Optimizing real power loss and voltage stability limit of a large transmission network using firefly algorithm

Directory of Open Access Journals (Sweden)

P. Balachennaiah

2016-06-01

Full Text Available This paper proposes a Firefly algorithm based technique to optimize the control variables for simultaneous optimization of real power loss and voltage stability limit of the transmission system. Mathematically, this issue can be formulated as nonlinear equality and inequality constrained optimization problem with an objective function integrating both real power loss and voltage stability limit. Transformers taps, unified power flow controller and its parameters have been included as control variables in the problem formulation. The effectiveness of the proposed algorithm has been tested on New England 39-bus system. Simulation results obtained with the proposed algorithm are compared with the real coded genetic algorithm for single objective of real power loss minimization and multi-objective of real power loss minimization and voltage stability limit maximization. Also, a classical optimization method known as interior point successive linear programming technique is considered here to compare the results of firefly algorithm for single objective of real power loss minimization. Simulation results confirm the potentiality of the proposed algorithm in solving optimization problems.

Effect of Local Junction Losses in the Optimization of T-shaped Flow Channels

Science.gov (United States)

Kosaraju, Srinivas

2015-11-01

T-shaped channels are extensively used in flow distribution applications such as irrigation, chemical dispersion, gas pipelines and space heating and cooling. The geometry of T-shaped channels can be optimized to reduce the overall pressure drop in stem and branch sections. Results of such optimizