controls (n = 2,711. In a subset of subjects (n = 1,062, this SNP was analyzed in association with circulating SP-D concentrations, insulin resistance, and T2D. This SNP and others were also screened in the publicly available Genome Wide Association (GWA database of the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC. RESULTS: We found the significant association of rs721917 with circulating SP-D, parameters of insulin resistance and T2D. Indeed, G carriers showed decreased circulating SP-D (p = 0.004, decreased fasting glucose (p = 0.0002, glycated hemoglobin (p = 0.0005, and 33% (p = 0.002 lower prevalence of T2D, estimated under a dominant model, especially among women. Interestingly, these differences remained significant after controlling for origin, age, gender, and circulating SP-D. Moreover, this SNP and others within the SP-D genomic region (i.e. rs10887344 were significantly associated with quantitative measures of glucose homeostasis, insulin sensitivity, and T2D, according to GWAS datasets from MAGIC. CONCLUSIONS: SP-D gene polymorphisms are associated with insulin resistance and T2D. These associations are independent of circulating SP-D concentrations.
Automated Flight Routing Using Stochastic Dynamic Programming
Ng, Hok K.; Morando, Alex; Grabbe, Shon
2010-01-01
Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.
Runway Scheduling Using Generalized Dynamic Programming
Montoya, Justin; Wood, Zachary; Rathinam, Sivakumar
2011-01-01
A generalized dynamic programming method for finding a set of pareto optimal solutions for a runway scheduling problem is introduced. The algorithm generates a set of runway fight sequences that are optimal for both runway throughput and delay. Realistic time-based operational constraints are considered, including miles-in-trail separation, runway crossings, and wake vortex separation. The authors also model divergent runway takeoff operations to allow for reduced wake vortex separation. A modeled Dallas/Fort Worth International airport and three baseline heuristics are used to illustrate preliminary benefits of using the generalized dynamic programming method. Simulated traffic levels ranged from 10 aircraft to 30 aircraft with each test case spanning 15 minutes. The optimal solution shows a 40-70 percent decrease in the expected delay per aircraft over the baseline schedulers. Computational results suggest that the algorithm is promising for real-time application with an average computation time of 4.5 seconds. For even faster computation times, two heuristics are developed. As compared to the optimal, the heuristics are within 5% of the expected delay per aircraft and 1% of the expected number of runway operations per hour ad can be 100x faster.
DEFF Research Database (Denmark)
Sorensen, G.L.; Hjelmborg, J.V.B.; Leth-Larsen, R.
2006-01-01
Surfactant protein D (SP-D) is a key regulator of pathogen-induced inflammation. SP-D is further involved in lipid homeostasis in mouse lung and circulation and recent data have demonstrated that the body mass index (BMI; in kg/m(2)) is influenced by genes in common with SP-D. The objective...
Directory of Open Access Journals (Sweden)
Oliver Fleck
2017-04-01
Full Text Available In fission yeast, the small, intrinsically disordered protein S-phase delaying protein 1 (Spd1 blocks DNA replication and causes checkpoint activation at least in part, by inhibiting the enzyme ribonucleotide reductase, which is responsible for the synthesis of DNA. The CRL4Cdt2 E3 ubiquitin ligase mediates degradation of Spd1 and the related protein Spd2 at S phase of the cell cycle. We have generated a conditional allele of CRL4Cdt2, by expressing the highly unstable substrate-recruiting protein Cdt2 from a repressible promoter. Unlike Spd1, Spd2 does not regulate deoxynucleotide triphosphate (dNTP pools; yet we find that Spd1 and Spd2 together inhibit DNA replication upon Cdt2 depletion. To directly test whether this block of replication was solely due to insufficient dNTP levels, we established a deoxy-nucleotide salvage pathway in fission yeast by expressing the human nucleoside transporter human equilibrative nucleoside transporter 1 (hENT1 and the Drosophila deoxynucleoside kinase. We present evidence that this salvage pathway is functional, as 2 µM of deoxynucleosides in the culture medium is able to rescue the growth of two different temperature-sensitive alleles controlling ribonucleotide reductase. However, salvage completely failed to rescue S phase delay, checkpoint activation, and damage sensitivity, which was caused by CRL4Cdt2 inactivation, suggesting that Spd1—in addition to repressing dNTP synthesis—together with Spd2, can inhibit other replication functions. We propose that this inhibition works at the point of the replication clamp proliferating cell nuclear antigen, a co-factor for DNA replication.
Pareto optimization in algebraic dynamic programming.
Saule, Cédric; Giegerich, Robert
2015-01-01
Pareto optimization combines independent objectives by computing the Pareto front of its search space, defined as the set of all solutions for which no other candidate solution scores better under all objectives. This gives, in a precise sense, better information than an artificial amalgamation of different scores into a single objective, but is more costly to compute. Pareto optimization naturally occurs with genetic algorithms, albeit in a heuristic fashion. Non-heuristic Pareto optimization so far has been used only with a few applications in bioinformatics. We study exact Pareto optimization for two objectives in a dynamic programming framework. We define a binary Pareto product operator [Formula: see text] on arbitrary scoring schemes. Independent of a particular algorithm, we prove that for two scoring schemes A and B used in dynamic programming, the scoring scheme [Formula: see text] correctly performs Pareto optimization over the same search space. We study different implementations of the Pareto operator with respect to their asymptotic and empirical efficiency. Without artificial amalgamation of objectives, and with no heuristics involved, Pareto optimization is faster than computing the same number of answers separately for each objective. For RNA structure prediction under the minimum free energy versus the maximum expected accuracy model, we show that the empirical size of the Pareto front remains within reasonable bounds. Pareto optimization lends itself to the comparative investigation of the behavior of two alternative scoring schemes for the same purpose. For the above scoring schemes, we observe that the Pareto front can be seen as a composition of a few macrostates, each consisting of several microstates that differ in the same limited way. We also study the relationship between abstract shape analysis and the Pareto front, and find that they extract information of a different nature from the folding space and can be meaningfully combined.
Implementing a Dynamic Street-Children's Program: Successes and ...
African Journals Online (AJOL)
dynamic street children's program in Mzuzu Malawi – using a developmental ... dynamics of parentchild, parent-parent and child-parent-environment; life-events; ... of child and adolescent development, and how they can influence the child's ...
Convergence of Sample Path Optimal Policies for Stochastic Dynamic Programming
National Research Council Canada - National Science Library
Fu, Michael C; Jin, Xing
2005-01-01
.... These results have practical implications for Monte Carlo simulation-based solution approaches to stochastic dynamic programming problems where it is impractical to extract the explicit transition...
The electrical conductivity of CuCrZr alloy after SPD processing
International Nuclear Information System (INIS)
Lipińska, M; Bazarnik, P; Lewandowska, M
2014-01-01
CuCrZr alloys exhibit very good relation between mechanical properties and electrical conductivity. However, for its use in some advanced applications improvement of mechanical strength while preserving high electrical conducting is required. Therefore, in this work a CuCrZr alloy was subjected to a series of thermo-mechanical treatments, including solution annealing and water quenching, SPD processing (using hydrostatic extrusion and ECAP) as well as aging in order to improve mechanical strength. The influence of these processing procedures on microstructure features and mechanical properties was determined by TEM observation and microhardness measurements, respectively. Electrical conductivity of the samples was measured by four-points method. The results have shown that it is possible to improve mechanical strength while preserving good electrical conductivity by a proper combination of SPD processing and heat treatment
Use of research and test reactors for SPD development and calibration
International Nuclear Information System (INIS)
LaFontaine, M.W.R.
2011-01-01
Prior to using a research or test reactor for performance studies or calibration of self powered detectors, it is first necessary to fully characterize the reactor environment in the region to be utilized. This presentation details Characterization Experiments performed to quantify research/test reactor core/site parameters as they would apply for use with SPD applications. Methods will be described to: Determine the Westcott parameter, r (T n /T o ) , for the region of interest; Characterize the neutron energy spectrum in terms of the cadmium absorption cut-off, i.e., consider neutrons of energy 5kT 0.13 eV to be epithermal neutrons; Determine T n , the effective neutron temperature, in the region of interest; Determine the gamma flux in the region of interest; and, Establish SPD calibration standard detectors.
SPD-based Logistics Management Model of Medical Consumables in Hospitals
LIU, Tongzhu; SHEN, Aizong; HU, Xiaojian; TONG, Guixian; GU, Wei; YANG, Shanlin
2016-01-01
Background: With the rapid development of health services, the progress of medical science and technology, and the improvement of materials research, the consumption of medical consumables (MCs) in medical activities has increased in recent years. However, owing to the lack of effective management methods and the complexity of MCs, there are several management problems including MC waste, low management efficiency, high management difficulty, and frequent medical accidents. Therefore, there is urgent need for an effective logistics management model to handle these problems and challenges in hospitals. Methods: We reviewed books and scientific literature (by searching the articles published from 2010 to 2015 in Engineering Village database) to understand supply chain related theories and methods and performed field investigations in hospitals across many cities to determine the actual state of MC logistics management of hospitals in China. Results: We describe the definition, physical model, construction, and logistics operation processes of the supply, processing, and distribution (SPD) of MC logistics because of the traditional SPD model. With the establishment of a supply-procurement platform and a logistics lean management system, we applied the model to the MC logistics management of Anhui Provincial Hospital with good effects. Conclusion: The SPD model plays a critical role in optimizing the logistics procedures of MCs, improving the management efficiency of logistics, and reducing the costs of logistics of hospitals in China. PMID:27957435
SPD-based Logistics Management Model of Medical Consumables in Hospitals.
Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei; Yang, Shanlin
2016-10-01
With the rapid development of health services, the progress of medical science and technology, and the improvement of materials research, the consumption of medical consumables (MCs) in medical activities has increased in recent years. However, owing to the lack of effective management methods and the complexity of MCs, there are several management problems including MC waste, low management efficiency, high management difficulty, and frequent medical accidents. Therefore, there is urgent need for an effective logistics management model to handle these problems and challenges in hospitals. We reviewed books and scientific literature (by searching the articles published from 2010 to 2015 in Engineering Village database) to understand supply chain related theories and methods and performed field investigations in hospitals across many cities to determine the actual state of MC logistics management of hospitals in China. We describe the definition, physical model, construction, and logistics operation processes of the supply, processing, and distribution (SPD) of MC logistics because of the traditional SPD model. With the establishment of a supply-procurement platform and a logistics lean management system, we applied the model to the MC logistics management of Anhui Provincial Hospital with good effects. The SPD model plays a critical role in optimizing the logistics procedures of MCs, improving the management efficiency of logistics, and reducing the costs of logistics of hospitals in China.
Spatial cluster detection using dynamic programming
Directory of Open Access Journals (Sweden)
Sverchkov Yuriy
2012-03-01
Full Text Available Abstract Background The task of spatial cluster detection involves finding spatial regions where some property deviates from the norm or the expected value. In a probabilistic setting this task can be expressed as finding a region where some event is significantly more likely than usual. Spatial cluster detection is of interest in fields such as biosurveillance, mining of astronomical data, military surveillance, and analysis of fMRI images. In almost all such applications we are interested both in the question of whether a cluster exists in the data, and if it exists, we are interested in finding the most accurate characterization of the cluster. Methods We present a general dynamic programming algorithm for grid-based spatial cluster detection. The algorithm can be used for both Bayesian maximum a-posteriori (MAP estimation of the most likely spatial distribution of clusters and Bayesian model averaging over a large space of spatial cluster distributions to compute the posterior probability of an unusual spatial clustering. The algorithm is explained and evaluated in the context of a biosurveillance application, specifically the detection and identification of Influenza outbreaks based on emergency department visits. A relatively simple underlying model is constructed for the purpose of evaluating the algorithm, and the algorithm is evaluated using the model and semi-synthetic test data. Results When compared to baseline methods, tests indicate that the new algorithm can improve MAP estimates under certain conditions: the greedy algorithm we compared our method to was found to be more sensitive to smaller outbreaks, while as the size of the outbreaks increases, in terms of area affected and proportion of individuals affected, our method overtakes the greedy algorithm in spatial precision and recall. The new algorithm performs on-par with baseline methods in the task of Bayesian model averaging. Conclusions We conclude that the dynamic
Development and Fit-for-Purpose Validation of a Soluble Human Programmed Death-1 Protein Assay.
Ni, Yan G; Yuan, Xiling; Newitt, John A; Peterson, Jon E; Gleason, Carol R; Haulenbeek, Jonathan; Santockyte, Rasa; Lafont, Virginie; Marsilio, Frank; Neely, Robert J; DeSilva, Binodh; Piccoli, Steven P
2015-07-01
Programmed death-1 (PD-1) protein is a co-inhibitory receptor which negatively regulates immune cell activation and permits tumors to evade normal immune defense. Anti-PD-1 antibodies have been shown to restore immune cell activation and effector function-an exciting breakthrough in cancer immunotherapy. Recent reports have documented a soluble form of PD-1 (sPD-1) in the circulation of normal and disease state individuals. A clinical assay to quantify sPD-1 would contribute to the understanding of sPD-1-function and facilitate the development of anti-PD-1 drugs. Here, we report the development and validation of a sPD-1 protein assay. The assay validation followed the framework for full validation of a biotherapeutic pharmacokinetic assay. A purified recombinant human PD-1 protein was characterized extensively and was identified as the assay reference material which mimics the endogenous analyte in structure and function. The lower limit of quantitation (LLOQ) was determined to be 100 pg/mL, with a dynamic range spanning three logs to 10,000 pg/mL. The intra- and inter-assay imprecision were ≤15%, and the assay bias (percent deviation) was ≤10%. Potential matrix effects were investigated in sera from both normal healthy volunteers and selected cancer patients. Bulk-prepared frozen standards and pre-coated Streptavidin plates were used in the assay to ensure consistency in assay performance over time. This assay appears to specifically measure total sPD-1 protein since the human anti-PD-1 antibody, nivolumab, and the endogenous ligands of PD-1 protein, PDL-1 and PDL-2, do not interfere with the assay.
Approximate Dynamic Programming Solving the Curses of Dimensionality
Powell, Warren B
2011-01-01
Praise for the First Edition "Finally, a book devoted to dynamic programming and written using the language of operations research (OR)! This beautiful book fills a gap in the libraries of OR specialists and practitioners."-Computing Reviews This new edition showcases a focus on modeling and computation for complex classes of approximate dynamic programming problems Understanding approximate dynamic programming (ADP) is vital in order to develop practical and high-quality solutions to complex industrial problems, particularly when those problems involve making decisions in the presence of unce
Granular contact dynamics using mathematical programming methods
DEFF Research Database (Denmark)
Krabbenhoft, K.; Lyamin, A. V.; Huang, J.
2012-01-01
granular contact dynamics formulation uses an implicit time discretization, thus allowing for large time steps. Moreover, in the limit of an infinite time step, the general dynamic formulation reduces to a static formulation that is useful in simulating common quasi-static problems such as triaxial tests...... is developed and it is concluded that the associated sliding rule, in the context of granular contact dynamics, may be viewed as an artifact of the time discretization and that the use of an associated flow rule at the particle scale level generally is physically acceptable. (C) 2012 Elsevier Ltd. All rights...
Stochastic dynamic programming model for optimal resource ...
Indian Academy of Sciences (India)
M Bhuvaneswari
2018-04-11
Apr 11, 2018 ... handover in VANET; because of high dynamics in net- work topology, collaboration ... containers, doctors, nurses, cash and stocks. Similarly, ... GTBA does not take the resource types and availability into consideration.
Dynamic Programming Algorithms in Speech Recognition
Directory of Open Access Journals (Sweden)
Titus Felix FURTUNA
2008-01-01
Full Text Available In a system of speech recognition containing words, the recognition requires the comparison between the entry signal of the word and the various words of the dictionary. The problem can be solved efficiently by a dynamic comparison algorithm whose goal is to put in optimal correspondence the temporal scales of the two words. An algorithm of this type is Dynamic Time Warping. This paper presents two alternatives for implementation of the algorithm designed for recognition of the isolated words.
International Nuclear Information System (INIS)
Hunter, J.A.
1984-01-01
Equipment qualification research is being conducted to investigate acceptable criteria, requirements, and methodologies for the dynamic (including seismic) and environmental qualification of mechanical equipment and for the dynamic (including seismic) qualification of electrical equipment. The program is organized into three elements: (1) General Research, (2) Environmental Research, and (3) Dynamic Research. This paper presents the highlights of the results to date in these three elements of the program
Ito, Nobuko; Chinzei, Mieko; Fujiwara, Haruko; Usui, Hisako; Hanaoka, Kazuo; Saitoh, Eisho
2006-04-01
Supply, Processing and Distribution system had been introduced to surgical center (the University of Tokyo Hospital) since October of 2002. This system had reduced stock for medicine and materials and decreased medical cost dramatically. We designed some kits for therapeutic drugs related to anesthesia. They were prepared for general anesthesia, epidural and spinal anesthesia, and cardiovascular anesthesia, respectively. One kit had been used for one patient, and new kits were prepared in the anesthesia preparation room by pharmaceutical department staffs. Equipment, for general anesthesia as well as epidural and spinal anesthesia, and central catheter set were also designed and provided for each patient by SPD system. According to the questionnaire of anesthesia residents before and after introduction of SPD system, the time spent for anesthesia preparation had been reduced and 92.3% residents had answered that preparation for anesthesia on the previous day was getting easier. Most of the anesthesia residents had been less stressed after introduction of SPD system. Beside the dramatic economical effect, coordination with SPD system and pharmaceutical department reduced anesthesia preparation time and stress of the staff. Introduction of Support system of SPD to surgical center is important for safe and effective management of operating rooms.
Dynamic programming approach to optimization of approximate decision rules
Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
2013-01-01
This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number
Dynamic Programming Approach for Exact Decision Rule Optimization
Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
2013-01-01
This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from
Directory of Open Access Journals (Sweden)
Oliver Wueseke
2016-10-01
Full Text Available Centrosomes are major microtubule-organizing centers composed of centrioles surrounded by an extensive proteinacious layer called the pericentriolar material (PCM. In Caenorhabditis elegans embryos, the mitotic PCM expands by Polo-like kinase 1 (PLK-1 phosphorylation-accelerated assembly of SPD-5 molecules into supramolecular scaffolds. However, how PLK-1 phosphorylation regulates SPD-5 assembly is not known. We found that a mutant version of SPD-5 that is insensitive to PLK-1 phosphorylation (SPD-54A could localize to PCM but was unable to rescue the reduction in PCM size and density when wild-type SPD-5 levels were decreased. In vitro, purified SPD-54A self-assembled into functional supramolecular scaffolds over long time scales, suggesting that phosphorylation only controls the rate of SPD-5 scaffold assembly. Furthermore, the SPD-5 scaffold, once assembled, remained intact and supported microtubule nucleation in the absence of PLK-1 activity in vivo. We conclude that PLK-1 is required for rapid assembly of the PCM scaffold but not for scaffold maintenance or function. Based on this idea, we developed a theoretical model that adequately predicted PCM growth rates in different mutant conditions in vivo. We propose that PLK-1 phosphorylation-dependent conversion of SPD-5 into an assembly-competent form underlies PCM formation in vivo and that the rate of this conversion determines final PCM size and density.
An Improved Dynamic Programming Decomposition Approach for Network Revenue Management
Dan Zhang
2011-01-01
We consider a nonlinear nonseparable functional approximation to the value function of a dynamic programming formulation for the network revenue management (RM) problem with customer choice. We propose a simultaneous dynamic programming approach to solve the resulting problem, which is a nonlinear optimization problem with nonlinear constraints. We show that our approximation leads to a tighter upper bound on optimal expected revenue than some known bounds in the literature. Our approach can ...
Dynamic Programming Approaches for the Traveling Salesman Problem with Drone
Bouman, Paul; Agatz, Niels; Schmidt, Marie
2017-01-01
markdownabstractA promising new delivery model involves the use of a delivery truck that collaborates with a drone to make deliveries. Effectively combining a drone and a truck gives rise to a new planning problem that is known as the Traveling Salesman Problem with Drone (TSP-D). This paper presents an exact solution approach for the TSP-D based on dynamic programming and present experimental results of different dynamic programming based heuristics. Our numerical experiments show that our a...
Dynamic Performance Tuning Supported by Program Specification
Directory of Open Access Journals (Sweden)
Eduardo César
2002-01-01
Full Text Available Performance analysis and tuning of parallel/distributed applications are very difficult tasks for non-expert programmers. It is necessary to provide tools that automatically carry out these tasks. These can be static tools that carry out the analysis on a post-mortem phase or can tune the application on the fly. Both kind of tools have their target applications. Static automatic analysis tools are suitable for stable application while dynamic tuning tools are more appropriate to applications with dynamic behaviour. In this paper, we describe KappaPi as an example of a static automatic performance analysis tool, and also a general environment based on parallel patterns for developing and dynamically tuning parallel/distributed applications.
Directory of Open Access Journals (Sweden)
Cizek L.
2017-12-01
Full Text Available A growing interest in wrought magnesium alloys has been noticed recently, mainly due to development of various SPD (severe plastic deformation methods that enable significant refinement of the microstructure and – as a result – improvement of various functional properties of products. However, forming as-cast magnesium alloys with the increased aluminum content at room temperature is almost impossible. Therefore, application of heat treatment before forming or forming at elevated temperature is recommended for these alloys. The paper presents the influence of selected heat treatment conditions on the microstructure and the mechanical properties of the as-cast AZ91 alloy. Deformation behaviour of the as-cast AZ61 alloy at elevated temperatures was analysed as well. The microstructure analysis was performed by means of both light microscopy and SEM. The latter one was used also for fracture analysis. Moreover, the effect of chemical composition modification by lithium addition on the microstructure of the AZ31-based alloy is presented. The test results can be helpful in preparation of the magnesium-aluminum alloys for further processing by means of SPD methods.
INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization
Energy Technology Data Exchange (ETDEWEB)
Groer, Christopher S [ORNL; Sullivan, Blair D [ORNL; Weerapurage, Dinesh P [ORNL
2012-10-01
It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms we have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.
Dynamic Learning Objects to Teach Java Programming Language
Narasimhamurthy, Uma; Al Shawkani, Khuloud
2010-01-01
This article describes a model for teaching Java Programming Language through Dynamic Learning Objects. The design of the learning objects was based on effective learning design principles to help students learn the complex topic of Java Programming. Visualization was also used to facilitate the learning of the concepts. (Contains 1 figure and 2…
Proving deadlock freedom of logic programs with dynamic scheduling
E. Marchiori; F. Teusink (Frank)
1996-01-01
textabstractIn increasingly many logic programming systems, the Prolog left to right selection rule has been replaced with dynamic selection rules, that select an atom of a query among those satisfying suitable conditions. These conditions describe the form of the arguments of every program
Nonlinear beam dynamics experimental program at SPEAR
International Nuclear Information System (INIS)
Tran, P.; Pellegrini, C.; Cornacchia, M.; Lee, M.; Corbett, W.
1995-01-01
Since nonlinear effects can impose strict performance limitations on modern colliders and storage rings, future performance improvements depend on further understanding of nonlinear beam dynamics. Experimental studies of nonlinear beam motion in three-dimensional space have begun in SPEAR using turn-by-turn transverse and longitudinal phase-space monitors. This paper presents preliminary results from an on-going experiment in SPEAR
Modelling of windmill induction generators in dynamic simulation programs
DEFF Research Database (Denmark)
Akhmatov, Vladislav; Knudsen, Hans
1999-01-01
with and without a model of the mechanical shaft. The reason for the discrepancies are explained, and it is shown that the phenomenon is due partly to the presence of DC offset currents in the induction machine stator, and partly to the mechanical shaft system of the wind turbine and the generator rotor......For AC networks with large amounts of induction generators-in case of e.g. windmills-the paper demonstrates a significant discrepancy in the simulated voltage recovery after faults in weak networks, when comparing result obtained with dynamic stability programs and transient programs, respectively....... It is shown that it is possible to include a transient model in dynamic stability programs and thus obtain correct results also in dynamic stability programs. A mechanical model of the shaft system has also been included in the generator model...
Program packages for dynamics systems analysis and design
International Nuclear Information System (INIS)
Athani, V.V.
1976-01-01
The development of computer program packages for dynamic system analysis and design are reported. The purpose of developing these program packages is to take the burden of writing computer programs off the mind of the system engineer and to enable him to concentrate on his main system analysis and design work. Towards this end, four standard computer program packages have been prepared : (1) TFANA - starting from system transfer function this program computes transient response, frequency response, root locus and stability by Routh Hurwitz criterion, (2) TFSYN - classical synthesis using algebraic method of Shipley, (3) MODANA - starting from state equations of the system this program computes solution of state equations, controllability, observability and stability, (4) OPTCON - This program obtains solutions of (i) linear regulator problem, (ii) servomechanism problems and (iii) problem of pole placement. The paper describes these program packages with the help of flowcharts and illustrates their use with the help of examples. (author)
Macroscopic reality and the dynamical reduction program
International Nuclear Information System (INIS)
Ghirardi, G.C.
1995-10-01
With reference to recently proposed theoretical models accounting for reduction in terms of a unified dynamics governing all physical processes, we analyze the problem of working out a worldview accommodating our knowledge about natural phenomena. We stress the relevant conceptual differences between the considered models and standard quantum mechanics. In spite of the fact that both theories describe individual physical systems within a genuine Hilbert space framework, the nice features of spontaneous reduction theories drastically limit the class of states which are dynamically stable. This allows one to work out a description of the world in terms of a mass density function in ordinary configuration space. A topology based on this function and differing radically from the one characterizing the Hilbert space is introduced and in terms of it the idea of similarity of macroscopic situations is made precise. Finally it is shown how the formalism and the proposed interpretation yield a natural criterion for establishing the psychophysical parallelism. The conclusion is that, within the considered theoretical models and at the nonrelativistic level, one can satisfy all sensible requirements for a consistent, unified, and objective description of reality at the macroscopic level. (author). 16 refs
Macroscopic reality and the dynamical reduction program
Energy Technology Data Exchange (ETDEWEB)
Ghirardi, G C
1995-10-01
With reference to recently proposed theoretical models accounting for reduction in terms of a unified dynamics governing all physical processes, we analyze the problem of working out a worldview accommodating our knowledge about natural phenomena. We stress the relevant conceptual differences between the considered models and standard quantum mechanics. In spite of the fact that both theories describe individual physical systems within a genuine Hilbert space framework, the nice features of spontaneous reduction theories drastically limit the class of states which are dynamically stable. This allows one to work out a description of the world in terms of a mass density function in ordinary configuration space. A topology based on this function and differing radically from the one characterizing the Hilbert space is introduced and in terms of it the idea of similarity of macroscopic situations is made precise. Finally it is shown how the formalism and the proposed interpretation yield a natural criterion for establishing the psychophysical parallelism. The conclusion is that, within the considered theoretical models and at the nonrelativistic level, one can satisfy all sensible requirements for a consistent, unified, and objective description of reality at the macroscopic level. (author). 16 refs.
The application of dynamic programming in production planning
Wu, Run
2017-05-01
Nowadays, with the popularity of the computers, various industries and fields are widely applying computer information technology, which brings about huge demand for a variety of application software. In order to develop software meeting various needs with most economical cost and best quality, programmers must design efficient algorithms. A superior algorithm can not only soul up one thing, but also maximize the benefits and generate the smallest overhead. As one of the common algorithms, dynamic programming algorithms are used to solving problems with some sort of optimal properties. When solving problems with a large amount of sub-problems that needs repetitive calculations, the ordinary sub-recursive method requires to consume exponential time, and dynamic programming algorithm can reduce the time complexity of the algorithm to the polynomial level, according to which we can conclude that dynamic programming algorithm is a very efficient compared to other algorithms reducing the computational complexity and enriching the computational results. In this paper, we expound the concept, basic elements, properties, core, solving steps and difficulties of the dynamic programming algorithm besides, establish the dynamic programming model of the production planning problem.
Nanostructuring of Ti-alloys by SPD processing to achieve superior fatigue properties
Energy Technology Data Exchange (ETDEWEB)
Semenova, Irina P.; Yakushina, Evgeniya B.; Nurgaleeva, Veronika V.; Valiev, Ruslan Z. [Ufa State Aviation Technical Univ., Ufa (Russian Federation). Inst. of Physics of Advanced Materials
2009-12-15
This work is related to the enhancement of the fatigue properties in ultrafine-grained Ti alloys produced by severe plastic deformation techniques (SPD). To process commercially pure Ti Grade 4 and Ti-6Al-4V alloys, combined severe plastic deformation techniques that include equal channel angular pressing and additional thermal and deformation treatments were used. As a result we could produce ultrafine-grained Ti materials with a similar grain size of less than 300-400 nm but different in their shape and grain boundary structure (both low- and high-angle, equilibrium and non-equilibrium grain boundaries). It is shown that tailoring grain boundaries by severe plastic deformation techniques makes it possible to considerably enhance the strength of Ti materials while preserving high ductility. In turn, ultrafine-grained materials with enhanced strength and ductility demonstrate superior fatigue endurance and life.
Approximate dynamic programming solving the curses of dimensionality
Powell, Warren B
2007-01-01
Warren B. Powell, PhD, is Professor of Operations Research and Financial Engineering at Princeton University, where he is founder and Director of CASTLE Laboratory, a research unit that works with industrial partners to test new ideas found in operations research. The recipient of the 2004 INFORMS Fellow Award, Dr. Powell has authored over 100 refereed publications on stochastic optimization, approximate dynamic programming, and dynamic resource management.
Dynamic electricity pricing—Which programs do consumers prefer?
International Nuclear Information System (INIS)
Dütschke, Elisabeth; Paetz, Alexandra-Gwyn
2013-01-01
Dynamic pricing is being discussed as one method of demand side management (DSM) which could be crucial for integrating more renewable energy sources into the electricity system. At the same time, there have been very few analyses of consumer preferences in this regard: Which type of pricing program are consumers most likely to choose and why? This paper sheds some light on these issues based on two empirical studies from Germany: (1) A questionnaire study including a conjoint analysis-design and (2) A field experiment with test-residents of a smart home laboratory. The results show that consumers are open to dynamic pricing, but prefer simple programs to complex and highly dynamic ones; smart home technologies including demand automation are seen as a prerequisite for DSM. The study provides some indications that consumers might be more willing to accept more dynamic pricing programs if they have the chance to experience in practice how these can be managed in everyday life. At the same time, the individual and societal advantages of such programs are not obvious to consumers. For this reason, any market roll-out will need to be accompanied by convincing communication and information campaigns to ensure that these advantages are perceived. - Highlights: • Little is known about consumer preferences on dynamic pricing. • Two studies are conducted to analyze this topic. • A survey shows that consumers without experience prefer conventional programs. • Test residents of a smart home were more open to dynamic pricing. • They also prefer well-structured programs
Directory of Open Access Journals (Sweden)
Chafidz Achmad
2018-01-01
Full Text Available This research focused on the development of an innovative design of solar-powered desalination (SPD system which was expected to solve the water and energy problem simultaneously. We have developed a portable and hybrid solar-powered desalination (SPD system for producing potable water from saline water. It is a self-contained and integrated system which combines solar-thermal collector and solar-photovoltaic for its operation, and thus the system can operate to produce water by only using solar energy. Therefore, the system is highly suitable to be implemented in remote arid and coastal areas without infrastructures or connection to the grid (water and power, but blessed with abundant solar irradiation, like in Saudi Arabia. A Memsys Vacuum Multi-Effect Membrane Distillation (V-MEMD unit was used as the core of the SPD system. A heat pump was also integrated into the SPD system for energy recovery and to improve the performance of the system. The system could be considered as sustainable and “green” desalination technology, which will be very useful for the Kingdom of Saudi Arabia. To study the performance of the system, small-scale tests have been carried out at the Engineering College - King Saud University, Saudi Arabia. Based on the experimental results, the system has run successfully by only utilizing solar energy.
Step by step parallel programming method for molecular dynamics code
International Nuclear Information System (INIS)
Orii, Shigeo; Ohta, Toshio
1996-07-01
Parallel programming for a numerical simulation program of molecular dynamics is carried out with a step-by-step programming technique using the two phase method. As a result, within the range of a certain computing parameters, it is found to obtain parallel performance by using the level of parallel programming which decomposes the calculation according to indices of do-loops into each processor on the vector parallel computer VPP500 and the scalar parallel computer Paragon. It is also found that VPP500 shows parallel performance in wider range computing parameters. The reason is that the time cost of the program parts, which can not be reduced by the do-loop level of the parallel programming, can be reduced to the negligible level by the vectorization. After that, the time consuming parts of the program are concentrated on less parts that can be accelerated by the do-loop level of the parallel programming. This report shows the step-by-step parallel programming method and the parallel performance of the molecular dynamics code on VPP500 and Paragon. (author)
Fast and Cache-Oblivious Dynamic Programming with Local Dependencies
DEFF Research Database (Denmark)
Bille, Philip; Stöckel, Morten
2012-01-01
are widely used in bioinformatics to compare DNA and protein sequences. These problems can all be solved using essentially the same dynamic programming scheme over a two-dimensional matrix, where each entry depends locally on at most 3 neighboring entries. We present a simple, fast, and cache......-oblivious algorithm for this type of local dynamic programming suitable for comparing large-scale strings. Our algorithm outperforms the previous state-of-the-art solutions. Surprisingly, our new simple algorithm is competitive with a complicated, optimized, and tuned implementation of the best cache-aware algorithm...
A short note on dynamic programming in a band.
Gibrat, Jean-François
2018-06-15
Third generation sequencing technologies generate long reads that exhibit high error rates, in particular for insertions and deletions which are usually the most difficult errors to cope with. The only exact algorithm capable of aligning sequences with insertions and deletions is a dynamic programming algorithm. In this note, for the sake of efficiency, we consider dynamic programming in a band. We show how to choose the band width in function of the long reads' error rates, thus obtaining an [Formula: see text] algorithm in space and time. We also propose a procedure to decide whether this algorithm, when applied to semi-global alignments, provides the optimal score. We suggest that dynamic programming in a band is well suited to the problem of aligning long reads between themselves and can be used as a core component of methods for obtaining a consensus sequence from the long reads alone. The function implementing the dynamic programming algorithm in a band is available, as a standalone program, at: https://forgemia.inra.fr/jean-francois.gibrat/BAND_DYN_PROG.git.
A Dynamic Programming Algorithm for the k-Haplotyping Problem
Institute of Scientific and Technical Information of China (English)
Zhen-ping Li; Ling-yun Wu; Yu-ying Zhao; Xiang-sun Zhang
2006-01-01
The Minimum Fragments Removal (MFR) problem is one of the haplotyping problems: given a set of fragments, remove the minimum number of fragments so that the resulting fragments can be partitioned into k classes of non-conflicting subsets. In this paper, we formulate the k-MFR problem as an integer linear programming problem, and develop a dynamic programming approach to solve the k-MFR problem for both the gapless and gap cases.
Effect of the CTL proliferation program on virus dynamics
DEFF Research Database (Denmark)
Wodarz, Dominik; Thomsen, Allan Randrup
2005-01-01
Experiments have established that CTLs do not require continuous antigenic stimulation for expansion. Instead, responses develop by a process of programmed proliferation which involves approximately 7-10 antigen-independent cell divisions, the generation of effector cells and the differentiation...... virus loads and thus acute symptoms. The reason is that the programmed divisions are independent from antigenic stimulation, and an increase in virus load does not speed up the rate of CTL expansion. We hypothesize that the 7-10 programmed divisions observed in vivo represent an optimal solution...... into memory cells. The effect of this program on the infection dynamics and the advantages gained by the program have, however, not been explored yet. We investigate this with mathematical models. We find that more programmed divisions can make virus clearance more efficient because CTL division continues...
A note on dynamic programming in accounts receivable management
Dirickx, Y.M.I.; Kistner, K.-P.
1982-01-01
The paper considers a dynamic programming formulation of the accounts receivable problem for single outstanding amounts. An optimal collection policy can be computed efficiently by invoking a “planning horizon” result that determines a time period beyond which the decision process cannot extend. The
PACE: A dynamic programming algorithm for hardware/software partitioning
DEFF Research Database (Denmark)
Knudsen, Peter Voigt; Madsen, Jan
1996-01-01
This paper presents the PACE partitioning algorithm which is used in the LYCOS co-synthesis system for partitioning control/dataflow graphs into hardware and software parts. The algorithm is a dynamic programming algorithm which solves both the problem of minimizing system execution time...
Dynamic Programming Approach for Exact Decision Rule Optimization
Amin, Talha
2013-01-01
This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from UCI Machine Learning Repository. © Springer-Verlag Berlin Heidelberg 2013.
Dynamic Frames Based Verification Method for Concurrent Java Programs
Mostowski, Wojciech
2016-01-01
In this paper we discuss a verification method for concurrent Java programs based on the concept of dynamic frames. We build on our earlier work that proposes a new, symbolic permission system for concurrent reasoning and we provide the following new contributions. First, we describe our approach
Optimum workforce-size model using dynamic programming approach
African Journals Online (AJOL)
This paper presents an optimum workforce-size model which determines the minimum number of excess workers (overstaffing) as well as the minimum total recruitment cost during a specified planning horizon. The model is an extension of other existing dynamic programming models for manpower planning in the sense ...
The Functional Programming Language R and the Paradigm of Dynamic Scientific Programming
Trancón y Widemann, B.; Bolz, C.F.; Grelck, C.; Loidl, H.-W.; Peña, R.
2013-01-01
R is an environment and functional programming language for statistical data analysis and visualization. Largely unknown to the functional programming community, it is popular and influential in many empirical sciences. Due to its integrated combination of dynamic and reflective scripting on one
Intensive Research Program on Advances in Nonsmooth Dynamics 2016
Jeffrey, Mike; Lázaro, J; Olm, Josep
2017-01-01
This volume contains extended abstracts outlining selected talks and other selected presentations given by participants throughout the "Intensive Research Program on Advances in Nonsmooth Dynamics 2016", held at the Centre de Recerca Matemàtica (CRM) in Barcelona from February 1st to April 29th, 2016. They include brief research articles reporting new results, descriptions of preliminary work or open problems, and outlines of prominent discussion sessions. The articles are all the result of direct collaborations initiated during the research program. The topic is the theory and applications of Nonsmooth Dynamics. This includes systems involving elements of: impacting, switching, on/off control, hybrid discrete-continuous dynamics, jumps in physical properties, and many others. Applications include: electronics, climate modeling, life sciences, mechanics, ecology, and more. Numerous new results are reported concerning the dimensionality and robustness of nonsmooth models, shadowing variables, numbers of limit...
Hybrid Semantics of Stochastic Programs with Dynamic Reconfiguration
Directory of Open Access Journals (Sweden)
Alberto Policriti
2009-10-01
Full Text Available We begin by reviewing a technique to approximate the dynamics of stochastic programs --written in a stochastic process algebra-- by a hybrid system, suitable to capture a mixed discrete/continuous evolution. In a nutshell, the discrete dynamics is kept stochastic while the continuous evolution is given in terms of ODEs, and the overall technique, therefore, naturally associates a Piecewise Deterministic Markov Process with a stochastic program. The speciﬁc contribution in this work consists in an increase of the ﬂexibility of the translation scheme, obtained by allowing a dynamic reconﬁguration of the degree of discreteness/continuity of the semantics. We also discuss the relationships of this approach with other hybrid simulation strategies for biochemical systems.
Optimal Operation of Radial Distribution Systems Using Extended Dynamic Programming
DEFF Research Database (Denmark)
Lopez, Juan Camilo; Vergara, Pedro P.; Lyra, Christiano
2018-01-01
An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation o...... approach is illustrated using real-scale systems and comparisons with commercial programming solvers. Finally, generalizations to consider other EDS operation problems are also discussed.......An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation...... of the EDS by setting the values of the controllable variables at each time period. A suitable definition for the stages of the problem makes it possible to represent the optimal ac power flow of radial EDS as a dynamic programming problem, wherein the 'curse of dimensionality' is a minor concern, since...
Synthesizing Dynamic Programming Algorithms from Linear Temporal Logic Formulae
Rosu, Grigore; Havelund, Klaus
2001-01-01
The problem of testing a linear temporal logic (LTL) formula on a finite execution trace of events, generated by an executing program, occurs naturally in runtime analysis of software. We present an algorithm which takes an LTL formula and generates an efficient dynamic programming algorithm. The generated algorithm tests whether the LTL formula is satisfied by a finite trace of events given as input. The generated algorithm runs in linear time, its constant depending on the size of the LTL formula. The memory needed is constant, also depending on the size of the formula.
GLOBEC (Global Ocean Ecosystems Dynamics: Northwest Atlantic program
1991-01-01
The specific objective of the meeting was to plan an experiment in the Northwestern Atlantic to study the marine ecosystem and its role, together with that of climate and physical dynamics, in determining fisheries recruitment. The underlying focus of the GLOBEC initiative is to understand the marine ecosystem as it related to marine living resources and to understand how fluctuation in these resources are driven by climate change and exploitation. In this sense the goal is a solid scientific program to provide basic information concerning major fisheries stocks and the environment that sustains them. The plan is to attempt to reach this understanding through a multidisciplinary program that brings to bear new techniques as disparate as numerical fluid dynamic models of ocean circulation, molecular biology and modern acoustic imaging. The effort will also make use of the massive historical data sets on fisheries and the state of the climate in a coordinated manner.
Adaptive Dynamic Programming for Control Algorithms and Stability
Zhang, Huaguang; Luo, Yanhong; Wang, Ding
2013-01-01
There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming for Control approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-...
Adaptive dynamic programming with applications in optimal control
Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang
2017-01-01
This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...
Impact of serum SP-A and SP-D levels on comparison and prognosis of idiopathic pulmonary fibrosis
Wang, Kai; Ju, Qing; Cao, Jing; Tang, Wenze; Zhang, Jian
2017-01-01
Abstract Background and objective: Idiopathic pulmonary fibrosis (IPF) has a poor prognosis in general; however, it is heterogeneous to detect relative biomarkers for predicting the disease progression. Serum biomarkers can be conveniently collected to detect and help to differentially diagnose IPF and predict IPF prognosis. This meta-analysis aimed to evaluate the use of serum surfactant proteins A and D (SP-A and SP-D) for differential diagnosis and prognosis of IPF. Methods: Relevant artic...
Optimization of a pump-pipe system by dynamic programming
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui; Ferreira, Jose S.
1984-01-01
In this paper the problem of minimizing the total cost of a pump-pipe system in series is considered. The route of the pipeline and the number of pumping stations are known. The optimization will then consist in determining the control variables, diameter and thickness of the pipe and the size of...... of the pumps. A general mathematical model is formulated and Dynamic Programming is used to find an optimal solution....
Systems and methods for interpolation-based dynamic programming
Rockwood, Alyn
2013-01-03
Embodiments of systems and methods for interpolation-based dynamic programming. In one embodiment, the method includes receiving an object function and a set of constraints associated with the objective function. The method may also include identifying a solution on the objective function corresponding to intersections of the constraints. Additionally, the method may include generating an interpolated surface that is in constant contact with the solution. The method may also include generating a vector field in response to the interpolated surface.
Dynamic Programming Approach for Construction of Association Rule Systems
Alsolami, Fawaz
2016-11-18
In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.
Systems and methods for interpolation-based dynamic programming
Rockwood, Alyn
2013-01-01
Embodiments of systems and methods for interpolation-based dynamic programming. In one embodiment, the method includes receiving an object function and a set of constraints associated with the objective function. The method may also include identifying a solution on the objective function corresponding to intersections of the constraints. Additionally, the method may include generating an interpolated surface that is in constant contact with the solution. The method may also include generating a vector field in response to the interpolated surface.
DYNAMIC PROGRAMMING – EFFICIENT TOOL FOR POWER SYSTEM EXPANSION PLANNING
Directory of Open Access Journals (Sweden)
SIMO A.
2015-03-01
Full Text Available The paper isfocusing on dynamic programming use for power system expansion planning (EP – transmission network (TNEP and distribution network (DNEP. The EP problem has been approached from the retrospective and prospective point of view. To achieve this goal, the authors are developing two software-tools in Matlab environment. Two techniques have been tackled: particle swarm optimization (PSO and genetic algorithms (GA. The case study refers to Test 25 buses test power system developed within the Power Systems Department.
Dynamic Programming Approach for Construction of Association Rule Systems
Alsolami, Fawaz; Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
2016-01-01
In the paper, an application of dynamic programming approach for optimization of association rules from the point of view of knowledge representation is considered. The association rule set is optimized in two stages, first for minimum cardinality and then for minimum length of rules. Experimental results present cardinality of the set of association rules constructed for information system and lower bound on minimum possible cardinality of rule set based on the information obtained during algorithm work as well as obtained results for length.
SEWER NETWORK DISCHARGE OPTIMIZATION USING THE DYNAMIC PROGRAMMING
Directory of Open Access Journals (Sweden)
Viorel MINZU
2015-12-01
Full Text Available It is necessary to adopt an optimal control that allows an efficient usage of the existing sewer networks, in order to avoid the building of new retention facilities. The main objective of the control action is to minimize the overflow volume of a sewer network. This paper proposes a method to apply a solution obtained by discrete dynamic programming through a realistic closed loop system.
An Approximate Dynamic Programming Mode for Optimal MEDEVAC Dispatching
2015-03-26
over the myopic policy. This indicates the ADP policy is efficiently managing resources by 28 not immediately sending the nearest available MEDEVAC...DISPATCHING THESIS Presented to the Faculty Department of Operational Sciences Graduate School of Engineering and Management Air Force Institute of Technology...medical evacuation (MEDEVAC) dispatch policies. To solve the MDP, we apply an ap- proximate dynamic programming (ADP) technique. The problem of deciding
Approximate Dynamic Programming Based on High Dimensional Model Representation
Czech Academy of Sciences Publication Activity Database
Pištěk, Miroslav
2013-01-01
Roč. 49, č. 5 (2013), s. 720-737 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GAP102/11/0437 Institutional support: RVO:67985556 Keywords : approximate dynamic programming * Bellman equation * approximate HDMR minimization * trust region problem Subject RIV: BC - Control Systems Theory Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/pistek-0399560.pdf
An algorithm for the solution of dynamic linear programs
Psiaki, Mark L.
1989-01-01
The algorithm's objective is to efficiently solve Dynamic Linear Programs (DLP) by taking advantage of their special staircase structure. This algorithm constitutes a stepping stone to an improved algorithm for solving Dynamic Quadratic Programs, which, in turn, would make the nonlinear programming method of Successive Quadratic Programs more practical for solving trajectory optimization problems. The ultimate goal is to being trajectory optimization solution speeds into the realm of real-time control. The algorithm exploits the staircase nature of the large constraint matrix of the equality-constrained DLPs encountered when solving inequality-constrained DLPs by an active set approach. A numerically-stable, staircase QL factorization of the staircase constraint matrix is carried out starting from its last rows and columns. The resulting recursion is like the time-varying Riccati equation from multi-stage LQR theory. The resulting factorization increases the efficiency of all of the typical LP solution operations over that of a dense matrix LP code. At the same time numerical stability is ensured. The algorithm also takes advantage of dynamic programming ideas about the cost-to-go by relaxing active pseudo constraints in a backwards sweeping process. This further decreases the cost per update of the LP rank-1 updating procedure, although it may result in more changes of the active set that if pseudo constraints were relaxed in a non-stagewise fashion. The usual stability of closed-loop Linear/Quadratic optimally-controlled systems, if it carries over to strictly linear cost functions, implies that the saving due to reduced factor update effort may outweigh the cost of an increased number of updates. An aerospace example is presented in which a ground-to-ground rocket's distance is maximized. This example demonstrates the applicability of this class of algorithms to aerospace guidance. It also sheds light on the efficacy of the proposed pseudo constraint relaxation
A dynamic programming approach to missing data estimation using neural networks
CSIR Research Space (South Africa)
Nelwamondo, FV
2013-01-01
Full Text Available method where dynamic programming is not used. This paper also suggests a different way of formulating a missing data problem such that the dynamic programming is applicable to estimate the missing data....
Programming Unconventional Computers: Dynamics, Development, Self-Reference
Directory of Open Access Journals (Sweden)
Susan Stepney
2012-10-01
Full Text Available Classical computing has well-established formalisms for specifying, refining, composing, proving, and otherwise reasoning about computations. These formalisms have matured over the past 70 years or so. Unconventional Computing includes the use of novel kinds of substrates–from black holes and quantum effects, through to chemicals, biomolecules, even slime moulds–to perform computations that do not conform to the classical model. Although many of these unconventional substrates can be coerced into performing classical computation, this is not how they “naturally” compute. Our ability to exploit unconventional computing is partly hampered by a lack of corresponding programming formalisms: we need models for building, composing, and reasoning about programs that execute in these substrates. What might, say, a slime mould programming language look like? Here I outline some of the issues and properties of these unconventional substrates that need to be addressed to find “natural” approaches to programming them. Important concepts include embodied real values, processes and dynamical systems, generative systems and their meta-dynamics, and embodied self-reference.
A program for dynamic noise investigations of reactor systems
International Nuclear Information System (INIS)
Antonov, N.A.; Yaneva, N.B.
1980-01-01
A stochastic process analysis in nuclear reactors is used for the state diagnosis and dynamic characteristic investigation of the reactor system. A program DENSITY adapted and tested on an IBM 360 ES type computer is developed. The program is adjusted for fast processing of long series exploiting a relatively small memory. The testing procedure is discussed and the method of the periodic sequences corresponding to characteristic reactivity perturbations of the reactor systems is considered. The program is written for calculating the auto-power spectral density and the cross-power spectral density, as well as the coherence function of stationary statistical time series using the advantages of the fast Fourier transformation. In particular, it is shown that the multi-frequency binary sequences are very useful with respect to the signal-to-noise ratio and the frequency distribution in view of the frequency reactor test
2012-03-30
... DEPARTMENT OF TRANSPORTATION Dynamic Mobility Applications and Data Capture Management Programs... stakeholders an update on the Data Capture and Management (DCM) and Dynamic Mobility Applications (DMA... critical issues designed to garner stakeholder feedback. About the Dynamic Mobility Application and Data...
Temporal information encoding in dynamic memristive devices
Energy Technology Data Exchange (ETDEWEB)
Ma, Wen; Chen, Lin; Du, Chao; Lu, Wei D., E-mail: wluee@eecs.umich.edu [Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan 48109 (United States)
2015-11-09
We show temporal and frequency information can be effectively encoded in memristive devices with inherent short-term dynamics. Ag/Ag{sub 2}S/Pd based memristive devices with low programming voltage (∼100 mV) were fabricated and tested. At weak programming conditions, the devices exhibit inherent decay due to spontaneous diffusion of the Ag atoms. When the devices were subjected to pulse train inputs emulating different spiking patterns, the switching probability distribution function diverges from the standard Poisson distribution and evolves according to the input pattern. The experimentally observed switching probability distributions and the associated cumulative probability functions can be well-explained using a model accounting for the short-term decay effects. Such devices offer an intriguing opportunity to directly encode neural signals for neural information storage and analysis.
Development and demonstration program for dynamic nuclear materials control
International Nuclear Information System (INIS)
Augustson, R.H.; Baron, N.; Ford, R.F.; Ford, W.; Hagen, J.; Li, T.K.; Marshall, R.S.; Reams, V.S.; Severe, W.R.; Shirk, D.G.
1978-01-01
A significant portion of the Los Alamos Scientific Laboratory Safeguards Program is directed toward the development and demonstration of dynamic nuclear materials control. The building chosen for the demonstration system is the new Plutonium Processing Facility in Los Alamos, which houses such operations as metal-to-oxide conversion, fuel pellet fabrication, and scrap recovery. A DYnamic MAterials Control (DYMAC) system is currently being installed in the facility as an integral part of the processing operation. DYMAC is structured around interlocking unit-process accounting areas. It relies heavily on nondestructive assay measurements made in the process line to draw dynamic material balances in near real time. In conjunction with the nondestructive assay instrumentation, process operators use interactive terminals to transmit additional accounting and process information to a dedicated computer. The computer verifies and organizes the incoming data, immediately updates the inventory records, monitors material in transit using elapsed time, and alerts the Nuclear Materials Officer in the event that material balances exceed the predetermined action limits. DYMAC is part of the United States safeguards system under control of the facility operator. Because of its advanced features, the system will present a new set of inspection conditions to the IAEA, whose response is the subject of a study being sponsored by the US-IAEA Technical Assistance Program. The central issue is how the IAEA can use the increased capabilities of such a system and still maintain independent verification
DEFF Research Database (Denmark)
Wu, Y P; Liu, Z H; Wei, R
2009-01-01
Pulmonary SP-D is a defence lectin promoting clearance of viral infections. SP-D is recognized to bind the S protein of SARS-CoV and enhance phagocytosis. Moreover, systemic SP-D is widely used as a biomarker of alveolar integrity. We investigated the relation between plasma SP-D, SARS-type pneum......Pulmonary SP-D is a defence lectin promoting clearance of viral infections. SP-D is recognized to bind the S protein of SARS-CoV and enhance phagocytosis. Moreover, systemic SP-D is widely used as a biomarker of alveolar integrity. We investigated the relation between plasma SP-D, SARS......-type pneumonia and the SARS-specific IgG response. Sixteen patients with SARS, 19 patients with community-acquired pneumonia (CAP) (Streptococcus pneumonia) and 16 healthy control subjects were enrolled in the study. Plasma SP-D and anti-SARS-CoV N protein IgG were measured using ELISA. SP-D was significantly...... elevated in SARS-type pneumonia [median (95% CI), 453 (379-963) ng/ml versus controls 218 (160-362) ng/ml, P protein IgG (r(2) = 0.5995, P = 0.02). The possible re-emergence of SARS or SARS-like infections suggests a need...
Musical structure analysis using similarity matrix and dynamic programming
Shiu, Yu; Jeong, Hong; Kuo, C.-C. Jay
2005-10-01
Automatic music segmentation and structure analysis from audio waveforms based on a three-level hierarchy is examined in this research, where the three-level hierarchy includes notes, measures and parts. The pitch class profile (PCP) feature is first extracted at the note level. Then, a similarity matrix is constructed at the measure level, where a dynamic time warping (DTW) technique is used to enhance the similarity computation by taking the temporal distortion of similar audio segments into account. By processing the similarity matrix, we can obtain a coarse-grain music segmentation result. Finally, dynamic programming is applied to the coarse-grain segments so that a song can be decomposed into several major parts such as intro, verse, chorus, bridge and outro. The performance of the proposed music structure analysis system is demonstrated for pop and rock music.
Dynamic Programming and Graph Algorithms in Computer Vision*
Felzenszwalb, Pedro F.; Zabih, Ramin
2013-01-01
Optimization is a powerful paradigm for expressing and solving problems in a wide range of areas, and has been successfully applied to many vision problems. Discrete optimization techniques are especially interesting, since by carefully exploiting problem structure they often provide non-trivial guarantees concerning solution quality. In this paper we briefly review dynamic programming and graph algorithms, and discuss representative examples of how these discrete optimization techniques have been applied to some classical vision problems. We focus on the low-level vision problem of stereo; the mid-level problem of interactive object segmentation; and the high-level problem of model-based recognition. PMID:20660950
Optimization of Algorithms Using Extensions of Dynamic Programming
AbouEisha, Hassan M.
2017-04-09
We study and answer questions related to the complexity of various important problems such as: multi-frontal solvers of hp-adaptive finite element method, sorting and majority. We advocate the use of dynamic programming as a viable tool to study optimal algorithms for these problems. The main approach used to attack these problems is modeling classes of algorithms that may solve this problem using a discrete model of computation then defining cost functions on this discrete structure that reflect different complexity measures of the represented algorithms. As a last step, dynamic programming algorithms are designed and used to optimize those models (algorithms) and to obtain exact results on the complexity of the studied problems. The first part of the thesis presents a novel model of computation (element partition tree) that represents a class of algorithms for multi-frontal solvers along with cost functions reflecting various complexity measures such as: time and space. It then introduces dynamic programming algorithms for multi-stage and bi-criteria optimization of element partition trees. In addition, it presents results based on optimal element partition trees for famous benchmark meshes such as: meshes with point and edge singularities. New improved heuristics for those benchmark meshes were ob- tained based on insights of the optimal results found by our algorithms. The second part of the thesis starts by introducing a general problem where different problems can be reduced to and show how to use a decision table to model such problem. We describe how decision trees and decision tests for this table correspond to adaptive and non-adaptive algorithms for the original problem. We present exact bounds on the average time complexity of adaptive algorithms for the eight elements sorting problem. Then bounds on adaptive and non-adaptive algorithms for a variant of the majority problem are introduced. Adaptive algorithms are modeled as decision trees whose depth
DEGAS: Dynamic Exascale Global Address Space Programming Environments
Energy Technology Data Exchange (ETDEWEB)
Demmel, James [Univ. of California, Berkeley, CA (United States)
2018-02-23
The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics. The Berkeley part of the project concentrated on communication-optimal code generation to optimize speed and energy efficiency by reducing data movement. Our work developed communication lower bounds, and/or communication avoiding algorithms (that either meet the lower bound, or do much less communication than their conventional counterparts) for a variety of algorithms, including linear algebra, machine learning and genomics.
Dynamics of the public concern and risk communication program implementation.
Zaryabova, Victoria; Israel, Michel
2015-09-01
The public concern about electromagnetic field (EMF) exposure varies due to different reasons. A part of them are connected with the better and higher quality of information that people receive from science, media, Internet, social networks, industry, but others are based on good communication programs performed by the responsible institutions, administration and persons. Especially, in Bulgaria, public concern follows interesting changes, some of them in correlation with the European processes of concern, but others following the economic and political processes in the country. Here, we analyze the dynamics of the public concern over the last 10 years. Our explanation of the decrease of the people's complaints against EMF exposure from base stations for mobile communication is as a result of our risk communication program that is in implementation for >10 years.
Development of nonlinear dynamic analysis program for nuclear piping systems
International Nuclear Information System (INIS)
Kamichika, Ryoichi; Izawa, Masahiro; Yamadera, Masao
1980-01-01
In the design for nuclear power piping, pipe-whip protection shall be considered in order to keep the function of safety related system even when postulated piping rupture occurs. This guideline was shown in U.S. Regulatory Guide 1.46 for the first time and has been applied in Japanese nuclear power plants. In order to analyze the dynamic behavior followed by pipe rupture, nonlinear analysis is required for the piping system including restraints which play the role of an energy absorber. REAPPS (Rupture Effective Analysis of Piping Systems) has been developed for this purpose. This program can be applied to general piping systems having branches etc. Pre- and post- processors are prepared in this program in order to easily input the data for the piping engineer and show the results optically by use of a graphic display respectively. The piping designer can easily solve many problems in his daily work by use of this program. This paper describes about the theoretical background and functions of this program and shows some examples. (author)
Evaluation of Electric Power Procurement Strategies by Stochastic Dynamic Programming
Saisho, Yuichi; Hayashi, Taketo; Fujii, Yasumasa; Yamaji, Kenji
In deregulated electricity markets, the role of a distribution company is to purchase electricity from the wholesale electricity market at randomly fluctuating prices and to provide it to its customers at a given fixed price. Therefore the company has to take risk stemming from the uncertainties of electricity prices and/or demand fluctuation instead of the customers. The way to avoid the risk is to make a bilateral contact with generating companies or install its own power generation facility. This entails the necessity to develop a certain method to make an optimal strategy for electric power procurement. In such a circumstance, this research has the purpose for proposing a mathematical method based on stochastic dynamic programming and additionally considering the characteristics of the start-up cost of electric power generation facility to evaluate strategies of combination of the bilateral contract and power auto-generation with its own facility for procuring electric power in deregulated electricity market. In the beginning we proposed two approaches to solve the stochastic dynamic programming, and they are a Monte Carlo simulation method and a finite difference method to derive the solution of a partial differential equation of the total procurement cost of electric power. Finally we discussed the influences of the price uncertainty on optimal strategies of power procurement.
A mathematical programming approach for sequential clustering of dynamic networks
Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia
2016-02-01
A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.
Approximate Dynamic Programming in Tracking Control of a Robotic Manipulator
Directory of Open Access Journals (Sweden)
Marcin Szuster
2016-02-01
Full Text Available This article focuses on the implementation of an approximate dynamic programming algorithm in the discrete tracking control system of the three-degrees of freedom Scorbot-ER 4pc robotic manipulator. The controlled system is included in an articulated robots group which uses rotary joints to access their work space. The main part of the control system is a dual heuristic dynamic programming algorithm that consists of two structures designed in the form of neural networks: an actor and a critic. The actor generates the suboptimal control law while the critic approximates the difference of the value function from Bellman's equation with respect to the state. The residual elements of the control system are the PD controller, the supervisory term and an additional control signal. The structure of the supervisory term derives from the stability analysis performed using the Lyapunov stability theorem. The control system works online, the neural networks' weights-adaptation procedure is performed in every iteration step, and the neural networks' preliminary learning process is not required. The performance of the control system was verified by a series of computer simulations and experiments performed using the Scorbot-ER 4pc robotic manipulator.
Directory of Open Access Journals (Sweden)
Max Reinhardt
2011-05-01
Full Text Available This article discusses methods and results of an explorative study of two generations of the Social Democratic Party of Germany (SPD: the two generations comprise, on the one hand, older and younger members of the postwar generation who witnessed the Second World War as young soldiers or as children, and on the other hand, the generation that was born in the 1950s and has mainly been responsible for shaping policy for some years. The aim of my dissertation was to analyze the ability of the social democratic leadership to represent the full range of party members and (base voters by comparing two generations, using a sample of political leaders and the habitus/field-analysis inspired by Pierre BOURDIEU. The basis of the analysis were partly biographical, partly theme-focused interviews, as well as a range of sources and already published literature regarding the biographies of these political leaders. The following article is based on my dissertation and is focused on a description of selected theoretical implications, on the description of the essential criteria for selecting the sample and on some of the methods used. These are an analysis of the life, life and field effects, the factions and the development of types of political leaders. I will present some results to exemplify the methods used. They show that the ability of the SPD to represent the full range of party members and (base voters and the power structure of the SPD have changed, thus threatening the party’s status as a "Volkspartei." URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs1102197
Patriarca, M.; Kuronen, A.; Robles, M.; Kaski, K.
2007-01-01
The study of crystal defects and the complex processes underlying their formation and time evolution has motivated the development of the program ALINE for interactive molecular dynamics experiments. This program couples a molecular dynamics code to a Graphical User Interface and runs on a UNIX-X11 Window System platform with the MOTIF library, which is contained in many standard Linux releases. ALINE is written in C, thus giving the user the possibility to modify the source code, and, at the same time, provides an effective and user-friendly framework for numerical experiments, in which the main parameters can be interactively varied and the system visualized in various ways. We illustrate the main features of the program through some examples of detection and dynamical tracking of point-defects, linear defects, and planar defects, such as stacking faults in lattice-mismatched heterostructures. Program summaryTitle of program:ALINE Catalogue identifier:ADYJ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADYJ_v1_0 Program obtainable from: CPC Program Library, Queen University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: Computers:DEC ALPHA 300, Intel i386 compatible computers, G4 Apple Computers Installations:Laboratory of Computational Engineering, Helsinki University of Technology, Helsinki, Finland Operating systems under which the program has been tested:True64 UNIX, Linux-i386, Mac OS X 10.3 and 10.4 Programming language used:Standard C and MOTIF libraries Memory required to execute with typical data:6 Mbytes but may be larger depending on the system size No. of lines in distributed program, including test data, etc.:16 901 No. of bytes in distributed program, including test data, etc.:449 559 Distribution format:tar.gz Nature of physical problem:Some phenomena involving defects take place inside three-dimensional crystals at times which can be hardly predicted. For this reason they are
Congedo, Marco; Barachant, Alexandre
2015-01-01
Currently the Riemannian geometry of symmetric positive definite (SPD) matrices is gaining momentum as a powerful tool in a wide range of engineering applications such as image, radar and biomedical data signal processing. If the data is not natively represented in the form of SPD matrices, typically we may summarize them in such form by estimating covariance matrices of the data. However once we manipulate such covariance matrices on the Riemannian manifold we lose the representation in the original data space. For instance, we can evaluate the geometric mean of a set of covariance matrices, but not the geometric mean of the data generating the covariance matrices, the space of interest in which the geometric mean can be interpreted. As a consequence, Riemannian information geometry is often perceived by non-experts as a "black-box" tool and this perception prevents a wider adoption in the scientific community. Hereby we show that we can overcome this limitation by constructing a special form of SPD matrix embedding both the covariance structure of the data and the data itself. Incidentally, whenever the original data can be represented in the form of a generic data matrix (not even square), this special SPD matrix enables an exhaustive and unique description of the data up to second-order statistics. This is achieved embedding the covariance structure of both the rows and columns of the data matrix, allowing naturally a wide range of possible applications and bringing us over and above just an interpretability issue. We demonstrate the method by manipulating satellite images (pansharpening) and event-related potentials (ERPs) of an electroencephalography brain-computer interface (BCI) study. The first example illustrates the effect of moving along geodesics in the original data space and the second provides a novel estimation of ERP average (geometric mean), showing that, in contrast to the usual arithmetic mean, this estimation is robust to outliers. In
Impact of serum SP-A and SP-D levels on comparison and prognosis of idiopathic pulmonary fibrosis
Wang, Kai; Ju, Qing; Cao, Jing; Tang, Wenze; Zhang, Jian
2017-01-01
Abstract Background and objective: Idiopathic pulmonary fibrosis (IPF) has a poor prognosis in general; however, it is heterogeneous to detect relative biomarkers for predicting the disease progression. Serum biomarkers can be conveniently collected to detect and help to differentially diagnose IPF and predict IPF prognosis. This meta-analysis aimed to evaluate the use of serum surfactant proteins A and D (SP-A and SP-D) for differential diagnosis and prognosis of IPF. Methods: Relevant articles were searched in PubMed, Embase, and Chinese National Knowledge Infrastructure databases and reviewed by 2 independent readers. Standard mean difference (SMD) and 95% confidence interval (CI) were calculated to assess the difference in serum levels of SP-A/D among patients with IPF, when compared to patients with non-IPF interstitial lung disease (ILD), pulmonary infection, and healthy control. Hazard ratio (HR) and 95% CI were used to compare the relative risk of mortality. Results: Twenty-one articles (totalling 1289 IPF patients) were included in final meta-analysis. Serum SP-A levels were significantly higher in patients with IPF than in patients with non-IPF ILD (SMD: 1.108 [0.584, 1.632], P infection (SMD: 1.320 [0.999, 1.640], P SMD: 2.802 [1.901, 3.702], P SMD: 0.459 [−0.000, 0.919], P = .050). Serum SP-D levels were significantly higher in patients with IPF than in patients with pulmonary infection (SMD: 1.308 [0.813, 1.803], P SMD: 2.235 [1.739, 2.731], P < .001). Risk of death in patients with IPF and elevated serum SP-A was increased 39% compared to patients with low SP-A groups. Elevated SP-D increased risk by 111% when compared to low SP-D. In acute exacerbation of IPF, serum SP-A/D were higher than those in stable stage. The comparisons and prognosis might be different in Asian and Caucasian patients. Conclusions: Serum SP-A/D detection might be useful for differential diagnosis and prediction of survival in patients with IPF. PMID:28591049
Dynamic electricity pricing for electric vehicles using stochastic programming
International Nuclear Information System (INIS)
Soares, João; Ghazvini, Mohammad Ali Fotouhi; Borges, Nuno; Vale, Zita
2017-01-01
Electric Vehicles (EVs) are an important source of uncertainty, due to their variable demand, departure time and location. In smart grids, the electricity demand can be controlled via Demand Response (DR) programs. Smart charging and vehicle-to-grid seem highly promising methods for EVs control. However, high capital costs remain a barrier to implementation. Meanwhile, incentive and price-based schemes that do not require high level of control can be implemented to influence the EVs' demand. Having effective tools to deal with the increasing level of uncertainty is increasingly important for players, such as energy aggregators. This paper formulates a stochastic model for day-ahead energy resource scheduling, integrated with the dynamic electricity pricing for EVs, to address the challenges brought by the demand and renewable sources uncertainty. The two-stage stochastic programming approach is used to obtain the optimal electricity pricing for EVs. A realistic case study projected for 2030 is presented based on Zaragoza network. The results demonstrate that it is more effective than the deterministic model and that the optimal pricing is preferable. This study indicates that adequate DR schemes like the proposed one are promising to increase the customers' satisfaction in addition to improve the profitability of the energy aggregation business. - Highlights: • A stochastic model for energy scheduling tackling several uncertainty sources. • A two-stage stochastic programming is used to tackle the developed model. • Optimal EV electricity pricing seems to improve the profits. • The propose results suggest to increase the customers' satisfaction.
Directory of Open Access Journals (Sweden)
Korry Apriandi
2015-01-01
Full Text Available The object of this research in PT. SPD Semarang by using the type and design was qualitative and descriptive research the were aims to know the execution of SMK3 application on OHSAS 18001: 2007 in PT. SPD Semarang. From the results show that implementation of SMK3 on OHSAS PT. SPD as much as 131 points (87,3%. For points that haven’t met the standards yet as much as 10 points (6.7%. And for the points which don’t meet as many as 9 points (6%. So, PT. SPD were included in the category level assessment good or equivalent certificate flag gold tally. It was advisable to PT. SPD to enhance the application of SMK3 based on OHSAS with: (1 required to have a manual SMK3 on OHSAS, (2 required to have procedures for identifying, accessing and updating rules K3, (3 required to provide competent resources to SMK3 implementations, (4 the HSE training should be distinguished the responsibilities, competencies, languages, skills and risk, (5 should be doing simulated fire emergency, (6 must have data calibration tools in accordance with the regulations.
Lewis, F L; Vamvoudakis, Kyriakos G
2011-02-01
Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.
Directory of Open Access Journals (Sweden)
Jooyoung Park
2015-05-01
Full Text Available Recently, the optimization of power flows in portable hybrid power-supply systems (HPSSs has become an important issue with the advent of a variety of mobile systems and hybrid energy technologies. In this paper, a control strategy is considered for dynamically managing power flows in portable HPSSs employing batteries and supercapacitors. Our dynamic power management strategy utilizes the concept of approximate dynamic programming (ADP. ADP methods are important tools in the fields of stochastic control and machine learning, and the utilization of these tools for practical engineering problems is now an active and promising research field. We propose an ADP-based procedure based on optimization under constraints including the iterated Bellman inequalities, which can be solved by convex optimization carried out offline, to find the optimal power management rules for portable HPSSs. The effectiveness of the proposed procedure is tested through dynamic simulations for smartphone workload scenarios, and simulation results show that the proposed strategy can successfully cope with uncertain workload demands.
Hamiltonian-Driven Adaptive Dynamic Programming for Continuous Nonlinear Dynamical Systems.
Yang, Yongliang; Wunsch, Donald; Yin, Yixin
2017-08-01
This paper presents a Hamiltonian-driven framework of adaptive dynamic programming (ADP) for continuous time nonlinear systems, which consists of evaluation of an admissible control, comparison between two different admissible policies with respect to the corresponding the performance function, and the performance improvement of an admissible control. It is showed that the Hamiltonian can serve as the temporal difference for continuous-time systems. In the Hamiltonian-driven ADP, the critic network is trained to output the value gradient. Then, the inner product between the critic and the system dynamics produces the value derivative. Under some conditions, the minimization of the Hamiltonian functional is equivalent to the value function approximation. An iterative algorithm starting from an arbitrary admissible control is presented for the optimal control approximation with its convergence proof. The implementation is accomplished by a neural network approximation. Two simulation studies demonstrate the effectiveness of Hamiltonian-driven ADP.
Optimization of decision rules based on dynamic programming approach
Zielosko, Beata
2014-01-14
This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.
Estimating Arrhenius parameters using temperature programmed molecular dynamics
International Nuclear Information System (INIS)
Imandi, Venkataramana; Chatterjee, Abhijit
2016-01-01
Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.
Estimating Arrhenius parameters using temperature programmed molecular dynamics
Energy Technology Data Exchange (ETDEWEB)
Imandi, Venkataramana; Chatterjee, Abhijit, E-mail: abhijit@che.iitb.ac.in [Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai 400076 (India)
2016-07-21
Kinetic rates at different temperatures and the associated Arrhenius parameters, whenever Arrhenius law is obeyed, are efficiently estimated by applying maximum likelihood analysis to waiting times collected using the temperature programmed molecular dynamics method. When transitions involving many activated pathways are available in the dataset, their rates may be calculated using the same collection of waiting times. Arrhenius behaviour is ascertained by comparing rates at the sampled temperatures with ones from the Arrhenius expression. Three prototype systems with corrugated energy landscapes, namely, solvated alanine dipeptide, diffusion at the metal-solvent interphase, and lithium diffusion in silicon, are studied to highlight various aspects of the method. The method becomes particularly appealing when the Arrhenius parameters can be used to find rates at low temperatures where transitions are rare. Systematic coarse-graining of states can further extend the time scales accessible to the method. Good estimates for the rate parameters are obtained with 500-1000 waiting times.
The sequence relay selection strategy based on stochastic dynamic programming
Zhu, Rui; Chen, Xihao; Huang, Yangchao
2017-07-01
Relay-assisted (RA) network with relay node selection is a kind of effective method to improve the channel capacity and convergence performance. However, most of the existing researches about the relay selection did not consider the statically channel state information and the selection cost. This shortage limited the performance and application of RA network in practical scenarios. In order to overcome this drawback, a sequence relay selection strategy (SRSS) was proposed. And the performance upper bound of SRSS was also analyzed in this paper. Furthermore, in order to make SRSS more practical, a novel threshold determination algorithm based on the stochastic dynamic program (SDP) was given to work with SRSS. Numerical results are also presented to exhibit the performance of SRSS with SDP.
Approximate dynamic programming approaches for appointment scheduling with patient preferences.
Li, Xin; Wang, Jin; Fung, Richard Y K
2018-04-01
During the appointment booking process in out-patient departments, the level of patient satisfaction can be affected by whether or not their preferences can be met, including the choice of physicians and preferred time slot. In addition, because the appointments are sequential, considering future possible requests is also necessary for a successful appointment system. This paper proposes a Markov decision process model for optimizing the scheduling of sequential appointments with patient preferences. In contrast to existing models, the evaluation of a booking decision in this model focuses on the extent to which preferences are satisfied. Characteristics of the model are analysed to develop a system for formulating booking policies. Based on these characteristics, two types of approximate dynamic programming algorithms are developed to avoid the curse of dimensionality. Experimental results suggest directions for further fine-tuning of the model, as well as improving the efficiency of the two proposed algorithms. Copyright © 2018 Elsevier B.V. All rights reserved.
Design and Analysis of Decision Rules via Dynamic Programming
Amin, Talha M.
2017-04-24
The areas of machine learning, data mining, and knowledge representation have many different formats used to represent information. Decision rules, amongst these formats, are the most expressive and easily-understood by humans. In this thesis, we use dynamic programming to design decision rules and analyze them. The use of dynamic programming allows us to work with decision rules in ways that were previously only possible for brute force methods. Our algorithms allow us to describe the set of all rules for a given decision table. Further, we can perform multi-stage optimization by repeatedly reducing this set to only contain rules that are optimal with respect to selected criteria. One way that we apply this study is to generate small systems with short rules by simulating a greedy algorithm for the set cover problem. We also compare maximum path lengths (depth) of deterministic and non-deterministic decision trees (a non-deterministic decision tree is effectively a complete system of decision rules) with regards to Boolean functions. Another area of advancement is the presentation of algorithms for constructing Pareto optimal points for rules and rule systems. This allows us to study the existence of “totally optimal” decision rules (rules that are simultaneously optimal with regards to multiple criteria). We also utilize Pareto optimal points to compare and rate greedy heuristics with regards to two criteria at once. Another application of Pareto optimal points is the study of trade-offs between cost and uncertainty which allows us to find reasonable systems of decision rules that strike a balance between length and accuracy.
Dynamic Line Rating Oncor Electric Delivery Smart Grid Program
Energy Technology Data Exchange (ETDEWEB)
Johnson, Justin; Smith, Cale; Young, Mike; Donohoo, Ken; Owen, Ross; Clark, Eddit; Espejo, Raul; Aivaliotis, Sandy; Stelmak, Ron; Mohr, Ron; Barba, Cristian; Gonzalez, Guillermo; Malkin, Stuart; Dimitrova, Vessela; Ragsdale, Gary; Mitchem, Sean; Jeirath, Nakul; Loomis, Joe; Trevino, Gerardo; Syracuse, Steve; Hurst, Neil; Mereness, Matt; Johnson, Chad; Bivens, Carrie
2013-05-04
Electric transmission lines are the lifeline of the electric utility industry, delivering its product from source to consumer. This critical infrastructure is often constrained such that there is inadequate capacity on existing transmission lines to efficiently deliver the power to meet demand in certain areas or to transport energy from high-generation areas to high-consumption regions. When this happens, the cost of the energy rises; more costly sources of power are used to meet the demand or the system operates less reliably. These economic impacts are known as congestion, and they can amount to substantial dollars for any time frame of reference: hour, day or year. There are several solutions to the transmission constraint problem, including: construction of new generation, construction of new transmission facilities, rebuilding and reconductoring of existing transmission assets, and Dynamic Line Rating (DLR). All of these options except DLR are capital intensive, have long lead times and often experience strong public and regulatory opposition. The Smart Grid Demonstration Program (SGDP) project co-funded by the Department of Energy (DOE) and Oncor Electric Delivery Company developed and deployed the most extensive and advanced DLR installation to demonstrate that DLR technology is capable of resolving many transmission capacity constraint problems with a system that is reliable, safe and very cost competitive. The SGDP DLR deployment is the first application of DLR technology to feed transmission line real-time dynamic ratings directly into the system operation’s State Estimator and load dispatch program, which optimizes the matching of generation with load demand on a security, reliability and economic basis. The integrated Dynamic Line Rating (iDLR)1 collects transmission line parameters at remote locations on the lines, calculates the real-time line rating based on the equivalent conductor temperature, ambient temperature and influence of wind and solar
1975-12-01
Frequency domain computer programs developed or acquired by TSC for the analysis of rail vehicle dynamics are described in two volumes. Volume I defines the general analytical capabilities required for computer programs applicable to single rail vehi...
Dynamic programming approach to optimization of approximate decision rules
Amin, Talha
2013-02-01
This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number of unordered pairs of rows with different decisions in the decision table T. For a nonnegative real number β, we consider β-decision rules that localize rows in subtables of T with uncertainty at most β. Our algorithm constructs a directed acyclic graph Δβ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most β. The graph Δβ(T) allows us to describe the whole set of so-called irredundant β-decision rules. We can describe all irredundant β-decision rules with minimum length, and after that among these rules describe all rules with maximum coverage. We can also change the order of optimization. The consideration of irredundant rules only does not change the results of optimization. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2012 Elsevier Inc. All rights reserved.
Dynamic programming approach for partial decision rule optimization
Amin, Talha
2012-10-04
This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.
Optimization of control poison management by dynamic programming
International Nuclear Information System (INIS)
Ponzoni Filho, P.
1974-01-01
A dynamic programming approach was used to optimize the poison distribution in the core of a nuclear power plant between reloading. This method was applied to a 500 M We PWR subject to two different fuel management policies. The beginning of a stage is marked by a fuel management decision. The state vector of the system is defined by the burnups in the three fuel zones of the core. The change of the state vector is computed in several time steps. A criticality conserving poison management pattern is chosen at the beginning of each step. The burnups at the end of a step are obtained by means of depletion calculations, assuming constant neutron distribution during the step. The violation of burnup and power peaking constraints during the step eliminates the corresponding end states. In the case of identical end states, all except that which produced the largest amount of energy, are eliminated. Among the several end states one is selected for the subsequent stage, when it is subjected to a fuel management decision. This selection is based on an optimally criterion previously chosen, such as: discharged fuel burnup maximization, energy generation cost minimization, etc. (author)
Dynamic programming approach for partial decision rule optimization
Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
2012-01-01
This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.
Replacement model of city bus: A dynamic programming approach
Arifin, Dadang; Yusuf, Edhi
2017-06-01
This paper aims to develop a replacement model of city bus vehicles operated in Bandung City. This study is driven from real cases encountered by the Damri Company in the efforts to improve services to the public. The replacement model propounds two policy alternatives: First, to maintain or keep the vehicles, and second is to replace them with new ones taking into account operating costs, revenue, salvage value, and acquisition cost of a new vehicle. A deterministic dynamic programming approach is used to solve the model. The optimization process was heuristically executed using empirical data of Perum Damri. The output of the model is to determine the replacement schedule and the best policy if the vehicle has passed the economic life. Based on the results, the technical life of the bus is approximately 20 years old, while the economic life is an average of 9 (nine) years. It means that after the bus is operated for 9 (nine) years, managers should consider the policy of rejuvenation.
Lymph node segmentation by dynamic programming and active contours.
Tan, Yongqiang; Lu, Lin; Bonde, Apurva; Wang, Deling; Qi, Jing; Schwartz, Lawrence H; Zhao, Binsheng
2018-03-03
Enlarged lymph nodes are indicators of cancer staging, and the change in their size is a reflection of treatment response. Automatic lymph node segmentation is challenging, as the boundary can be unclear and the surrounding structures complex. This work communicates a new three-dimensional algorithm for the segmentation of enlarged lymph nodes. The algorithm requires a user to draw a region of interest (ROI) enclosing the lymph node. Rays are cast from the center of the ROI, and the intersections of the rays and the boundary of the lymph node form a triangle mesh. The intersection points are determined by dynamic programming. The triangle mesh initializes an active contour which evolves to low-energy boundary. Three radiologists independently delineated the contours of 54 lesions from 48 patients. Dice coefficient was used to evaluate the algorithm's performance. The mean Dice coefficient between computer and the majority vote results was 83.2%. The mean Dice coefficients between the three radiologists' manual segmentations were 84.6%, 86.2%, and 88.3%. The performance of this segmentation algorithm suggests its potential clinical value for quantifying enlarged lymph nodes. © 2018 American Association of Physicists in Medicine.
DEFF Research Database (Denmark)
Lee, Mary Y K; Sørensen, Grith L; Holmskov, Uffe
2009-01-01
Surfactant protein D (SP-D) mediates clearance of microorganisms and modulates inflammation in response to cytotoxic stimulation. It is present in various epithelia, but also in vascular smooth muscle and endothelial cells. Experiments were designed to determine whether or not SP-D is present......Da and 50 kDa). The 37-38 kDa SP-D forms were the dominant isoforms in the porcine endothelium and were prominent at #1 but partially lost at #4. Tumor necrosis factor-alpha (TNF-alpha) significantly augmented the level of SP-D expression at #1 but not at #4. The basal level of 37-38 kDa SP-D isoforms at #1...
Energy Technology Data Exchange (ETDEWEB)
Tanabe, R.; Yasuda, K.; Yokoyama, R. (Tokyo Metropolitan Univ., Tokyo (Japan))
1992-05-20
To supply cheap, high-reliable and a planty of the electricity is an important task of the electric supply system because the requirement for the electricity is rapidly increased in Japan. In order to solve this problem, the authors of the paper are developing a most suitable practical method based on algorithm, according to which the generation expansion planning is divided into two problems: the optimal generation mix and the optimal generation construction process and the two problems are solved respectively. But there are some bad points in the method, for example, there are only approximative practical restriction of the capacity of single machine and the existing electric supply etc., because the optimal generation mix is determined on the basis of non-linear planning. So, in the present paper, the electric supply support system is practically constructed while proposing an unified generation expansion planning based on the dynamic programming that is possible to consider these restrictions strictly and the usefullness of the method is inspected. 12 refs., 7 figs., 5 tabs.
Skin tumor area extraction using an improved dynamic programming approach.
Abbas, Qaisar; Celebi, M E; Fondón García, Irene
2012-05-01
Border (B) description of melanoma and other pigmented skin lesions is one of the most important tasks for the clinical diagnosis of dermoscopy images using the ABCD rule. For an accurate description of the border, there must be an effective skin tumor area extraction (STAE) method. However, this task is complicated due to uneven illumination, artifacts present in the lesions and smooth areas or fuzzy borders of the desired regions. In this paper, a novel STAE algorithm based on improved dynamic programming (IDP) is presented. The STAE technique consists of the following four steps: color space transform, pre-processing, rough tumor area detection and refinement of the segmented area. The procedure is performed in the CIE L(*) a(*) b(*) color space, which is approximately uniform and is therefore related to dermatologist's perception. After pre-processing the skin lesions to reduce artifacts, the DP algorithm is improved by introducing a local cost function, which is based on color and texture weights. The STAE method is tested on a total of 100 dermoscopic images. In order to compare the performance of STAE with other state-of-the-art algorithms, various statistical measures based on dermatologist-drawn borders are utilized as a ground truth. The proposed method outperforms the others with a sensitivity of 96.64%, a specificity of 98.14% and an error probability of 5.23%. The results demonstrate that this STAE method by IDP is an effective solution when compared with other state-of-the-art segmentation techniques. The proposed method can accurately extract tumor borders in dermoscopy images. © 2011 John Wiley & Sons A/S.
The NASA Computational Fluid Dynamics (CFD) program - Building technology to solve future challenges
Richardson, Pamela F.; Dwoyer, Douglas L.; Kutler, Paul; Povinelli, Louis A.
1993-01-01
This paper presents the NASA Computational Fluid Dynamics program in terms of a strategic vision and goals as well as NASA's financial commitment and personnel levels. The paper also identifies the CFD program customers and the support to those customers. In addition, the paper discusses technical emphasis and direction of the program and some recent achievements. NASA's Ames, Langley, and Lewis Research Centers are the research hubs of the CFD program while the NASA Headquarters Office of Aeronautics represents and advocates the program.
A user's guide to the Flexible Spacecraft Dynamics and Control Program
Fedor, J. V.
1984-01-01
A guide to the use of the Flexible Spacecraft Dynamics Program (FSD) is presented covering input requirements, control words, orbit generation, spacecraft description and simulation options, and output definition. The program can be used in dynamics and control analysis as well as in orbit support of deployment and control of spacecraft. The program is applicable to inertially oriented spinning, Earth oriented or gravity gradient stabilized spacecraft. Internal and external environmental effects can be simulated.
Evolutionary programming for goal-driven dynamic planning
Vaccaro, James M.; Guest, Clark C.; Ross, David O.
2002-03-01
Many complex artificial intelligence (IA) problems are goal- driven in nature and the opportunity exists to realize the benefits of a goal-oriented solution. In many cases, such as in command and control, a goal-oriented approach may be the only option. One of many appropriate applications for such an approach is War Gaming. War Gaming is an important tool for command and control because it provides a set of alternative courses of actions so that military leaders can contemplate their next move in the battlefield. For instance, when making decisions that save lives, it is necessary to completely understand the consequences of a given order. A goal-oriented approach provides a slowly evolving tractably reasoned solution that inherently follows one of the principles of war: namely concentration on the objective. Future decision-making will depend not only on the battlefield, but also on a virtual world where military leaders can wage wars and determine their options by playing computer war games much like the real world. The problem with these games is that the built-in AI does not learn nor adapt and many times cheats, because the intelligent player has access to all the information, while the user has access to limited information provided on a display. These games are written for the purpose of entertainment and actions are calculated a priori and off-line, and are made prior or during their development. With these games getting more sophisticated in structure and less domain specific in scope, there needs to be a more general intelligent player that can adapt and learn in case the battlefield situations or the rules of engagement change. One such war game that might be considered is Risk. Risk incorporates the principles of war, is a top-down scalable model, and provides a good application for testing a variety of goal- oriented AI approaches. By integrating a goal-oriented hybrid approach, one can develop a program that plays the Risk game effectively and move
An energy management for series hybrid electric vehicle using improved dynamic programming
Peng, Hao; Yang, Yaoquan; Liu, Chunyu
2018-02-01
With the increasing numbers of hybrid electric vehicle (HEV), management for two energy sources, engine and battery, is more and more important to achieve the minimum fuel consumption. This paper introduces several working modes of series hybrid electric vehicle (SHEV) firstly and then describes the mathematical model of main relative components in SHEV. On the foundation of this model, dynamic programming is applied to distribute energy of engine and battery on the platform of matlab and acquires less fuel consumption compared with traditional control strategy. Besides, control rule recovering energy in brake profiles is added into dynamic programming, so shorter computing time is realized by improved dynamic programming and optimization on algorithm.
Testing Object-Oriented Programs using Dynamic Aspects and Non-Determinism
DEFF Research Database (Denmark)
Achenbach, Michael; Ostermann, Klaus
2010-01-01
decisions exposing private data. We present an approach that both improves the expressiveness of test cases using non-deterministic choice and reduces design modifications using dynamic aspect-oriented programming techniques. Non-deterministic choice facilitates local definitions of multiple executions...... without parameterization or generation of tests. It also eases modelling naturally non-deterministic program features like IO or multi-threading in integration tests. Dynamic AOP facilitates powerful design adaptations without exposing test features, keeping the scope of these adaptations local to each...... test. We also combine non-determinism and dynamic aspects in a new approach to testing multi-threaded programs using co-routines....
DEFF Research Database (Denmark)
Rong, Aiying; Hakonen, Henri; Lahdelma, Risto
2009-01-01
efficiency of the plants. We introduce in this paper the DRDP-RSC algorithm, which is a dynamic regrouping based dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units, sequential commitment of units in small groups. Relaxed states of the plants are used to reduce...... the dimension of the UC problem and dynamic regrouping is used to improve the solution quality. Numerical results based on real-life data sets show that this algorithm is efficient and optimal or near-optimal solutions with very small optimality gap are obtained....
Optimization of Algorithms Using Extensions of Dynamic Programming
AbouEisha, Hassan M.
2017-01-01
of the thesis presents a novel model of computation (element partition tree) that represents a class of algorithms for multi-frontal solvers along with cost functions reflecting various complexity measures such as: time and space. It then introduces dynamic
SPATIAL SEARCH IN COMMERCIAL FISHING: A DISCRETE CHOICE DYNAMIC PROGRAMMING APPROACH
Smith, Martin D.; Provencher, Bill
2003-01-01
We specify a discrete choice dynamic programming model of commercial fishing participation and location choices. This approach allows us to examine how fishermen collect information about resource abundance and whether their behavior is forward-looking.
Spin physics experiments at NICA-SPD with polarized proton and deuteron beams
Energy Technology Data Exchange (ETDEWEB)
Savin, I.; Efremov, A.; Pshekhonov, D.; Kovalenko, A.; Teryaev, O.; Shevchenko, O.; Nagajcev, A.; Guskov, A.; Kukhtin, V.; Toplilin, N. [JINR, Dubna (Russian Federation)
2016-08-15
This is a brief description of suggested measurements of asymmetries of the Drell-Yan (DY) pair production in collisions of non-polarized, longitudinally and transversally polarized protons and deuterons which provide an access to all leading-twist collinear and TMD PDFs of quarks and anti-quarks in nucleons. Other spin effects in hadronic and heavy-ion collisions may be also studied constituting the spin physics program at NICA. (orig.)
Program participation, labor force dynamics, and accepted wage rates
DEFF Research Database (Denmark)
Munch, Jakob Roland; Skipper, Lars
2008-01-01
We apply a recently suggested econometric approach to measure the effects of active labor market programs on employment, unemployment, and wage histories among participants. We find that participation in most of these training programs produces an initial locking-in effect and for some even a lower...
WHAMSE: a program for three-dimensional nonlinear structural dynamics
International Nuclear Information System (INIS)
Belytschko, T.; Tsay, C.S.
1982-02-01
WHAMSE is a computer program for the nonlinear, transient analysis of structures. The formulation includes both geometric and material nonlinearities, so problems with large displacements and elastic-plastic behavior can be treated. Explicit time integration is used, so the program is most suitable for implusive loads. Energy balance calculations are provided to check numerical stability. The mass matrix is lumped. A finite element format is used for the description of the problem geometry, so the program is quite versatile in treating complex engineering structures. The following elements are included: a triangular element for thin plates and shells, a beam element, a spring element and a rigid body. Mesh generation features are provided to simplify program input. Other features of the program are: (1) a restart capability; (2) a variety of output options, such as printer plots or CALCOMP plots of selected time histories, picture (snapshot) output, and CALCOMP plots of the undeformed and deformed structure
An optimal maintenance policy for machine replacement problem using dynamic programming
Mohsen Sadegh Amalnik; Morteza Pourgharibshahi
2017-01-01
In this article, we present an acceptance sampling plan for machine replacement problem based on the backward dynamic programming model. Discount dynamic programming is used to solve a two-state machine replacement problem. We plan to design a model for maintenance by consid-ering the quality of the item produced. The purpose of the proposed model is to determine the optimal threshold policy for maintenance in a finite time horizon. We create a decision tree based on a sequential sampling inc...
James Mabli; Thomas Godfrey; Nancy Wemmerus; Joshua Leftin; Stephen Tordella
2014-01-01
Mathematica nutrition experts recently conducted research on the dynamics and determinants of Supplemental Nutrition Assistance Program (SNAP) participation. A study examines SNAP participation dynamics between October 2008 and December 2012. In particular, it describes patterns of SNAP entry, length of time on the program, and re-entry for policy-relevant subgroups, and discusses how these patterns have changed over time. This work was conducted in conjunction with an analysis presented on t...
Discrete Globalised Dual Heuristic Dynamic Programming in Control of the Two-Wheeled Mobile Robot
Marcin Szuster; Zenon Hendzel
2014-01-01
Network-based control systems have been emerging technologies in the control of nonlinear systems over the past few years. This paper focuses on the implementation of the approximate dynamic programming algorithm in the network-based tracking control system of the two-wheeled mobile robot, Pioneer 2-DX. The proposed discrete tracking control system consists of the globalised dual heuristic dynamic programming algorithm, the PD controller, the supervisory term, and an additional control signal...
DEFF Research Database (Denmark)
Shuai, Hang; Ai, Xiaomeng; Wen, Jinyu
2017-01-01
This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future...
Strong sp-d exchange coupling in ZnMnTe/ZnMgTe core/shell nanowires
Energy Technology Data Exchange (ETDEWEB)
Wojnar, Piotr; Janik, Elzbieta; Szymura, Malgorzata; Zaleszczyk, Wojciech; Kret, Slawomir; Klopotowski, Lukasz; Wojciechowski, Tomasz; Baczewski, Lech T.; Wiater, Maciej; Karczewski, Grzegorz; Wojtowicz, Tomasz; Kossut, Jacek [Institute of Physics, Polish Academy of Sciences, Al. Lotnikow 32/46, 02-668 Warsaw (Poland); Suffczynski, Jan; Papierska, Joanna [Institute of Experimental Physics, Warsaw University, ul. Hoza 69, 00-681 Warsaw (Poland)
2014-07-15
In this work, our recent progress in the growth and optical studies of telluride nanowire heterostructures containing a small molar fraction of magnetic Mn-ions of only a few percent is overviewed. ZnMnTe/ZnMgTe core/shell nanowires (NWs) are grown by molecular beam epitaxy by employing the vapor-liquid-solid growth mechanism assisted with gold catalyst. The structures are studied by means of photoluminescence and microphotoluminescence in an external magnetic field. In the first step, however, an activation of the near band edge emission from ZnTe and ZnMnTe nanowires is described, which is achieved by coating the nanowires with shells made of ZnMgTe. The role of these shells is to passivate Zn(Mn)Te surface states. The incorporation of Mn ions into the crystalline lattice of ZnMnTe nanowires is manifested as a considerable blue shift of near band edge emission with increasing Mn concentration inside the nanowire cores, which reflects directly the increase of their energy gap. In an external magnetic field the near band edge emission exhibits a giant spectral redshift accompanied by an increase of the circular polarization of the emitted light. Both effect are fingerprints of giant Zeeman splitting of the band edges due to sp-d exchange interaction between the band carriers and magnetic Mn-ions. (copyright 2014 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)
Bellman’s GAP—a language and compiler for dynamic programming in sequence analysis
Sauthoff, Georg; Möhl, Mathias; Janssen, Stefan; Giegerich, Robert
2013-01-01
Motivation: Dynamic programming is ubiquitous in bioinformatics. Developing and implementing non-trivial dynamic programming algorithms is often error prone and tedious. Bellman’s GAP is a new programming system, designed to ease the development of bioinformatics tools based on the dynamic programming technique. Results: In Bellman’s GAP, dynamic programming algorithms are described in a declarative style by tree grammars, evaluation algebras and products formed thereof. This bypasses the design of explicit dynamic programming recurrences and yields programs that are free of subscript errors, modular and easy to modify. The declarative modules are compiled into C++ code that is competitive to carefully hand-crafted implementations. This article introduces the Bellman’s GAP system and its language, GAP-L. It then demonstrates the ease of development and the degree of re-use by creating variants of two common bioinformatics algorithms. Finally, it evaluates Bellman’s GAP as an implementation platform of ‘real-world’ bioinformatics tools. Availability: Bellman’s GAP is available under GPL license from http://bibiserv.cebitec.uni-bielefeld.de/bellmansgap. This Web site includes a repository of re-usable modules for RNA folding based on thermodynamics. Contact: robert@techfak.uni-bielefeld.de Supplementary information: Supplementary data are available at Bioinformatics online PMID:23355290
Bellman's GAP--a language and compiler for dynamic programming in sequence analysis.
Sauthoff, Georg; Möhl, Mathias; Janssen, Stefan; Giegerich, Robert
2013-03-01
Dynamic programming is ubiquitous in bioinformatics. Developing and implementing non-trivial dynamic programming algorithms is often error prone and tedious. Bellman's GAP is a new programming system, designed to ease the development of bioinformatics tools based on the dynamic programming technique. In Bellman's GAP, dynamic programming algorithms are described in a declarative style by tree grammars, evaluation algebras and products formed thereof. This bypasses the design of explicit dynamic programming recurrences and yields programs that are free of subscript errors, modular and easy to modify. The declarative modules are compiled into C++ code that is competitive to carefully hand-crafted implementations. This article introduces the Bellman's GAP system and its language, GAP-L. It then demonstrates the ease of development and the degree of re-use by creating variants of two common bioinformatics algorithms. Finally, it evaluates Bellman's GAP as an implementation platform of 'real-world' bioinformatics tools. Bellman's GAP is available under GPL license from http://bibiserv.cebitec.uni-bielefeld.de/bellmansgap. This Web site includes a repository of re-usable modules for RNA folding based on thermodynamics.
Optimal blood glucose level control using dynamic programming based on minimal Bergman model
Rettian Anggita Sari, Maria; Hartono
2018-03-01
The purpose of this article is to simulate the glucose dynamic and the insulin kinetic of diabetic patient. The model used in this research is a non-linear Minimal Bergman model. Optimal control theory is then applied to formulate the problem in order to determine the optimal dose of insulin in the treatment of diabetes mellitus such that the glucose level is in the normal range for some specific time range. The optimization problem is solved using dynamic programming. The result shows that dynamic programming is quite reliable to represent the interaction between glucose and insulin levels in diabetes mellitus patient.
Dynamics of WIC Program Participation by Infants and Children, 2001 to 2003. Final Report
Castner, Laura; Mabli, James; Sykes, Julie
2009-01-01
The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides nutritious foods that promote the health of low-income pregnant women, new mothers, infants, and preschool children. This study examines WIC participation dynamics of infants and children from 2001 to 2003 using the Survey of Income and Program Participation…
Drobnes, Emilie; Littleton, A.; Pesnell, William D.; Beck, K.; Buhr, S.; Durscher, R.; Hill, S.; McCaffrey, M.; McKenzie, D. E.; Myers, D.;
2013-01-01
We outline the context and overall philosophy for the combined Solar Dynamics Observatory (SDO) Education and Public Outreach (E/PO) program, present a brief overview of all SDO E/PO programs along with more detailed highlights of a few key programs, followed by a review of our results to date, conclude a summary of the successes, failures, and lessons learned, which future missions can use as a guide, while incorporating their own content to enhance the public's knowledge and appreciation of science and technology as well as its benefit to society.
Numerical simulation of particle dynamics in storage rings using BETACOOL program
International Nuclear Information System (INIS)
Meshkov, I.N.; Pivin, R.V.; Sidorin, A.O.; Smirnov, A.V.; Trubnikov, G.V.
2006-01-01
BETACOOL program developed by JINR electron cooling group is a kit of algorithms based on common format of input and output files. The program is oriented to simulation of the ion beam dynamics in a storage ring in the presence of cooling and heating effects. The version presented in this report includes three basic algorithms: simulation of rms parameters of the ion distribution function evolution in time, simulation of the distribution function evolution using Monte-Carlo method and tracking algorithm based on molecular dynamics technique. General processes to be investigated with the program are intrabeam scattering in the ion beam, electron cooling, interaction with residual gas and internal target
Directory of Open Access Journals (Sweden)
Wakui Reiko
2010-05-01
Full Text Available Abstract Purpose To determine the risk factors of severe radiation pneumonitis (RP after stereotactic body radiation therapy (SBRT for primary or secondary lung tumors. Materials and methods From January 2003 to March 2009, SBRT was performed on 117 patients (32 patients before 2005 and 85 patients after 2006 with lung tumors (primary = 74 patients and metastatic/recurrent = 43 patients in our institution. In the current study, the results on cases with severe RP (grades 4-5 were evaluated. Serum Krebs von den Lungen-6 (KL-6 and serum Surfactant protein-D (SP-D were used to predict the incidence of RP. A shadow of interstitial pneumonitis (IP on the CT image before performing SBRT was also used as an indicator for RP. Since 2006, patients have been prescreened for biological markers (KL-6 & SP-D as well as checking for an IP-shadow in CT. Results Grades 4-5 RP was observed in nine patients (7.7% after SBRT and seven of these cases (6.0% were grade 5 in our institution. A correlation was found between the incidence of RP and higher serum KL-6 & SP-D levels. IP-shadow in patient's CT was also found to correlate well with the severe RP. Severe RP was reduced from 18.8% before 2005 to 3.5% after 2006 (p = 0.042. There was no correlation between the dose volume histogram parameters and these severe RP patients. Conclusion Patients presenting with an IP shadow in the CT and a high value of the serum KL-6 & SP-D before SBRT treatment developed severe radiation pneumonitis at a high rate. The reduction of RP incidence in patients treated after 2006 may have been attributed to prescreening of the patients. Therefore, pre-screening before SBRT for an IP shadow in CT and serum KL-6 & SP-D is recommended in the management and treatment of patients with primary or secondary lung tumors.
Transient dynamic and inelastic analysis of shells of revolution - a survey of programs
International Nuclear Information System (INIS)
Svalbonas, V.
1976-01-01
Advances in the limits of structural use in the aerospace and nuclear power industries over the past years have increased the requirements upon the applicable analytical computer programs to include accurate capabilities for inelastic and transient dynamic analyses. In many minds, however, this advanced capability is unequivocally linked with the large scale, general purpose, finite element programs. This idea is also combined with the view that such analyses are therefore prohibitively expensive and should be relegated to the 'last resort' classification. While this, in the general sense, may indeed be the case, if the user needs only to analyze structures falling into limited categories, however, he may find that a variety of smaller special purpose programs are available which do not put an undue strain upon his resources. One such structural category is shells of revolution. This survey of programs concentrates upon the analytical tools which have been developed predominantly for shells of revolution. The survey is subdivided into three parts: (a) consideration of programs for transient dynamic analysis; (b) consideration of programs for inelastic analysis and finally; (c) consideration of programs capable of dynamic plasticity analysis. In each part, programs based upon finite difference, finite element, and numerical integration methods are considered. The programs are compared on the basis of analytical capabilities, and ease of idealization and use. In each part of the survey sample problems are utilized to exemplify the state-of-the-art. (Auth.)
A Case for Dynamic Reverse-code Generation to Debug Non-deterministic Programs
Directory of Open Access Journals (Sweden)
Jooyong Yi
2013-09-01
Full Text Available Backtracking (i.e., reverse execution helps the user of a debugger to naturally think backwards along the execution path of a program, and thinking backwards makes it easy to locate the origin of a bug. So far backtracking has been implemented mostly by state saving or by checkpointing. These implementations, however, inherently do not scale. Meanwhile, a more recent backtracking method based on reverse-code generation seems promising because executing reverse code can restore the previous states of a program without state saving. In the literature, there can be found two methods that generate reverse code: (a static reverse-code generation that pre-generates reverse code through static analysis before starting a debugging session, and (b dynamic reverse-code generation that generates reverse code by applying dynamic analysis on the fly during a debugging session. In particular, we espoused the latter one in our previous work to accommodate non-determinism of a program caused by e.g., multi-threading. To demonstrate the usefulness of our dynamic reverse-code generation, this article presents a case study of various backtracking methods including ours. We compare the memory usage of various backtracking methods in a simple but nontrivial example, a bounded-buffer program. In the case of non-deterministic programs such as this bounded-buffer program, our dynamic reverse-code generation outperforms the existing backtracking methods in terms of memory efficiency.
Zhao, Yongzhen; Jia, Yumei; Li, Chunsheng; Fang, Yingying; Shao, Rui
2018-01-01
To evaluate the efficacy of soluble programmed death-1 (sPD-1) for risk stratification and prediction of 28-day mortality in patients with sepsis, we compared serum sPD-1 with procalcitonin (PCT), C-reactive protein (CRP), and the Mortality in Emergency Department Sepsis (MEDS) score. A total of 60 healthy volunteers and 595 emergency department (ED) patients were recruited for this prospective cohort study. According to the severity of their condition on ED arrival, the patients were allocated to the systemic inflammatory response syndrome group (130 cases), sepsis group (276 cases), severe sepsis group (121 cases), and septic shock group (68 cases). In addition, all patients with sepsis were also divided into the survivor group (349 cases) and nonsurvivor group (116 cases) according to the 28-day outcomes. When the severity of sepsis increased, the levels of sPD-1 gradually increased. The levels of sPD-1, PCT, CRP and the MEDS score were also higher in the nonsurvivor group compared to the survivor group. Logistic regression suggested that sPD-1, PCT, and the MEDS score were independent risk factors for 28-day mortality of patients with sepsis. Area under the curve (AUC) of sPD-1, PCT and the MEDS score for 28-day mortality was 0.725, 0.693, and 0.767, respectively, and the AUC was improved when all 3 factors were combined (0.843). Serum sPD-1 is positively correlated with the severity of sepsis, and it is valuable for risk stratification of patients and prediction of 28-day mortality. Combining sPD-1 with PCT and the MEDS score improves the prognostic evaluation. Copyright © 2017 Elsevier Inc. All rights reserved.
BEAMPATH: a program library for beam dynamics simulation in linear accelerators
International Nuclear Information System (INIS)
Batygin, Y.K.
1992-01-01
A structured programming technique was used to develop software for space charge dominated beams investigation in linear accelerators. The method includes hierarchical program design using program independent modules and a flexible combination of modules to provide a most effective version of structure for every specific case of simulation. A modular program BEAMPATH was developed for 2D and 3D particle-in-cell simulation of beam dynamics in a structure containing RF gaps, radio-frequency quadrupoles (RFQ), multipole lenses, waveguides, bending magnets and solenoids. (author) 5 refs.; 2 figs
Endocardium and Epicardium Segmentation in MR Images Based on Developed Otsu and Dynamic Programming
Directory of Open Access Journals (Sweden)
Shengzhou XU
2014-03-01
Full Text Available In order to accurately extract the endocardium and epicardium of the left ventricle from cardiac magnetic resonance (MR images, a method based on developed Otsu and dynamic programming has been proposed. First, regions with high gray value are divided into several left ventricle candidate regions by the developed Otsu algorithm, which based on constraining the search range of the ideal segmentation threshold. Then, left ventricular blood pool is selected from the candidate regions and its convex hull is found out as the endocardium. The epicardium is derived by applying dynamic programming method to find a closed path with minimum local cost. The local cost function of the dynamic programming method consists of two factors: boundary gradient and shape features. In order to improve the accuracy of segmentation, a non-maxima gradient suppression technique is adopted to get the boundary gradient. The experimental result of 138 MR images show that the method proposed has high accuracy and robustness.
Repetitive elements dynamics in cell identity programming, maintenance and disease
Bodega, Beatrice
2014-12-01
The days of \\'junk DNA\\' seem to be over. The rapid progress of genomics technologies has been unveiling unexpected mechanisms by which repetitive DNA and in particular transposable elements (TEs) have evolved, becoming key issues in understanding genome structure and function. Indeed, rather than \\'parasites\\', recent findings strongly suggest that TEs may have a positive function by contributing to tissue specific transcriptional programs, in particular as enhancer-like elements and/or modules for regulation of higher order chromatin structure. Further, it appears that during development and aging genomes experience several waves of TEs activation, and this contributes to individual genome shaping during lifetime. Interestingly, TEs activity is major target of epigenomic regulation. These findings are shedding new light on the genome-phenotype relationship and set the premises to help to explain complex disease manifestation, as consequence of TEs activity deregulation.
Approximate Dynamic Programming: Combining Regional and Local State Following Approximations.
Deptula, Patryk; Rosenfeld, Joel A; Kamalapurkar, Rushikesh; Dixon, Warren E
2018-06-01
An infinite-horizon optimal regulation problem for a control-affine deterministic system is solved online using a local state following (StaF) kernel and a regional model-based reinforcement learning (R-MBRL) method to approximate the value function. Unlike traditional methods such as R-MBRL that aim to approximate the value function over a large compact set, the StaF kernel approach aims to approximate the value function in a local neighborhood of the state that travels within a compact set. In this paper, the value function is approximated using a state-dependent convex combination of the StaF-based and the R-MBRL-based approximations. As the state enters a neighborhood containing the origin, the value function transitions from being approximated by the StaF approach to the R-MBRL approach. Semiglobal uniformly ultimately bounded (SGUUB) convergence of the system states to the origin is established using a Lyapunov-based analysis. Simulation results are provided for two, three, six, and ten-state dynamical systems to demonstrate the scalability and performance of the developed method.
Optimal Risk Reduction in the Railway Industry by Using Dynamic Programming
Michael Todinov; Eberechi Weli
2013-01-01
The paper suggests for the first time the use of dynamic programming techniques for optimal risk reduction in the railway industry. It is shown that by using the concept ‘amount of removed risk by a risk reduction option’, the problem related to optimal allocation of a fixed budget to achieve a maximum risk reduction in the railway industry can be reduced to an optimisation problem from dynamic programming. For n risk reduction options and size of the available risk reduction budget B (expres...
DEFF Research Database (Denmark)
Davidsen, Claus; Liu, Suxia; Mo, Xinguo
2014-01-01
. A stochastic dynamic programming (SDP) approach is used to minimize the basin-wide total costs arising from water allocations and water curtailments. Dynamic allocation problems with inclusion of groundwater resources proved to be more complex to solve with SDP than pure surface water allocation problems due...... to head-dependent pumping costs. These dynamic pumping costs strongly affect the total costs and can lead to non-convexity of the future cost function. The water user groups (agriculture, industry, domestic) are characterized by inelastic demands and fixed water allocation and water supply curtailment...
A new shared-memory programming paradigm for molecular dynamics simulations on the Intel Paragon
International Nuclear Information System (INIS)
D'Azevedo, E.F.; Romine, C.H.
1994-12-01
This report describes the use of shared memory emulation with DOLIB (Distributed Object Library) to simplify parallel programming on the Intel Paragon. A molecular dynamics application is used as an example to illustrate the use of the DOLIB shared memory library. SOTON-PAR, a parallel molecular dynamics code with explicit message-passing using a Lennard-Jones 6-12 potential, is rewritten using DOLIB primitives. The resulting code has no explicit message primitives and resembles a serial code. The new code can perform dynamic load balancing and achieves better performance than the original parallel code with explicit message-passing
OpenDx programs for visualization of computational fluid dynamics (CFD) simulations
International Nuclear Information System (INIS)
Silva, Marcelo Mariano da
2008-01-01
The search for high performance and low cost hardware and software solutions always guides the developments performed at the IEN parallel computing laboratory. In this context, this dissertation about the building of programs for visualization of computational fluid dynamics (CFD) simulations using the open source software OpenDx was written. The programs developed are useful to produce videos and images in two or three dimensions. They are interactive, easily to use and were designed to serve fluid dynamics researchers. A detailed description about how this programs were developed and the complete instructions of how to use them was done. The use of OpenDx as development tool is also introduced. There are examples that help the reader to understand how programs can be useful for many applications. (author)
Software complex for developing dynamically packed program system for experiment automation
International Nuclear Information System (INIS)
Baluka, G.; Salamatin, I.M.
1985-01-01
Software complex for developing dynamically packed program system for experiment automation is considered. The complex includes general-purpose programming systems represented as the RT-11 standard operating system and specially developed problem-oriented moduli providing execution of certain jobs. The described complex is realized in the PASKAL' and MAKRO-2 languages and it is rather flexible to variations of the technique of the experiment
Effect of Various SPD Techniques on Structure and Superplastic Deformation of Two Phase MgLiAl Alloy
Dutkiewicz, Jan; Bobrowski, Piotr; Rusz, Stanislav; Hilser, Ondrej; Tański, Tomasz A.; Borek, Wojciech; Łagoda, Marek; Ostachowski, Paweł; Pałka, Paweł; Boczkal, Grzegorz; Kuc, Dariusz; Mikuszewski, Tomasz
2018-03-01
MgLiAl alloy containing 9 wt% Li and 1.5% Al composed of hexagonal α and bcc β phases was cast under protecting atmosphere and hot extruded. Various methods of severe plastic deformation were applied to study their effect on structure and grain refinement. Rods were subjected to 1-3 passes of Twist Channel Angular Pressing TCAP (with helical component), cyclic compression to total strain ɛ = 5 using MAXStrain Gleeble equipment, both performed at temperature interval 160-200 °C and, as third SPD method, KOBO type extrusion at RT. The TCAP pass resulted in grain refinement of α phase from 30 μm down to about 2 μm and that of β phase from 12 to 5 μm. Maxstrain cycling 10 × up to ɛ = 5 led to much finer grain size of 300 nm. KOBO method performed at RT caused average grain size refinement of α and β phases down to about 1 μm. Hardness of alloy decreased slightly with increasing number of TCAP passes due to increase of small void density. It was higher after MAXStrain cycling and after KOBO extrusion. TEM studies after TCAP passes showed higher dislocation density in the β region than in the α phase. Crystallographic relationship (001) α|| (110) β indicated parallel positioning of slip planes of both phases. Electron diffraction technique confirmed increase of grain misorientation with number of TCAP passes. Stress/strain curves recorded at temperature 200 °C showed superplastic forming after 1st and 3rd TCAP passes with better superplastic properties due to higher elongation with increasing number of passes. Values of strain rate sensitivity coefficient m were calculated at 0.29 after 3rd TCAP pass for strain rate range 10-5 to 5 × 10-3 s-1. Deformation by MAXStrain cycling caused much more effective grain refinement with fine microtwins in α phase. Superplastic deformation was also observed in alloy deformed by KOBO method, however the value of m = 0.21 was obtained at lower temperature of deformation equal to 160 °C and deformation rate in the
SP-D impedes transfer of HIV-1 from multi-layered vaginal epithelium with a distinct gene signature
Directory of Open Access Journals (Sweden)
Hrishikesh Pandit
2017-12-01
Full Text Available Surfactant Protein (SP D is a member of the collectin family of soluble pattern recognition receptors. We have previously shown that a recombinant fragment of SP-D (rhSP-D inhibits gp120-CD4 interaction and HIV-1 entry in target cells. To potentiate its prophylactic use as a vaginal microbicide, we determined ex vivo efficacy using organotypic human vaginal-ectocervical epithelia (VEC-100 that closely resemble the native tissues of origin. VEC-100, stratified human vaginal-ectocervical tissues grown on membrane inserts were treated with rhSP-D followed by a challenge with HIV-1 to assess the transfer of HIV-1 through the VEC-100 tissues to PBMCs in the basal submucosal compartment. Treated VEC tissues were subjected to mRNA Illumina microarray analysis. Levels of transcripts encoding for immune mediators, adhesion and tight junction proteins were also evaluated. Effect of rhSP-D on viability, NFκB activation, cytokine secretion and bacterial colonization of cervical vaginal epithelial cells was determined. rhSP-D significantly inhibited HIV-1 transfer from the multi-layered epithelial tissues to the basal PBMCs as compared to HIV-1 alone. Global gene expression profile of HIV-1 challenged VEC-100 tissues revealed differential regulation of genes and pathways majorly involved in inflammation, cell survival and transcription factors. Levels of Guanylate-binding proteins (GBPs and interferon-inducible proteins were significantly upregulated suggesting an interferon host defense response. rhSP-D showed an inhibition in the levels of GBPs and rescued the cell adhesion molecules such as Claudin 2, 3, 4, 5 and Occludin, known to be down regulated by HIV-1 in primary vaginal cells. Importantly, rhSP-D conditioned VEC tissue supernatants did not enhance susceptibility of target cells to HIV-1. rhSP-D treated vaginal epithelial cells did not show any significant alteration in viability, NFκB activation and levels of immune mediators like IL-1RA, Elafin
Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R
2013-01-01
This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.
Wang, Kai; Ju, Qing; Cao, Jing; Tang, Wenze; Zhang, Jian
2017-06-01
Idiopathic pulmonary fibrosis (IPF) has a poor prognosis in general; however, it is heterogeneous to detect relative biomarkers for predicting the disease progression. Serum biomarkers can be conveniently collected to detect and help to differentially diagnose IPF and predict IPF prognosis. This meta-analysis aimed to evaluate the use of serum surfactant proteins A and D (SP-A and SP-D) for differential diagnosis and prognosis of IPF. Relevant articles were searched in PubMed, Embase, and Chinese National Knowledge Infrastructure databases and reviewed by 2 independent readers. Standard mean difference (SMD) and 95% confidence interval (CI) were calculated to assess the difference in serum levels of SP-A/D among patients with IPF, when compared to patients with non-IPF interstitial lung disease (ILD), pulmonary infection, and healthy control. Hazard ratio (HR) and 95% CI were used to compare the relative risk of mortality. Twenty-one articles (totalling 1289 IPF patients) were included in final meta-analysis. Serum SP-A levels were significantly higher in patients with IPF than in patients with non-IPF ILD (SMD: 1.108 [0.584, 1.632], P infection (SMD: 1.320 [0.999, 1.640], P SMD: 2.802 [1.901, 3.702], P SMD: 0.459 [-0.000, 0.919], P = .050). Serum SP-D levels were significantly higher in patients with IPF than in patients with pulmonary infection (SMD: 1.308 [0.813, 1.803], P SMD: 2.235 [1.739, 2.731], P < .001). Risk of death in patients with IPF and elevated serum SP-A was increased 39% compared to patients with low SP-A groups. Elevated SP-D increased risk by 111% when compared to low SP-D. In acute exacerbation of IPF, serum SP-A/D were higher than those in stable stage. The comparisons and prognosis might be different in Asian and Caucasian patients. Serum SP-A/D detection might be useful for differential diagnosis and prediction of survival in patients with IPF.
Directory of Open Access Journals (Sweden)
Jingtao Shi
2013-01-01
Full Text Available This paper is concerned with the relationship between maximum principle and dynamic programming for stochastic recursive optimal control problems. Under certain differentiability conditions, relations among the adjoint processes, the generalized Hamiltonian function, and the value function are given. A linear quadratic recursive utility portfolio optimization problem in the financial engineering is discussed as an explicitly illustrated example of the main result.
Welte, R; Kretzschmar, M; Leidl, R; Van den Hoek, A; Jager, JC; Postma, MJ
2000-01-01
Background: Models commonly used for the economic assessment of chamydial screening programs do not consider population effects. Goal: To develop a novel dynamic approach for the economic evaluation of chlamydial prevention measures and to determine the cost-effectiveness of a general
DEFF Research Database (Denmark)
Davidsen, Claus; Cardenal, Silvio Javier Pereira; Liu, Suxia
2015-01-01
of stochastic dynamic programming, to optimize water resources management in the Ziya River basin. Natural runoff from the upper basin was estimated with a rainfall-runoff model autocalibrated using in situ measured discharge. The runoff serial correlation was described by a Markov chain and used as input...
Dynamic Programming for Re-Mapping Noisy Fixations in Translation Tasks
DEFF Research Database (Denmark)
Carl, Michael
2013-01-01
possible fixated symbols, including those on the line above and below the naïve fixation mapping. In a second step a dynamic programming algorithm applies a number of heuristics to find the best path through the lattice, based on the probable distance in characters, in words and in pixels between...
Dynamic Programming for Re-Mapping Noisy Fixations in Translation Tasks
DEFF Research Database (Denmark)
Carl, Michael
2013-01-01
this "naïve" gaze-to-word mapping by introducing background knowledge about the gazing task. In a first step, the sequence of "naïve" gaze-to-symbol mappings is projected into a lattice of several possible gaze locations above and below the current fixation on the text. In a second step a dynamic programming...
DEFF Research Database (Denmark)
Rong, Aiying; Hakonen, Henri; Lahdelma, Risto
2008-01-01
introduce in this paper the DP-RSC1 algorithm, which is a variant of the dynamic programming (DP) algorithm based on linear relaxation of the ON/OFF states of the units and sequential commitment of units one by one. The time complexity of DP-RSC1 is proportional to the number of generating units...
The Repeated School-to-Work Transition: Evidence from a Dynamic Programming Model
DEFF Research Database (Denmark)
Nielsen, Helena Skyt
by youths after high school graduation. It is assumed that the decision is taken year by year, and it is analyzed in a discrete choice dynamic programming model. In this forward-looking behavioral model, it is shown that a small bonus would remove interruptions of the educational careers just after high...
On the Dynamic Programming Approach for the 3D Navier-Stokes Equations
International Nuclear Information System (INIS)
Manca, Luigi
2008-01-01
The dynamic programming approach for the control of a 3D flow governed by the stochastic Navier-Stokes equations for incompressible fluid in a bounded domain is studied. By a compactness argument, existence of solutions for the associated Hamilton-Jacobi-Bellman equation is proved. Finally, existence of an optimal control through the feedback formula and of an optimal state is discussed
DEFF Research Database (Denmark)
Haahr, Jørgen Thorlund; Pisinger, David; Sabbaghian, Mohammad
2017-01-01
This paper considers a novel solution method for generating improved train speed profiles with reduced energy consumption. The solution method makes use of a time-space graph formulation which can be solved through Dynamic Programming. Instead of using uniform discretization of time and space...
International Nuclear Information System (INIS)
Sutrisno; Widowati; Solikhin
2016-01-01
In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well. (paper)
Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming.
Wang, Haizhou; Song, Mingzhou
2011-12-01
The heuristic k -means algorithm, widely used for cluster analysis, does not guarantee optimality. We developed a dynamic programming algorithm for optimal one-dimensional clustering. The algorithm is implemented as an R package called Ckmeans.1d.dp . We demonstrate its advantage in optimality and runtime over the standard iterative k -means algorithm.
Dynamic programming for optimization of timber production and grazing in ponderosa pine
Kurt H. Riitters; J. Douglas Brodie; David W. Hann
1982-01-01
Dynamic programming procedures are presented for optimizing thinning and rotation of even-aged ponderosa pine by using the four descriptors: age, basal area, number of trees, and time since thinning. Because both timber yield and grazing yield are functions of stand density, the two outputs-forage and timber-can both be optimized. The soil expectation values for single...
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
The design of measurement programs devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program...
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
The design of a measured program devoted to parameter identification of structural dynamic systems is considered, the design problem is formulated as an optimization problem due to minimize the total expected cost of the measurement program. All the calculations are based on a priori knowledge...... and engineering judgement. One of the contribution of the approach is that the optimal nmber of sensors can be estimated. This is sown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program for estimating the modal damping parameters...
Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo
2017-07-01
This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.
Upper atmosphere research satellite program. [to study the chemistry energetics, and dynamics
Huntress, W. T., Jr.
1978-01-01
A satellite program to conduct research on the chemistry, energetics, and dynamics of the upper atmosphere was developed. The scientific goals of the Upper Atmospheric Research Program, the program requirements, and the approach toward meeting those requirements are outlined. An initial series of two overlapping spacecraft missions is described. Both spacecraft are launched and recovered by the STS, one in the winter of 1983 at a 56 deg inclination, and the other a year later at a 70 deg inclination. The duration of each mission is 18 months, and each carries instruments to make global measurements of the temperature, winds, composition, irradation, and radiance in the stratosphere, mesosphere, and lower thermosphere between the tropopause and 120 km altitude. The program requires a dedicated ground-based data system and a science team organization that leads to a strong interaction between the experiments and theory. The program includes supportive observations from other platforms such as rockets, balloons, and the Spacelab.
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Christensen, Tue; Andersen, Kim Allan; Klose, Andreas
2013-01-01
This paper considers a minimum-cost network flow problem in a bipartite graph with a single sink. The transportation costs exhibit a staircase cost structure because such types of transportation cost functions are often found in practice. We present a dynamic programming algorithm for solving...... this so-called single-sink, fixed-charge, multiple-choice transportation problem exactly. The method exploits heuristics and lower bounds to peg binary variables, improve bounds on flow variables, and reduce the state-space variable. In this way, the dynamic programming method is able to solve large...... instances with up to 10,000 nodes and 10 different transportation modes in a few seconds, much less time than required by a widely used mixed-integer programming solver and other methods proposed in the literature for this problem....
A multithreaded parallel implementation of a dynamic programming algorithm for sequence comparison.
Martins, W S; Del Cuvillo, J B; Useche, F J; Theobald, K B; Gao, G R
2001-01-01
This paper discusses the issues involved in implementing a dynamic programming algorithm for biological sequence comparison on a general-purpose parallel computing platform based on a fine-grain event-driven multithreaded program execution model. Fine-grain multithreading permits efficient parallelism exploitation in this application both by taking advantage of asynchronous point-to-point synchronizations and communication with low overheads and by effectively tolerating latency through the overlapping of computation and communication. We have implemented our scheme on EARTH, a fine-grain event-driven multithreaded execution and architecture model which has been ported to a number of parallel machines with off-the-shelf processors. Our experimental results show that the dynamic programming algorithm can be efficiently implemented on EARTH systems with high performance (e.g., speedup of 90 on 120 nodes), good programmability and reasonable cost.
Lali, Mehdi
2009-03-01
A comprehensive computer program is designed in MATLAB to analyze, design and optimize the propulsion, dynamics, thermodynamics, and kinematics of any serial multi-staging rocket for a set of given data. The program is quite user-friendly. It comprises two main sections: "analysis and design" and "optimization." Each section has a GUI (Graphical User Interface) in which the rocket's data are entered by the user and by which the program is run. The first section analyzes the performance of the rocket that is previously devised by the user. Numerous plots and subplots are provided to display the performance of the rocket. The second section of the program finds the "optimum trajectory" via billions of iterations and computations which are done through sophisticated algorithms using numerical methods and incremental integrations. Innovative techniques are applied to calculate the optimal parameters for the engine and designing the "optimal pitch program." This computer program is stand-alone in such a way that it calculates almost every design parameter in regards to rocket propulsion and dynamics. It is meant to be used for actual launch operations as well as educational and research purposes.
Bellman, Richard
2003-01-01
An introduction to the mathematical theory of multistage decision processes, this text takes a ""functional equation"" approach to the discovery of optimum policies. Written by a leading developer of such policies, it presents a series of methods, uniqueness and existence theorems, and examples for solving the relevant equations. The text examines existence and uniqueness theorems, the optimal inventory equation, bottleneck problems in multistage production processes, a new formalism in the calculus of variation, strategies behind multistage games, and Markovian decision processes. Each chapte
International Nuclear Information System (INIS)
Surma, I.V.; Shvedunov, V.I.
1993-01-01
The paper presents modification results of the program for simulation of particle dynamics in cyclic accelerators with RTMTRACE linear gap. The program was modified with regard for the effect of space charge effect on particle dynamics. Calculation results of particle dynamics in 1 MeV energy continuous-duty accelerator with 10 kw beam were used to develop continuous powerful commercial accelerator. 3 refs., 2 figs
Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles
Morelli, Eugene A.; Klein, Vladislav
1990-01-01
A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.
Full-scale Mark II CRT program: dynamic response evaluation test of pressure transducers
International Nuclear Information System (INIS)
Kukita, Yutaka; Namatame, Ken; Takeshita, Isao; Shiba, Masayoshi
1982-12-01
A dynamic response evaluation test of pressure transducers was conducted in support of the JAERI Full-Scale Mark II CRT (Containment Response Test) Program. The test results indicated that certain of the cavity-type transducers used in the early blowdown test had undesirable response characteristics. The transducer mounting scheme was modified to avoid trapping of air bubbles in the pressure transmission tubing attached to the transducers. The dynamic response of the modified transducers was acceptable within the frequency range of 200 Hz. (author)
Merrill, J.
2017-12-01
Multidisciplinary undergraduate climate change education is critical for students entering any sector of the workforce. The University of Delaware has developed a new interdisciplinary affinity program—UD Climate Program for Undergraduates (CPUG)—open to undergraduate students of all majors to provide a comprehensive educational experience designed to educate skilled climate change problem-solvers for a wide range of professional careers. The program is designed to fulfill all General Education requirements, and includes a residential community commitment and experiential learning in community outreach and problem solving. Seminars will introduce current popular press and research materials and provide practice in confirming source credibility, communications training, and psychological support, as well as team building. As undergraduates, members of the UD CPUG team will define, describe, and develop a solution or solutions for a pressing local climate challenge that has the potential for global impact. The choice of a challenge and approach to addressing it will be guided by the student's advisor. Students are expected to develop a practical, multidisciplinary solution to address the challenge as defined, using their educational and experiential training. Solutions will be presented to the UD community during the spring semester of their senior year, as a collaborative team solution, with enhancement through individual portfolios from each team member. The logic model, structure, curricular and co-curricular supports for the CPUG will be provided. Mechanisms of support available through University administration will also be discussed.
Dynamic Positioning Capability Analysis for Marine Vessels Based on A DPCap Polar Plot Program
Wang, Lei; Yang, Jian-min; Xu, Sheng-wen
2018-03-01
Dynamic positioning capability (DPCap) analysis is essential in the selection of thrusters, in their configuration, and during preliminary investigation of the positioning ability of a newly designed vessel dynamic positioning system. DPCap analysis can help determine the maximum environmental forces, in which the DP system can counteract in given headings. The accuracy of the DPCap analysis is determined by the precise estimation of the environmental forces as well as the effectiveness of the thrust allocation logic. This paper is dedicated to developing an effective and efficient software program for the DPCap analysis for marine vessels. Estimation of the environmental forces can be obtained by model tests, hydrodynamic computation and empirical formulas. A quadratic programming method is adopted to allocate the total thrust on every thruster of the vessel. A detailed description of the thrust allocation logic of the software program is given. The effectiveness of the new program DPCap Polar Plot (DPCPP) was validated by a DPCap analysis for a supply vessel. The present study indicates that the developed program can be used in the DPCap analysis for marine vessels. Moreover, DPCap analysis considering the thruster failure mode might give guidance to the designers of vessels whose thrusters need to be safer.
A simple interface to computational fluid dynamics programs for building environment simulations
Energy Technology Data Exchange (ETDEWEB)
Broderick, III, C R; Chen, Q [Massachusetts Institute of Technology, Cambridge, MA (United States)
2000-07-01
It is becoming a popular practice for architects and HVAC engineers to simulate airflow in and around buildings by computational fluid dynamics (CFD) methods in order to predict indoor and outdoor environment. However, many CFD programs are crippled by a historically poor and inefficient user interface system, particularly for users with little training in numerical simulation. This investigation endeavors to create a simplified CFD interface (SCI) that allows architects and buildings engineers to use CFD without excessive training. The SCI can be easily integrated into new CFD programs. (author)
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
1993-01-01
The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensory can be estimated. This is shown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
1991-01-01
The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost, i.e. the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contributions of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...
An optimal maintenance policy for machine replacement problem using dynamic programming
Directory of Open Access Journals (Sweden)
Mohsen Sadegh Amalnik
2017-06-01
Full Text Available In this article, we present an acceptance sampling plan for machine replacement problem based on the backward dynamic programming model. Discount dynamic programming is used to solve a two-state machine replacement problem. We plan to design a model for maintenance by consid-ering the quality of the item produced. The purpose of the proposed model is to determine the optimal threshold policy for maintenance in a finite time horizon. We create a decision tree based on a sequential sampling including renew, repair and do nothing and wish to achieve an optimal threshold for making decisions including renew, repair and continue the production in order to minimize the expected cost. Results show that the optimal policy is sensitive to the data, for the probability of defective machines and parameters defined in the model. This can be clearly demonstrated by a sensitivity analysis technique.
A Case Study on Air Combat Decision Using Approximated Dynamic Programming
Directory of Open Access Journals (Sweden)
Yaofei Ma
2014-01-01
Full Text Available As a continuous state space problem, air combat is difficult to be resolved by traditional dynamic programming (DP with discretized state space. The approximated dynamic programming (ADP approach is studied in this paper to build a high performance decision model for air combat in 1 versus 1 scenario, in which the iterative process for policy improvement is replaced by mass sampling from history trajectories and utility function approximating, leading to high efficiency on policy improvement eventually. A continuous reward function is also constructed to better guide the plane to find its way to “winner” state from any initial situation. According to our experiments, the plane is more offensive when following policy derived from ADP approach other than the baseline Min-Max policy, in which the “time to win” is reduced greatly but the cumulated probability of being killed by enemy is higher. The reason is analyzed in this paper.
An intelligent environment for dynamic simulation program generation of nuclear reactor systems
International Nuclear Information System (INIS)
Ishizaka, Hiroaki; Gofuku, Akio; Yoshikawa, Hidekazu
2004-01-01
A graphical user interface system was developed for the two dynamic simulation systems based on modular programming methods: MSS and DSNP. The following works were made in conjunction with the system development: (1) conversion of the module libraries of both DSNP and MSS, (2) extension of DSNP- pre-compiler, (3) graphical interface for module integration, and (4) automatic converter of simple language descriptions for DSNP, where (1) and (2) were made on an engineering work station, while the rest (3) and (4), on Macintosh HyperCard. By using the graphical interface, a user can specify the structure of a simulation model, geometrical data, initial values of variables, etc. only by handling modules as icon on the pallet fields. The use of extended DSNP pre-compiler then generates the final product of dynamic simulation program automatically. The capability and effectiveness of the system was confirmed by a sample simulation of PWR SBLOCA transient in PORV stuck open event. (author)
Optimum Repartition of Transport Capacities in the Logistic System using Dynamic Programming
Directory of Open Access Journals (Sweden)
Gheorghe BĂŞANU
2011-08-01
Full Text Available Transportations take an essential role in logistics, interconnecting the majority of processes and operations within logistic system. The efficient use of transportation capacity is a priority whose achievement can diminish logistic costs. This objective is today difficult to achieve due to increasing complexity of transportation monitoring and coordination. This complexity is determined by transportation number and diversity, by the volume and diversity of orders, by increasing the targets to be supplied.Dynamic programming represents a highly useful tool for logistic managers, considering that its specific techniques and methods are oriented toward solving problems related to resource optimum allocation and utilization.The present paper presents briefly a series of theoretical elements of dynamic programming applied in logistics, based on which it is shown a mathematic model to determine the optimum policy for transport capacity repartition for the area attached to a logistic centre, through three distribution centres.
A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching.
Li, Ming; Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Wang, Lei; Pan, Yuanjin; Zhang, Peng
2017-09-08
Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images.
Nagy, Ivan
2017-01-01
This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.
Direct heuristic dynamic programming for damping oscillations in a large power system.
Lu, Chao; Si, Jennie; Xie, Xiaorong
2008-08-01
This paper applies a neural-network-based approximate dynamic programming method, namely, the direct heuristic dynamic programming (direct HDP), to a large power system stability control problem. The direct HDP is a learning- and approximation-based approach to addressing nonlinear coordinated control under uncertainty. One of the major design parameters, the controller learning objective function, is formulated to directly account for network-wide low-frequency oscillation with the presence of nonlinearity, uncertainty, and coupling effect among system components. Results include a novel learning control structure based on the direct HDP with applications to two power system problems. The first case involves static var compensator supplementary damping control, which is used to provide a comprehensive evaluation of the learning control performance. The second case aims at addressing a difficult complex system challenge by providing a new solution to a large interconnected power network oscillation damping control problem that frequently occurs in the China Southern Power Grid.
Gr-GDHP: A New Architecture for Globalized Dual Heuristic Dynamic Programming.
Zhong, Xiangnan; Ni, Zhen; He, Haibo
2017-10-01
Goal representation globalized dual heuristic dynamic programming (Gr-GDHP) method is proposed in this paper. A goal neural network is integrated into the traditional GDHP method providing an internal reinforcement signal and its derivatives to help the control and learning process. From the proposed architecture, it is shown that the obtained internal reinforcement signal and its derivatives can be able to adjust themselves online over time rather than a fixed or predefined function in literature. Furthermore, the obtained derivatives can directly contribute to the objective function of the critic network, whose learning process is thus simplified. Numerical simulation studies are applied to show the performance of the proposed Gr-GDHP method and compare the results with other existing adaptive dynamic programming designs. We also investigate this method on a ball-and-beam balancing system. The statistical simulation results are presented for both the Gr-GDHP and the GDHP methods to demonstrate the improved learning and controlling performance.
Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors.
Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin
2018-04-03
Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.
Optimization of fuel-cell tram operation based on two dimension dynamic programming
Zhang, Wenbin; Lu, Xuecheng; Zhao, Jingsong; Li, Jianqiu
2018-02-01
This paper proposes an optimal control strategy based on the two-dimension dynamic programming (2DDP) algorithm targeting at minimizing operation energy consumption for a fuel-cell tram. The energy consumption model with the tram dynamics is firstly deduced. Optimal control problem are analyzed and the 2DDP strategy is applied to solve the problem. The optimal tram speed profiles are obtained for each interstation which consist of three stages: accelerate to the set speed with the maximum traction power, dynamically adjust to maintain a uniform speed and decelerate to zero speed with the maximum braking power at a suitable timing. The optimal control curves of all the interstations are connected with the parking time to form the optimal control method of the whole line. The optimized speed profiles are also simplified for drivers to follow.
Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach
Energy Technology Data Exchange (ETDEWEB)
Pham, Huyên, E-mail: pham@math.univ-paris-diderot.fr; Wei, Xiaoli, E-mail: tyswxl@gmail.com [Laboratoire de Probabilités et Modèles Aléatoires, CNRS, UMR 7599, Université Paris Diderot (France)
2016-12-15
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.
The Effect of Water Exercise Program on Static and Dynamic Balance in Elderly Women
Directory of Open Access Journals (Sweden)
Heydar Sadeghi
2008-01-01
Full Text Available Objectives: Poor balance is one of risk factors of falling, a cause of injury and even death in elderly. The aim of this study was to evaluate the effect of a water exercise program on static and dynamic balance in elder women. Methods & Materials: Thirty participants aged 55-70 years completed an exercise program (60 min, 3 days and 6 weeks, in 2 groups, exercise and control, voluntarily. Static and dynamic balances were measured before and after exercise program in both groups. Postural sway parameters, including mean displacement of center of pressure and velocity of center of pressure in Medio-Lateral (ML and Anterio-Posterior (AP directions, in single stance position, as a measure of static balance and functional reach test, functional reach right test and functional reach left test, as dynamic measure of balance was considered. T test for deepened groups was used for evaluation of changes within groups, and T test for independent groups was used for between groups' changes at threshold of 0.05 After 6 weeks. Results: Significant changes were observed in results of Functional Reach Test (FRT, Functional Reach Left Test (FRLT after exercise program, also in average displacement of cop and velocity of cop in ML direction. Between groups significant differences were observed in results of average cop displacement and velocity of displacement, FRT and FRLT. Conclusion: These results suggest that challenging the physiological systems involved in balance control, in water, while on the non stable support surface, improved both static and dynamic balance and probably might decrease the risk of falling.
Raso , L.; Malaterre , P.O.; Bader , J.C.
2017-01-01
International audience; This article presents an innovative streamflow process model for use in reservoir operational rule design in stochastic dual dynamic programming (SDDP). Model features, which can be applied independently, are (1) a multiplicative process model for the forward phase and its linearized version for the backward phase; and (2) a nonuniform time-step length that is inversely proportional to seasonal variability. The advantages are (1) guaranteeing positive streamflow values...
Directory of Open Access Journals (Sweden)
Stanimirović Ivan
2009-01-01
Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.
Discrete Time McKean–Vlasov Control Problem: A Dynamic Programming Approach
International Nuclear Information System (INIS)
Pham, Huyên; Wei, Xiaoli
2016-01-01
We consider the stochastic optimal control problem of nonlinear mean-field systems in discrete time. We reformulate the problem into a deterministic control problem with marginal distribution as controlled state variable, and prove that dynamic programming principle holds in its general form. We apply our method for solving explicitly the mean-variance portfolio selection and the multivariate linear-quadratic McKean–Vlasov control problem.
Automatic programming via iterated local search for dynamic job shop scheduling.
Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen
2015-01-01
Dispatching rules have been commonly used in practice for making sequencing and scheduling decisions. Due to specific characteristics of each manufacturing system, there is no universal dispatching rule that can dominate in all situations. Therefore, it is important to design specialized dispatching rules to enhance the scheduling performance for each manufacturing environment. Evolutionary computation approaches such as tree-based genetic programming (TGP) and gene expression programming (GEP) have been proposed to facilitate the design task through automatic design of dispatching rules. However, these methods are still limited by their high computational cost and low exploitation ability. To overcome this problem, we develop a new approach to automatic programming via iterated local search (APRILS) for dynamic job shop scheduling. The key idea of APRILS is to perform multiple local searches started with programs modified from the best obtained programs so far. The experiments show that APRILS outperforms TGP and GEP in most simulation scenarios in terms of effectiveness and efficiency. The analysis also shows that programs generated by APRILS are more compact than those obtained by genetic programming. An investigation of the behavior of APRILS suggests that the good performance of APRILS comes from the balance between exploration and exploitation in its search mechanism.
Dynamic trunk stabilization: a conceptual back injury prevention program for volleyball athletes.
Smith, Chad E; Nyland, John; Caudill, Paul; Brosky, Joseph; Caborn, David N M
2008-11-01
The sport of volleyball creates considerable dynamic trunk stability demands. Back injury occurs all too frequently in volleyball, particularly among female athletes. The purpose of this clinical commentary is to review functional anatomy, muscle coactivation strategies, assessment of trunk muscle performance, and the characteristics of effective exercises for the trunk or core. From this information, a conceptual progressive 3-phase volleyball-specific training program is presented to improve dynamic trunk stability and to potentially reduce the incidence of back injury among volleyball athletes. Phase 1 addresses low-velocity motor control, kinesthetic awareness, and endurance, with the clinician providing cues to teach achievement of biomechanically neutral spine alignment. Phase 2 focuses on progressively higher velocity dynamic multiplanar endurance, coordination, and strength-power challenges integrating upper and lower extremity movements, while maintaining neutral spine alignment. Phase 3 integrates volleyball-specific skill simulations by breaking down composite movement patterns into their component parts, with differing dynamic trunk stability requirements, while maintaining neutral spine alignment. Prospective research is needed to validate the efficacy of this program.
Extraction of Static and Dynamic Reservoir Operation Rules by Genetic Programming
Directory of Open Access Journals (Sweden)
Habib Akbari Alashti
2014-11-01
Full Text Available Considering the necessity of desirable operation of limited water resources and assuming the significant role of dams in controlling and consuming the surface waters, highlights the advantageous of suitable operation rules for optimal and sustainable operation of dams. This study investigates the hydroelectric supply of a one-reservoir system of Karoon3 using nonlinear programming (NLP, genetic algorithm (GA, genetic programming (GP and fixed length gen GP (FLGGP in real-time operation of dam considering two approaches of static and dynamic operation rules. In static operation rule, only one rule curve is extracted for all months in a year whereas in dynamic operation rule, monthly rule curves (12 rules are extracted for each month of a year. In addition, nonlinear decision rule (NLDR curves are considered, and the total deficiency function as the target (objective function have been used for evaluating the performance of each method and approach. Results show appropriate efficiency of GP and FLGGP methods in extracting operation rules in both approaches. Superiority of these methods to operation methods yielded by GA and NLP is 5%. Moreover, according to the results, it can be remarked that, FLGGP method is an alternative for GP method, whereas the GP method cannot be used due to its limitations. Comparison of two approaches of static and dynamic operation rules demonstrated the superiority of dynamic operation rule to static operation rule (about 10% and therefore this method has more capabilities in real-time operation of the reservoirs systems.
Zhou, Yuan; Cheng, Xinyao; Xu, Xiangyang; Song, Enmin
2013-12-01
Segmentation of carotid artery intima-media in longitudinal ultrasound images for measuring its thickness to predict cardiovascular diseases can be simplified as detecting two nearly parallel boundaries within a certain distance range, when plaque with irregular shapes is not considered. In this paper, we improve the implementation of two dynamic programming (DP) based approaches to parallel boundary detection, dual dynamic programming (DDP) and piecewise linear dual dynamic programming (PL-DDP). Then, a novel DP based approach, dual line detection (DLD), which translates the original 2-D curve position to a 4-D parameter space representing two line segments in a local image segment, is proposed to solve the problem while maintaining efficiency and rotation invariance. To apply the DLD to ultrasound intima-media segmentation, it is imbedded in a framework that employs an edge map obtained from multiplication of the responses of two edge detectors with different scales and a coupled snake model that simultaneously deforms the two contours for maintaining parallelism. The experimental results on synthetic images and carotid arteries of clinical ultrasound images indicate improved performance of the proposed DLD compared to DDP and PL-DDP, with respect to accuracy and efficiency. Copyright © 2013 Elsevier B.V. All rights reserved.
Discrete Globalised Dual Heuristic Dynamic Programming in Control of the Two-Wheeled Mobile Robot
Directory of Open Access Journals (Sweden)
Marcin Szuster
2014-01-01
Full Text Available Network-based control systems have been emerging technologies in the control of nonlinear systems over the past few years. This paper focuses on the implementation of the approximate dynamic programming algorithm in the network-based tracking control system of the two-wheeled mobile robot, Pioneer 2-DX. The proposed discrete tracking control system consists of the globalised dual heuristic dynamic programming algorithm, the PD controller, the supervisory term, and an additional control signal. The structure of the supervisory term derives from the stability analysis realised using the Lyapunov stability theorem. The globalised dual heuristic dynamic programming algorithm consists of two structures: the actor and the critic, realised in a form of neural networks. The actor generates the suboptimal control law, while the critic evaluates the realised control strategy by approximation of value function from the Bellman’s equation. The presented discrete tracking control system works online, the neural networks’ weights adaptation process is realised in every iteration step, and the neural networks preliminary learning procedure is not required. The performance of the proposed control system was verified by a series of computer simulations and experiments realised using the wheeled mobile robot Pioneer 2-DX.
International Nuclear Information System (INIS)
Steele, R. Jr.; Bramwell, D.L.; Watkins, J.C.; DeWall, K.G.
1994-02-01
This report documents the results of the main projects undertaken under the Environmental and Dynamic Equipment Qualification Research Program (EDQP) sponsored by the U.S. Nuclear Regulatory Commission (NRC) under FIN A6322. Lasting from fiscal year 1983 to 1987, the program dealt with environmental and dynamic (including seismic) equipment qualification issues for mechanical and electromechanical components and systems used in nuclear power plants. The research results have since been used by both the NRC and industry. The program included seven major research projects that addressed the following issues: (a) containment purge and vent valves performing under design basis loss of coolant accident loads, (b) containment piping penetrations and isolation valves performing under seismic loadings and design basis and severe accident containment wall displacements, (c) shaft seals for primary coolant pumps performing under station blackout conditions, (d) electrical cabinet internals responding to in-structure generated motion (rattling), and (e) in situ piping and valves responding to seismic loadings. Another project investigating whether certain containment isolation valves will close under design basis conditions was also started under this program. This report includes eight main section, each of which provides a brief description of one of the projects, a summary of the findings, and an overview of the application of the results. A bibliography lists the journal articles, papers, and reports that document the research
Dynamic Impact Testing and Model Development in Support of NASA's Advanced Composites Program
Melis, Matthew E.; Pereira, J. Michael; Goldberg, Robert; Rassaian, Mostafa
2018-01-01
The purpose of this paper is to provide an executive overview of the HEDI effort for NASA's Advanced Composites Program and establish the foundation for the remaining papers to follow in the 2018 SciTech special session NASA ACC High Energy Dynamic Impact. The paper summarizes the work done for the Advanced Composites Program to advance our understanding of the behavior of composite materials during high energy impact events and to advance the ability of analytical tools to provide predictive simulations. The experimental program carried out at GRC is summarized and a status on the current development state for MAT213 will be provided. Future work will be discussed as the HEDI effort transitions from fundamental analysis and testing to investigating sub-component structural concept response to impact events.
International Nuclear Information System (INIS)
Gofuku, Akio
1993-01-01
In this study, two support tools are developed for construction of a dynamic simulation program for engineering systems (especially nuclear systems) by combining software modules. These are (1) a sub-system to support the module selection suitable for dynamic simulation and (2) a graphical user interface to support visual construction of simulation programs. The support tools are designed to be independent on the conception of software modules (data communication methods between modules). In the module selection sub-system of item 1, a module is characterized beforehand by keywords for several criteria. The similarity between the characteristic of requested module by users and that of registered modules in the module library is estimated by a weighted average of similarity indexes for criteria. In the module selection sub-system, the weights are flexibly extracted from users by applying the analytic hierarchy process. The graphical user interface helps users to specify both calling order of modules and data transfer between two modules. The availability of the support tools is evaluated by several sample problems of module selection and dynamic simulation model construction. The support tools will be a strong tool for the efficient usage of software modules. (author)
Li, Rui; Cauchy, Pierre; Ramamoorthy, Senthilkumar; Boller, Sören; Chavez, Lukas; Grosschedl, Rudolf
2018-01-15
B-cell fate determination requires the action of transcription factors that operate in a regulatory network to activate B-lineage genes and repress lineage-inappropriate genes. However, the dynamics and hierarchy of events in B-cell programming remain obscure. To uncouple the dynamics of transcription factor expression from functional consequences, we generated induction systems in developmentally arrested Ebf1 -/- pre-pro-B cells to allow precise experimental control of EBF1 expression in the genomic context of progenitor cells. Consistent with the described role of EBF1 as a pioneer transcription factor, we show in a time-resolved analysis that EBF1 occupancy coincides with EBF1 expression and precedes the formation of chromatin accessibility. We observed dynamic patterns of EBF1 target gene expression and sequential up-regulation of transcription factors that expand the regulatory network at the pro-B-cell stage. A continuous EBF1 function was found to be required for Cd79a promoter activity and for the maintenance of an accessible chromatin domain that is permissive for binding of other transcription factors. Notably, transient EBF1 occupancy was detected at lineage-inappropriate genes prior to their silencing in pro-B cells. Thus, persistent and transient functions of EBF1 allow for an ordered sequence of epigenetic and transcriptional events in B-cell programming. © 2018 Li et al.; Published by Cold Spring Harbor Laboratory Press.
Yang, Ruiduo; Sarkar, Sudeep; Loeding, Barbara
2010-03-01
We consider two crucial problems in continuous sign language recognition from unaided video sequences. At the sentence level, we consider the movement epenthesis (me) problem and at the feature level, we consider the problem of hand segmentation and grouping. We construct a framework that can handle both of these problems based on an enhanced, nested version of the dynamic programming approach. To address movement epenthesis, a dynamic programming (DP) process employs a virtual me option that does not need explicit models. We call this the enhanced level building (eLB) algorithm. This formulation also allows the incorporation of grammar models. Nested within this eLB is another DP that handles the problem of selecting among multiple hand candidates. We demonstrate our ideas on four American Sign Language data sets with simple background, with the signer wearing short sleeves, with complex background, and across signers. We compared the performance with Conditional Random Fields (CRF) and Latent Dynamic-CRF-based approaches. The experiments show more than 40 percent improvement over CRF or LDCRF approaches in terms of the frame labeling rate. We show the flexibility of our approach when handling a changing context. We also find a 70 percent improvement in sign recognition rate over the unenhanced DP matching algorithm that does not accommodate the me effect.
Programming Cells for Dynamic Assembly of Inorganic Nano-Objects with Spatiotemporal Control.
Wang, Xinyu; Pu, Jiahua; An, Bolin; Li, Yingfeng; Shang, Yuequn; Ning, Zhijun; Liu, Yi; Ba, Fang; Zhang, Jiaming; Zhong, Chao
2018-04-01
Programming living cells to organize inorganic nano-objects (NOs) in a spatiotemporally precise fashion would advance new techniques for creating ordered ensembles of NOs and new bio-abiotic hybrid materials with emerging functionalities. Bacterial cells often grow in cellular communities called biofilms. Here, a strategy is reported for programming dynamic biofilm formation for the synchronized assembly of discrete NOs or hetero-nanostructures on diverse interfaces in a dynamic, scalable, and hierarchical fashion. By engineering Escherichia coli to sense blue light and respond by producing biofilm curli fibers, biofilm formation is spatially controlled and the patterned NOs' assembly is simultaneously achieved. Diverse and complex fluorescent quantum dot patterns with a minimum patterning resolution of 100 µm are demonstrated. By temporally controlling the sequential addition of NOs into the culture, multilayered heterostructured thin films are fabricated through autonomous layer-by-layer assembly. It is demonstrated that biologically dynamic self-assembly can be used to advance a new repertoire of nanotechnologies and materials with increasing complexity that would be otherwise challenging to produce. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
MyDTW - Dynamic Time Warping program for stratigraphical time series
Kotov, Sergey; Paelike, Heiko
2017-04-01
One of the general tasks in many geological disciplines is matching of one time or space signal to another. It can be classical correlation between two cores or cross-sections in sedimentology or marine geology. For example, tuning a paleoclimatic signal to a target curve, driven by variations in the astronomical parameters, is a powerful technique to construct accurate time scales. However, these methods can be rather time-consuming and can take ours of routine work even with the help of special semi-automatic software. Therefore, different approaches to automate the processes have been developed during last decades. Some of them are based on classical statistical cross-correlations such as the 'Correlator' after Olea [1]. Another ones use modern ideas of dynamic programming. A good example is as an algorithm developed by Lisiecki and Lisiecki [2] or dynamic time warping based algorithm after Pälike [3]. We introduce here an algorithm and computer program, which are also stemmed from the Dynamic Time Warping algorithm class. Unlike the algorithm of Lisiecki and Lisiecki, MyDTW does not lean on a set of penalties to follow geological logics, but on a special internal structure and specific constrains. It differs also from [3] in basic ideas of implementation and constrains design. The algorithm is implemented as a computer program with a graphical user interface using Free Pascal and Lazarus IDE and available for Windows, Mac OS, and Linux. Examples with synthetic and real data are demonstrated. Program is available for free download at http://www.marum.de/Sergey_Kotov.html . References: 1. Olea, R.A. Expert systems for automated correlation and interpretation of wireline logs // Math Geol (1994) 26: 879. doi:10.1007/BF02083420 2. Lisiecki L. and Lisiecki P. Application of dynamic programming to the correlation of paleoclimate records // Paleoceanography (2002), Volume 17, Issue 4, pp. 1-1, CiteID 1049, doi: 10.1029/2001PA000733 3. Pälike, H. Extending the
Park, Sang Cheol; Leader, Joseph Ken; Tan, Jun; Lee, Guee Sang; Kim, Soo Hyung; Na, In Seop; Zheng, Bin
2011-01-01
Objective this article presents a new computerized scheme that aims to accurately and robustly separate left and right lungs on CT examinations. Methods we developed and tested a method to separate the left and right lungs using sequential CT information and a guided dynamic programming algorithm using adaptively and automatically selected start point and end point with especially severe and multiple connections. Results the scheme successfully identified and separated all 827 connections on the total 4034 CT images in an independent testing dataset of CT examinations. The proposed scheme separated multiple connections regardless of their locations, and the guided dynamic programming algorithm reduced the computation time to approximately 4.6% in comparison with the traditional dynamic programming and avoided the permeation of the separation boundary into normal lung tissue. Conclusions The proposed method is able to robustly and accurately disconnect all connections between left and right lungs and the guided dynamic programming algorithm is able to remove redundant processing. PMID:21412104
AbouEisha, Hassan M.; Moshkov, Mikhail; Calo, Victor M.; Paszynski, Maciej; Goik, Damian; Jopek, Konrad
2014-01-01
In this paper we present a dynamic programming algorithm for finding optimal elimination trees for computational grids refined towards point or edge singularities. The elimination tree is utilized to guide the multi-frontal direct solver algorithm
Directory of Open Access Journals (Sweden)
Amal F Soliman
2016-01-01
Conclusion Twelve weeks of intensive dynamic exercise program should be recommended to patients with FM as it was effective in decreasing the oxidative stress parameters, increasing the antioxidant parameters, and improving the clinical outcome of this disease.
Energy Technology Data Exchange (ETDEWEB)
Zhang, Xiaodong, E-mail: xiaodong.zhang@beg.utexas.edu [Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX 78713 (United States); Huang, Gordon [Institute of Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada)
2013-02-15
Highlights: ► A dynamic stochastic possibilistic multiobjective programming model is developed. ► Greenhouse gas emission control is considered. ► Three planning scenarios are analyzed and compared. ► Optimal decision schemes under three scenarios and different p{sub i} levels are obtained. ► Tradeoffs between economics and environment are reflected. -- Abstract: Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjective programming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different p{sub i} levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help
A Hybrid Dynamic Programming for Solving Fixed Cost Transportation with Discounted Mechanism
Directory of Open Access Journals (Sweden)
Farhad Ghassemi Tari
2016-01-01
Full Text Available The problem of allocating different types of vehicles for transporting a set of products from a manufacturer to its depots/cross docks, in an existing transportation network, to minimize the total transportation costs, is considered. The distribution network involves a heterogeneous fleet of vehicles, with a variable transportation cost and a fixed cost in which a discount mechanism is applied on the fixed part of the transportation costs. It is assumed that the number of available vehicles is limited for some types. A mathematical programming model in the form of the discrete nonlinear optimization model is proposed. A hybrid dynamic programming algorithm is developed for finding the optimal solution. To increase the computational efficiency of the solution algorithm, several concepts and routines, such as the imbedded state routine, surrogate constraint concept, and bounding schemes, are incorporated in the dynamic programming algorithm. A real world case problem is selected and solved by the proposed solution algorithm, and the optimal solution is obtained.
A Dynamic Programming Approach for Pricing Weather Derivatives under Issuer Default Risk
Directory of Open Access Journals (Sweden)
Wolfgang Karl Härdle
2017-10-01
Full Text Available Weather derivatives are contingent claims with payoff based on a pre-specified weather index. Firms exposed to weather risk can transfer it to financial markets via weather derivatives. We develop a utility-based model for pricing baskets of weather derivatives under default risk on the issuer side in over-the-counter markets. In our model, agents maximise the expected utility of their terminal wealth, while they dynamically rebalance their weather portfolios over a finite investment horizon. Using dynamic programming approach, we obtain semi-closed forms for the equilibrium prices of weather derivatives and for the optimal strategies of the agents. We give an example on how to price rainfall derivatives on selected stations in China in the universe of a financial investor and a weather exposed crop insurer.
Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai
2013-09-01
In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.
Improved dynamic-programming-based algorithms for segmentation of masses in mammograms
International Nuclear Information System (INIS)
Dominguez, Alfonso Rojas; Nandi, Asoke K.
2007-01-01
In this paper, two new boundary tracing algorithms for segmentation of breast masses are presented. These new algorithms are based on the dynamic programming-based boundary tracing (DPBT) algorithm proposed in Timp and Karssemeijer, [S. Timp and N. Karssemeijer, Med. Phys. 31, 958-971 (2004)] The DPBT algorithm contains two main steps: (1) construction of a local cost function, and (2) application of dynamic programming to the selection of the optimal boundary based on the local cost function. The validity of some assumptions used in the design of the DPBT algorithm is tested in this paper using a set of 349 mammographic images. Based on the results of the tests, modifications to the computation of the local cost function have been designed and have resulted in the Improved-DPBT (IDPBT) algorithm. A procedure for the dynamic selection of the strength of the components of the local cost function is presented that makes these parameters independent of the image dataset. Incorporation of this dynamic selection procedure has produced another new algorithm which we have called ID 2 PBT. Methods for the determination of some other parameters of the DPBT algorithm that were not covered in the original paper are presented as well. The merits of the new IDPBT and ID 2 PBT algorithms are demonstrated experimentally by comparison against the DPBT algorithm. The segmentation results are evaluated with base on the area overlap measure and other segmentation metrics. Both of the new algorithms outperform the original DPBT; the improvements in the algorithms performance are more noticeable around the values of the segmentation metrics corresponding to the highest segmentation accuracy, i.e., the new algorithms produce more optimally segmented regions, rather than a pronounced increase in the average quality of all the segmented regions
A model to simulate the dynamic of a PWR pressurizer using the CSMP program
International Nuclear Information System (INIS)
Woiski, E.R.
1981-01-01
A mathematical model has been developed to simulate the dynamic behavior of a PWR pressurizer using the CSMP program. A two-control-volume formulation non-equilibrium model has been used for this purpose. Thermodynamic states are obtained after each integration cycle. The code was tested against experimental results of Shippingport and NPD (Nuclear Power Demonstration Plant) pressurizers. It was also tested against available data from Angra I and Angra II/III safety analysis report. Despite the model simplicity, the lack of important data and the low reliability or the experimental curves, the calculated and experimental results compared well. (Author) [pt
International Nuclear Information System (INIS)
Porteus, E.
1982-01-01
The study of infinite-horizon nonstationary dynamic programs using the operator approach is continued. The point of view here differs slightly from that taken by others, in that Denardo's local income function is not used as a starting point. Infinite-horizon values are defined as limits of finite-horizon values, as the horizons get long. Two important conditions of an earlier paper are weakened, yet the optimality equations, the optimality criterion, and the existence of optimal ''structured'' strategies are still obtained
Dynamic Programming Used to Align Protein Structures with a Spectrum Is Robust
Directory of Open Access Journals (Sweden)
Allen Holder
2013-11-01
Full Text Available Several efficient algorithms to conduct pairwise comparisons among large databases of protein structures have emerged in the recent literature. The central theme is the design of a measure between the Cα atoms of two protein chains, from which dynamic programming is used to compute an alignment. The efficiency and efficacy of these algorithms allows large-scale computational studies that would have been previously impractical. The computational study herein shows that the structural alignment algorithm eigen-decomposition alignment with the spectrum (EIGAs is robust against both parametric and structural variation.
STYCA, a computer program in the dynamic structural analysis of a PWR core
International Nuclear Information System (INIS)
Silva Macedo, L.V. da; Breyne Salvagni, R. de
1992-01-01
A procedure for the dynamic structural analysis of a PWR core is presented, impacts between fuel assemblies may occur because of the existence of gaps between them. Thus, the problem is non-linear and an spectral analysis is avoided. A time-history response analysis is necessary. The Modal Superposition Method with the Duhamel integral was used in order to solve the problem. An algorithm of solution and also results obtained with the STYCA computer program, developed on the basis of what was proposed here, are presented. (author)
Optimization and analysis of decision trees and rules: Dynamic programming approach
Alkhalid, Abdulaziz
2013-08-01
This paper is devoted to the consideration of software system Dagger created in KAUST. This system is based on extensions of dynamic programming. It allows sequential optimization of decision trees and rules relative to different cost functions, derivation of relationships between two cost functions (in particular, between number of misclassifications and depth of decision trees), and between cost and uncertainty of decision trees. We describe features of Dagger and consider examples of this systems work on decision tables from UCI Machine Learning Repository. We also use Dagger to compare 16 different greedy algorithms for decision tree construction. © 2013 Taylor and Francis Group, LLC.
Real-Time Reactive Power Distribution in Microgrids by Dynamic Programing
DEFF Research Database (Denmark)
Levron, Yoash; Beck, Yuval; Katzir, Liran
2017-01-01
In this paper a new real-time optimization method for reactive power distribution in microgrids is proposed. The method enables location of a globally optimal distribution of reactive power under normal operating conditions. The method exploits the typical compact structure of microgrids to obtain...... combination of reactive powers, by means of dynamic programming. Since every single step involves a one-dimensional problem, the complexity of the solution is only linear with the number of clusters, and as a result, a globally optimal solution may be obtained in real time. The paper includes the results...
Optimization and analysis of decision trees and rules: Dynamic programming approach
Alkhalid, Abdulaziz; Amin, Talha M.; Chikalov, Igor; Hussain, Shahid; Moshkov, Mikhail; Zielosko, Beata
2013-01-01
This paper is devoted to the consideration of software system Dagger created in KAUST. This system is based on extensions of dynamic programming. It allows sequential optimization of decision trees and rules relative to different cost functions, derivation of relationships between two cost functions (in particular, between number of misclassifications and depth of decision trees), and between cost and uncertainty of decision trees. We describe features of Dagger and consider examples of this systems work on decision tables from UCI Machine Learning Repository. We also use Dagger to compare 16 different greedy algorithms for decision tree construction. © 2013 Taylor and Francis Group, LLC.
Dynamic Isotope Power System: technology verification phase, program plan, 1 October 1978
International Nuclear Information System (INIS)
1979-01-01
The technology verification phase program plan of the Dynamic Isotope Power System (DIPS) project is presented. DIPS is a project to develop a 0.5 to 2.0 kW power system for spacecraft using an isotope heat source and a closed-cycle Rankine power-system with an organic working fluid. The technology verification phase's purposes are to increase the system efficiency to over 18%, to demonstrate system reliability, and to provide an estimate for flight test scheduling. Progress toward these goals is reported
Human dynamics of spending: Longitudinal study of a coalition loyalty program
Yi, Il Gu; Jeong, Hyang Min; Choi, Woosuk; Jang, Seungkwon; Lee, Heejin; Kim, Beom Jun
2014-09-01
Large-scale data of a coalition loyalty program is analyzed in terms of the temporal dynamics of customers' behaviors. We report that the two main activities of a loyalty program, earning and redemption of points, exhibit very different behaviors. It is also found that as customers become older from their early 20's, both male and female customers increase their earning and redemption activities until they arrive at the turning points, beyond which both activities decrease. The positions of turning points as well as the maximum earned and redeemed points are found to differ for males and females. On top of these temporal behaviors, we identify that there exists a learning effect and customers learn how to earn and redeem points as their experiences accumulate in time.
K-TIF: a two-fluid computer program for downcomer flow dynamics. [PWR
Energy Technology Data Exchange (ETDEWEB)
Amsden, A.A.; Harlow, F.H.
1977-10-01
The K-TIF computer program has been developed for numerical solution of the time-varying dynamics of steam and water in a pressurized water reactor downcomer. The current status of physical and mathematical modeling is presented in detail. The report also contains a complete description of the numerical solution technique, a full description and listing of the computer program, instructions for its use, with a sample printout for a specific test problem. A series of calculations, performed with no change in the modeling parameters, shows consistent agreement with the experimental trends over a wide range of conditions, which gives confidence to the calculations as a basis for investigating the complicated physics of steam-water flows in the downcomer.
Mixed integer linear programming model for dynamic supplier selection problem considering discounts
Directory of Open Access Journals (Sweden)
Adi Wicaksono Purnawan
2018-01-01
Full Text Available Supplier selection is one of the most important elements in supply chain management. This function involves evaluation of many factors such as, material costs, transportation costs, quality, delays, supplier capacity, storage capacity and others. Each of these factors varies with time, therefore, supplier identified for one period is not necessarily be same for the next period to supply the same product. So, mixed integer linear programming (MILP was developed to overcome the dynamic supplier selection problem (DSSP. In this paper, a mixed integer linear programming model is built to solve the lot-sizing problem with multiple suppliers, multiple periods, multiple products and quantity discounts. The buyer has to make a decision for some products which will be supplied by some suppliers for some periods cosidering by discount. To validate the MILP model with randomly generated data. The model is solved by Lingo 16.
DEFF Research Database (Denmark)
Hu, Rui; Hu, Weihao; Li, Pengfei
2016-01-01
and relatively low cost. Thus, many countries are increasing the wind power penetration in their power system step by step, such as Denmark, Spain and Germany. The incremental wind power penetration brings a lot of new issues in operation and programming. The power system sometimes will operate close to its...... stable limits. Once the blackout happens, a well-designed restoration strategy is significant. This paper focuses on how to ameliorate the power system restoration procedures to adapt the high wind power penetration and how to take full advantages of the wind power plants during the restoration....... In this paper, the possibility to exploit the stochastic wind power during restoration was discussed, and a Dynamic Programming (DP) method was proposed to make wind power contribute in the restoration rationally as far as possible. In this paper, the method is tested and verified by a modified IEEE 30 Buses...
Addressing gender dynamics and engaging men in HIV programs: lessons learned from Horizons research.
Pulerwitz, Julie; Michaelis, Annie; Verma, Ravi; Weiss, Ellen
2010-01-01
In the field of human immunodeficiency virus (HIV) prevention, there has been increasing interest in the role that gender plays in HIV and violence risk, and in successfully engaging men in the response. This article highlights findings from more than 10 studies in Asia, Africa, and Latin America--conducted from 1997 through 2007 as part of the Horizons program--that have contributed to understanding the relationship between gender and men's behaviors, developing useful measurement tools for gender norms, and designing and evaluating the impact of gender-focused program strategies. Studies showed significant associations between support for inequitable norms and risk, such as more partner violence and less condom use. Programmatic lessons learned ranged from insights into appropriate media messages, to strategies to engage men in critically reflecting upon gender inequality, to the qualities of successful program facilitators. The portfolio of work reveals the potential and importance of directly addressing gender dynamics in HIV- and violence-prevention programs for both men and women.
Zhang, Xiaodong; Huang, Gordon
2013-02-15
Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjective programming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different p(i) levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help the decision makers justify and/or adjust their waste management strategies based on their implicit knowledge and preferences. Copyright © 2012 Elsevier B.V. All rights reserved.
MacGillivray, Laurie; Goode, Gretchen S.
2016-01-01
Researchers of after-school tutoring primarily focus on educational outcomes with little attention to the social dynamics of such programs. In our qualitative case study, we examined the nature of interactions among tutors in a tutoring program at a homeless shelter for families. Employing Bourdieu's concepts of "social capital" and…
Baldwin, Robin Lynn Brunty
2013-01-01
The purpose of this study was to evaluate the dynamics of a successful planned giving program utilizing shared leadership at Historically Black Colleges and Universities (HBCUs). This information will assist the leadership in determining if and how a successful planned giving program can be established for HBCUs. It is possible for planned gifts…
Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing
Ono, Masahiro; Kuwata, Yoshiaki
2013-01-01
A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.
Jiang, Luan; Ling, Shan; Li, Qiang
2016-03-01
Cardiovascular diseases are becoming a leading cause of death all over the world. The cardiac function could be evaluated by global and regional parameters of left ventricle (LV) of the heart. The purpose of this study is to develop and evaluate a fully automated scheme for segmentation of LV in short axis cardiac cine MR images. Our fully automated method consists of three major steps, i.e., LV localization, LV segmentation at end-diastolic phase, and LV segmentation propagation to the other phases. First, the maximum intensity projection image along the time phases of the midventricular slice, located at the center of the image, was calculated to locate the region of interest of LV. Based on the mean intensity of the roughly segmented blood pool in the midventricular slice at each phase, end-diastolic (ED) and end-systolic (ES) phases were determined. Second, the endocardial and epicardial boundaries of LV of each slice at ED phase were synchronously delineated by use of a dual dynamic programming technique. The external costs of the endocardial and epicardial boundaries were defined with the gradient values obtained from the original and enhanced images, respectively. Finally, with the advantages of the continuity of the boundaries of LV across adjacent phases, we propagated the LV segmentation from the ED phase to the other phases by use of dual dynamic programming technique. The preliminary results on 9 clinical cardiac cine MR cases show that the proposed method can obtain accurate segmentation of LV based on subjective evaluation.
An Online Energy Management Control for Hybrid Electric Vehicles Based on Neuro-Dynamic Programming
Directory of Open Access Journals (Sweden)
Feiyan Qin
2018-03-01
Full Text Available Hybrid electric vehicles are a compromise between traditional vehicles and pure electric vehicles and can be part of the solution to the energy shortage problem. Energy management strategies (EMSs are highly related to energy utilization in HEVs’ fuel economy. In this research, we have employed a neuro-dynamic programming (NDP method to simultaneously optimize fuel economy and battery state of charge (SOC. In this NDP method, the critic network is a multi-resolution wavelet neural network based on the Meyer wavelet function, and the action network is a conventional wavelet neural network based on the Morlet function. The weights and parameters of both networks are obtained by an algorithm of backpropagation type. The NDP-based EMS has been applied to a parallel HEV and compared with a previously reported NDP EMS and a stochastic dynamic programing-based method. Simulation results under ADVISOR2002 have shown that the proposed NDP approach achieves better performance than both the methods. These indicate that the proposed NDP EMS, and the CWNN and MRWNN, are effective in approximating a nonlinear system.
Ground test program for a full-size solar dynamic heat receiver
Sedgwick, L. M.; Kaufmann, K. J.; Mclallin, K. L.; Kerslake, T. W.
1991-01-01
Test hardware, facilities, and procedures were developed to conduct ground testing of a full-size, solar dynamic heat receiver in a partially simulated, low earth orbit environment. The heat receiver was designed to supply 102 kW of thermal energy to a helium and xenon gas mixture continuously over a 94 minute orbit, including up to 36 minutes of eclipse. The purpose of the test program was to quantify the receiver thermodynamic performance, its operating temperatures, and thermal response to changes in environmental and power module interface boundary conditions. The heat receiver was tested in a vacuum chamber using liquid nitrogen cold shrouds and an aperture cold plate. Special test equipment was designed to provide the required ranges in interface boundary conditions that typify those expected or required for operation as part of the solar dynamic power module on the Space Station Freedom. The support hardware includes an infrared quartz lamp heater with 30 independently controllable zones and a closed-Brayton cycle engine simulator to circulate and condition the helium-xenon gas mixture. The test article, test support hardware, facilities, and instrumentation developed to conduct the ground test program are all described.
IMPLICIT DUAL CONTROL BASED ON PARTICLE FILTERING AND FORWARD DYNAMIC PROGRAMMING.
Bayard, David S; Schumitzky, Alan
2010-03-01
This paper develops a sampling-based approach to implicit dual control. Implicit dual control methods synthesize stochastic control policies by systematically approximating the stochastic dynamic programming equations of Bellman, in contrast to explicit dual control methods that artificially induce probing into the control law by modifying the cost function to include a term that rewards learning. The proposed implicit dual control approach is novel in that it combines a particle filter with a policy-iteration method for forward dynamic programming. The integration of the two methods provides a complete sampling-based approach to the problem. Implementation of the approach is simplified by making use of a specific architecture denoted as an H-block. Practical suggestions are given for reducing computational loads within the H-block for real-time applications. As an example, the method is applied to the control of a stochastic pendulum model having unknown mass, length, initial position and velocity, and unknown sign of its dc gain. Simulation results indicate that active controllers based on the described method can systematically improve closed-loop performance with respect to other more common stochastic control approaches.
Adhikari, Shyam Prasad; Yang, Changju; Slot, Krzysztof; Kim, Hyongsuk
2018-01-10
This paper presents a vision sensor-based solution to the challenging problem of detecting and following trails in highly unstructured natural environments like forests, rural areas and mountains, using a combination of a deep neural network and dynamic programming. The deep neural network (DNN) concept has recently emerged as a very effective tool for processing vision sensor signals. A patch-based DNN is trained with supervised data to classify fixed-size image patches into "trail" and "non-trail" categories, and reshaped to a fully convolutional architecture to produce trail segmentation map for arbitrary-sized input images. As trail and non-trail patches do not exhibit clearly defined shapes or forms, the patch-based classifier is prone to misclassification, and produces sub-optimal trail segmentation maps. Dynamic programming is introduced to find an optimal trail on the sub-optimal DNN output map. Experimental results showing accurate trail detection for real-world trail datasets captured with a head mounted vision system are presented.
Stockpile strategy for China's emergency oil reserve: A dynamic programming approach
International Nuclear Information System (INIS)
Bai, Y.; Dahl, C.A.; Zhou, D.Q.; Zhou, P.
2014-01-01
China is currently accelerating construction of its strategic petroleum reserves. How should China fill the SPR in a cost-effective manner in the short-run? How might this affect world oil prices? Using a dynamic programming model to answer these questions, the objective of this paper is to minimize the stockpiling costs, including consumer surplus as well as crude acquisition and holding costs. The crude oil acquisition price in the model is determined by global equilibrium between supply and demand. Demand, in turn, depends on world market conditions including China's stockpile filling rate. Our empirical study under different market conditions shows that China's optimal stockpile acquisition rate varies from 9 to 19 million barrels per month, and the optimal stockpiling drives up the world oil price by 3–7%. The endogenous price increase accounts for 52% of total stockpiling costs in the base case. When the market is tighter or the demand function is more inelastic, the stockpiling affects the market more significantly and pushes prices even higher. Alternatively, in a disruption, drawdown from the stockpile can effectively dampen soaring prices, though the shortage is likely to leave the price higher than before the disruption. - Highlights: • China's SPR policies are examined by dynamic programming. • The optimal stockpile acquisition rate varies from 9 to 19 million barrels per month. • The optimal stockpiling drives up world oil price by 3–7%
Higaki, Takumi; Kadota, Yasuhiro; Goh, Tatsuaki; Hayashi, Teruyuki; Kutsuna, Natsumaro; Sano, Toshio; Hasezawa, Seiichiro; Kuchitsu, Kazuyuki
2008-09-01
Responses of plant cells to environmental stresses often involve morphological changes, differentiation and redistribution of various organelles and cytoskeletal network. Tobacco BY-2 cells provide excellent model system for in vivo imaging of these intracellular events. Treatment of the cell cycle-synchronized BY-2 cells with a proteinaceous oomycete elicitor, cryptogein, induces highly synchronous programmed cell death (PCD) and provide a model system to characterize vacuolar and cytoskeletal dynamics during the PCD. Sequential observation revealed dynamic reorganization of the vacuole and actin microfilaments during the execution of the PCD. We further characterized the effects cryptogein on mitotic microtubule organization in cell cycle-synchronized cells. Cryptogein treatment at S phase inhibited formation of the preprophase band, a cortical microtubule band that predicts the cell division site. Cortical microtubules kept their random orientation till their disruption that gradually occurred during the execution of the PCD twelve hours after the cryptogein treatment. Possible molecular mechanisms and physiological roles of the dynamic behavior of the organelles and cytoskeletal network in the pathogenic signal-induced PCD are discussed.
A Dynamic Programming Solution for Energy-Optimal Video Playback on Mobile Devices
Directory of Open Access Journals (Sweden)
Minseok Song
2016-01-01
Full Text Available Due to the development of mobile technology and wide availability of smartphones, the Internet of Things (IoT starts to handle high volumes of video data to facilitate multimedia-based services, which requires energy-efficient video playback. In video playback, frames have to be decoded and rendered at high playback rate, increasing the computation cost on the CPU. To save the CPU power, dynamic voltage and frequency scaling (DVFS dynamically adjusts the operating voltage of the processor along with frequency, in which appropriate selection of frequency on power could achieve a balance between performance and power. We present a decoding model that allows buffering frames to let the CPU run at low frequency and then propose an algorithm that determines the CPU frequency needed to decode each frame in a video, with the aim of minimizing power consumption while meeting buffer size and deadline constraints, using a dynamic programming technique. We finally extend this algorithm to optimize CPU frequencies over a short sequence of frames, producing a practical method of reducing the energy required for video decoding. Experimental results show a system-wide reduction in energy of 27%, compared with a processor running at full speed.
Boundary Control of Linear Uncertain 1-D Parabolic PDE Using Approximate Dynamic Programming.
Talaei, Behzad; Jagannathan, Sarangapani; Singler, John
2018-04-01
This paper develops a near optimal boundary control method for distributed parameter systems governed by uncertain linear 1-D parabolic partial differential equations (PDE) by using approximate dynamic programming. A quadratic surface integral is proposed to express the optimal cost functional for the infinite-dimensional state space. Accordingly, the Hamilton-Jacobi-Bellman (HJB) equation is formulated in the infinite-dimensional domain without using any model reduction. Subsequently, a neural network identifier is developed to estimate the unknown spatially varying coefficient in PDE dynamics. Novel tuning law is proposed to guarantee the boundedness of identifier approximation error in the PDE domain. A radial basis network (RBN) is subsequently proposed to generate an approximate solution for the optimal surface kernel function online. The tuning law for near optimal RBN weights is created, such that the HJB equation error is minimized while the dynamics are identified and closed-loop system remains stable. Ultimate boundedness (UB) of the closed-loop system is verified by using the Lyapunov theory. The performance of the proposed controller is successfully confirmed by simulation on an unstable diffusion-reaction process.
Lu, Zhao; Sun, Jing; Butts, Kenneth
2014-05-01
Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.
Zhu, Yuanheng; Zhao, Dongbin; Li, Xiangjun
2017-03-01
H ∞ control is a powerful method to solve the disturbance attenuation problems that occur in some control systems. The design of such controllers relies on solving the zero-sum game (ZSG). But in practical applications, the exact dynamics is mostly unknown. Identification of dynamics also produces errors that are detrimental to the control performance. To overcome this problem, an iterative adaptive dynamic programming algorithm is proposed in this paper to solve the continuous-time, unknown nonlinear ZSG with only online data. A model-free approach to the Hamilton-Jacobi-Isaacs equation is developed based on the policy iteration method. Control and disturbance policies and value are approximated by neural networks (NNs) under the critic-actor-disturber structure. The NN weights are solved by the least-squares method. According to the theoretical analysis, our algorithm is equivalent to a Gauss-Newton method solving an optimization problem, and it converges uniformly to the optimal solution. The online data can also be used repeatedly, which is highly efficient. Simulation results demonstrate its feasibility to solve the unknown nonlinear ZSG. When compared with other algorithms, it saves a significant amount of online measurement time.
The Configuration Of Supply Chain Agritourism To Improve The Performance With Dynamic Programming
Directory of Open Access Journals (Sweden)
Sahnaz Ubud
2015-09-01
Full Text Available The purposes of this research is to implementation about the configuration of Supply Chain Agritourism in Mekarsari Tours Garden and result a decision making which must be done by top level management about their supply chain configuration. Because now Mekarsari, the biggest fruit garden in the world, have a lot of type of fruit which must be supply for the customer depend on the season with on time. So Mekarsari must know about their configuration from supplier to customer to improve their performance. The Respondents for this research is selected based on the results of supply chain maping from the worker in the garden, the top level management until the end customer. Supply chian network is formed consisting of farm workers to the end customers, especially those located in the tourist are of green land zone. The type of data is displayed in a supply chain modeling approach is to use the dynamic system. It’s consists of numeric data, the written data and mental models. That data is collected and processed into a design model. The design model is using system dynamics methodology. In compiling the system dynamics model has been used software Vensim Professional Academic Ventana 5.7. The result of this research is a configuration of Supply Chain Agritourism which is developed from the supplier until the end customer in Mekarsari tours Garden. From the Dynamic Programming, the result is a decision making which must be done by the top level management to improve the supply chain performance, especially in the green land zone.
International Nuclear Information System (INIS)
Chang, Ji Woon; Shin, Young Joon; Lee, Tae Hoon; Lee, Ki Young; Kim, Yong Wan; Chang, Jong Hwa; Youn, Cheung
2011-01-01
The Sulfur-Iodine (SI) cycle which can produce hydrogen by using nuclear heat consists of a Bunsen reaction (Section 1), a sulfur acid concentration and decomposition (Section 2), and a hydriodic acid concentration and decomposition (Section 3). The heat required in the SI process can be supplied through an intermediate heat exchanger (IHX) by a Very High Temperature Gas Cooled Reactor (VHTR). The Korea Atomic Energy Research Institute-Dynamic Simulation Code (KAERI-DySCo) based on the Visual C++ is an integration application software that simulates the dynamic behavior of the SI process. KAERI-DySCo was prepared to solve dynamic problem of the seven chemical reactors which consist of Sections 2 and 3. Section 3 is the key part of the SI process, because the strong non-ideality and the partial immiscibility of the binary HI.H 2 O and the ternary HI.I 2 .H 2 O (HIX solution) mixture make it difficult to model and simulate the dynamic behavior of the system. Therefore, it is necessary to compose separately a dynamic simulation program for Section 3 in KAERI-DySCo optimization. In this paper, a simulation program to analyze the dynamic behavior of Section 3 is introduced using the prepared KAERI-DySCo, and results of dynamic simulation are represented by running the program
Programming chemical kinetics: engineering dynamic reaction networks with DNA strand displacement
Srinivas, Niranjan
Over the last century, the silicon revolution has enabled us to build faster, smaller and more sophisticated computers. Today, these computers control phones, cars, satellites, assembly lines, and other electromechanical devices. Just as electrical wiring controls electromechanical devices, living organisms employ "chemical wiring" to make decisions about their environment and control physical processes. Currently, the big difference between these two substrates is that while we have the abstractions, design principles, verification and fabrication techniques in place for programming with silicon, we have no comparable understanding or expertise for programming chemistry. In this thesis we take a small step towards the goal of learning how to systematically engineer prescribed non-equilibrium dynamical behaviors in chemical systems. We use the formalism of chemical reaction networks (CRNs), combined with mass-action kinetics, as our programming language for specifying dynamical behaviors. Leveraging the tools of nucleic acid nanotechnology (introduced in Chapter 1), we employ synthetic DNA molecules as our molecular architecture and toehold-mediated DNA strand displacement as our reaction primitive. Abstraction, modular design and systematic fabrication can work only with well-understood and quantitatively characterized tools. Therefore, we embark on a detailed study of the "device physics" of DNA strand displacement (Chapter 2). We present a unified view of strand displacement biophysics and kinetics by studying the process at multiple levels of detail, using an intuitive model of a random walk on a 1-dimensional energy landscape, a secondary structure kinetics model with single base-pair steps, and a coarse-grained molecular model that incorporates three-dimensional geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Our findings are consistent with previously measured or inferred rates for
Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming.
Mu, Chaoxu; Ni, Zhen; Sun, Changyin; He, Haibo
2017-03-01
In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking control based on action-dependent heuristic dynamic programming (ADHDP). The control action is generated by the combination of sliding mode control (SMC) and the ADHDP controller to track the desired velocity and the desired altitude. In particular, the ADHDP controller observes the differences between the actual velocity/altitude and the desired velocity/altitude, and then provides a supplementary control action accordingly. The ADHDP controller does not rely on the accurate mathematical model function and is data driven. Meanwhile, it is capable to adjust its parameters online over time under various working conditions, which is very suitable for hypersonic vehicle system with parameter uncertainties and disturbances. We verify the adaptive supplementary control approach versus the traditional SMC in the cruising flight, and provide three simulation studies to illustrate the improved performance with the proposed approach.
Stochastic Dynamic Programming for Three-Echelon Inventory System of Limited Shelf Life Products
Directory of Open Access Journals (Sweden)
Galal Noha M.
2016-01-01
Full Text Available Coordination of inventory decisions within the supply chain is one of the major determinants of its competitiveness in the global market. Products with limited shelf life impose additional challenges in managing the inventory across the supply chain because of the additional wastage costs incurred in case of being stored beyond product’s useful life. This paper presents a stochastic dynamic programming model for inventory replenishment in a serial multi-echelon distribution supply chain. The model considers uncertain stationary discrete demand at the retailer and zero lead time. The objective is to minimize expected total costs across the supply chain echelons, while maintaining a preset service level. The results illustrate that a cost saving of around 17% is achievable due to coordinating inventory decisions across the supply chain.
Detection and Extraction of Roads from High Resolution Satellites Images with Dynamic Programming
Benzouai, Siham; Smara, Youcef
2010-12-01
The advent of satellite images allows now a regular and a fast digitizing and update of geographic data, especially roads which are very useful for Geographic Information Systems (GIS) applications such as transportation, urban pollution, geomarketing, etc. For this, several studies have been conducted to automate roads extraction in order to minimize the manual processes [4]. In this work, we are interested in roads extraction from satellite imagery with high spatial resolution (at best equal to 10 m). The method is semi automatic and follows a linear approach where road is considered as a linear object. As roads extraction is a pattern recognition problem, it is useful, above all, to characterize roads. After, we realize a pre-processing by applying an Infinite Size Edge Filter -ISEF- and processing method based on dynamic programming concept, in particular, Fishler algorithm designed by F*.
Penalty dynamic programming algorithm for dim targets detection in sensor systems.
Huang, Dayu; Xue, Anke; Guo, Yunfei
2012-01-01
In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.
Druce, Donald J.
1990-01-01
A monthly stochastic dynamic programing model was recently developed and implemented at British Columbia (B.C.) Hydro to provide decision support for short-term energy exports and, if necessary, for flood control on the Peace River in northern British Columbia. The model establishes the marginal cost of supplying energy from the B.C. Hydro system, as well as a monthly operating policy for the G.M. Shrum and Peace Canyon hydroelectric plants and the Williston Lake storage reservoir. A simulation model capable of following the operating policy then determines the probability of refilling Williston Lake and possible spill rates and volumes. Reservoir inflows are input to both models in daily and monthly formats. The results indicate that flood control can be accommodated without sacrificing significant export revenue.
Energy Technology Data Exchange (ETDEWEB)
Druce, D.J. (British Columbia Hydro and Power Authority, Vancouver, British Columbia (Canada))
1990-01-01
A monthly stochastic dynamic programing model was recently developed and implemented at British Columbia (B.C.) Hydro to provide decision support for short-term energy exports and, if necessary, for flood control on the Peace River in northern British Columbia. The model established the marginal cost of supplying energy from the B.C. Hydro system, as well as a monthly operating policy for the G.M. Shrum and Peace Canyon hydroelectric plants and the Williston Lake storage reservoir. A simulation model capable of following the operating policy then determines the probability of refilling Williston Lake and possible spill rates and volumes. Reservoir inflows are input to both models in daily and monthly formats. The results indicate that flood control can be accommodated without sacrificing significant export revenue.
Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost
International Nuclear Information System (INIS)
Bokanowski, Olivier; Picarelli, Athena; Zidani, Hasnaa
2015-01-01
This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach
International Nuclear Information System (INIS)
Early, J.W.; Abernathey, R.M.
1982-04-01
This apparatus, a prototype of one being constructed for hotcell examination of irradiated nuclear materials, measures dynamic release rates and integrated volumes of individual gases from materials heated under controlled temperature-time programs. It consists of an inductively heated vacuum furnace connected to a quadrupole mass spectrometer. A computerized control system with data acquisition provides scanning rates down to 1s and on-line tabular and graphic displays. Heating rates are up to 1300 0 C/min to a maximum temperature of 2000 0 C. The measurement range is about 10 -6 to 10 -2 torr-liter/s for H 2 , CH 4 , H 2 O, N 2 , and CO and 10 -8 to 10 -2 torr-liter/s for He, Kr, and Xe. Applications are described for measurements of Kr and Xe in mixed oxide fuel, various gases in UO 2 pellets, and He in 238 PuO 2 power and heat sources
Directory of Open Access Journals (Sweden)
Diamantidis A. C.
2004-01-01
Full Text Available In this study, the buffer allocation problem (BAP in homogeneous, asymptotically reliable serial production lines is considered. A known aggregation method, given by Lim, Meerkov, and Top (1990, for the performance evaluation (i.e., estimation of throughput of this type of production lines when the buffer allocation is known, is used as an evaluative method in conjunction with a newly developed dynamic programming (DP algorithm for the BAP. The proposed algorithm is applied to production lines where the number of machines is varying from four up to a hundred machines. The proposed algorithm is fast because it reduces the volume of computations by rejecting allocations that do not lead to maximization of the line's throughput. Numerical results are also given for large production lines.
Dynamic Programming and Error Estimates for Stochastic Control Problems with Maximum Cost
Energy Technology Data Exchange (ETDEWEB)
Bokanowski, Olivier, E-mail: boka@math.jussieu.fr [Laboratoire Jacques-Louis Lions, Université Paris-Diderot (Paris 7) UFR de Mathématiques - Bât. Sophie Germain (France); Picarelli, Athena, E-mail: athena.picarelli@inria.fr [Projet Commands, INRIA Saclay & ENSTA ParisTech (France); Zidani, Hasnaa, E-mail: hasnaa.zidani@ensta.fr [Unité de Mathématiques appliquées (UMA), ENSTA ParisTech (France)
2015-02-15
This work is concerned with stochastic optimal control for a running maximum cost. A direct approach based on dynamic programming techniques is studied leading to the characterization of the value function as the unique viscosity solution of a second order Hamilton–Jacobi–Bellman (HJB) equation with an oblique derivative boundary condition. A general numerical scheme is proposed and a convergence result is provided. Error estimates are obtained for the semi-Lagrangian scheme. These results can apply to the case of lookback options in finance. Moreover, optimal control problems with maximum cost arise in the characterization of the reachable sets for a system of controlled stochastic differential equations. Some numerical simulations on examples of reachable analysis are included to illustrate our approach.
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Rauff Lind Christensen, Tue; Klose, Andreas; Andersen, Kim Allan
important aspects of supplier selection, an important application of the SSFCTP, this does not reflect the real life situation. First, transportation costs faced by many companies are in fact piecewise linear. Secondly, when suppliers offer discounts, either incremental or all-unit discounts, such savings......The Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem (SSFCMCTP) is a problem with versatile applications. This problem is a generalization of the Single-Sink, Fixed-Charge Transportation Problem (SSFCTP), which has a fixed-charge, linear cost structure. However, in at least two...... are neglected in the SSFCTP. The SSFCMCTP overcome this problem by incorporating a staircase cost structure in the cost function instead of the usual one used in SSFCTP. We present a dynamic programming algorithm for the resulting problem. To enhance the performance of the generic algorithm a number...
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
Energy Technology Data Exchange (ETDEWEB)
Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)
2015-01-15
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Dynamic Programming Optimization of Multi-rate Multicast Video-Streaming Services
Directory of Open Access Journals (Sweden)
Nestor Michael Caños Tiglao
2010-06-01
Full Text Available In large scale IP Television (IPTV and Mobile TV distributions, the video signal is typically encoded and transmitted using several quality streams, over IP Multicast channels, to several groups of receivers, which are classified in terms of their reception rate. As the number of video streams is usually constrained by both the number of TV channels and the maximum capacity of the content distribution network, it is necessary to find the selection of video stream transmission rates that maximizes the overall user satisfaction. In order to efficiently solve this problem, this paper proposes the Dynamic Programming Multi-rate Optimization (DPMO algorithm. The latter was comparatively evaluated considering several user distributions, featuring different access rate patterns. The experimental results reveal that DPMO is significantly more efficient than exhaustive search, while presenting slightly higher execution times than the non-optimal Multi-rate Step Search (MSS algorithm.
DYNAMIC PROGRAMMING APPROACH TO TESTING RESOURCE ALLOCATION PROBLEM FOR MODULAR SOFTWARE
Directory of Open Access Journals (Sweden)
P.K. Kapur
2003-02-01
Full Text Available Testing phase of a software begins with module testing. During this period modules are tested independently to remove maximum possible number of faults within a specified time limit or testing resource budget. This gives rise to some interesting optimization problems, which are discussed in this paper. Two Optimization models are proposed for optimal allocation of testing resources among the modules of a Software. In the first model, we maximize the total fault removal, subject to budgetary Constraint. In the second model, additional constraint representing aspiration level for fault removals for each module of the software is added. These models are solved using dynamic programming technique. The methods have been illustrated through numerical examples.
Chiu, Stephanie J.; Toth, Cynthia A.; Bowes Rickman, Catherine; Izatt, Joseph A.; Farsiu, Sina
2012-01-01
This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique. PMID:22567602
Variable Displacement Control of the Concrete Pumping System Based on Dynamic Programming
Directory of Open Access Journals (Sweden)
Ye Min
2017-01-01
Full Text Available To solve the problems of cylinder piston striking cylinder and the hydraulic shocking of the main pump, and causing energy waste problem, the method of variable displacement control of piston stroke was proposed. In order to achieve effective control of the piston stroke, variable displacement control model was established under the physical constraint condition of non-collision between piston and cylinder. And the control process was realized by Dynamic Programming(DP, the simulation and test results show that piston of concrete pumping system don’t strike cylinder and reduce the hydraulic shock of the main pump outlet, meanwhile improve the response speed of the cylinder and achieve energy-saving purposes under varying loads. This control model built in the integration design space of structure variable and control variable is of guiding significance for solving open-loop system’s engineering problems.
DEFF Research Database (Denmark)
Davidsen, Claus; Liu, Suxia; Mo, Xingguo
2015-01-01
Few studies address water quality in hydro-economic models, which often focus primarily on optimal allocation of water quantities. Water quality and water quantity are closely coupled, and optimal management with focus solely on either quantity or quality may cause large costs in terms of the oth......-er component. In this study, we couple water quality and water quantity in a joint hydro-economic catchment-scale optimization problem. Stochastic dynamic programming (SDP) is used to minimize the basin-wide total costs arising from water allocation, water curtailment and water treatment. The simple water...... quality module can handle conservative pollutants, first order depletion and non-linear reactions. For demonstration purposes, we model pollutant releases as biochemical oxygen demand (BOD) and use the Streeter-Phelps equation for oxygen deficit to compute the resulting min-imum dissolved oxygen...
Scherer, Klaus R; Ellgring, Heiner
2007-02-01
The different assumptions made by discrete and componential emotion theories about the nature of the facial expression of emotion and the underlying mechanisms are reviewed. Explicit and implicit predictions are derived from each model. It is argued that experimental expression-production paradigms rather than recognition studies are required to critically test these differential predictions. Data from a large-scale actor portrayal study are reported to demonstrate the utility of this approach. The frequencies with which 12 professional actors use major facial muscle actions individually and in combination to express 14 major emotions show little evidence for emotion-specific prototypical affect programs. Rather, the results encourage empirical investigation of componential emotion model predictions of dynamic configurations of appraisal-driven adaptive facial actions. (c) 2007 APA, all rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Yang, Zongru; Buerger, Sebastian; Lohmann, Boris [Technische Univ. Muenchen, Garching (Germany). Lehrstuhl fuer Regelungstechnik
2009-07-01
Driving is a metal forming process throughout hammering in cold state. It can create almost any 2D and 3D metal sheets using universal tools. During driving, many parameters of the tools and the sheets affect the forming process, which inhibits a complete automation. In this paper, a model based control for a 2D driving process is proposed. The process of stretching L-shaped metal sheets is analytically modelled. Three phases, namely hybrid deformations, material flow as well as springback and inverse bending, describe the deformation process at one stroke. This results in a nonlinear (non-affine), time-discrete state space model. A model predictive controller (MPC) is then designed to determine the optimal control inputs at every time step. Thereby, an objective function that describes the costs from a start angle to an end condition is minimized by means of discrete dynamic programming (DDP). (orig.)
DNA-programmed dynamic assembly of quantum dots for molecular computation.
He, Xuewen; Li, Zhi; Chen, Muzi; Ma, Nan
2014-12-22
Despite the widespread use of quantum dots (QDs) for biosensing and bioimaging, QD-based bio-interfaceable and reconfigurable molecular computing systems have not yet been realized. DNA-programmed dynamic assembly of multi-color QDs is presented for the construction of a new class of fluorescence resonance energy transfer (FRET)-based QD computing systems. A complete set of seven elementary logic gates (OR, AND, NOR, NAND, INH, XOR, XNOR) are realized using a series of binary and ternary QD complexes operated by strand displacement reactions. The integration of different logic gates into a half-adder circuit for molecular computation is also demonstrated. This strategy is quite versatile and straightforward for logical operations and would pave the way for QD-biocomputing-based intelligent molecular diagnostics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Optimization of fuel management and control poison of a nuclear power reactor by dynamic programming
International Nuclear Information System (INIS)
Lima, C.A.R. de.
1977-01-01
The distribution of fuel and control poison in a nuclear reactor was optimized by the method of Dynamic Programming. A 620 M We Pressurized Water Reactor similar to Angra-1 was studied. The reactor operation was simulated in a IBM-1130 computer. Two fuel shuffling schemes and three poison management schemes were simultaneously employed in the reactor divided into three regions of equal volume and two consecutive stages were studied in order to determine the influence of poison management on the optimum fuel management policy. When uniform poisoning on all the three regions was permitted the traditional out-in fuel management policy proved to be more economic. On introducing simultaneous poison management, the optimum fuel management sequence was found to be different. The results obtained indicate a stronger interaction between the fuel management and the poison management than anticipated in previous works. (author)
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
International Nuclear Information System (INIS)
Hirata, Yoshito; Aihara, Kazuyuki; Suzuki, Hideyuki; Shiro, Masanori; Takahashi, Nozomu; Mas, Paloma
2015-01-01
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data
Optimal Control of Complex Systems Based on Improved Dual Heuristic Dynamic Programming Algorithm
Directory of Open Access Journals (Sweden)
Hui Li
2017-01-01
Full Text Available When applied to solving the data modeling and optimal control problems of complex systems, the dual heuristic dynamic programming (DHP technique, which is based on the BP neural network algorithm (BP-DHP, has difficulty in prediction accuracy, slow convergence speed, poor stability, and so forth. In this paper, a dual DHP technique based on Extreme Learning Machine (ELM algorithm (ELM-DHP was proposed. Through constructing three kinds of network structures, the paper gives the detailed realization process of the DHP technique in the ELM. The controller designed upon the ELM-DHP algorithm controlled a molecular distillation system with complex features, such as multivariability, strong coupling, and nonlinearity. Finally, the effectiveness of the algorithm is verified by the simulation that compares DHP and HDP algorithms based on ELM and BP neural network. The algorithm can also be applied to solve the data modeling and optimal control problems of similar complex systems.
Approximating high-dimensional dynamics by barycentric coordinates with linear programming.
Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma
2015-01-01
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Directory of Open Access Journals (Sweden)
Shaolin Ji
2013-01-01
Full Text Available This paper is devoted to a stochastic differential game (SDG of decoupled functional forward-backward stochastic differential equation (FBSDE. For our SDG, the associated upper and lower value functions of the SDG are defined through the solution of controlled functional backward stochastic differential equations (BSDEs. Applying the Girsanov transformation method introduced by Buckdahn and Li (2008, the upper and the lower value functions are shown to be deterministic. We also generalize the Hamilton-Jacobi-Bellman-Isaacs (HJBI equations to the path-dependent ones. By establishing the dynamic programming principal (DPP, we derive that the upper and the lower value functions are the viscosity solutions of the corresponding upper and the lower path-dependent HJBI equations, respectively.
Stochastic optimal control in infinite dimension dynamic programming and HJB equations
Fabbri, Giorgio; Święch, Andrzej
2017-01-01
Providing an introduction to stochastic optimal control in infinite dimension, this book gives a complete account of the theory of second-order HJB equations in infinite-dimensional Hilbert spaces, focusing on its applicability to associated stochastic optimal control problems. It features a general introduction to optimal stochastic control, including basic results (e.g. the dynamic programming principle) with proofs, and provides examples of applications. A complete and up-to-date exposition of the existing theory of viscosity solutions and regular solutions of second-order HJB equations in Hilbert spaces is given, together with an extensive survey of other methods, with a full bibliography. In particular, Chapter 6, written by M. Fuhrman and G. Tessitore, surveys the theory of regular solutions of HJB equations arising in infinite-dimensional stochastic control, via BSDEs. The book is of interest to both pure and applied researchers working in the control theory of stochastic PDEs, and in PDEs in infinite ...
Noninvasive fetal QRS detection using an echo state network and dynamic programming.
Lukoševičius, Mantas; Marozas, Vaidotas
2014-08-01
We address a classical fetal QRS detection problem from abdominal ECG recordings with a data-driven statistical machine learning approach. Our goal is to have a powerful, yet conceptually clean, solution. There are two novel key components at the heart of our approach: an echo state recurrent neural network that is trained to indicate fetal QRS complexes, and several increasingly sophisticated versions of statistics-based dynamic programming algorithms, which are derived from and rooted in probability theory. We also employ a standard technique for preprocessing and removing maternal ECG complexes from the signals, but do not take this as the main focus of this work. The proposed approach is quite generic and can be extended to other types of signals and annotations. Open-source code is provided.
Noninvasive fetal QRS detection using an echo state network and dynamic programming
International Nuclear Information System (INIS)
Lukoševičius, Mantas; Marozas, Vaidotas
2014-01-01
We address a classical fetal QRS detection problem from abdominal ECG recordings with a data-driven statistical machine learning approach. Our goal is to have a powerful, yet conceptually clean, solution. There are two novel key components at the heart of our approach: an echo state recurrent neural network that is trained to indicate fetal QRS complexes, and several increasingly sophisticated versions of statistics-based dynamic programming algorithms, which are derived from and rooted in probability theory. We also employ a standard technique for preprocessing and removing maternal ECG complexes from the signals, but do not take this as the main focus of this work. The proposed approach is quite generic and can be extended to other types of signals and annotations. Open-source code is provided. (paper)
Directory of Open Access Journals (Sweden)
Zhi-Jun Fu
2017-01-01
Full Text Available In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP. Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.
Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.
Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L
2017-10-01
The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.
Memory-efficient dynamic programming backtrace and pairwise local sequence alignment.
Newberg, Lee A
2008-08-15
A backtrace through a dynamic programming algorithm's intermediate results in search of an optimal path, or to sample paths according to an implied probability distribution, or as the second stage of a forward-backward algorithm, is a task of fundamental importance in computational biology. When there is insufficient space to store all intermediate results in high-speed memory (e.g. cache) existing approaches store selected stages of the computation, and recompute missing values from these checkpoints on an as-needed basis. Here we present an optimal checkpointing strategy, and demonstrate its utility with pairwise local sequence alignment of sequences of length 10,000. Sample C++-code for optimal backtrace is available in the Supplementary Materials. Supplementary data is available at Bioinformatics online.
Wei, Qinglai; Liu, Derong; Lin, Qiao
In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.
AbouEisha, Hassan M.
2017-07-13
We consider a class of two-and three-dimensional h-refined meshes generated by an adaptive finite element method. We introduce an element partition tree, which controls the execution of the multi-frontal solver algorithm over these refined grids. We propose and study algorithms with polynomial computational cost for the optimization of these element partition trees. The trees provide an ordering for the elimination of unknowns. The algorithms automatically optimize the element partition trees using extensions of dynamic programming. The construction of the trees by the dynamic programming approach is expensive. These generated trees cannot be used in practice, but rather utilized as a learning tool to propose fast heuristic algorithms. In this first part of our paper we focus on the dynamic programming approach, and draw a sketch of the heuristic algorithm. The second part will be devoted to a more detailed analysis of the heuristic algorithm extended for the case of hp-adaptive
AbouEisha, Hassan M.; Calo, Victor Manuel; Jopek, Konrad; Moshkov, Mikhail; Paszyńka, Anna; Paszyński, Maciej; Skotniczny, Marcin
2017-01-01
We consider a class of two-and three-dimensional h-refined meshes generated by an adaptive finite element method. We introduce an element partition tree, which controls the execution of the multi-frontal solver algorithm over these refined grids. We propose and study algorithms with polynomial computational cost for the optimization of these element partition trees. The trees provide an ordering for the elimination of unknowns. The algorithms automatically optimize the element partition trees using extensions of dynamic programming. The construction of the trees by the dynamic programming approach is expensive. These generated trees cannot be used in practice, but rather utilized as a learning tool to propose fast heuristic algorithms. In this first part of our paper we focus on the dynamic programming approach, and draw a sketch of the heuristic algorithm. The second part will be devoted to a more detailed analysis of the heuristic algorithm extended for the case of hp-adaptive
Closed Cycle Engine Program Used in Solar Dynamic Power Testing Effort
Ensworth, Clint B., III; McKissock, David B.
1998-01-01
NASA Lewis Research Center is testing the world's first integrated solar dynamic power system in a simulated space environment. This system converts solar thermal energy into electrical energy by using a closed-cycle gas turbine and alternator. A NASA-developed analysis code called the Closed Cycle Engine Program (CCEP) has been used for both pretest predictions and post-test analysis of system performance. The solar dynamic power system has a reflective concentrator that focuses solar thermal energy into a cavity receiver. The receiver is a heat exchanger that transfers the thermal power to a working fluid, an inert gas mixture of helium and xenon. The receiver also uses a phase-change material to store the thermal energy so that the system can continue producing power when there is no solar input power, such as when an Earth-orbiting satellite is in eclipse. The system uses a recuperated closed Brayton cycle to convert thermal power to mechanical power. Heated gas from the receiver expands through a turbine that turns an alternator and a compressor. The system also includes a gas cooler and a radiator, which reject waste cycle heat, and a recuperator, a gas-to-gas heat exchanger that improves cycle efficiency by recovering thermal energy.
A heuristic algorithm to approximate dynamic program of a novel new product development process
Directory of Open Access Journals (Sweden)
Hamed Fazlollahtabar
2016-01-01
Full Text Available We are concerned with a new product development (NPD network in digital environment in which the aim is to find integrated attributes for value added purposes. Different views exist for new product development. Here, the effective factors are categorized into customers, competitors and the company’s own past experience. Also, various attributes are considered for the development of a product. Thus, using digital data of attributes, the optimal set of attributes is chosen for user in the new product development. Regarding the multi stage decision making process of the customer, competitor and company’s own past experience, we develop a multi-dimensional dynamic program as a useful tool for multi stage decision making. To counteract the dynamism of the digital data in different time periods, two concepts of state and policy direction are introduced to determine the cost of moving through the stages of the proposed NPD digital network. Since the space requirements and value function computations become impractical for even moderate size, we approximate the optimal value function developing a heuristic algorithm.
Ostrowski, M; Paulevé, L; Schaub, T; Siegel, A; Guziolowski, C
2016-11-01
Boolean networks (and more general logic models) are useful frameworks to study signal transduction across multiple pathways. Logic models can be learned from a prior knowledge network structure and multiplex phosphoproteomics data. However, most efficient and scalable training methods focus on the comparison of two time-points and assume that the system has reached an early steady state. In this paper, we generalize such a learning procedure to take into account the time series traces of phosphoproteomics data in order to discriminate Boolean networks according to their transient dynamics. To that end, we identify a necessary condition that must be satisfied by the dynamics of a Boolean network to be consistent with a discretized time series trace. Based on this condition, we use Answer Set Programming to compute an over-approximation of the set of Boolean networks which fit best with experimental data and provide the corresponding encodings. Combined with model-checking approaches, we end up with a global learning algorithm. Our approach is able to learn logic models with a true positive rate higher than 78% in two case studies of mammalian signaling networks; for a larger case study, our method provides optimal answers after 7min of computation. We quantified the gain in our method predictions precision compared to learning approaches based on static data. Finally, as an application, our method proposes erroneous time-points in the time series data with respect to the optimal learned logic models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Pradanti, Paskalia; Hartono
2018-03-01
Determination of insulin injection dose in diabetes mellitus treatment can be considered as an optimal control problem. This article is aimed to simulate optimal blood glucose control for patient with diabetes mellitus. The blood glucose regulation of diabetic patient is represented by Ackerman’s Linear Model. This problem is then solved using dynamic programming method. The desired blood glucose level is obtained by minimizing the performance index in Lagrange form. The results show that dynamic programming based on Ackerman’s Linear Model is quite good to solve the problem.
International Nuclear Information System (INIS)
Thiriet, L.; Deledicq, A.
1968-09-01
First, the point of applying Dynamic Programming to optimization and Operational Research problems in chemical industries are recalled, as well as the conditions in which a dynamic program is illustrated by a sequential graph. A new algorithm for the determination of sub-optimal politics in a sequential graph is then developed. Finally, the applications of sub-optimality concept is shown when taking into account the indirect effects related to possible strategies, or in the case of stochastic choices and of problems of the siting of plants... application examples are given. (authors) [fr
International Nuclear Information System (INIS)
Hu Erbang; Gao Zhanrong; Zhang Heyuan; Wei Weiqiang
1996-12-01
A dynamic food-chain model and program, DYFOM-95, for predicting the radiological consequences of nuclear accident has been developed, which is not only suitable to the West food-chain but also to Chinese food chain. The following processes, caused by accident release which will make an impact on radionuclide concentration in the edible parts of vegetable are considered: dry and wet deposition interception and initial retention, translocation, percolation, root uptake and tillage. Activity intake rate of animals, effects of processing and activity intake of human through ingestion pathway are also considered in calculations. The effects of leaf area index LAI of vegetable are considered in dry deposition model. A method for calculating the contribution of rain with different period and different intensity to total wet deposition is established. The program contains 1 main code and 5 sub-codes to calculate dry and wet deposition on surface of vegetable and soil, translocation of nuclides in vegetable, nuclide concentration in the edible parts of vegetable and in animal products and activity intake of human and so on. (24 refs., 9 figs., 11 tabs.)
Ibarra, Ignacio L; Melo, Francisco
2010-07-01
Dynamic programming (DP) is a general optimization strategy that is successfully used across various disciplines of science. In bioinformatics, it is widely applied in calculating the optimal alignment between pairs of protein or DNA sequences. These alignments form the basis of new, verifiable biological hypothesis. Despite its importance, there are no interactive tools available for training and education on understanding the DP algorithm. Here, we introduce an interactive computer application with a graphical interface, for the purpose of educating students about DP. The program displays the DP scoring matrix and the resulting optimal alignment(s), while allowing the user to modify key parameters such as the values in the similarity matrix, the sequence alignment algorithm version and the gap opening/extension penalties. We hope that this software will be useful to teachers and students of bioinformatics courses, as well as researchers who implement the DP algorithm for diverse applications. The software is freely available at: http:/melolab.org/sat. The software is written in the Java computer language, thus it runs on all major platforms and operating systems including Windows, Mac OS X and LINUX. All inquiries or comments about this software should be directed to Francisco Melo at fmelo@bio.puc.cl.
DSNP, Program and Data Library System for Dynamic Simulation of Nuclear Power Plant
International Nuclear Information System (INIS)
Saphier, D.; Madell, J.; Dean, E.
1988-01-01
1 - Description of problem or function: DSNP (Dynamic Simulator for Nuclear Power-Plants) is a system of programs and data files by which a nuclear power plant, or part thereof, can be simulated. The acronym DSNP is used interchangeably for the DSNP language, the DSNP libraries, the DSNP pre-compiler, and the DSNP document generator. The DSNP language is a special-purpose, block-oriented digital- simulation language developed to facilitate the preparation of dynamic simulations of a large variety of nuclear power plants. It is a user-oriented language that permits the user to prepare simulation programs directly from power plant block diagrams and flow charts by recognizing the symbolic DSNP statements for the appropriate physical components and listing these statements in a logical sequence according to the flow of physical properties in the simulated power plant. Physical components of nuclear power plants are represented by functional blocks, or modules. Many of the more complex components are represented by several modules. The nuclear reactor, for example, has a kinetic module, a power distribution module, a feedback module, a thermodynamic module, a hydraulic module, and a radioactive heat decay module. These modules are stored in DSNP libraries in the form of a DSNP subroutine or function, a block of statements, a macro, or a combination of the above. Basic functional blocks such as integrators, pipes, function generators, connectors, and many auxiliary functions representing properties of materials used in nuclear power plants are also available. The DSNP pre-compiler analyzes the DSNP simulation program, performs the appropriate translations, inserts the requested modules from the library, links these modules together, searches necessary data files, and produces a simulation program in FORTRAN. FORTRAN is considered to be a subset of DSNP and can be inserted anywhere in the simulation program without restriction. I/O statements can be located anywhere in
International Nuclear Information System (INIS)
Ainul Hayati Daud; Khairul Zaman Mohd Dahlan
2002-01-01
Over the last two decades, Malaysia has implemented more than 80 R and D projects valued almost USD 20 millions, under the multilateral, bilateral and regional Technical Cooperation Program (TCP). Attempts were made to examine the dynamics of R and D of the TCP focusing on radiation processing projects using the analytical frameworks such as absorptive capacity, crisis construction, dynamic learning process and technology transfer. This paper describes the contribution of TCP towards the process of technological learning and discusses the process of building technological capability in the dynamic of R and D evolution from imitation to innovation. (Author)
Mogo, César; Brandão, João
2014-06-30
READY (REActive DYnamics) is a program for studying reactive dynamic systems using a global potential energy surface (PES) built from previously existing PESs corresponding to each of the most important elementary reactions present in the system. We present an application to the combustion dynamics of a mixture of hydrogen and oxygen using accurate PESs for all the systems involving up to four oxygen and hydrogen atoms. Results at the temperature of 4000 K and pressure of 2 atm are presented and compared with model based on rate constants. Drawbacks and advantages of this approach are discussed and future directions of research are pointed out. Copyright © 2014 Wiley Periodicals, Inc.
Li, Fu-Hai; Chiu, Yung-Yueh; Lee, Yen-Hui; Chang, Ru-Wei; Yang, Bo-Jun; Sun, Wein-Town; Lee, Eric; Kuo, Chao-Wei; Shirota, Riichiro
2013-04-01
In this study, we precisely investigate the charge distribution in SiN layer by dynamic programming of channel hot hole induced hot electron injection (CHHIHE) in p-channel silicon-oxide-nitride-oxide-silicon (SONOS) memory device. In the dynamic programming scheme, gate voltage is increased as a staircase with fixed step amplitude, which can prohibits the injection of holes in SiN layer. Three-dimensional device simulation is calibrated and is compared with the measured programming characteristics. It is found, for the first time, that the hot electron injection point quickly traverses from drain to source side synchronizing to the expansion of charged area in SiN layer. As a result, the injected charges quickly spread over on the almost whole channel area uniformly during a short programming period, which will afford large tolerance against lateral trapped charge diffusion by baking.
Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.
2011-01-01
This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques
Kouramas, K.I.
2011-08-01
This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.
Fast pairwise structural RNA alignments by pruning of the dynamical programming matrix.
Directory of Open Access Journals (Sweden)
Jakob H Havgaard
2007-10-01
Full Text Available It has become clear that noncoding RNAs (ncRNA play important roles in cells, and emerging studies indicate that there might be a large number of unknown ncRNAs in mammalian genomes. There exist computational methods that can be used to search for ncRNAs by comparing sequences from different genomes. One main problem with these methods is their computational complexity, and heuristics are therefore employed. Two heuristics are currently very popular: pre-folding and pre-aligning. However, these heuristics are not ideal, as pre-aligning is dependent on sequence similarity that may not be present and pre-folding ignores the comparative information. Here, pruning of the dynamical programming matrix is presented as an alternative novel heuristic constraint. All subalignments that do not exceed a length-dependent minimum score are discarded as the matrix is filled out, thus giving the advantage of providing the constraints dynamically. This has been included in a new implementation of the FOLDALIGN algorithm for pairwise local or global structural alignment of RNA sequences. It is shown that time and memory requirements are dramatically lowered while overall performance is maintained. Furthermore, a new divide and conquer method is introduced to limit the memory requirement during global alignment and backtrack of local alignment. All branch points in the computed RNA structure are found and used to divide the structure into smaller unbranched segments. Each segment is then realigned and backtracked in a normal fashion. Finally, the FOLDALIGN algorithm has also been updated with a better memory implementation and an improved energy model. With these improvements in the algorithm, the FOLDALIGN software package provides the molecular biologist with an efficient and user-friendly tool for searching for new ncRNAs. The software package is available for download at http://foldalign.ku.dk.
EDISON-WMW: Exact Dynamic Programing Solution of the Wilcoxon–Mann–Whitney Test
Directory of Open Access Journals (Sweden)
Alexander Marx
2016-02-01
Full Text Available In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon–Mann–Whitney (WMW test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molecular diagnosis. Generally, the solution of the WMW test takes a high combinatorial effort for large sample cohorts containing a significant number of ties. Hence, P value is frequently approximated by a normal distribution. We developed EDISON-WMW, a new approach to calculate the exact permutation of the two-tailed unpaired WMW test without any corrections required and allowing for ties. The method relies on dynamic programing to solve the combinatorial problem of the WMW test efficiently. Beyond a straightforward implementation of the algorithm, we presented different optimization strategies and developed a parallel solution. Using our program, the exact P value for large cohorts containing more than 1000 samples with ties can be calculated within minutes. We demonstrate the performance of this novel approach on randomly-generated data, benchmark it against 13 other commonly-applied approaches and moreover evaluate molecular biomarkers for lung carcinoma and chronic obstructive pulmonary disease (COPD. We found that approximated P values were generally higher than the exact solution provided by EDISON-WMW. Importantly, the algorithm can also be applied to high-throughput omics datasets, where hundreds or thousands of features are included. To provide easy access to the multi-threaded version of EDISON-WMW, a web-based solution of our algorithm is freely available at http://www.ccb.uni-saarland.de/software/wtest/.
International Nuclear Information System (INIS)
Timp, Sheila; Karssemeijer, Nico
2004-01-01
Mass segmentation plays a crucial role in computer-aided diagnosis (CAD) systems for classification of suspicious regions as normal, benign, or malignant. In this article we present a robust and automated segmentation technique--based on dynamic programming--to segment mass lesions from surrounding tissue. In addition, we propose an efficient algorithm to guarantee resulting contours to be closed. The segmentation method based on dynamic programming was quantitatively compared with two other automated segmentation methods (region growing and the discrete contour model) on a dataset of 1210 masses. For each mass an overlap criterion was calculated to determine the similarity with manual segmentation. The mean overlap percentage for dynamic programming was 0.69, for the other two methods 0.60 and 0.59, respectively. The difference in overlap percentage was statistically significant. To study the influence of the segmentation method on the performance of a CAD system two additional experiments were carried out. The first experiment studied the detection performance of the CAD system for the different segmentation methods. Free-response receiver operating characteristics analysis showed that the detection performance was nearly identical for the three segmentation methods. In the second experiment the ability of the classifier to discriminate between malignant and benign lesions was studied. For region based evaluation the area A z under the receiver operating characteristics curve was 0.74 for dynamic programming, 0.72 for the discrete contour model, and 0.67 for region growing. The difference in A z values obtained by the dynamic programming method and region growing was statistically significant. The differences between other methods were not significant
Energy Technology Data Exchange (ETDEWEB)
Dall' Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.
2015-07-01
This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of pertinent network-wide optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual e-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference signals. Global convergence is guaranteed for diminishing stepsize rules, even when the reference inputs are updated at a faster rate than the dynamical-system settling time. The application of the proposed framework to the control of power-electronic inverters in AC distribution systems is discussed. The objective is to bridge the time-scale separation between real-time inverter control and network-wide optimization. Optimization objectives assume the form of SDP relaxations of prototypical AC optimal power flow problems.
A Dynamic Programming Model for Internal Attack Detection in Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Qiong Shi
2017-01-01
Full Text Available Internal attack is a crucial security problem of WSN (wireless sensor network. In this paper, we focus on the internal attack detection which is an important way to locate attacks. We propose a state transition model, based on the continuous time Markov chain (CTMC, to study the behaviors of the sensors in a WSN under internal attack. Then we conduct the internal attack detection model as the epidemiological model. In this model, we explore the detection rate as the rate of a compromised state transition to a response state. By using the Bellman equation, the utility for the state transitions of a sensor can be written in standard forms of dynamic programming. It reveals a natural way to find the optimal detection rate that is by maximizing the total utility of the compromised state of the node (the sum of current utility and future utility. In particular, we encapsulate the current state, survivability, availability, and energy consumption of the WSN into an information set. We conduct extensive experiments and the results show the effectiveness of our solutions.
Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.
Verschuuren, Marlies; De Vylder, Jonas; Catrysse, Hannes; Robijns, Joke; Philips, Wilfried; De Vos, Winnok H
2017-01-01
A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.
Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems
Directory of Open Access Journals (Sweden)
Yunfei Guo
2012-04-01
Full Text Available In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD called penalty DP-TBD (PDP-TBD is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.
Directory of Open Access Journals (Sweden)
Fakhruddin Wirakusuma
2017-01-01
Full Text Available Kebutuhan daya listrik saat ini meningkat pesat seiring dengan perkembangan teknologi. Peningkatan kebutuhan daya listrik ini bertolak belakang dengan menipisnya ketersediaan sumber energy minyak dan batu bara. Permasalahan ini berdampak pada ketahanan listrik nasional. Untuk memenuhi kebutuhan daya listrik yang besar dengan cakupan wilayah yang luas diperlukan pembangkit tersebar berskala kecil. Pembangkit tersebar ini diupayakan bersumber pada energi terbarukan untuk meminimalkan pemakaian dari sumber energy minyak dan batu bara lalu dihubungkan ke Micro Grid serta digunakan baterai sebagai power balance. Oleh karena banyaknya pembangkit tersebar dan penggunaan baterai maka penting untuk menentukan besarnya pembangkitan daya listrik yang optimal dari masing-masing pembangkit serta penggunaan baterai berdasarkan kapasitas yang optimal sehingga kebutuhan daya listrik dapat dipenuhi dengan biaya yang minimal tiap waktunya. Optimisasi ini dikenal dengan istilah Dynamic Economic Dispatch. Optimisasi ini sudah banyak dilakukan dilakukan dengan berbagai macam metode Artificial Intelligence. Pada penelitian ini, metode Artificial Intellegence yang diaplikasikan yakni Quadratic Programming. Metode ini diterapkan pada software MATLAB. Dengan metode tersebut, diketahui bahwa penggunaan baterai mampu mengurangi total biaya pembangkitan.
Chun, Tae Yoon; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho
2018-06-01
In this paper, we propose two multirate generalised policy iteration (GPI) algorithms applied to discrete-time linear quadratic regulation problems. The proposed algorithms are extensions of the existing GPI algorithm that consists of the approximate policy evaluation and policy improvement steps. The two proposed schemes, named heuristic dynamic programming (HDP) and dual HDP (DHP), based on multirate GPI, use multi-step estimation (M-step Bellman equation) at the approximate policy evaluation step for estimating the value function and its gradient called costate, respectively. Then, we show that these two methods with the same update horizon can be considered equivalent in the iteration domain. Furthermore, monotonically increasing and decreasing convergences, so called value iteration (VI)-mode and policy iteration (PI)-mode convergences, are proved to hold for the proposed multirate GPIs. Further, general convergence properties in terms of eigenvalues are also studied. The data-driven online implementation methods for the proposed HDP and DHP are demonstrated and finally, we present the results of numerical simulations performed to verify the effectiveness of the proposed methods.
Implementation of a Small Type DC Microgrid Based on Fuzzy Control and Dynamic Programming
Directory of Open Access Journals (Sweden)
Chin-Hsing Cheng
2016-09-01
Full Text Available A DC microgrid (DC-MG is a novel power system that uses DC distribution in order to provide high quality power. The study system is made by a photovoltaic array (PV, a wind generator (WG, a fuel cell (FC, and an energy storage system (ESS to establish a small type DC microgrid, with the bus being established by DC/DC converters with fuzzy controllers. An overall power dispatch was designed for the proposed system to distribute the power flows among the different energy sources and the storage unit in the system in order to satisfy the load requirements throughout an entire 24-h period. The structure of a power supervisor based on an optimal power dispatch algorithm is here proposed. Optimization was performed using dynamic programming (DP. In this paper, a system configuration of a DC microgrid is analyzed in different scenarios to show the efficacy of the control for all devices for the variable weather conditions with different DC loads. Thus, the voltage level and the power flow of the system are shown for different load conditions.
Accurate Detection of Dysmorphic Nuclei Using Dynamic Programming and Supervised Classification.
Directory of Open Access Journals (Sweden)
Marlies Verschuuren
Full Text Available A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND, which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows.
Brodin, Anders; Nilsson, Jan-Åke; Nord, Andreas
2017-09-01
Several species of small birds are resident in boreal forests where environmental temperatures can be -20 to -30 °C, or even lower, in winter. As winter days are short, and food is scarce, winter survival is a challenge for small endothermic animals. A bird of this size will have to gain almost 10% of its lean body mass in fat every day to sustain overnight metabolism. Birds such as parids (titmice and chickadees) can use facultative hypothermia, a process in which body temperature is actively down-regulated to a specific level, to reduce heat loss and thus save energy. During cold winter nights, these birds may decrease body temperature from the normal from 42 ° down to 35 °C, or even lower in some species. However, birds are unable to move in this deep hypothermic state, making it a risky strategy if predators are around. Why, then, do small northern birds enter a potentially dangerous physiological state for a relatively small reduction in energy expenditure? We used stochastic dynamic programming to investigate this. Our model suggests that the use of nocturnal hypothermia at night is paramount in these biomes, as it would increase winter survival for a small northern bird by 58% over a winter of 100 days. Our model also explains the phenomenon known as winter fattening, and its relationship to thermoregulation, in northern birds.
Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.
Wei, Qinglai; Liu, Derong; Lin, Hanquan
2016-03-01
In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.
Kremen, Arie; Tsompanakis, Yiannis
2010-04-01
The slope-stability of a proposed vertical extension of a balefill was investigated in the present study, in an attempt to determine a geotechnically conservative design, compliant with New Jersey Department of Environmental Protection regulations, to maximize the utilization of unclaimed disposal capacity. Conventional geotechnical analytical methods are generally limited to well-defined failure modes, which may not occur in landfills or balefills due to the presence of preferential slip surfaces. In addition, these models assume an a priori stress distribution to solve essentially indeterminate problems. In this work, a different approach has been applied, which avoids several of the drawbacks of conventional methods. Specifically, the analysis was performed in a two-stage process: (a) calculation of stress distribution, and (b) application of an optimization technique to identify the most probable failure surface. The stress analysis was performed using a finite element formulation and the location of the failure surface was located by dynamic programming optimization method. A sensitivity analysis was performed to evaluate the effect of the various waste strength parameters of the underlying mathematical model on the results, namely the factor of safety of the landfill. Although this study focuses on the stability investigation of an expanded balefill, the methodology presented can easily be applied to general geotechnical investigations.
Directory of Open Access Journals (Sweden)
Lihe Xi
2017-11-01
Full Text Available The extended range electric vehicle (EREV can store much clean energy from the electric grid when it arrives at the charging station with lower battery energy. Consuming minimum gasoline during the trip is a common goal for most energy management controllers. To achieve these objectives, an intelligent energy management controller for EREV based on dynamic programming and neural networks (IEMC_NN is proposed. The power demand split ratio between the extender and battery are optimized by DP, and the control objectives are presented as a cost function. The online controller is trained by neural networks. Three trained controllers, constructing the controller library in IEMC_NN, are obtained from training three typical lengths of the driving cycle. To determine an appropriate NN controller for different driving distance purposes, the selection module in IEMC_NN is developed based on the remaining battery energy and the driving distance to the charging station. Three simulation conditions are adopted to validate the performance of IEMC_NN. They are target driving distance information, known and unknown, changing the destination during the trip. Simulation results using these simulation conditions show that the IEMC_NN had better fuel economy than the charging deplete/charging sustain (CD/CS algorithm. More significantly, with known driving distance information, the battery SOC controlled by IEMC_NN can just reach the lower bound as the EREV arrives at the charging station, which was also feasible when the driver changed the destination during the trip.
Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining
Hussain, Shahid
2016-01-01
This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.
Comparison between dynamic programming and genetic algorithm for hydro unit economic load dispatch
Directory of Open Access Journals (Sweden)
Bin Xu
2014-10-01
Full Text Available The hydro unit economic load dispatch (ELD is of great importance in energy conservation and emission reduction. Dynamic programming (DP and genetic algorithm (GA are two representative algorithms for solving ELD problems. The goal of this study was to examine the performance of DP and GA while they were applied to ELD. We established numerical experiments to conduct performance comparisons between DP and GA with two given schemes. The schemes included comparing the CPU time of the algorithms when they had the same solution quality, and comparing the solution quality when they had the same CPU time. The numerical experiments were applied to the Three Gorges Reservoir in China, which is equipped with 26 hydro generation units. We found the relation between the performance of algorithms and the number of units through experiments. Results show that GA is adept at searching for optimal solutions in low-dimensional cases. In some cases, such as with a number of units of less than 10, GA's performance is superior to that of a coarse-grid DP. However, GA loses its superiority in high-dimensional cases. DP is powerful in obtaining stable and high-quality solutions. Its performance can be maintained even while searching over a large solution space. Nevertheless, due to its exhaustive enumerating nature, it costs excess time in low-dimensional cases.
GrDHP: a general utility function representation for dual heuristic dynamic programming.
Ni, Zhen; He, Haibo; Zhao, Dongbin; Xu, Xin; Prokhorov, Danil V
2015-03-01
A general utility function representation is proposed to provide the required derivable and adjustable utility function for the dual heuristic dynamic programming (DHP) design. Goal representation DHP (GrDHP) is presented with a goal network being on top of the traditional DHP design. This goal network provides a general mapping between the system states and the derivatives of the utility function. With this proposed architecture, we can obtain the required derivatives of the utility function directly from the goal network. In addition, instead of a fixed predefined utility function in literature, we conduct an online learning process for the goal network so that the derivatives of the utility function can be adaptively tuned over time. We provide the control performance of both the proposed GrDHP and the traditional DHP approaches under the same environment and parameter settings. The statistical simulation results and the snapshot of the system variables are presented to demonstrate the improved learning and controlling performance. We also apply both approaches to a power system example to further demonstrate the control capabilities of the GrDHP approach.
International Nuclear Information System (INIS)
Xu, Yancai; Liu, Derong; Wei, Qinglai
2015-01-01
Highlights: • The algorithm is developed in the two-household energy management environment. • We develop the absent energy penalty cost for the first time. • The algorithm has ability to keep adapting in real-time operations. • Its application can lower total costs and achieve better load balancing. - Abstract: Residential energy scheduling is a hot topic nowadays in the background of energy saving and environmental protection worldwide. To achieve this objective, a new residential energy scheduling algorithm is developed for energy management, based on action dependent heuristic dynamic programming. The algorithm works under the circumstance of residential real-time pricing and two adjacent housing units with energy inter-exchange, which can reduce the overall cost and enhance renewable energy efficiency after long-term operation. It is designed to obtain the optimal control policy to manage the directions and amounts of electricity energy flux. The algorithm’s architecture is mainly constructed based on neural networks, denoting the learned characteristics in the linkage of layers. To get close to real situations, many constraints such as maximum charging/discharging power of batteries are taken into account. The absent energy penalty cost is developed for the first time as a part of the performance index function. When the environment changes, the residential energy scheduling algorithm gains new features and keeps adapting in real-time operations. Simulation results show that the developed algorithm is beneficial to energy conversation
Playa Soil Moisture and Evaporation Dynamics During the MATERHORN Field Program
Hang, Chaoxun; Nadeau, Daniel F.; Jensen, Derek D.; Hoch, Sebastian W.; Pardyjak, Eric R.
2016-06-01
We present an analysis of field data collected over a desert playa in western Utah, USA in May 2013, the most synoptically active month of the year, as part of the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program. The results show that decreasing surface albedo, decreasing Bowen ratio and increasing net radiation with increasing soil moisture sustained a powerful positive feedback mechanism promoting large evaporation rates immediately following rain events. Additionally, it was found that, while nocturnal evaporation was negligible during dry periods, it was quite significant (up to 30 % of the daily cumulative flux) during nights following rain events. Our results further show that the highest spatial variability in surface soil moisture is found under dry conditions. Finally, we report strong spatial heterogeneities in evaporation rates following a rain event. The cumulative evaporation for the different sampling sites over a five-day period varied from ≈ 0.1 to ≈ 6.6 mm. Overall, this study allows us to better understand the mechanisms underlying soil moisture dynamics of desert playas as well as evaporation following occasional rain events.
Integer 1/0 Knapsack Problem Dynamic Programming Approach in Building Maintenance Optimization
Directory of Open Access Journals (Sweden)
Viska Dewi Fawzy
2017-12-01
Full Text Available The most common problem in urban areas is the high public demand and the limited provision of housing. In meeting the needs of affordable housing for low income communities, the Government of Indonesia implements Rusunawa Project. Object of this research is Pandanarang Rusunawa. Rusunawa Pandanarang is one of the vertical housing in Cilacap that is facing deterioration issue and needs good maintenance management. This study aims at insetting priority and optimizing maintenance plan due to limited funds (limited budget and the amount of damage that must be repaired.This study uses one of the optimization methods of Dynamic Programing on the application of Integer 1/0 Knapsack Problem, to determine an schedule the maintenance activities. The Criteria that are used such as: the level of building components damage and the level of occupants participation. In the first criterion, the benefit (p is the percentage of damage that is fixed with the cost (w. While on the second criterion, the benefit (p is the percentage of occupant participation rate on the maintenance activities with the cost (w. For the budget of Rp 125.000.000, 00, it was obtained from the simulation that the value of the optimum solution on the first criterion at the 7th stage of 71.88% with total cost Rp 106.000.000, 00. At the second criterion, the value of the optimum solution at the 7th stage of 89.29% with total cost Rp 124.000.000, 00.
A Dynamic Programming Approach for Base Station Sleeping in Cellular Networks
Gong, Jie; Zhou, Sheng; Niu, Zhisheng
The energy consumption of the information and communication technology (ICT) industry, which has become a serious problem, is mostly due to the network infrastructure rather than the mobile terminals. In this paper, we focus on reducing the energy consumption of base stations (BSs) by adjusting their working modes (active or sleep). Specifically, the objective is to minimize the energy consumption while satisfying quality of service (QoS, e.g., blocking probability) requirement and, at the same time, avoiding frequent mode switching to reduce signaling and delay overhead. The problem is modeled as a dynamic programming (DP) problem, which is NP-hard in general. Based on cooperation among neighboring BSs, a low-complexity algorithm is proposed to reduce the size of state space as well as that of action space. Simulations demonstrate that, with the proposed algorithm, the active BS pattern well meets the time variation and the non-uniform spatial distribution of system traffic. Moreover, the tradeoff between the energy saving from BS sleeping and the cost of switching is well balanced by the proposed scheme.
Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games.
Wei, Qinglai; Liu, Derong; Lin, Qiao; Song, Ruizhuo
2018-04-01
In this paper, a novel adaptive dynamic programming (ADP) algorithm, called "iterative zero-sum ADP algorithm," is developed to solve infinite-horizon discrete-time two-player zero-sum games of nonlinear systems. The present iterative zero-sum ADP algorithm permits arbitrary positive semidefinite functions to initialize the upper and lower iterations. A novel convergence analysis is developed to guarantee the upper and lower iterative value functions to converge to the upper and lower optimums, respectively. When the saddle-point equilibrium exists, it is emphasized that both the upper and lower iterative value functions are proved to converge to the optimal solution of the zero-sum game, where the existence criteria of the saddle-point equilibrium are not required. If the saddle-point equilibrium does not exist, the upper and lower optimal performance index functions are obtained, respectively, where the upper and lower performance index functions are proved to be not equivalent. Finally, simulation results and comparisons are shown to illustrate the performance of the present method.
International Nuclear Information System (INIS)
Zhang Xiaobing; Fan Ying; Wei Yiming
2009-01-01
China's Strategic Petroleum Reserve (SPR) is currently being prepared. But how large the optimal stockpile size for China should be, what the best acquisition strategies are, how to release the reserve if a disruption occurs, and other related issues still need to be studied in detail. In this paper, we develop a stochastic dynamic programming model based on a total potential cost function of establishing SPRs to evaluate the optimal SPR policy for China. Using this model, empirical results are presented for the optimal size of China's SPR and the best acquisition and drawdown strategies for a few specific cases. The results show that with comprehensive consideration, the optimal SPR size for China is around 320 million barrels. This size is equivalent to about 90 days of net oil import amount in 2006 and should be reached in the year 2017, three years earlier than the national goal, which implies that the need for China to fill the SPR is probably more pressing; the best stockpile release action in a disruption is related to the disruption levels and expected continuation probabilities. The information provided by the results will be useful for decision makers.
Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining
Hussain, Shahid
2016-07-10
This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.
Directory of Open Access Journals (Sweden)
Viral H. Borisagar
2014-01-01
Full Text Available A novel hierarchical stereo matching algorithm is presented which gives disparity map as output from illumination variant stereo pair. Illumination difference between two stereo images can lead to undesirable output. Stereo image pair often experience illumination variations due to many factors like real and practical situation, spatially and temporally separated camera positions, environmental illumination fluctuation, and the change in the strength or position of the light sources. Window matching and dynamic programming techniques are employed for disparity map estimation. Good quality disparity map is obtained with the optimized path. Homomorphic filtering is used as a preprocessing step to lessen illumination variation between the stereo images. Anisotropic diffusion is used to refine disparity map to give high quality disparity map as a final output. The robust performance of the proposed approach is suitable for real life circumstances where there will be always illumination variation between the images. The matching is carried out in a sequence of images representing the same scene, however in different resolutions. The hierarchical approach adopted decreases the computation time of the stereo matching problem. This algorithm can be helpful in applications like robot navigation, extraction of information from aerial surveys, 3D scene reconstruction, and military and security applications. Similarity measure SAD is often sensitive to illumination variation. It produces unacceptable disparity map results for illumination variant left and right images. Experimental results show that our proposed algorithm produces quality disparity maps for both wide range of illumination variant and invariant stereo image pair.
Directory of Open Access Journals (Sweden)
Nisha
2015-03-01
Full Text Available BACKGROUND: Balance is highly integrative dynamic process involving coordination of multiple neurological pathways that allows for the maintenance of the COG over BOS . Football players often perform lower extremity passing , shooting , twisting , cutting and dribbling skills while wearing shoes , these actions require body to be in the equilibrium position to perform the task . This leads to t he conclusion of the great importance of the ability of balance in football . AIMS: 1 . To study the effect of 4 week multidirectional balance board training on dynamic balance in football players . 2 . To study the effect of 4 week Both Sides Up ball training on dynamic balance in football players . 3 . To compare the effect of multidirectional balance board training program and BOSU ball training program on dynamic balance in football players . STUDY DESIGN: Randomized Clinical trial . METHODS: Total of 60 competitive badminton players with age group between18 - 25 were recruited in this study . The participants were allocated into 2 groups viz ., Group A (multidirectional balance board training and Group B (BOSU ball Training for a period of 4 we eks . Participants were test for SEBT and vertical jump test on first day and after 4 weeks of balance training . STATISTICAL ANALYSIS: Student t test , Chi - Square Test . RESULTS: The data analysis and statistical inference showed that , after 4 weeks of balanc e training there was improvement in dynamic balance in both the groups but there was no significant difference in dynamic balance between two groups . As seen by difference in the SEBT and VJT scores pre and post training with p<0 . 001 . CONCLUSION: 4 weeks balance training using BOSU and multidirectional balance board is effective in improving dynamic balance and vertical jump performance in football players and also can be used as a component of multifaceted training to improve dynamic balance and game skills
Directory of Open Access Journals (Sweden)
Riza Fahmi Andriyanto
2017-01-01
Full Text Available Kebutuhan akan energi listrik terus menigkat seiring dengan perkembangan teknologi. meningkatnya beban listrik ini harus diimbangi dengan penambahan daya yang dibangkitkan. Hal ini sangat berpengaruh pada penjadwalan unit pembangkit yang harus ditentukan dengan baik agar didapatkan pembangkitan yang optimal. Pada Tugas Akhir ini mengambil topik mengenai unit commitment dan economic dispatch dengan mempertimbangkan nilai dari batasan generator (ramp-rate. Metode yang digunakan adalah complete enumeration dengan forward dynamic programming pada unit commitment dan quadratic programming pada economic dispatch. Metode - metode tersebut diterapkan dalam pemrograman matlab sehingga dapat dijadikan suatu program perhitungan unit commitment dan economic dispatch dengan mempertimbangkan nilai batasan ramp-rate. Dengan metode tersebut, diharapkan permasalahan penjadwalan unit pembangkit dapat terselesaikan dengan baik dan optimal sehingga memperoleh total biaya pembangkitan yang ekonomis.
Energy Technology Data Exchange (ETDEWEB)
Sabah, Fayroz A., E-mail: fayroz-arif@yahoo.com [Institue of Nano-Optoelectronics Research and Technology (INOR), School of Physics, Universiti Sains Malaysia, 11800 Penang (Malaysia); Department of Electrical Engineering, College of Engineering, Al-Mustansiriya University, Baghdad (Iraq); Ahmed, Naser M., E-mail: naser@usm.my; Hassan, Z., E-mail: zai@usm.my; Azzez, Shrook A. [Institue of Nano-Optoelectronics Research and Technology (INOR), School of Physics, Universiti Sains Malaysia, 11800 Penang (Malaysia); Rasheed, Hiba S., E-mail: hibasaad1980@yahoo.com [Institue of Nano-Optoelectronics Research and Technology (INOR), School of Physics, Universiti Sains Malaysia, 11800 Penang (Malaysia); Department of Physics, College of Education, Al-Mustansiriya University, Baghdad (Iraq); Al-Hazim, Nabeel Z., E-mail: nabeelnano333@gmail.com [Institue of Nano-Optoelectronics Research and Technology (INOR), School of Physics, Universiti Sains Malaysia, 11800 Penang (Malaysia); Ministry of Education, the General Directorate for Educational Anbar (Iraq)
2016-07-06
The copper sulphide (CuS) thin films were grown with good adhesion by spray pyrolysis deposition (SPD) on Ti, ITO and glass substrates at 200 °C. The distance between nozzle and substrate is 30 cm. The composition was prepared by mixing copper chloride CuCl{sub 2}.2H{sub 2}O as a source of Cu{sup 2+} and sodium thiosulfate Na{sub 2}S{sub 2}O{sub 3}.5H{sub 2}O as a source of and S{sup 2−}. Two concentrations (0.2 and 0.4 M) were used for each CuCl{sub 2} and Na{sub 2}S{sub 2}O{sub 3} to be prepared and then sprayed (20 ml). The process was started by spraying the solution for 3 seconds and after 10 seconds the cycle was repeated until the solution was sprayed completely on the hot substrates. The structural characteristics were studied using X-ray diffraction; they showed covellite CuS hexagonal crystal structure for 0.2 M concentration, and covellite CuS hexagonal crystal structure with two small peaks of chalcocite Cu{sub 2}S hexagonal crystal structure for 0.4 M concentration. Also the surface and electrical characteristics were investigated using Field Emission Scanning Electron Microscopy (FESEM) and current source device, respectively. The surface study for the CuS thin films showed nanorods to be established for 0.2 M concentration and mix of nanorods and nanoplates for 0.4 M concentration. The electrical study showed ohmic behavior and low resistivity for these films. Hall Effect was measured for these thin films, it showed that all samples of CuS are p- type thin films and ensured that the resistivity for thin films of 0.2 M concentration was lower than that of 0.4 M concentration; and for the two concentrations CuS thin film deposited on ITO had the lowest resistivity. This leads to the result that the conductivity was high for CuS thin film deposited on ITO substrate, and the conductivity of the three thin films of 0.2 M concentration was higher than that of 0.4 M concentration.
International Nuclear Information System (INIS)
Cheng Chuntian; Liao Shengli; Tang Zitian; Zhao Mingyan
2009-01-01
Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations.
A dynamic programming model for optimising feeding and slaughter decisions regarding fattening pigs
Directory of Open Access Journals (Sweden)
J. K. NIEMI
2008-12-01
Full Text Available Costs of purchasing new piglets and of feeding them until slaughter are the main variable expenditures in pig fattening. They both depend on slaughter intensity, the nature of feeding patterns and the technological constraints of pig fattening, such as genotype. Therefore, it is of interest to examine the effect of production technology and changes in input and output prices on feeding and slaughter decisions. This study examines the problem by using a dynamic programming model that links genetic characteristics of a pig to feeding decisions and the timing of slaughter and takes into account how these jointly affect the quality-adjusted value of a carcass. The state of nature and the genotype of a pig are known in the analysis. The results suggest that producer can benefit from improvements in the pigs genotype. Animals of improved genotype can reach optimal slaughter maturity quicker and produce leaner meat than animals of poor genotype. In order to fully utilise the benefits of animal breeding, the producer must adjust feeding and slaughter patterns on the basis of genotype. The results also suggest that the producer can benefit from flexible feeding technology. Typically, such a technology provides incentives to feed piglets with protein-rich feed. When the pig approaches slaughter maturity, the share of protein-rich feed in the diet gradually decreases and the amount of energy-rich feed increases. Generally, the optimal slaughter weight is within the weight range that pays the highest price per kilogram of pig meat. The optimal feeding pattern and the optimal timing of slaughter depend on price ratios. Particularly, an increase in the price of pig meat provides incentives to increase the growth rates up to the pigs biological maximum by increasing the amount of energy in the feed. Price changes and changes in slaughter premium can also have large income effects.;
Directory of Open Access Journals (Sweden)
Mariana Marselina
2016-08-01
Full Text Available The increasingly growth of population and industry sector have lead to an enhanced demand for electrical energy. One of the electricity providers in the area of Java-Madura Bali (Jamali is Saguling Reservoir. Saguling Reservoir is one of the three reservoirs that stem the flow of Citarum River in advance of to Jatiluhur and Cirata Reservoir. The average electricity production of Saguling Reservoir was 2,334,318.138 MWh/year in the period of 1986-2014. The water intake of Saguling Reservoir is the upstream Citarum Watershed with an area of 2340.88 km2 which also serves as the irrigation, inland fisheries, recreation, and other activities. An effort to improve the function of Saguling Reservoir in producing electrical energy is by optimizing the reservoir management. The optimization of Saguling Reservoir management in this study refers to Government Regulation No. 37/2010 on Dam/Reservoir Article 44 which states that the system of reservoir management consisting of the operation system in dry years, normal years, and wet years. In this research, the determination of the trajectory guideline in Saguling operation was divided in dry, normal and wet years. Trajectory guideline was conducted based on the electricity price of turbine inflow that various in every month. The determination of the trajectory guideline in various electricity price was done by using Program Dynamic Bellman (PD Bellman and “Du Couloir” iterative method which the objective to optimize the gain from electricity production. and “Du Couloir” iterative method was development of PD Bellman that can calculate the value of gain with a smaller discretization until 0,1 juta m3 effectively where PD Bellman just calculate until 10 million m3. Smaller discretization can give maximum benefit from electricity production and the trajectory guideline will be closer to trajectory actual so optimization of Saguling operation will be achieved.
Studying Operation Rules of Cascade Reservoirs Based on Multi-Dimensional Dynamics Programming
Directory of Open Access Journals (Sweden)
Zhiqiang Jiang
2017-12-01
Full Text Available Although many optimization models and methods are applied to the optimization of reservoir operation at present, the optimal operation decision that is made through these models and methods is just a retrospective review. Due to the limitation of hydrological prediction accuracy, it is practical and feasible to obtain the suboptimal or satisfactory solution by the established operation rules in the actual reservoir operation, especially for the mid- and long-term operation. In order to obtain the optimized sample data with global optimality; and make the extracted operation rules more reasonable and reliable, this paper presents the multi-dimensional dynamic programming model of the optimal joint operation of cascade reservoirs and provides the corresponding recursive equation and the specific solving steps. Taking Li Xianjiang cascade reservoirs as a case study, seven uncertain problems in the whole operation period of the cascade reservoirs are summarized after a detailed analysis to the obtained optimal sample data, and two sub-models are put forward to solve these uncertain problems. Finally, by dividing the whole operation period into four characteristic sections, this paper extracts the operation rules of each reservoir for each section respectively. When compared the simulation results of the extracted operation rules with the conventional joint operation method; the result indicates that the power generation of the obtained rules has a certain degree of improvement both in inspection years and typical years (i.e., wet year; normal year and dry year. So, the rationality and effectiveness of the extracted operation rules are verified by the comparative analysis.
Energy Technology Data Exchange (ETDEWEB)
Cheng Chuntian, E-mail: ctcheng@dlut.edu.c [Department of Civil and Hydraulic Engineering, Dalian University of Technology, 116024 Dalian (China); Liao Shengli; Tang Zitian [Department of Civil and Hydraulic Engineering, Dalian University of Technology, 116024 Dalian (China); Zhao Mingyan [Department of Environmental Science and Engineering, Tsinghua University, 100084 Beijing (China)
2009-12-15
Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations.
Energy Technology Data Exchange (ETDEWEB)
Chun-tian Cheng; Sheng-li Liao; Zi-Tian Tang [Dept. of Civil and Hydraulic Engineering, Dalian Univ. of Technology, 116024 Dalian (China); Ming-yan Zhao [Dept. of Environmental Science and Engineering, Tsinghua Univ., 100084 Beijing (China)
2009-12-15
Dynamic programming (DP) is one of classic and sophisticated optimization methods that have successfully been applied to solve the problem of hydro unit load dispatch (HULD). However, DP will be faced with the curse of dimensionality with the increase of unit number and installed generating capacity of hydropower station. With the appearance of the huge hydropower station similar to the Three George with 26 generators of 700 MW, it is hard to apply the DP to large scale HULD problem. It is crucial to seek for other optimization techniques in order to improve the operation quality and efficiency. Different with the most of literature about power generation scheduling that focused on the comparisons of novel PSO algorithms with other techniques, the paper will pay emphasis on comparison study of PSO with DP based on a case hydropower station. The objective of study is to seek for an effective and feasible method for the large scale of hydropower station of the current and future in China. This paper first compares the performance of PSO and DP using a sample load curve of the Wujiangdu hydropower plant located in the upper stream of the Yangtze River in China and contained five units with the installed capacity of 1250 MW. Next, the effect of different load interval and unit number on the optimal results and efficiency of two methods has also been implemented. The comparison results show that the PSO is feasible for HULD. Furthermore, we simulated the effect of the magnitude of unit number and load capacity on the optimal results and cost time. The simulation comparisons show that PSO has a great advantage over DP in the efficiency and will be one of effective methods for HULD problem of huge hydropower stations. (author)
1991-01-01
A Science Definition Team was established in December 1990 by the Space Physics Division, NASA, to develop a satellite program to conduct research on the energetics, dynamics, and chemistry of the mesosphere and lower thermosphere/ionosphere. This two-volume publication describes the TIMED (Thermosphere-Ionosphere-Mesosphere, Energetics and Dynamics) mission and associated science program. The report outlines the scientific objectives of the mission, the program requirements, and the approach towards meeting these requirements.
International Nuclear Information System (INIS)
Weidenhamer, G.H.
1986-06-01
The equipment qualification program described in this plan is intended to provide the technical basis for resolving uncertainties in existing equipment qualification standards. In addition, research results are contributing to the resolution of safety issues GI-23, GI-87, USI-A44, titled, ''Reactor Coolant Pump Seal Failure,'' ''Failure of HPCI Steam Line Without Isolation,'' and ''Station Blackout,'' respectively. Also, research effort is being directed at providing information on the behavior of containment isolation valves under severe accident environments. Although the results of the latter research will not contribute to resolving uncertainties in qualification standards, it has proven cost effective to obtain this information under this program
International Nuclear Information System (INIS)
Hasegawa, Keita; Komiyama, Ryoichi; Fujii, Yasumasa
2016-01-01
The paper presents an economic rationality analysis of power generation mix by stochastic dynamic programming considering fuel price uncertainties and supply disruption risks such as import disruption and nuclear power plant shutdown risk. The situation revolving around Japan's energy security adopted the past statistics, it cannot be applied to a quantitative analysis of future uncertainties. Further objective and quantitative evaluation methods are required in order to analyze Japan's energy system and make it more resilient in sight of long time scale. In this paper, the authors firstly develop the cost minimization model considering oil and natural gas price respectively by stochastic dynamic programming. Then, the authors show several premises of model and an example of result with related to crude oil stockpile, liquefied natural gas stockpile and nuclear power plant capacity. (author)
Directory of Open Access Journals (Sweden)
Elham Azimzadeh
2013-01-01
Full Text Available Objectives: Falling is a main cause of mortality in elderly. Balance training exercises can help to prevent falls in older adults. According to the principle of specificity of training, the perturbation-based trainings are more similar to the real world. So these training programs can improve balance in elderly. Furthermore, exercising in an aquatic environment can reduce the limitations for balance training rather than a non-aquatic on. The aim of this study is comparing the effectiveness of perturbed and non-perturbed balance training programs in water on static and dynamic balance in aforementioned population group. Methods & Materials: 37 old women (age 80-65, were randomized to the following groups: perturbation-based training (n=12, non-perturbation-based training (n=12 and control (n=13 groups. Static and dynamic balance had been tested before and after the eight weeks of training by the postural stability test of the Biodex balance system using dynamic (level 4 and static platform. The data were analyzed by one sample paired t-test, Independent t-test and ANOVA. Results: There was a significant improvement for all indexes of static and dynamic balance in perturbation-based training (P<0.05. However, in non-perturbed group, all indexes were improved except ML (P<0.05. ANOVA showed that perturbed training was more effective than non-perturbed training on both static and dynamic balances. Conclusion: The findings confirmed the specificity principle of training. Although balance training can improve balance abilities, these kinds of trainings are not such specific for improving balance neuromuscular activities.The perturbation-based trainings can activate postural compensatory responses and reduce falling risk. According to results, we can conclude that hydrotherapy especially with perturbation-based programs will be useful for rehabilitation interventions in elderly .
Energy Technology Data Exchange (ETDEWEB)
Masciola, M.; Jonkman, J.; Robertson, A.
2014-03-01
Techniques to model dynamic mooring lines come in various forms. The most widely used models include either a heuristic representation of the physics (such as a Lumped-Mass, LM, system), a Finite-Element Analysis (FEA) discretization of the lines (discretized in space), or a Finite-Difference (FD) model (which is discretized in both space and time). In this paper, we explore the features of the various models, weigh the advantages of each, and propose a plan for implementing one dynamic mooring line model into the open-source Mooring Analysis Program (MAP). MAP is currently used as a module for the FAST offshore wind turbine computer-aided engineering (CAE) tool to model mooring systems quasi-statically, although dynamic mooring capabilities are desired. Based on the exploration in this manuscript, the lumped-mass representation is selected for implementation in MAP based on its simplicity, computational cost, and ability to provide similar physics captured by higher-order models.
Neeraj Panwar, MPT (Sports); Gaurav Kadyan, MPT (Sports); Aseem Gupta, MPT (Sports); Ravinder Narwal, MPT (Ortho,Cardiopulmonary)
2014-01-01
Aim & Objective: The aim of the study was to determine the effect of wobble board balance training program on static & dynamic balance & on triple hop distance in male collegiate basketball athletes. Methodology: Fifty healthy basketball players within a age group of 18-22 yrs. were randomly selected with a baseline BESS score between 6 to 14 & modified SEBT score equal to or greater than 94 (till 100) and they randomly divided into control (n-25) & training group (n-25).The training grou...
Fetterman, David M.
A study identified causal linkages and basic interrelationships among components of the Career Intern Program (CIP) and observed outcomes. (The CIP is an alternative high school designed to enable disadvantaged and alienated dropouts or potential dropouts to earn regular high school diplomas, to prepare them for meaningful employment or…
Goodman, Lawrence E
2001-01-01
Beginning text presents complete theoretical treatment of mechanical model systems and deals with technological applications. Topics include introduction to calculus of vectors, particle motion, dynamics of particle systems and plane rigid bodies, technical applications in plane motions, theory of mechanical vibrations, and more. Exercises and answers appear in each chapter.
An object-oriented programming paradigm for parallelization of computational fluid dynamics
International Nuclear Information System (INIS)
Ohta, Takashi.
1997-03-01
We propose an object-oriented programming paradigm for parallelization of scientific computing programs, and show that the approach can be a very useful strategy. Generally, parallelization of scientific programs tends to be complicated and unportable due to the specific requirements of each parallel computer or compiler. In this paper, we show that the object-oriented programming design, which separates the parallel processing parts from the solver of the applications, can achieve the large improvement in the maintenance of the codes, as well as the high portability. We design the program for the two-dimensional Euler equations according to the paradigm, and evaluate the parallel performance on IBM SP2. (author)
Frady, Greg; Nesman, Thomas; Zoladz, Thomas; Szabo, Roland
2010-01-01
For many years, the capabilities to determine the root-cause failure of component failures have been limited to the analytical tools and the state of the art data acquisition systems. With this limited capability, many anomalies have been resolved by adding material to the design to increase robustness without the ability to determine if the design solution was satisfactory until after a series of expensive test programs were complete. The risk of failure and multiple design, test, and redesign cycles were high. During the Space Shuttle Program, many crack investigations in high energy density turbomachines, like the SSME turbopumps and high energy flows in the main propulsion system, have led to the discovery of numerous root-cause failures and anomalies due to the coexistences of acoustic forcing functions, structural natural modes, and a high energy excitation, such as an edge tone or shedding flow, leading the technical community to understand many of the primary contributors to extremely high frequency high cycle fatique fluid-structure interaction anomalies. These contributors have been identified using advanced analysis tools and verified using component and system tests during component ground tests, systems tests, and flight. The structural dynamics and fluid dynamics communities have developed a special sensitivity to the fluid-structure interaction problems and have been able to adjust and solve these problems in a time effective manner to meet budget and schedule deadlines of operational vehicle programs, such as the Space Shuttle Program over the years.
Energy Technology Data Exchange (ETDEWEB)
Erez, Mattan
2018-02-21
The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models and runtime systems to meet the challenges of Exascale computing. Our approach is to provide an efficient and scalable programming model that can be adapted to application needs through the use of dynamic runtime features and domain-specific languages for computational kernels. We address the following technical challenges: Programmability: Rich set of programming constructs based on a Hierarchical Partitioned Global Address Space (HPGAS) model, demonstrated in UPC++. Scalability: Hierarchical locality control, lightweight communication (extended GASNet), and ef- ficient synchronization mechanisms (Phasers). Performance Portability: Just-in-time specialization (SEJITS) for generating hardware-specific code and scheduling libraries for domain-specific adaptive runtimes (Habanero). Energy Efficiency: Communication-optimal code generation to optimize energy efficiency by re- ducing data movement. Resilience: Containment Domains for flexible, domain-specific resilience, using state capture mechanisms and lightweight, asynchronous recovery mechanisms. Interoperability: Runtime and language interoperability with MPI and OpenMP to encourage broad adoption.
Using stochastic dynamic programming to support catchment-scale water resources management in China
Davidsen, Claus; Pereira-Cardenal, Silvio Javier; Liu, Suxia; Mo, Xingguo; Rosbjerg, Dan; Bauer-Gottwein, Peter
2013-04-01
A hydro-economic modelling approach is used to optimize reservoir management at river basin level. We demonstrate the potential of this integrated approach on the Ziya River basin, a complex basin on the North China Plain south-east of Beijing. The area is subject to severe water scarcity due to low and extremely seasonal precipitation, and the intense agricultural production is highly dependent on irrigation. Large reservoirs provide water storage for dry months while groundwater and the external South-to-North Water Transfer Project are alternative sources of water. An optimization model based on stochastic dynamic programming has been developed. The objective function is to minimize the total cost of supplying water to the users, while satisfying minimum ecosystem flow constraints. Each user group (agriculture, domestic and industry) is characterized by fixed demands, fixed water allocation costs for the different water sources (surface water, groundwater and external water) and fixed costs of water supply curtailment. The multiple reservoirs in the basin are aggregated into a single reservoir to reduce the dimensions of decisions. Water availability is estimated using a hydrological model. The hydrological model is based on the Budyko framework and is forced with 51 years of observed daily rainfall and temperature data. 23 years of observed discharge from an in-situ station located downstream a remote mountainous catchment is used for model calibration. Runoff serial correlation is described by a Markov chain that is used to generate monthly runoff scenarios to the reservoir. The optimal costs at a given reservoir state and stage were calculated as the minimum sum of immediate and future costs. Based on the total costs for all states and stages, water value tables were generated which contain the marginal value of stored water as a function of the month, the inflow state and the reservoir state. The water value tables are used to guide allocation decisions in
Dynamic programming re-ranking for PPI interactor and pair extraction in full-text articles
2011-01-01
Background Experimentally verified protein-protein interactions (PPIs) cannot be easily retrieved by researchers unless they are stored in PPI databases. The curation of such databases can be facilitated by employing text-mining systems to identify genes which play the interactor role in PPIs and to map these genes to unique database identifiers (interactor normalization task or INT) and then to return a list of interaction pairs for each article (interaction pair task or IPT). These two tasks are evaluated in terms of the area under curve of the interpolated precision/recall (AUC iP/R) score because the order of identifiers in the output list is important for ease of curation. Results Our INT system developed for the BioCreAtIvE II.5 INT challenge achieved a promising AUC iP/R of 43.5% by using a support vector machine (SVM)-based ranking procedure. Using our new re-ranking algorithm, we have been able to improve system performance (AUC iP/R) by 1.84%. Our experimental results also show that with the re-ranked INT results, our unsupervised IPT system can achieve a competitive AUC iP/R of 23.86%, which outperforms the best BC II.5 INT system by 1.64%. Compared to using only SVM ranked INT results, using re-ranked INT results boosts AUC iP/R by 7.84%. Statistical significance t-test results show that our INT/IPT system with re-ranking outperforms that without re-ranking by a statistically significant difference. Conclusions In this paper, we present a new re-ranking algorithm that considers co-occurrence among identifiers in an article to improve INT and IPT ranking results. Combining the re-ranked INT results with an unsupervised approach to find associations among interactors, the proposed method can boost the IPT performance. We also implement score computation using dynamic programming, which is faster and more efficient than traditional approaches. PMID:21342534
Turner, Sean; Galelli, Stefano; Wilcox, Karen
2015-04-01
Water reservoir systems are often affected by recurring large-scale ocean-atmospheric anomalies, known as teleconnections, that cause prolonged periods of climatological drought. Accurate forecasts of these events -- at lead times in the order of weeks and months -- may enable reservoir operators to take more effective release decisions to improve the performance of their systems. In practice this might mean a more reliable water supply system, a more profitable hydropower plant or a more sustainable environmental release policy. To this end, climate indices, which represent the oscillation of the ocean-atmospheric system, might be gainfully employed within reservoir operating models that adapt the reservoir operation as a function of the climate condition. This study develops a Stochastic Dynamic Programming (SDP) approach that can incorporate climate indices using a Hidden Markov Model. The model simulates the climatic regime as a hidden state following a Markov chain, with the state transitions driven by variation in climatic indices, such as the Southern Oscillation Index. Time series analysis of recorded streamflow data reveals the parameters of separate autoregressive models that describe the inflow to the reservoir under three representative climate states ("normal", "wet", "dry"). These models then define inflow transition probabilities for use in a classic SDP approach. The key advantage of the Hidden Markov Model is that it allows conditioning the operating policy not only on the reservoir storage and the antecedent inflow, but also on the climate condition, thus potentially allowing adaptability to a broader range of climate conditions. In practice, the reservoir operator would effect a water release tailored to a specific climate state based on available teleconnection data and forecasts. The approach is demonstrated on the operation of a realistic, stylised water reservoir with carry-over capacity in South-East Australia. Here teleconnections relating
Directory of Open Access Journals (Sweden)
Livia BOBU
2015-09-01
Full Text Available In most of the developing countries, dental caries continues to represent a major issue of public health. In Romania, the National Program for Oral and Dental Diseases Prevention was implemented between 1999-2010, addressed to children attending primary school and consisting of weekly mouth rinses with 0.2% NaF solution. In the present study, the dynamic evolution of oral health status of schoolchildren aged 6-12 years in Iasi, under the impact of this Program, was analyzed. The results showed a decreasing trend in the prevalence and incidence of dental caries, a constant decrease of caries experience indices DMFT and DMFS and, within them, the increasing trend of fillings indicator FS and the decrease of deep lesions weight. The conclusion is that tooth decay has declined in schoolchildren in Iasi during the development of the National Prevention Program.
Wölfer, Ralf; Scheithauer, Herbert
2014-01-01
Bullying is a social phenomenon and although preventive interventions consequently address social mechanisms, evaluations hardly consider the complexity of peer processes. Therefore, the present study analyzes the efficacy of the fairplayer.manual bullying prevention program from a social network perspective. Within a pretest-posttest control group design, longitudinal data were available from 328 middle-school students (MAge = 13.7 years; 51% girls), who provided information on bullying behavior and interaction patterns. The revealed network parameters were utilized to examine the network change (MANCOVA) and the network dynamics (SIENA). Across both forms of analyses, findings revealed the hypothesized intervention-based decrease of bullies' social influence. Hence the present bullying prevention program, as one example of programs that successfully addresses both individual skills and social mechanisms, demonstrates the desired effect of reducing contextual opportunities for the exhibition of bullying behavior. © 2014 Wiley Periodicals, Inc.
Birtas Atesoglu, Elif; Tarkun, Pinar; Demirsoy, Esra Terzi; Geduk, Ayfer; Mehtap, Ozgur; Batman, Adnan; Kaya, Fatih; Cekmen, Mustafa Baki; Gulbas, Zafer; Hacıhanefioglu, Abdullah
2016-04-01
Immune thrombocytopenia (ITP) is an autoimmune disease characterized by dysregulation of T cells. Programmed death (PD) 1 and programmed death 1 ligand 1 (PD-L1) are cosignaling molecules, and the major role of the PD-1 pathway is the inhibition of self-reactive T cells and to protect against autoimmune diseases. We measured levels of serum soluble PD 1 (sPD-1) and serum soluble PD-L1 (sPD-L1) in 67 patients with ITP (24 newly diagnosed ITP [ndITP], 43 chronic ITP [cITP]) and 21 healthy controls (HCs). We determined decreased serum sPD-1 levels both in patients with ndITP and in patients with cITP when compared to HC. Moreover, there was a positive correlation between sPD-1 levels and platelet counts. The sPD-L1 levels were decreased in patients with ndITP when compared to patients with cITP. This is the first study investigating PD-1 signaling pathway in ITP. Decreased sPD-1 levels may have a role in ITP pathogenesis as without the inhibitory regulation of PD-1, sustained activation of T cells may cause inflammatory responses which is the case in ITP. © The Author(s) 2014.
2015-03-26
Appendix C. Computational Example: 3-COP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Appendix D. Storyboard ...COP myopic policy. 105 Appendix D. Storyboard 106 Bibliography 1. Barnes-Schuster, Dawn, & Bassok, Yehuda. 1997. Direct shipping and the dynamic
Modelling the Influence of Awareness Programs by Media on the Drinking Dynamics
Directory of Open Access Journals (Sweden)
Hai-Feng Huo
2014-01-01
Full Text Available We develop a nonlinear mathematical model with the effect of awareness programs on the binge drinking. Due to the fact that awareness programs are capable of inducing behavioral changes in nondrinkers, we introduce a separate class by avoiding contacts with the heavy drinkers. Furthermore we assume that cumulative density of awareness programs increases at a rate proportional to the number of heavy drinkers. We establish some sufficient conditions for the stability of the alcohol free and the alcohol present equilibria and give some numerical simulations to explain our main result. Our results show that awareness programs is an effective measure in reducing alcohol problems.
Skouteris, Dimitris; Gervasi, Osvaldo; Laganà, Antonio
2009-03-01
A program that uses the time-dependent wavepacket method to study the motion of structureless particles in a force field of quasi-cylindrical symmetry is presented here. The program utilises cylindrical polar coordinates to express the wavepacket, which is subsequently propagated using a Chebyshev expansion of the Schrödinger propagator. Time-dependent exit flux as well as energy-dependent S matrix elements can be obtained for all states of the particle (describing its angular momentum component along the nanotube axis and the excitation of the radial degree of freedom in the cylinder). The program has been used to study the motion of an H atom across a carbon nanotube. Program summaryProgram title: CYLWAVE Catalogue identifier: AECL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AECL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 3673 No. of bytes in distributed program, including test data, etc.: 35 237 Distribution format: tar.gz Programming language: Fortran 77 Computer: RISC workstations Operating system: UNIX RAM: 120 MBytes Classification: 16.7, 16.10 External routines: SUNSOFT performance library (not essential) TFFT2D.F (Temperton Fast Fourier Transform), BESSJ.F (from Numerical Recipes, for the calculation of Bessel functions) (included in the distribution file). Nature of problem: Time evolution of the state of a structureless particle in a quasicylindrical potential. Solution method: Time dependent wavepacket propagation. Running time: 50000 secs. The test run supplied with the distribution takes about 10 minutes to complete.
Using System Dynamics as an Evaluation Tool: Experience from a Demonstration Program
Fredericks, Kimberly A.; Deegan, Michael; Carman, Joanne G.
2008-01-01
Evaluators are often faced with many challenges in the design and implementation of a program's evaluation. Because programs are entangled in complex networks of structures and stakeholders, they can be challenging to understand, and they often pose issues of competing and conflicting goals. However, by using a systems mapping approach to…
Cavity contour segmentation in chest radiographs using supervised learning and dynamic programming
Energy Technology Data Exchange (ETDEWEB)
Maduskar, Pragnya, E-mail: pragnya.maduskar@radboudumc.nl; Hogeweg, Laurens; Sánchez, Clara I.; Ginneken, Bram van [Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, 6525 GA (Netherlands); Jong, Pim A. de [Department of Radiology, University Medical Center Utrecht, 3584 CX (Netherlands); Peters-Bax, Liesbeth [Department of Radiology, Radboud University Medical Center, Nijmegen, 6525 GA (Netherlands); Dawson, Rodney [University of Cape Town Lung Institute, Cape Town 7700 (South Africa); Ayles, Helen [Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT (United Kingdom)
2014-07-15
Purpose: Efficacy of tuberculosis (TB) treatment is often monitored using chest radiography. Monitoring size of cavities in pulmonary tuberculosis is important as the size predicts severity of the disease and its persistence under therapy predicts relapse. The authors present a method for automatic cavity segmentation in chest radiographs. Methods: A two stage method is proposed to segment the cavity borders, given a user defined seed point close to the center of the cavity. First, a supervised learning approach is employed to train a pixel classifier using texture and radial features to identify the border pixels of the cavity. A likelihood value of belonging to the cavity border is assigned to each pixel by the classifier. The authors experimented with four different classifiers:k-nearest neighbor (kNN), linear discriminant analysis (LDA), GentleBoost (GB), and random forest (RF). Next, the constructed likelihood map was used as an input cost image in the polar transformed image space for dynamic programming to trace the optimal maximum cost path. This constructed path corresponds to the segmented cavity contour in image space. Results: The method was evaluated on 100 chest radiographs (CXRs) containing 126 cavities. The reference segmentation was manually delineated by an experienced chest radiologist. An independent observer (a chest radiologist) also delineated all cavities to estimate interobserver variability. Jaccard overlap measure Ω was computed between the reference segmentation and the automatic segmentation; and between the reference segmentation and the independent observer's segmentation for all cavities. A median overlap Ω of 0.81 (0.76 ± 0.16), and 0.85 (0.82 ± 0.11) was achieved between the reference segmentation and the automatic segmentation, and between the segmentations by the two radiologists, respectively. The best reported mean contour distance and Hausdorff distance between the reference and the automatic segmentation were
Cavity contour segmentation in chest radiographs using supervised learning and dynamic programming
International Nuclear Information System (INIS)
Maduskar, Pragnya; Hogeweg, Laurens; Sánchez, Clara I.; Ginneken, Bram van; Jong, Pim A. de; Peters-Bax, Liesbeth; Dawson, Rodney; Ayles, Helen
2014-01-01
Purpose: Efficacy of tuberculosis (TB) treatment is often monitored using chest radiography. Monitoring size of cavities in pulmonary tuberculosis is important as the size predicts severity of the disease and its persistence under therapy predicts relapse. The authors present a method for automatic cavity segmentation in chest radiographs. Methods: A two stage method is proposed to segment the cavity borders, given a user defined seed point close to the center of the cavity. First, a supervised learning approach is employed to train a pixel classifier using texture and radial features to identify the border pixels of the cavity. A likelihood value of belonging to the cavity border is assigned to each pixel by the classifier. The authors experimented with four different classifiers:k-nearest neighbor (kNN), linear discriminant analysis (LDA), GentleBoost (GB), and random forest (RF). Next, the constructed likelihood map was used as an input cost image in the polar transformed image space for dynamic programming to trace the optimal maximum cost path. This constructed path corresponds to the segmented cavity contour in image space. Results: The method was evaluated on 100 chest radiographs (CXRs) containing 126 cavities. The reference segmentation was manually delineated by an experienced chest radiologist. An independent observer (a chest radiologist) also delineated all cavities to estimate interobserver variability. Jaccard overlap measure Ω was computed between the reference segmentation and the automatic segmentation; and between the reference segmentation and the independent observer's segmentation for all cavities. A median overlap Ω of 0.81 (0.76 ± 0.16), and 0.85 (0.82 ± 0.11) was achieved between the reference segmentation and the automatic segmentation, and between the segmentations by the two radiologists, respectively. The best reported mean contour distance and Hausdorff distance between the reference and the automatic segmentation were
Directory of Open Access Journals (Sweden)
Huei Peng
2013-04-01
Full Text Available This paper compares two optimal energy management methods for parallel hybrid electric vehicles using an Automatic Manual Transmission (AMT. A control-oriented model of the powertrain and vehicle dynamics is built first. The energy management is formulated as a typical optimal control problem to trade off the fuel consumption and gear shifting frequency under admissible constraints. The Dynamic Programming (DP and Pontryagin’s Minimum Principle (PMP are applied to obtain the optimal solutions. Tuning with the appropriate co-states, the PMP solution is found to be very close to that from DP. The solution for the gear shifting in PMP has an algebraic expression associated with the vehicular velocity and can be implemented more efficiently in the control algorithm. The computation time of PMP is significantly less than DP.
Overview of Dynamics Integration Research (DIR) program at Langley Research Center
Sliwa, Steven M.; Abel, Irving
1989-01-01
Research goals and objectives for an ongoing activity at Langley Research Center (LaRC) are described. The activity is aimed principally at dynamics optimization for aircraft. The effort involves active participation by the Flight Systems, Structures, and Electronics directorates at LaRC. The Functional Integration Technology (FIT) team has been pursuing related goals since 1985. A prime goal has been the integration and optimization of vehicle dynamics through collaboration at the basic principles or equation level. Some significant technical progress has been accomplished since then and is reflected here. An augmentation for this activity, Dynamics Integration Research (DIR), has been proposed to NASA Headquarters and is being considered for funding in FY 1990 or FY 1991.
Amin, Talha
2013-01-01
In the paper, we present a comparison of dynamic programming and greedy approaches for construction and optimization of approximate decision rules relative to the number of misclassifications. We use an uncertainty measure that is a difference between the number of rows in a decision table T and the number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules that localize rows in subtables of T with uncertainty at most γ. Experimental results with decision tables from the UCI Machine Learning Repository are also presented. © 2013 Springer-Verlag.
Robust Adaptive Dynamic Programming of Two-Player Zero-Sum Games for Continuous-Time Linear Systems.
Fu, Yue; Fu, Jun; Chai, Tianyou
2015-12-01
In this brief, an online robust adaptive dynamic programming algorithm is proposed for two-player zero-sum games of continuous-time unknown linear systems with matched uncertainties, which are functions of system outputs and states of a completely unknown exosystem. The online algorithm is developed using the policy iteration (PI) scheme with only one iteration loop. A new analytical method is proposed for convergence proof of the PI scheme. The sufficient conditions are given to guarantee globally asymptotic stability and suboptimal property of the closed-loop system. Simulation studies are conducted to illustrate the effectiveness of the proposed method.
Qiu, J. P.; Niu, D. X.
Micro-grid is one of the key technologies of the future energy supplies. Take economic planning. reliability, and environmental protection of micro grid as a basis for the analysis of multi-strategy objective programming problems for micro grid which contains wind power, solar power, and battery and micro gas turbine. Establish the mathematical model of each power generation characteristics and energy dissipation. and change micro grid planning multi-objective function under different operating strategies to a single objective model based on AHP method. Example analysis shows that in combination with dynamic ant mixed genetic algorithm can get the optimal power output of this model.
International Nuclear Information System (INIS)
Yang, H.T.; Chen, S.L.
1989-01-01
A multi-objective optimization approach to generation expansion planning is presented. The approach is designed by adding a new multi-criteria decision (MCD) procedure to the conventional algorithm which combines dynamic programming with production simulation method. The MCD procedure can help decision makers weight the relative importance of multiple attributes associated with the decision alternatives, and find the near-best compromise solution efficiently at each optimization step of the conventional algorithm. Practical application of proposed approach to feasibility evaluation of the fourth nuclear power plant of Tawian is also presented, demonstrating the effectiveness and limitations of the approach
International Nuclear Information System (INIS)
Balkey, J.J.; Montoya, A.J.; Wieneke, Ronald E.
2002-01-01
The issuance of the Waste Isolation Pilot Plant's (WIPP) Hazardous Waste Facility Permit in August of 2000, specifically the attachment I3 Waste Analysis Plan (WAP),had a profound impact upon transuranic (TRU) waste certification at Los Alamos National Laboratory's (LANL) Plutonium Facility. Program certification was lost until Laboratory internal program documents could be amended to meet the new WAP requirements, waste management personnel could be retrained to incorporate the changes into waste operations and the entire program successfully pass subsequent Carlsbad Field Ofice (CBFO) audit. This action resulted in the suspension of transuranic waste shipments from LANL to WIPP. In addition the changes unnecessarily increased the complexity of TRU waste program activities in waste handling.
Directory of Open Access Journals (Sweden)
Serhii Kalmykov
2017-12-01
Full Text Available Purpose: to study hemodynamic parameters and the reaction of the cardiovascular system to the dosed physical load of patients combined aortic defect with heart failure of the I degree under the influence of the complex physical therapy program developed by us during the rehabilitation process. Material & Methods: the study involved 26 middle-aged men with a diagnosis: combined aortic valve disease, HF I st. Result: dynamics of functional parameters of the cardiovascular system of patients under the influence of the physical therapy program is analyzed. Conclusion: the combination of morning hygienic gymnastics, therapeutic gymnastics, independent activities and dosed walking with a therapeutic massage contributes to the normalization of vascular tone, motor-vascular reflexes and blood pressure, increasing the tolerance of the cardiovascular system to physical activity.
Marshall, Neil; Buteau, Chantal
2014-01-01
As part of their undergraduate mathematics curriculum, students at Brock University learn to create and use computer-based tools with dynamic, visual interfaces, called Exploratory Objects, developed for the purpose of conducting pure or applied mathematical investigations. A student's Development Process Model of creating and using an Exploratory…
Summer Study Program in Geophysical Fluid Dynamics, Woods Hole Oceanographic Institution: Chaos.
1985-11-01
Cleopatra, periodic solutions to Galileo and perhaps chaos to Poincar. Today we often think about dynamical systems in terms o- oincae surfaces of section...P. Berge, 1983. Phys. Rev. Lett. L51, 1446 and 2345. Nadal, J.P., B. Derrida and J. Vannimenus, 1982. J. de Phys. 43, , 1561 and V. Hakim and J.P
Whyte, E F; Richter, C; O'Connor, S; Moran, K A
2018-02-01
Deficits in trunk control predict ACL injuries which frequently occur during high-risk activities such as cutting. However, no existing trunk control/core stability program has been found to positively affect trunk kinematics during cutting activities. This study investigated the effectiveness of a 6-week dynamic core stability program (DCS) on the biomechanics of anticipated and unanticipated side and crossover cutting maneuvers. Thirty-one male, varsity footballers participated in this randomized controlled trial. Three-dimensional trunk and lower limb biomechanics were captured in a motion analysis laboratory during the weight acceptance phase of anticipated and unanticipated side and crossover cutting maneuvers at baseline and 6-week follow-up. The DCS group performed a DCS program three times weekly for 6 weeks in a university rehabilitation room. Both the DCS and control groups concurrently completed their regular practice and match play. Statistical parametric mapping and repeated measures analysis of variance were used to determine any group (DCS vs control) by time (pre vs post) interactions. The DCS resulted in greater internal hip extensor (P=.017, η 2 =0.079), smaller internal knee valgus (P=.026, η 2 =0.076), and smaller internal knee external rotator moments (P=.041, η 2 =0.066) during anticipated side cutting compared with the control group. It also led to reduced posterior ground reaction forces for all cutting activities (P=.015-.030, η 2 =0.074-0.105). A 6-week DCS program did not affect trunk kinematics, but it did reduce a small number of biomechanical risk factors for ACL injury, predominantly during anticipated side cutting. A DCS program could play a role in multimodal ACL injury prevention programs. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
The Computer Program LIAR for Beam Dynamics Calculations in Linear Accelerators
International Nuclear Information System (INIS)
Assmann, R.W.; Adolphsen, C.; Bane, K.; Raubenheimer, T.O.; Siemann, R.H.; Thompson, K.
2011-01-01
Linear accelerators are the central components of the proposed next generation of linear colliders. They need to provide acceleration of up to 750 GeV per beam while maintaining very small normalized emittances. Standard simulation programs, mainly developed for storage rings, do not meet the specific requirements for high energy linear accelerators. We present a new program LIAR ('LInear Accelerator Research code') that includes wakefield effects, a 6D coupled beam description, specific optimization algorithms and other advanced features. Its modular structure allows to use and to extend it easily for different purposes. The program is available for UNIX workstations and Windows PC's. It can be applied to a broad range of accelerators. We present examples of simulations for SLC and NLC.
International Nuclear Information System (INIS)
Li, Chunlong; Zhou, Jianzhong; Ouyang, Shuo; Ding, Xiaoling; Chen, Lu
2014-01-01
Highlights: • Optimization of large-scale hydropower system in the Yangtze River basin. • Improved decomposition–coordination and discrete differential dynamic programming. • Generating initial solution randomly to reduce generation time. • Proposing relative coefficient for more power generation. • Proposing adaptive bias corridor technology to enhance convergence speed. - Abstract: With the construction of major hydro plants, more and more large-scale hydropower systems are taking shape gradually, which brings up a challenge to optimize these systems. Optimization of large-scale hydropower system (OLHS), which is to determine water discharges or water levels of overall hydro plants for maximizing total power generation when subjecting to lots of constrains, is a high dimensional, nonlinear and coupling complex problem. In order to solve the OLHS problem effectively, an improved decomposition–coordination and discrete differential dynamic programming (IDC–DDDP) method is proposed in this paper. A strategy that initial solution is generated randomly is adopted to reduce generation time. Meanwhile, a relative coefficient based on maximum output capacity is proposed for more power generation. Moreover, an adaptive bias corridor technology is proposed to enhance convergence speed. The proposed method is applied to long-term optimal dispatches of large-scale hydropower system (LHS) in the Yangtze River basin. Compared to other methods, IDC–DDDP has competitive performances in not only total power generation but also convergence speed, which provides a new method to solve the OLHS problem
International Nuclear Information System (INIS)
Moulin, D.J.
1994-01-01
The Silver self-powered neutron detector (SPND) is a common detector used in the ramp program at the OSIRIS reactor. The Silver SPND signal is a reference during steady states, but its response is too slow for monitoring transient tests. In order to compensate for the inherent time delay a mathematical processing method of the Silver SPND signal was developed. Based on a convolution-type resolution of the kinetics equations, a dynamic compensation algorithm can be used for transient conditions as well as steady state conditions. A computer program reconstructs, in real-time, the dynamic neutron flux sensed by the Silver detector from the current measured between the emitter and the collector of the SPND. Although this method decreases slightly the signal-to-noise ratio, it maintains the SPND's characteristics and reduces the response time from about 10 minutes to less than 4 seconds for a step change in flux. This provides for prompt and accurate measurement of fuel rod power during ramp experiments in the OSIRIS reactor. This development makes the Silver SPND very suitable for many on-line monitoring applications
Multi-coupling dynamic model and 3d simulation program for in-situ leaching of uranium mining
International Nuclear Information System (INIS)
Tan Kaixuan; Zeng Sheng; Sang Xiao; Sun Bing
2010-01-01
The in-situ leaching of uranium mining is a very complicated non-linear dynamic system, which involves couplings and positive/negative feedback among many factors and processes. A comprehensive, coupled multi-factors and processes dynamic model and simulation method was established to study the in-situ leaching of uranium mining. The model accounts for most coupling among various processes as following: (1) rock texture mechanics and its evolution, (2)the incremental stress rheology of rock deformation, (3) 3-D viscoelastic/ plastic multi-deformation processes, (4) hydrofracturing, (5) tensorial (anisotropic) fracture and rock permeability, (6) water-rock interactions and mass-transport (both advective and diffusive), (7) dissolution-induced chemical compaction, (8) multi-phase fluid flow. A 3-D simulation program was compiled based on Fortran and C++. An example illustrating the application of this model to simulating acidification, production and terminal stage of in situ leaching of uranium mining is presented for the some mine in Xinjiang, China. This model and program can be used for theoretical study, mine design, production management, the study of contaminant transport and restoration in groundwater of in-situ leaching of uranium mining. (authors)
Liao, Bolin; Zhang, Yunong; Jin, Long
2016-02-01
In this paper, a new Taylor-type numerical differentiation formula is first presented to discretize the continuous-time Zhang neural network (ZNN), and obtain higher computational accuracy. Based on the Taylor-type formula, two Taylor-type discrete-time ZNN models (termed Taylor-type discrete-time ZNNK and Taylor-type discrete-time ZNNU models) are then proposed and discussed to perform online dynamic equality-constrained quadratic programming. For comparison, Euler-type discrete-time ZNN models (called Euler-type discrete-time ZNNK and Euler-type discrete-time ZNNU models) and Newton iteration, with interesting links being found, are also presented. It is proved herein that the steady-state residual errors of the proposed Taylor-type discrete-time ZNN models, Euler-type discrete-time ZNN models, and Newton iteration have the patterns of O(h(3)), O(h(2)), and O(h), respectively, with h denoting the sampling gap. Numerical experiments, including the application examples, are carried out, of which the results further substantiate the theoretical findings and the efficacy of Taylor-type discrete-time ZNN models. Finally, the comparisons with Taylor-type discrete-time derivative model and other Lagrange-type discrete-time ZNN models for dynamic equality-constrained quadratic programming substantiate the superiority of the proposed Taylor-type discrete-time ZNN models once again.
Lee, Hyunki; Kim, Min Young; Moon, Jeon Il
2017-12-01
Phase measuring profilometry and moiré methodology have been widely applied to the three-dimensional shape measurement of target objects, because of their high measuring speed and accuracy. However, these methods suffer from inherent limitations called a correspondence problem, or 2π-ambiguity problem. Although a kind of sensing method to combine well-known stereo vision and phase measuring profilometry (PMP) technique simultaneously has been developed to overcome this problem, it still requires definite improvement for sensing speed and measurement accuracy. We propose a dynamic programming-based stereo PMP method to acquire more reliable depth information and in a relatively small time period. The proposed method efficiently fuses information from two stereo sensors in terms of phase and intensity simultaneously based on a newly defined cost function of dynamic programming. In addition, the important parameters are analyzed at the view point of the 2π-ambiguity problem and measurement accuracy. To analyze the influence of important hardware and software parameters related to the measurement performance and to verify its efficiency, accuracy, and sensing speed, a series of experimental tests were performed with various objects and sensor configurations.
Yu, Rong; Zhong, Weifeng; Xie, Shengli; Zhang, Yan; Zhang, Yun
2016-02-01
As the next-generation power grid, smart grid will be integrated with a variety of novel communication technologies to support the explosive data traffic and the diverse requirements of quality of service (QoS). Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In this paper, we study the QoS differential scheduling problem in the CR-based smart grid communications networks. The scheduler is responsible for managing the spectrum resources and arranging the data transmissions of smart grid users (SGUs). To guarantee the differential QoS, the SGUs are assigned to have different priorities according to their roles and their current situations in the smart grid. Based on the QoS-aware priority policy, the scheduler adjusts the channels allocation to minimize the transmission delay of SGUs. The entire transmission scheduling problem is formulated as a semi-Markov decision process and solved by the methodology of adaptive dynamic programming. A heuristic dynamic programming (HDP) architecture is established for the scheduling problem. By the online network training, the HDP can learn from the activities of primary users and SGUs, and adjust the scheduling decision to achieve the purpose of transmission delay minimization. Simulation results illustrate that the proposed priority policy ensures the low transmission delay of high priority SGUs. In addition, the emergency data transmission delay is also reduced to a significantly low level, guaranteeing the differential QoS in smart grid.
Stochastic linear dynamical programming in order to apply it in energy modelling
Energy Technology Data Exchange (ETDEWEB)
El Hachem, S
1995-11-01
This thesis contributes to the development of new algorithms for the computation of stochastic dynamic problem and its mini-maxi variant for the case of imperfect knowledge on random data. The proposed algorithms are scenarios aggregation type. It also contributes to integrate these algorithms in a decision support approach and to discuss the stochastic modeling of two energy problems: the refining and the portfolio gas contracts. (author). 112 refs., 5 tabs.
A Dynamical Systems Theory Examination of Social Connections in Outdoor Recreation Programs
Jostad, Jeremy
2015-01-01
Adolescence is a developmental time period in which social connections are an important aspect to fostering positive growth and identity. Outdoor Adventure Education (OAE) programs are strategically positioned to help in this developmental process because of the novel social environment, however, little is known about how these types of social…
Griffith, Daniel; Bedford, Marilyn; Hundley, Stephen
2008-01-01
Traditional leadership development programs for higher education staff are challenged to blend theory with a real-world context that is meaningful to participants' work. Standard student leadership curriculum is strong on theory, but often thin on providing this real-world context. Both HR training departments and academic units charged with…
Dang, Shilpa; Chaudhury, Santanu; Lall, Brejesh; Roy, Prasun Kumar
2017-06-15
Determination of effective connectivity (EC) among brain regions using fMRI is helpful in understanding the underlying neural mechanisms. Dynamic Bayesian Networks (DBNs) are an appropriate class of probabilistic graphical temporal-models that have been used in past to model EC from fMRI, specifically order-one. High-order DBNs (HO-DBNs) have still not been explored for fMRI data. A fundamental problem faced in the structure-learning of HO-DBN is high computational-burden and low accuracy by the existing heuristic search techniques used for EC detection from fMRI. In this paper, we propose using dynamic programming (DP) principle along with integration of properties of scoring-function in a way to reduce search space for structure-learning of HO-DBNs and finally, for identifying EC from fMRI which has not been done yet to the best of our knowledge. The proposed exact search-&-score learning approach HO-DBN-DP is an extension of the technique which was originally devised for learning a BN's structure from static data (Singh and Moore, 2005). The effectiveness in structure-learning is shown on synthetic fMRI dataset. The algorithm reaches globally-optimal solution in appreciably reduced time-complexity than the static counterpart due to integration of properties. The proof of optimality is provided. The results demonstrate that HO-DBN-DP is comparably more accurate and faster than currently used structure-learning algorithms used for identifying EC from fMRI. The real data EC from HO-DBN-DP shows consistency with previous literature than the classical Granger Causality method. Hence, the DP algorithm can be employed for reliable EC estimates from experimental fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.
Ryan, J. W.; Ma, C.; Caprette, D. S.
1993-01-01
The Goddard VLBI group reports the results of analyzing 1648 Mark 3 data sets acquired from fixed and mobile observing sites through the end of 1991, and available to the Crustal Dynamics Project. Two large solutions were used to obtain Earth rotation parameters, nutation offsets, radio source positions, site positions, site velocities, and baseline evolution. Site positions are tabulated on a yearly basis for 1979 to 1995, inclusive. Site velocities are presented in both geocentric Cartesian and topocentric coordinates. Baseline evolution is plotted for 200 baselines, and individual length determinations are presented for an additional 356 baselines. This report includes 155 quasar radio sources, 96 fixed stations and mobile sites, and 556 baselines.
Physical models and numerical methods of the reactor dynamic computer program RETRAN
International Nuclear Information System (INIS)
Kamelander, G.; Woloch, F.; Sdouz, G.; Koinig, H.
1984-03-01
This report describes the physical models and the numerical methods of the reactor dynamic code RETRAN simulating reactivity transients in Light-Water-Reactors. The neutron-physical part of RETRAN bases on the two-group-diffusion equations which are solved by discretization similar to the TWIGL-method. An exponential transformation is applied and the inner iterations are accelerated by a coarse-mesh-rebalancing procedure. The thermo-hydraulic model approximates the equation of state by a built-in steam-water-table and disposes of options for the calculation of heat-conduction coefficients and heat transfer coefficients. (Author) [de
Study of Real-Time Programming for Simulation of Nuclear Reactor Dynamics
International Nuclear Information System (INIS)
Aliq; Widi Setiawan; Hendro Tjahjono
2003-01-01
Many aspects of real-time system are reviewed including the method, programming techniques, and its possibility to be applied in research reactor. The main point of real-time system is that it must designed to have a characteristics not only fast response but the most important is on-time response. In order to cover this requirements, real-time system need also a simple operating system consist of a kernel and application software. At the level of programming, real-time system require a modular approach, hard and soft time division and interprocess communications. The implementation can include some real-time (RT) operation system such as: RT-Linux, RT-OS9 and RT-Mat lab. Because of fast and on-time response requirements, if this system is going to be applied to research reactor, the transfer function model maybe more appropriate model compared to point kinetics model for the reason of computation time. (author)
Static and Dynamic Coupling and Cohesion Measures in Object Oriented Programming
Vasudha Dixit, Dr. Rajeev Vishwkarma
2013-01-01
A large numbers of metrics have been proposed for measuring properties of object-oriented software such as size, inheritance, cohesion and coupling. The coupling metrics presented in this paper exploring the difference between inheritance and interface programming. This paper presents a measurement to measure coupling between object (CBO), number of associations between classes (NASSocC), number of dependencies in metric (NDepIN) and number of dependenciesout m...
Directory of Open Access Journals (Sweden)
S. Sofana Reka
2016-09-01
Full Text Available This paper proposes a cloud computing framework in smart grid environment by creating small integrated energy hub supporting real time computing for handling huge storage of data. A stochastic programming approach model is developed with cloud computing scheme for effective demand side management (DSM in smart grid. Simulation results are obtained using GUI interface and Gurobi optimizer in Matlab in order to reduce the electricity demand by creating energy networks in a smart hub approach.
GLOBEC: Global Ocean Ecosystems Dynamics: A component of the US Global Change Research Program
1991-01-01
GLOBEC (GLOBal ocean ECosystems dynamics) is a research initiative proposed by the oceanographic and fisheries communities to address the question of how changes in global environment are expected to affect the abundance and production of animals in the sea. The approach to this problem is to develop a fundamental understanding of the mechanisms that determine both the abundance of key marine animal populations and their variances in space and time. The assumption is that the physical environment is a major contributor to patterns of abundance and production of marine animals, in large part because the planktonic life stages typical of most marine animals are intrinsically at the mercy of the fluid motions of the medium in which they live. Consequently, the authors reason that a logical approach to predicting the potential impact of a globally changing environment is to understand how the physical environment, both directly and indirectly, contributes to animal abundance and its variability in marine ecosystems. The plans for this coordinated study of of the potential impact of global change on ocean ecosystems dynamics are discussed.
Describing the macroscopic world: Closing the circle within the dynamical reduction program
International Nuclear Information System (INIS)
Ghirardi, G.C.; Grassi, R.; Benatti, F.
1994-06-01
With reference to recently proposed theoretical models accounting for reduction in terms of a unified dynamics governing all physical processes we analyze the problem of working out a world view accommodating our knowledge about natural phenomena. We stress the relevant conceptual differences between the considered models and standard quantum mechanics. In spite of the fact that both theories describe systems within a genuine Hilbert space framework, the peculiar features of the spontaneous reduction models limit drastically the states which are dynamically stable. This fact by itself allows one to work out an interpretation of the formalism which makes possible to give a satisfactory description of the world in terms of the values taken by an appropriately defined mass density function in ordinary configuration space. A topology based on this function and which is radically different from the one characterizing the Hilbert space is introduced and in terms of it the ideal of similarity of macroscopic situations is precisely defined. Finally, the formalism and the interpretation are shown to yield a natural criterion for establishing the psycho-physical parallelism. The conclusion is that, within the considered theories and at the nonrelativistic level, one can satisfy all sensible requirements for a completely satisfactory macro-objective description of reality. (author). 21 refs, 1 fig
Bhattacharjya, D.; Mukerji, T.; Mascarenhas, O.; Weyant, J.
2005-12-01
Designing a cost-effective and reliable monitoring program is crucial to the success of any geological CO2 storage project. Effective design entails determining both, the optimal measurement modality, as well as the frequency of monitoring the site. Time-lapse seismic provides the best spatial coverage and resolution for reservoir monitoring. Initial results from Sleipner (Norway) have demonstrated effective monitoring of CO2 plume movement. However, time-lapse seismic is an expensive monitoring technique especially over the long term life of a storage project and should be used judiciously. We present a mathematical model based on dynamic programming that can be used to estimate site-specific optimal frequency of time-lapse surveys. The dynamics of the CO2 sequestration process are simplified and modeled as a four state Markov process with transition probabilities. The states are M: injected CO2 safely migrating within the target zone; L: leakage from the target zone to the adjacent geosphere; R: safe migration after recovery from leakage state; and S: seepage from geosphere to the biosphere. The states are observed only when a monitoring survey is performed. We assume that the system may go to state S only from state L. We also assume that once observed to be in state L, remedial measures are always taken to bring it back to state R. Remediation benefits are captured by calculating the expected penalty if CO2 seeped into the biosphere. There is a trade-off between the conflicting objectives of minimum discounted costs of performing the next time-lapse survey and minimum risk of seepage and its associated costly consequences. A survey performed earlier would spot the leakage earlier. Remediation methods would have been utilized earlier, resulting in savings in costs attributed to excessive seepage. On the other hand, there are also costs for the survey and remedial measures. The problem is solved numerically using Bellman's optimality principal of dynamic
Treatment of the decay heat production in the reactor dynamics program TINTE
International Nuclear Information System (INIS)
Gerwin, H.; Scherer, W.
1993-07-01
The TINTE code system deals with the nuclear and the thermal transient behaviour of the primary circuit of an HTGR taking into consideration the mutual feedback effects in two-dimensional r-z-geometry. An update of the treatment of delayed heat production is presented. It is based on the German norm DIN 25485, the rules of which had to be adjusted for use in a dynamics code. For the description of the fuel element power history a substitute-histogram has been constructed from local burnup and optionally from information about shuffling of the fuel balls. As an example the depressurisation accident of a MODUL-HTR is calculated. The results obtained are very similiar to others previously reported. (orig./HP) [de
Fast pairwise structural RNA alignments by pruning of the dynamical programming matrix
DEFF Research Database (Denmark)
Havgaard, Jakob Hull; Torarinsson, Elfar; Gorodkin, Jan
2007-01-01
and backtracked in a normal fashion. Finally, the FOLDALIGN algorithm has also been updated with a better memory implementation and an improved energy model. With these improvements in the algorithm, the FOLDALIGN software package provides the molecular biologist with an efficient and user-friendly tool...... the advantage of providing the constraints dynamically. This has been included in a new implementation of the FOLDALIGN algorithm for pairwise local or global structural alignment of RNA sequences. It is shown that time and memory requirements are dramatically lowered while overall performance is maintained....... Furthermore, a new divide and conquer method is introduced to limit the memory requirement during global alignment and backtrack of local alignment. All branch points in the computed RNA structure are found and used to divide the structure into smaller unbranched segments. Each segment is then realigned...
Portable Parallel Programming for the Dynamic Load Balancing of Unstructured Grid Applications
Biswas, Rupak; Das, Sajal K.; Harvey, Daniel; Oliker, Leonid
1999-01-01
The ability to dynamically adapt an unstructured -rid (or mesh) is a powerful tool for solving computational problems with evolving physical features; however, an efficient parallel implementation is rather difficult, particularly from the view point of portability on various multiprocessor platforms We address this problem by developing PLUM, tin automatic anti architecture-independent framework for adaptive numerical computations in a message-passing environment. Portability is demonstrated by comparing performance on an SP2, an Origin2000, and a T3E, without any code modifications. We also present a general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication pattern, with a goal to providing a global view of system loads across processors. Experiments on, an SP2 and an Origin2000 demonstrate the portability of our approach which achieves superb load balance at the cost of minimal extra overhead.
Automatic Identification of Closed-Loop Wind Turbine Dynamics via Genetic Programming
Energy Technology Data Exchange (ETDEWEB)
La Cava, William; Danai, Kourosh; Lackner, Matthew; Spector, Lee; Fleming, Paul; Wright, Alan
2015-10-03
Wind turbines are nonlinear systems that operate in turbulent environments. As such, their behavior is difficult to characterize accurately across a wide range of operating conditions by physically meaningful models. Customarily, data-based models of wind turbines are defined in 'black box' format, lacking in both conciseness and physical intelligibility. To address this deficiency, we identify models of a modern horizontal-axis wind turbine in symbolic form using a recently developed symbolic regression method. The method used relies on evolutionary multi-objective optimization to produce succinct dynamic models from operational data without 'a priori' knowledge of the system. We compare the produced models with models derived by other methods for their estimation capacity and evaluate the tradeoff between model intelligibility and accuracy. Several succinct models are found that predict wind turbine behavior as well as or better than more complex alternatives derived by other methods.
Dynamic Analyses of Result Quality in Energy-Aware Approximate Programs
RIngenburg, Michael F.
Energy efficiency is a key concern in the design of modern computer systems. One promising approach to energy-efficient computation, approximate computing, trades off output precision for energy efficiency. However, this tradeoff can have unexpected effects on computation quality. This thesis presents dynamic analysis tools to study, debug, and monitor the quality and energy efficiency of approximate computations. We propose three styles of tools: prototyping tools that allow developers to experiment with approximation in their applications, online tools that instrument code to determine the key sources of error, and online tools that monitor the quality of deployed applications in real time. Our prototyping tool is based on an extension to the functional language OCaml. We add approximation constructs to the language, an approximation simulator to the runtime, and profiling and auto-tuning tools for studying and experimenting with energy-quality tradeoffs. We also present two online debugging tools and three online monitoring tools. The first online tool identifies correlations between output quality and the total number of executions of, and errors in, individual approximate operations. The second tracks the number of approximate operations that flow into a particular value. Our online tools comprise three low-cost approaches to dynamic quality monitoring. They are designed to monitor quality in deployed applications without spending more energy than is saved by approximation. Online monitors can be used to perform real time adjustments to energy usage in order to meet specific quality goals. We present prototype implementations of all of these tools and describe their usage with several applications. Our prototyping, profiling, and autotuning tools allow us to experiment with approximation strategies and identify new strategies, our online tools succeed in providing new insights into the effects of approximation on output quality, and our monitors succeed in
Veiga-Lopez, A; Ye, W; Phillips, D J; Herkimer, C; Knight, P G; Padmanabhan, V
2008-04-01
Prenatal testosterone excess leads to neuroendocrine, ovarian, and metabolic disruptions, culminating in reproductive phenotypes mimicking that of women with polycystic ovary syndrome (PCOS). The objective of this study was to determine the consequences of prenatal testosterone treatment on periovulatory hormonal dynamics and ovulatory outcomes. To generate prenatal testosterone-treated females, pregnant sheep were injected intramuscularly (days 30-90 of gestation, term=147 days) with 100 mg of testosterone-propionate in cottonseed oil semi-weekly. Female offspring born to untreated control females and prenatal testosterone-treated females were then studied during their first two breeding seasons. Sheep were given two injections of prostaglandin F2alpha 11 days apart, and blood samples were collected at 2-h intervals for 120 h, 10-min intervals for 8 h during the luteal phase (first breeding season only), and daily for an additional 15 days to characterize changes in reproductive hormonal dynamics. During the first breeding season, prenatal testosterone-treated females manifested disruptions in the timing and magnitude of primary gonadotropin surges, luteal defects, and reduced responsiveness to progesterone negative feedback. Disruptions in the periovulatory sequence of events during the second breeding season included: 1) delayed but increased preovulatory estradiol rise, 2) delayed and severely reduced primary gonadotropin surge in prenatal testosterone-treated females having an LH surge, 3) tendency for an amplified secondary FSH surge and a shift in the relative balance of FSH regulatory proteins, and 4) luteal responses that ranged from normal to anovulatory. These outcomes are likely to be of relevance to developmental origin of infertility disorders and suggest that differences in fetal exposure or fetal susceptibility to testosterone may account for the variability in reproductive phenotypes.
Computational Performance Analysis of Nonlinear Dynamic Systems using Semi-infinite Programming
Directory of Open Access Journals (Sweden)
Tor A. Johansen
2001-01-01
Full Text Available For nonlinear systems that satisfy certain regularity conditions it is shown that upper and lower bounds on the performance (cost function can be computed using linear or quadratic programming. The performance conditions derived from Hamilton-Jacobi inequalities are formulated as linear inequalities defined pointwise by discretizing the state-space when assuming a linearly parameterized class of functions representing the candidate performance bounds. Uncertainty with respect to some system parameters can be incorporated by also gridding the parameter set. In addition to performance analysis, the method can also be used to compute Lyapunov functions that guarantees uniform exponential stability.
Analysis of dynamic behavior of a PWR utilizing the computer program SARDAN 2
International Nuclear Information System (INIS)
Pessanha, J.A.O.
1982-07-01
In the design of a PWR nuclear plant it is necessary to verify if the design limits are respected, even under abnormal operation condition. An evolution of SARDAN code, developed to simulate transients in PWR, are presented. The new aspects incorporeted in SARDAN 2 are: the fuel ROD analysis in finite-diference, an open channel model for the critic subchannel analysis and the introduction of a simplified model for the automatic control system. The program has been tested in accident condition II, in special, uncontrolled ROD cluster assembly bank withoraw, dropped full-length assembly group, uncontrolled Boron dilution, and the results obtained were considered satisfactory. (Author) [pt
Pfile, Kate R; Gribble, Phillip A; Buskirk, Gretchen E; Meserth, Sara M; Pietrosimone, Brian G
2016-08-01
Epidemiological data demonstrate the need for lower-extremity injury-prevention training. Neuromuscular-control (NMC) programs are immediately effective at minimizing lower-extremity injury risk and improving sport-related performance measures. Research investigating lasting effects after an injury-prevention program is limited. To determine whether dynamic balance, landing mechanics, and hamstring and quadriceps strength could be improved after a 6-wk NMC intervention and maintained for a season. Prospective case series. Controlled laboratory. 11 Division I women's basketball players (age 19.40 ± 1.35 y, height 178.05 ± 7.52 cm, mass 72.86 ± 10.70 kg). Subjects underwent testing 3 times, completing the Star Excursion Balance Test (SEBT), Landing Error Scoring System (LESS), and isometric strength testing for the hamstrings and quadriceps muscles. Pretest and posttest 1 occurred immediately before and after the intervention, respectively, and posttest 2 at the end of the competitive season, 9 mo after posttest 1. Subjects participated in eighteen 30-min plyometric and NMC-training sessions over a 6-wk period. The normalized SEBT composite score, normalized peak isometric hamstrings:quadriceps (H:Q) ratio, and the LESS total score. The mean composite reach significantly improved over time (F2,10 = 6.96, P = .005) where both posttest scores were significantly higher than pretest (70.41% ± 4.08%) (posttest 1 73.48% ± 4.19%, t10 = -3.11, P = .011) and posttest 2 (74.2% ± 4.77%, t10 = -3.78, P = .004). LESS scores significantly improved over time (F2,10 = 6.29, P = .009). The pretest LESS score (7.30 ± 3.40) was higher than posttest 1 (4.9 ± 1.20, t10 = 2.71, P = .024) and posttest 2 (5.44 ± 1.83, t10 = 2.58, P = .030). There were no statistically significant differences (P > .05) over time for the H:Q ratio when averaging both legs (F2,10 = 0.83, P = .45). A 6-wk NMC program improved landing mechanics and dynamic balance over a 9-mo period in women
AbouEisha, Hassan M.
2014-06-06
In this paper we present a dynamic programming algorithm for finding optimal elimination trees for computational grids refined towards point or edge singularities. The elimination tree is utilized to guide the multi-frontal direct solver algorithm. Thus, the criterion for the optimization of the elimination tree is the computational cost associated with the multi-frontal solver algorithm executed over such tree. We illustrate the paper with several examples of optimal trees found for grids with point, isotropic edge and anisotropic edge mixed with point singularity. We show the comparison of the execution time of the multi-frontal solver algorithm with results of MUMPS solver with METIS library, implementing the nested dissection algorithm.
Marsili, Simone; Signorini, Giorgio Federico; Chelli, Riccardo; Marchi, Massimo; Procacci, Piero
2010-04-15
We present the new release of the ORAC engine (Procacci et al., Comput Chem 1997, 18, 1834), a FORTRAN suite to simulate complex biosystems at the atomistic level. The previous release of the ORAC code included multiple time steps integration, smooth particle mesh Ewald method, constant pressure and constant temperature simulations. The present release has been supplemented with the most advanced techniques for enhanced sampling in atomistic systems including replica exchange with solute tempering, metadynamics and steered molecular dynamics. All these computational technologies have been implemented for parallel architectures using the standard MPI communication protocol. ORAC is an open-source program distributed free of charge under the GNU general public license (GPL) at http://www.chim.unifi.it/orac. 2009 Wiley Periodicals, Inc.
International Nuclear Information System (INIS)
Shimizu, Yoshiaki
1991-01-01
In recent complicated nuclear systems, there are increasing demands for developing highly advanced procedures for various problems-solvings. Among them keen interests have been paid on man-machine communications to improve both safety and economy factors. Many optimization methods have been good enough to elaborate on these points. In this preliminary note, we will concern with application of linear programming (LP) for this purpose. First we will present a new superior version of the generalized PAPA method (GEPAPA) to solve LP problems. We will then examine its effectiveness when applied to derive dynamic matrix control (DMC) as the LP solution. The approach is to aim at the above goal through a quality control of process that will appear in the system. (author)
Directory of Open Access Journals (Sweden)
K. Tsimaras Vasileios
2015-05-01
Full Text Available Traditional dance is gaining popularity as an intervention choice for improving poor balance ability of people with intellectual disability (ID. Balance improvement for individuals with ID through dance provides opportunities for participation in sport activities and promotes independent living. This short review provides in brief research evidence of dynamic balance improvement as measured by means of a balance deck in duration of 30, 45, and 60 sec intervals, highlighting the need to incorporate traditional dance programs in Physical Education (PE lessons applied on participants with ID. Overall, traditional dances provide emotional and cognitive interaction that has a direct positive effect on quality of life and successful motor performance of individuals with ID.
International Nuclear Information System (INIS)
Bouchard, Bruno; Vu, Thanh Nam
2010-01-01
We provide an obstacle version of the Geometric Dynamic Programming Principle of Soner and Touzi (J. Eur. Math. Soc. 4:201-236, 2002) for stochastic target problems. This opens the doors to a wide range of applications, particularly in risk control in finance and insurance, in which a controlled stochastic process has to be maintained in a given set on a time interval [0,T]. As an example of application, we show how it can be used to provide a viscosity characterization of the super-hedging cost of American options under portfolio constraints, without appealing to the standard dual formulation from mathematical finance. In particular, we allow for a degenerate volatility, a case which does not seem to have been studied so far in this context.
Directory of Open Access Journals (Sweden)
Vasileios K. Tsimaras
2015-04-01
Full Text Available Traditional dance is gaining popularity as an intervention choice for improving poor balance ability of people with intellectual disability (ID. Balance improvement for individuals with ID through dance provides opportunities for participation in sport activities and promotes independent living. This short review provides in brief research evidence of dynamic balance improvement as measured by means of a balance deck in duration of 30, 45, and 60 sec intervals, highlighting the need to incorporate traditional dance programs in Physical Education (PE lessons applied on participants with ID. Overall, traditional dances provide emotional and cognitive interaction that has a direct positive effect on quality of life and successful motor performance of individuals with ID.
Zhang, Huaguang; Jiang, He; Luo, Chaomin; Xiao, Geyang
2017-10-01
In this paper, we investigate the nonzero-sum games for a class of discrete-time (DT) nonlinear systems by using a novel policy iteration (PI) adaptive dynamic programming (ADP) method. The main idea of our proposed PI scheme is to utilize the iterative ADP algorithm to obtain the iterative control policies, which not only ensure the system to achieve stability but also minimize the performance index function for each player. This paper integrates game theory, optimal control theory, and reinforcement learning technique to formulate and handle the DT nonzero-sum games for multiplayer. First, we design three actor-critic algorithms, an offline one and two online ones, for the PI scheme. Subsequently, neural networks are employed to implement these algorithms and the corresponding stability analysis is also provided via the Lyapunov theory. Finally, a numerical simulation example is presented to demonstrate the effectiveness of our proposed approach.
International Nuclear Information System (INIS)
Chen, Yuche; Zhang, Yunteng; Fan, Yueyue; Hu, Kejia; Zhao, Jianyou
2017-01-01
Highlights: • Dynamic programming method is used in transportation fuel portfolio planning. • The learning effect in new fuel technology is endogenously modeled through an experience curve. • Cellulosic biofuels play critical role in de-carbonization transport sector in near term. • The initial 3–4 billion gallons production is critical to bring down cellulosic biofuels’ cost. • Large penetration of Zero Emission Vehicles will discourage development of cellulosic biofuels. - Abstract: Promoting the adoption of low-carbon technologies in the transportation fuel portfolio is an effective strategy to mitigate greenhouse gas emissions from the transportation sector worldwide. However, as one of the most promising low-carbon fuels, cellulosic biofuel has not fully entered commercial production. Governments could provide guidance in developing cellulosic biofuel technologies, but no systematic approach has been proposed yet. We establish a dynamic programming framework for investigating time-dependent and adaptive decision-making processes to develop advanced fuel technologies. The learning-by-doing effect inherited in the technology development process is included in the framework. The proposed framework is applied in a case study to explore the most economical pathway for California to develop a solid cellulosic biofuel industry under its Low Carbon Fuel Standard. Our results show that cellulosic biofuel technology is playing a critical role in guaranteeing California’s 10% greenhouse gas emission reduction by 2020. Three to four billion gallons of cumulative production are needed to ensure that cellulosic biofuel is cost-competitive with petroleum-based fuels or conventional biofuels. Zero emission vehicle promoting policies will discourage the development of cellulosic biofuel. The proposed framework, with small adjustments, can also be applied to study new technology development in other energy sectors.
International Nuclear Information System (INIS)
Hancevic, Pedro Ignacio
2017-01-01
The Acid Rain Program (ARP) was implemented in 1995. Since then, coal-fired boilers have had to choose among three main compliance alternatives: purchase pollution permits; switch to an alternative lower-sulfur coal; or adopt a scrubber. This decision problem is driven by the evolution of several economic variables and is revised when significant changes (to prices, quality of inputs, output level, technology, transport costs, regulations, among others) occur. Using a structural dynamic discrete choice model, I recover cost parameters and use them to evaluate two different counterfactual policies. The results confirm there is a trade-off between fuel switching and scrubbing costs (with the latter having a higher investment cost and a lower variable cost), and also the existence of regional heterogeneity. Finally, the ARP implied cost savings of approximately $4.7 billions if compared to a uniform emission rate standard and $14.8 billions if compared to compulsory scrubbing for the 1995–2005 period. - Highlights: • With the cap-and-trade system of the ARP boilers had three main compliance options. • Purchase allowances; retrofit the boiler to burn low-sulfur coal; adopt scrubbers. • We develop and estimate a rigorous structural dynamic discrete choice model. • Trade-off between fuel switching and scrubbing (capital versus operating costs). • Cost savings from the ARP were substantial if compared to previous regulations.
Sun, Jingliang; Liu, Chunsheng
2018-01-01
In this paper, the problem of intercepting a manoeuvring target within a fixed final time is posed in a non-linear constrained zero-sum differential game framework. The Nash equilibrium solution is found by solving the finite-horizon constrained differential game problem via adaptive dynamic programming technique. Besides, a suitable non-quadratic functional is utilised to encode the control constraints into a differential game problem. The single critic network with constant weights and time-varying activation functions is constructed to approximate the solution of associated time-varying Hamilton-Jacobi-Isaacs equation online. To properly satisfy the terminal constraint, an additional error term is incorporated in a novel weight-updating law such that the terminal constraint error is also minimised over time. By utilising Lyapunov's direct method, the closed-loop differential game system and the estimation weight error of the critic network are proved to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is demonstrated by using a simple non-linear system and a non-linear missile-target interception system, assuming first-order dynamics for the interceptor and target.
International Nuclear Information System (INIS)
Jackson, M.A.
1982-01-01
The programmer's task is often taken to be the construction of algorithms, expressed in hierarchical structures of procedures: this view underlies the majority of traditional programming languages, such as Fortran. A different view is appropriate to a wide class of problem, perhaps including some problems in High Energy Physics. The programmer's task is regarded as having three main stages: first, an explicit model is constructed of the reality with which the program is concerned; second, this model is elaborated to produce the required program outputs; third, the resulting program is transformed to run efficiently in the execution environment. The first two stages deal in network structures of sequential processes; only the third is concerned with procedure hierarchies. (orig.)
Jackson, M A
1982-01-01
The programmer's task is often taken to be the construction of algorithms, expressed in hierarchical structures of procedures: this view underlies the majority of traditional programming languages, such as Fortran. A different view is appropriate to a wide class of problem, perhaps including some problems in High Energy Physics. The programmer's task is regarded as having three main stages: first, an explicit model is constructed of the reality with which the program is concerned; second, thi...
A Dynamic Programming-Based Heuristic for the Shift Design Problem in Airport Ground Handling
DEFF Research Database (Denmark)
Clausen, Tommy
We consider the heterogeneous shift design problem for a workforce with multiple skills, where work shifts are created to cover a given demand as well as possible while minimizing cost and satisfying a flexible set of constraints. We focus mainly on applications within airport ground handling whe...... programming that allows flexibility in modeling the workforce. Parameters allow a planner to determine the level of demand coverage that best fulfills the requirements of the organization. Results are presented from several diverse real-life ground handling instances.......We consider the heterogeneous shift design problem for a workforce with multiple skills, where work shifts are created to cover a given demand as well as possible while minimizing cost and satisfying a flexible set of constraints. We focus mainly on applications within airport ground handling where...
Think Scientifically: The NASA Solar Dynamics Observatory's Elementary Science Literacy Program
Van Norden, Wendy M.
2013-07-01
The pressure to focus on math and reading at the elementary level has increased in recent years. As a result, science education has taken a back seat in elementary classrooms. The Think Scientifically book series provides a way for science to easily integrate with existing math and reading curriculum. This story-based science literature program integrates a classic storybook format with solar science concepts, to make an educational product that meets state literacy standards. Each story is accompanied by hands-on labs and activities that teachers can easily conduct in their classrooms with minimal training and materials, as well as math and language arts extensions. These books are being distributed through teacher workshops and conferences, and are available free at http://sdo.gsfc.nasa.gov/epo/educators/thinkscientifically.php.
Adler, D; Mahler, Y
1980-04-01
A procedure for automatic detection and digital processing of the maximum first derivative of the intraventricular pressure (dp/dtmax), time to dp/dtmax(t - dp/dt) and beat-to-beat intervals have been developed. The procedure integrates simple electronic circuits with a short program using a simple algorithm for the detection of the points of interest. The tasks of differentiating the pressure signal and detecting the onset of contraction were done by electronics, while the tasks of finding the values of dp/dtmax, t - dp/dt, beat-to-beat intervals and all computations needed were done by software. Software/hardware 'trade off' considerations and the accuracy and reliability of the system are discussed.
2-D Modeling of Energy-z Beam Dynamics Using the LiTrack Matlab Program
International Nuclear Information System (INIS)
Cauley, S.K.
2005-01-01
Short bunches and the bunch length distribution have important consequences for both the LCLS project at SLAC and the proposed ILC project. For both these projects, it is important to simulate what bunch length distributions are expected and then to perform actual measurements. The goal of the research is to determine the sensitivity of the bunch length distribution to accelerator phase and voltage. This then indicates the level of control and stability that is needed. In this project I simulated beamlines to find the rms bunch length in three different beam lines at SLAC, which are the test beam to End Station A (ILC-ESA) for the ILC studies, Linac Coherent Light Source (LCLS) and LCLS-ESA. To simulate the beamlines, I used the LiTrack program, which does a 2-dimensional tracking of an electron bunch's longitudinal (z) and the energy spread beam (E) parameters. In order to reduce the time of processing the information, I developed a small program to loop over adjustable machine parameters. LiTrack is a Matlab script and Matlab is also used for plotting and saving and loading files. The results show that the LCLS in Linac-A is the most sensitive when looking at the ratio of change in phase degree to rate of change. The results also show a noticeable difference between the LCLS and LCLS-ESA, which suggest that further testing should go into looking the Beam Switch Yard and End Station A to determine why the result of the LCLS and LCLS-ESA vary
“Push” dynamics in policy experimentation: Downscaling climate change adaptation programs in Canada
Directory of Open Access Journals (Sweden)
Adam Wellstead
2016-12-01
Full Text Available Policy experiments have often been touted as valuable mechanisms for ensuring sustainability transitions and climate change adaptation. However problems exist both in the definition of ‘experiments’, and in their design and realization. While valuable, most experiments examined in the literature to date have been small-scale micro-level deployments or evaluations of policy tools in which the most problematic element revolves around their “scaling-up” or diffusion. The literature on the subject has generally neglected the problems and issues related to another class of experiments in which macro or meso-level initiatives are ‘scaled-down’ to the micro-level. This paper examines a recent effort of this kind in Canada involving the creation of Regional Adaptation Collaboratives (RACs across the country whose main purpose is to push national level initiatives down to the regions and localities. As the discussion shows, this top-down process has its own dynamics distinct from those involved in ‘scaling up’ and should be examined as a separate category of policy experiments in its own right.
International Nuclear Information System (INIS)
Nitej, N.V.; Sharovarov, G.A.
1982-01-01
The method of estimation of counterflow heat exchanger characteristics is presented. Mathematical description of the processes is presented by the mass, energy and pulse conservation equations for both coolants and energy conservation equation for the wall which devides them. In the presence of chemical reactions the system is supplemented by equations, characterizing the kinetics of their progress. The methods of numerical solution of static and dynamic problems have been chosen, and the computer programs on the Fortran language have been developed. The schemes of solution of both problems are so constructed, that the conservation equations are placed in the main program, and such characteristics of the coolants as properties, heat transfer and friction coefficients, the mechanism of chemical reaction are concentrated in the subprogram unit. This allows to create the single method of solution with the flow of single-phase and two-phase coolants of abovecritical and supercritical paramters. The evaluation results of three heat exchangers are given: with heating of N 2 O 4 gas phase by heat of flue gas; with cooling of N 2 O 4 supercritical parameters by water; regenerator on N 2 O 4
Energy Technology Data Exchange (ETDEWEB)
Homem-de-Mello, Tito [University of Illinois at Chicago, Department of Mechanical and Industrial Engineering, Chicago, IL (United States); Matos, Vitor L. de; Finardi, Erlon C. [Universidade Federal de Santa Catarina, LabPlan - Laboratorio de Planejamento de Sistemas de Energia Eletrica, Florianopolis (Brazil)
2011-03-15
The long-term hydrothermal scheduling is one of the most important problems to be solved in the power systems area. This problem aims to obtain an optimal policy, under water (energy) resources uncertainty, for hydro and thermal plants over a multi-annual planning horizon. It is natural to model the problem as a multi-stage stochastic program, a class of models for which algorithms have been developed. The original stochastic process is represented by a finite scenario tree and, because of the large number of stages, a sampling-based method such as the Stochastic Dual Dynamic Programming (SDDP) algorithm is required. The purpose of this paper is two-fold. Firstly, we study the application of two alternative sampling strategies to the standard Monte Carlo - namely, Latin hypercube sampling and randomized quasi-Monte Carlo - for the generation of scenario trees, as well as for the sampling of scenarios that is part of the SDDP algorithm. Secondly, we discuss the formulation of stopping criteria for the optimization algorithm in terms of statistical hypothesis tests, which allows us to propose an alternative criterion that is more robust than that originally proposed for the SDDP. We test these ideas on a problem associated with the whole Brazilian power system, with a three-year planning horizon. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Silva, Marcelo Mariano da
2008-01-15
The search for high performance and low cost hardware and software solutions always guides the developments performed at the IEN parallel computing laboratory. In this context, this dissertation about the building of programs for visualization of computational fluid dynamics (CFD) simulations using the open source software OpenDx was written. The programs developed are useful to produce videos and images in two or three dimensions. They are interactive, easily to use and were designed to serve fluid dynamics researchers. A detailed description about how this programs were developed and the complete instructions of how to use them was done. The use of OpenDx as development tool is also introduced. There are examples that help the reader to understand how programs can be useful for many applications. (author)
Xiao, Jingjie
A key hurdle for implementing real-time pricing of electricity is a lack of consumers' responses. Solutions to overcome the hurdle include the energy management system that automatically optimizes household appliance usage such as plug-in hybrid electric vehicle charging (and discharging with vehicle-to-grid) via a two-way communication with the grid. Real-time pricing, combined with household automation devices, has a potential to accommodate an increasing penetration of plug-in hybrid electric vehicles. In addition, the intelligent energy controller on the consumer-side can help increase the utilization rate of the intermittent renewable resource, as the demand can be managed to match the output profile of renewables, thus making the intermittent resource such as wind and solar more economically competitive in the long run. One of the main goals of this dissertation is to present how real-time retail pricing, aided by control automation devices, can be integrated into the wholesale electricity market under various uncertainties through approximate dynamic programming. What distinguishes this study from the existing work in the literature is that whole- sale electricity prices are endogenously determined as we solve a system operator's economic dispatch problem on an hourly basis over the entire optimization horizon. This modeling and algorithm framework will allow a feedback loop between electricity prices and electricity consumption to be fully captured. While we are interested in a near-optimal solution using approximate dynamic programming; deterministic linear programming benchmarks are use to demonstrate the quality of our solutions. The other goal of the dissertation is to use this framework to provide numerical evidence to the debate on whether real-time pricing is superior than the current flat rate structure in terms of both economic and environmental impacts. For this purpose, the modeling and algorithm framework is tested on a large-scale test case
Dynamic fMRI networks predict success in a behavioral weight loss program among older adults.
Mokhtari, Fatemeh; Rejeski, W Jack; Zhu, Yingying; Wu, Guorong; Simpson, Sean L; Burdette, Jonathan H; Laurienti, Paul J
2018-06-01
More than one-third of adults in the United States are obese, with a higher prevalence among older adults. Obesity among older adults is a major cause of physical dysfunction, hypertension, diabetes, and coronary heart diseases. Many people who engage in lifestyle weight loss interventions fail to reach targeted goals for weight loss, and most will regain what was lost within 1-2 years following cessation of treatment. This variability in treatment efficacy suggests that there are important phenotypes predictive of success with intentional weight loss that could lead to tailored treatment regimen, an idea that is consistent with the concept of precision-based medicine. Although the identification of biochemical and metabolic phenotypes are one potential direction of research, neurobiological measures may prove useful as substantial behavioral change is necessary to achieve success in a lifestyle intervention. In the present study, we use dynamic brain networks from functional magnetic resonance imaging (fMRI) data to prospectively identify individuals most likely to succeed in a behavioral weight loss intervention. Brain imaging was performed in overweight or obese older adults (age: 65-79 years) who participated in an 18-month lifestyle weight loss intervention. Machine learning and functional brain networks were combined to produce multivariate prediction models. The prediction accuracy exceeded 95%, suggesting that there exists a consistent pattern of connectivity which correctly predicts success with weight loss at the individual level. Connectivity patterns that contributed to the prediction consisted of complex multivariate network components that substantially overlapped with known brain networks that are associated with behavior emergence, self-regulation, body awareness, and the sensory features of food. Future work on independent datasets and diverse populations is needed to corroborate our findings. Additionally, we believe that efforts can begin to
Rebaudo, François; Dangles, Olivier
2011-10-01
Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' "diffusion of innovation theory". In particular, the success of integrated pest management (IPM) extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM) combining social (diffusion theory) and biological (pest population dynamics) models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations.
International Nuclear Information System (INIS)
Nwulu, Nnamdi I.; Xia, Xiaohua
2015-01-01
Highlights: • In this work, a game theory based DR program is integrated into the DEED problem. • Objectives are to minimize fuel and emissions costs and maximize the DR benefit. • Optimal generator output, customer load and customer incentive are determined. • Developed model is tested with two different scenarios. • Model provides superior results than independent optimization of DR or DEED. - Abstract: The dynamic economic emission dispatch (DEED) of electric power generation is a multi-objective mathematical optimization problem with two objective functions. The first objective is to minimize all the fuel costs of the generators in the power system, whilst the second objective seeks to minimize the emissions cost. Both objective functions are subject to constraints such as load demand constraint, ramp rate constraint, amongst other constraints. In this work, we integrate a game theory based demand response program into the DEED problem. The game theory based demand response program determines the optimal hourly incentive to be offered to customers who sign up for load curtailment. The game theory model has in built mechanisms to ensure that the incentive offered the customers is greater than the cost of interruption while simultaneously being beneficial to the utility. The combined DEED and game theoretic demand response model presented in this work, minimizes fuel and emissions costs and simultaneously determines the optimal incentive and load curtailment customers have to perform for maximal power system relief. The developed model is tested on two test systems with industrial customers and obtained results indicate the practical benefits of the proposed model
Programming strategy for efficient modeling of dynamics in a population of heterogeneous cells.
Hald, Bjørn Olav; Garkier Hendriksen, Morten; Sørensen, Preben Graae
2013-05-15
Heterogeneity is a ubiquitous property of biological systems. Even in a genetically identical population of a single cell type, cell-to-cell differences are observed. Although the functional behavior of a given population is generally robust, the consequences of heterogeneity are fairly unpredictable. In heterogeneous populations, synchronization of events becomes a cardinal problem-particularly for phase coherence in oscillating systems. The present article presents a novel strategy for construction of large-scale simulation programs of heterogeneous biological entities. The strategy is designed to be tractable, to handle heterogeneity and to handle computational cost issues simultaneously, primarily by writing a generator of the 'model to be simulated'. We apply the strategy to model glycolytic oscillations among thousands of yeast cells coupled through the extracellular medium. The usefulness is illustrated through (i) benchmarking, showing an almost linear relationship between model size and run time, and (ii) analysis of the resulting simulations, showing that contrary to the experimental situation, synchronous oscillations are surprisingly hard to achieve, underpinning the need for tools to study heterogeneity. Thus, we present an efficient strategy to model the biological heterogeneity, neglected by ordinary mean-field models. This tool is well posed to facilitate the elucidation of the physiologically vital problem of synchronization. The complete python code is available as Supplementary Information. bjornhald@gmail.com or pgs@kiku.dk Supplementary data are available at Bioinformatics online.
Cottrell, Paul Edward
There is a lack of research in the area of hedging future contracts, especially in illiquid or very volatile market conditions. It is important to understand the volatility of the oil and currency markets because reduced fluctuations in these markets could lead to better hedging performance. This study compared different hedging methods by using a hedging error metric, supplementing the Receding Horizontal Control and Stochastic Programming (RHCSP) method by utilizing the London Interbank Offered Rate with the Levy process. The RHCSP hedging method was investigated to determine if improved hedging error was accomplished compared to the Black-Scholes, Leland, and Whalley and Wilmott methods when applied on simulated, oil, and currency futures markets. A modified RHCSP method was also investigated to determine if this method could significantly reduce hedging error under extreme market illiquidity conditions when applied on simulated, oil, and currency futures markets. This quantitative study used chaos theory and emergence for its theoretical foundation. An experimental research method was utilized for this study with a sample size of 506 hedging errors pertaining to historical and simulation data. The historical data were from January 1, 2005 through December 31, 2012. The modified RHCSP method was found to significantly reduce hedging error for the oil and currency market futures by the use of a 2-way ANOVA with a t test and post hoc Tukey test. This study promotes positive social change by identifying better risk controls for investment portfolios and illustrating how to benefit from high volatility in markets. Economists, professional investment managers, and independent investors could benefit from the findings of this study.
Analysis of Natural Frequencies in the Universal Programs for Dynamic Processes Analysis
Directory of Open Access Journals (Sweden)
V. A. Trudonoshin
2016-01-01
Full Text Available Finding the natural frequencies of complex technical objects is an important design procedure. This type of analysis allows us to determine the resonant frequencies and, as a consequence, to avoid their adverse impact on dynamics the projected object or that of under study. This applies to both the objects with distributed parameters, and the objects with lumped parameters. As to the first type of the objects, in almost every package that implements the finite element method, this type of analysis is available. The situation is different for the objects with lumped parameters. Methods to have the mathematical models for these objects look to implicit methods of numerical integration of ordinary differential equations. And the component equations of the reactive branches are sampled by numerical integration formulas, and the derivatives of state variables disappear from the vector of the unknowns of a mathematical model. In this case, talk about the implementation of the procedure for finding natural frequencies by finding eigenvalues is simply unnecessary. In cases where a mathematical model of the object is given in the normal Cauchy form, obtaining the natural frequencies is reduced to finding the eigenvalues of the coefficient matrix. There are methods to form the mathematical models in which the derivatives of the state variables make a sub-vector of the vector of unknowns. These are generalized, advanced nodal methods, and an advanced nodal one for mechanical systems. There can be a try for reduction of the mathematical models of objects, obtained by these methods, to the normal Cauchy form. The article discusses a similar procedure for the generalized and advanced nodal methods. As for the extended nodal method for mechanical systems there is specifics the article does not show. For the model obtained by generalized method the vector of unknown variables is permutated so that a sub-vector of the derivatives of the state variables was in
Kularathna, M.D.U.P.
1992-01-01
The technique of Stochastic Dynamic Programming (SDP) is ideally suited for operation policy analyses of water resources systems. However SDP has a major drawback which is appropriately termed as its "curse of dimensionality".
Aggregation/Disaggregation techniques based on SDP and
Sandner, Raimar; Vukics, András
2014-09-01
++ libraries, GNU Scientific Library, Blitz++, FLENS, NumPy, SciPy Catalogue identifier of previous version: AELU_v1_0 Journal reference of previous version: Comput. Phys. Comm. 183 (2012) 1381 Does the new version supersede the previous version?: Yes Nature of problem: Definition of (open) composite quantum systems out of elementary building blocks [2,3]. Manipulation of such systems, with emphasis on dynamical simulations such as Master-equation evolution [4] and Monte Carlo wave-function simulation [5]. Solution method: Master equation, Monte Carlo wave-function method Reasons for new version: The new version is mainly a feature release, but it does correct some problems of the previous version, especially as regards the build system. Summary of revisions: We give an example for a typical Python script implementing the ring-cavity system presented in Sec. 3.3 of Ref. [2]: Restrictions: Total dimensionality of the system. Master equation-few thousands. Monte Carlo wave-function trajectory-several millions. Unusual features: Because of the heavy use of compile-time algorithms, compilation of programs written in the framework may take a long time and much memory (up to several GBs). Additional comments: The framework is not a program, but provides and implements an application-programming interface for developing simulations in the indicated problem domain. We use several C++11 features which limits the range of supported compilers (g++ 4.7, clang++ 3.1) Documentation, http://cppqed.sourceforge.net/ Running time: Depending on the magnitude of the problem, can vary from a few seconds to weeks. References: [1] Entry point: http://cppqed.sf.net [2] A. Vukics, C++QEDv2: The multi-array concept and compile-time algorithms in the definition of composite quantum systems, Comp. Phys. Comm. 183(2012)1381. [3] A. Vukics, H. Ritsch, C++QED: an object-oriented framework for wave-function simulations of cavity QED systems, Eur. Phys. J. D 44 (2007) 585. [4] H. J. Carmichael, An Open
Ali, A; Fahmy, S
2007-07-01
The objective was to evaluate ovarian dynamics and progesterone concentrations in cyclic (CYC, n=10) and non-cyclic (NCY, n=8) buffalo-cows during Ovsynch program. All cows received GnRH on day 0, PGF2alpha on day 7, and GnRH on day 9, and AI 14 h later. Ovarian structures were monitored by ultrasound and milk samples were collected for progesterone (P4) analysis. The first GnRH resulted in ovulation in CYC (90%) and NCY (62.5%) cows. By day 7, almost all cows had large follicle and lutein tissue. Luteolytic responses to PGF2alpha were 80 and 87.5% for CYC and NCY cows, respectively. Following second GnRH, ovulation occurred in 80% of CYC and 100% of NCY cows. Ovulation began earlier (12 h following second GnRH) and extended for longer (36 h) in NCY cows, when compared to CYC cows (36 and 12 h, respectively). The mean P4 levels increased from days 0 through 7 in CYC and NCY cows and levels were higher in CYC group. Conception rates were 60 and 37.5% in CYC and NYC cows, respectively. Early and asynchronous ovulation and luteal sub-function seemed to be a problem in NCY cows. Inseminating NCY cows twice, at 0 and 24 h of the second GnRH is recommended.
International Nuclear Information System (INIS)
Wu, Gang; Fan, Ying; Wei, Yi-Ming; Liu, Lan-Cui
2008-01-01
The world's future oil price is affected by many factors. The challenge, therefore, is how to select optimal stockpile acquisition strategies to minimize the cost of maintaining a reserve. This paper provides a new method for analyzing this problem using an uncertain dynamic programming model to analyze stockpile acquisition strategies for strategic petroleum reserve. Using this model, we quantify the impact of uncertain world oil price on optimal stockpile acquisition strategies of China's strategic petroleum reserve for the period 2007-2010 and 2011-2020. Our results show that the future stockpile acquisition is related to oil prices and their probability and, if not considering the occurrence of oil supply shortage, China should at least purchase 25 million barrels when world oil price is at an optimal level. The optimal price of stockpile acquisition of every year has a stronger relationship with the probability of high price; and the optimal expected price and size of stockpile acquisition is different in each year. (author)
Ahonen, Lauri; Cowley, Benjamin Ultan; Hellas, Arto; Puolamäki, Kai
2018-02-16
Collaboration is a complex phenomenon, where intersubjective dynamics can greatly affect the productive outcome. Evaluation of collaboration is thus of great interest, and can potentially help achieve better outcomes and performance. However, quantitative measurement of collaboration is difficult, because much of the interaction occurs in the intersubjective space between collaborators. Manual observation and/or self-reports are subjective, laborious, and have a poor temporal resolution. The problem is compounded in natural settings where task-activity and response-compliance cannot be controlled. Physiological signals provide an objective mean to quantify intersubjective rapport (as synchrony), but require novel methods to support broad deployment outside the lab. We studied 28 student dyads during a self-directed classroom pair-programming exercise. Sympathetic and parasympathetic nervous system activation was measured during task performance using electrodermal activity and electrocardiography. Results suggest that (a) we can isolate cognitive processes (mental workload) from confounding environmental effects, and (b) electrodermal signals show role-specific but correlated affective response profiles. We demonstrate the potential for social physiological compliance to quantify pair-work in natural settings, with no experimental manipulation of participants required. Our objective approach has a high temporal resolution, is scalable, non-intrusive, and robust.
Energy Technology Data Exchange (ETDEWEB)
1986-01-01
The executive committee of the Social Democratic Party (SPD) at its meeting on May 26, 1986 in Hannover has set up a commission to inquire into the possibilities of 'safeguarding energy supplies without nuclear energy'. The commission's first report was to be prepared for the party convention in Nuernberg. This interim report is presented here, after unanimous vote of acceptance by commission members. The report gives preliminary outline solutions to the problem of safeguarding energy supplies without recourse to the nuclear energy source. An annex to the report presents significant facts and data relating to the energy sector, (part 1), together with the energy policy making decisions of the SPD since the year 1956 (part 2).
Software Acquisition Program Dynamics
2011-10-24
greatest capability, which requires latest technologies • Contractors prefer using latest technologies to boost staff competency for future bids Risk...mistakes Build foundation to test future mitigation/solution approaches to assess value • Qualitatively validate new approaches before applying them to...classroom training, eLearning , certification, and more—to serve the needs of customers and partners worldwide.
Elements of Dynamic Programming,
1981-02-02
step/pitch lies in the fact that us ia .o eacerprise P, cf means x". to enter.rise P2 - means xan sc L Jsing widely used teraiAo.j, :onrrol U, it is... acca ~acj ,,L ra sauticn of protlem. Is qenertity intuitively it ii cliax thi-t with at. increat-e in the number aoc = 80151502 FAG E of stips/pitches...Ad.aua inccme W*.. 5S on the ,raph/curve Fig. 9.10 bitn ;.A Leut Z, = 0.75.x2 + 0.3 (Z, - xl); it is obtained value w. 4 . .o.& acca ayq.n they are
Airoldi, Edoardo M.; Miller, Darach; Athanasiadou, Rodoniki; Brandt, Nathan; Abdul-Rahman, Farah; Neymotin, Benjamin; Hashimoto, Tatsu; Bahmani, Tayebeh; Gresham, David
2016-01-01
Cell growth rate is regulated in response to the abundance and molecular form of essential nutrients. In Saccharomyces cerevisiae (budding yeast), the molecular form of environmental nitrogen is a major determinant of cell growth rate, supporting growth rates that vary at least threefold. Transcriptional control of nitrogen use is mediated in large part by nitrogen catabolite repression (NCR), which results in the repression of specific transcripts in the presence of a preferred nitrogen source that supports a fast growth rate, such as glutamine, that are otherwise expressed in the presence of a nonpreferred nitrogen source, such as proline, which supports a slower growth rate. Differential expression of the NCR regulon and additional nitrogen-responsive genes results in >500 transcripts that are differentially expressed in cells growing in the presence of different nitrogen sources in batch cultures. Here we find that in growth rate–controlled cultures using nitrogen-limited chemostats, gene expression programs are strikingly similar regardless of nitrogen source. NCR expression is derepressed in all nitrogen-limiting chemostat conditions regardless of nitrogen source, and in these conditions, only 34 transcripts exhibit nitrogen source–specific differential gene expression. Addition of either the preferred nitrogen source, glutamine, or the nonpreferred nitrogen source, proline, to cells growing in nitrogen-limited chemostats results in rapid, dose-dependent repression of the NCR regulon. Using a novel means of computational normalization to compare global gene expression programs in steady-state and dynamic conditions, we find evidence that the addition of nitrogen to nitrogen-limited cells results in the transient overproduction of transcripts required for protein translation. Simultaneously, we find that that accelerated mRNA degradation underlies the rapid clearing of a subset of transcripts, which is most pronounced for the highly expressed NCR
International Nuclear Information System (INIS)
Chen, Xin; Mu, Hailin; Li, Huanan; Gui, Shusen
2014-01-01
There has been much attention paid to oil security in China in recent years. Although China has begun to establish its own strategic petroleum reserve (SPR) to prevent potential losses caused by oil supply interruptions, the system aiming to ensure China's oil security is still incomplete. This paper describes and provides evidence for the benefits of an auxiliary strategic oil policy choice, which aims to strengthen China's oil supply security and offer a solution for strategic oil operations with different holding costs. In this paper, we develop a multi-dimension stochastic dynamic programming model to analyze the oil stockpile delegation policy, which is an intermediate policy between public and private oil stockpiles and is appropriate for the Chinese immature private oil stockpile sector. The model examines the effects of the oil stockpile delegation policy in the context of several distinct situations, including normal world oil market conditions, slight oil supply interruption, and serious oil supply interruption. Operating strategies that respond to different oil supply situations for both the SPR and the delegated oil stockpile were obtained. Different time horizons, interruption times and holding costs of delegated oil stockpiles were examined. The construction process of China's SPR was also taken into account. - Highlights: • We provided an auxiliary strategic oil policy rooted in Chinese local conditions. • The policy strengthen China's capability for preventing oil supply interruption. • We model to obtain the managing strategies for China's strategic petroleum reserve. • Both of the public and delegated oil stockpile were taken into consideration. • The three phase's construction process of China's SPR was taken into account
International Nuclear Information System (INIS)
Takada, Shoji; Takizuka, Takakazu; Kunitomi, Kazuhiko; Kosugiyama, Shinichi; Yan, Xing
2003-01-01
A program for test on rotor dynamics was planned for the turbo-machine of the Gas Turbine High Temperature Reactor (GTHTR300). The rotor system of the turbo-machine consists of a turbo-compressor rotor and a generator rotor connected with a flexible coupling, each suspended with two radial magnetic bearings. The rotors, which are flexible rotors, pass over the critical speeds of bending mode. The magnetic bearing is required to have a high load capacity, about 10 times larger than any built thus far to support a flexible rotor. In the rotor design, the standard limit of the vibration amplitude of 75 μm at the rated rotational speed of 3,600 rpm was fulfilled by optimizing the stiffness of the magnetic bearings. A test apparatus was designed to verify the design of the magnetic bearing suspended turbo-machine rotor of the GTHTR300. The test apparatus is composed of 1/3-scale test rotors, which are connected with a flexible coupling and driven by a variable speed motor. The test magnetic bearing was designed within the state-of-the-art technology to have a load capacity about 1/10 of that of the actual one. The test rotors were designed to closely simulate the critical speeds and vibration modes of the actual ones. This paper shows the test apparatus and the test plan for the magnetic bearing suspended rotor system. The present study is entrusted from the Ministry of Education, Culture, Sports, Science and Technology of Japan. (author)
Vitharana, V. H. P.; Chinda, T.
2018-04-01
Lower back pain (LBP), prevalence is high among the heavy equipment operators leading to high compensation cost in the construction industry. It is found that proper training program assists in reducing chances of having LBP. This study, therefore aims to examine different safety related budget available to support LBP related training program for different age group workers, utilizing system dynamics modeling approach. The simulation results show that at least 2.5% of the total budget must be allocated in the safety and health budget to reduce the chances of having LBP cases.
Chen, Zehong; Hu, Kang; Feng, Lieting; Su, Ruxiong; Lai, Nan; Yang, Zike; Kang, Shijun
2018-06-01
Various types of vaccines have been proposed as approaches for prevention or delay of the onset of cancer by boosting the endogenous immune system. We previously developed a senescent-cell-based vaccine, induced by radiation and veliparib, as a preventive and therapeutic tool against triple-negative breast cancer. However, the programmed death receptor-1/programmed death ligand-1 (PD-1/PD-L1) pathway was found to play an important role in vaccine failure. Hence, we further developed soluble programmed death receptor-1 (sPD1)-expressing senescent cells to overcome PD-L1/PD-1-mediated immune suppression while vaccinating to promote dendritic cell (DC) maturity, thereby amplifying T-cell activation. In the present study, sPD1-expressing senescent cells showed a particularly active status characterized by growth arrest and modified immunostimulatory cytokine secretion in vitro. As expected, sPD1-expressing senescent tumor cell vaccine (STCV/sPD-1) treatment attracted more mature DC and fewer exhausted-PD1 + T cells in vivo. During the course of the vaccine studies, we observed greater safety and efficacy for STCV/sPD-1 than for control treatments. STCV/sPD-1 pre-injections provided complete protection from 4T1 tumor challenge in mice. Additionally, the in vivo therapeutic study of mice with s.c. 4T1 tumor showed that STCV/sPD-1 vaccination delayed tumorigenesis and suppressed tumor progression at early stages. These results showed that STCV/sPD-1 effectively induced a strong antitumor immune response against cancer and suggested that it might be a potential strategy for TNBC prevention. © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.
Energy Technology Data Exchange (ETDEWEB)
Edo, S; Kenmoku, Y; Sakakibara, T [Toyohashi University of Technology, Aichi (Japan); Nakagawa, S [Maizuru College of Technology, Kyoto (Japan); Kawamoto, T [Shizuoka University, Shizuoka (Japan)
1997-11-25
With regard to utilization of a solar/electric hot-water system, a discussion was given by using a dynamic programming method on operation of a system which minimizes power charge. The discussed system is an installation in a welfare facility accommodating 100 persons, where solar heat is stored in a heat storage tank from a heat collector, and utilized for hot water supply. If the solar heat is insufficient for required hot water quantity, the water is heated by using an electric heater. The discussion compared the system operation using the dynamic programming method with the following two systems: the operation method 1, which does not utilize insolation forecast and the operation method 2, in which insolation forecast is utilized and late-night electric power is utilized for heating water in shortage. As a result of the calculation, the operation using the dynamic programming method conducts heat storage by utilizing the late-night power even if insolation is sufficient in winter in order to suppress heating by utilizing late-night power for days with less insolation. Thus, suppression is given on excessive utilization of day-time power and on rise in annual maximum power demand. It was found that the present system reduces power consumption by 37.7% when compared with the operation method 1, and 22.7% when compared even with the operation method 2. 3 refs., 5 figs., 3 tabs.
Du, Likai; Lan, Zhenggang
2015-04-14
Nonadiabatic dynamics simulations have rapidly become an indispensable tool for understanding ultrafast photochemical processes in complex systems. Here, we present our recently developed on-the-fly nonadiabatic dynamics package, JADE, which allows researchers to perform nonadiabatic excited-state dynamics simulations of polyatomic systems at an all-atomic level. The nonadiabatic dynamics is based on Tully's surface-hopping approach. Currently, several electronic structure methods (CIS, TDHF, TDDFT(RPA/TDA), and ADC(2)) are supported, especially TDDFT, aiming at performing nonadiabatic dynamics on medium- to large-sized molecules. The JADE package has been interfaced with several quantum chemistry codes, including Turbomole, Gaussian, and Gamess (US). To consider environmental effects, the Langevin dynamics was introduced as an easy-to-use scheme into the standard surface-hopping dynamics. The JADE package is mainly written in Fortran for greater numerical performance and Python for flexible interface construction, with the intent of providing open-source, easy-to-use, well-modularized, and intuitive software in the field of simulations of photochemical and photophysical processes. To illustrate the possible applications of the JADE package, we present a few applications of excited-state dynamics for various polyatomic systems, such as the methaniminium cation, fullerene (C20), p-dimethylaminobenzonitrile (DMABN) and its primary amino derivative aminobenzonitrile (ABN), and 10-hydroxybenzo[h]quinoline (10-HBQ).
International Nuclear Information System (INIS)
Ezaki, Masahiro; Mitake, Susumu; Ozawa, Tamotsu
1979-06-01
The SCOTCH program solves the one-dimensional (R or Z), two-group reactor kinetics equations with multi-channel temperature transients and fluid dynamics. Sub-program SCOTCH-RX simulates the space-time neutron diffusion in radial direction, and sub-program SCOTCH-AX simulates the same in axial direction. The program has about 8,000 steps of FORTRAN statement and requires about 102 kilo-words of computer memory. (author)
2017-07-26
The datasets in this zip file are in support of FHWA-JPO-16-379, Analysis, Modeling, and Simulation (AMS) Testbed Development and Evaluation to Support Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) Program...
Waiboer, R.R.
2007-01-01
Robotised laser welding is an innovative joining technique which is increasingly finding applications, especially in the automotive industry. In order to reduce the time needed to prepare and programthe laser welding robot, off-line programming systems are used. The off-line programming systems
International Nuclear Information System (INIS)
Pilati, T.; Dermartin, F.; Gramaccioli, C.M.
1993-01-01
A wide-purpose computer program has been written (Fortran) for lattice dynamical evaluation of crystallographic and thermodynamic properties of solids, especially minerals or inorganic substances.The program essentially consists of a routine affording first and second derivatives of energy with respect to mass weighted coordinates, properly modulated by a wave vector algorithm, so that diagonalization can immediately follow and arrive at frequencies, density of states, and eventually to thermodynamic functions and Debye-Waller parameters thorough an automatic Brillouin-zone sampling procedure. The input consists of crystallographic data (unit-cell parameters, space group symmetry operations, atomic coordinates), plus atomic charge and empirical parameters, such as force constants or non-bonded atom-atom interaction energy functions in almost any form. It is also possible to obtain the structure corresponding to the energy minimum, or even to work with partial rigid bodies, in order to reduce the order of the dynamical matrices. The program provides for automatic symmetry labelling of the vibrational modes, in order to compare them with the experimental data; there is possibility of improving the empirical functions through a minimization routine. Examples of application and transferability of force fields to a series of minerals are provided. (author)
Herrera Ramos, Estefanía
2015-01-01
Programa de doctorado: Salud pública: Epidemiología, nutrición y planificación [ES]La presente Tesis Doctoral plantea la hipótesis de que la variabilidad genética de las proteínas surfactantes A y D (SP-A y SP-D) pueden influir en la susceptibilidad y pronóstico de diversas enfermedades pulmonares. Esas variantes podrían utilizarse como marcadores para identificar a los subgrupos de individuos con mayor predisposición a desarrollar una de estas enf...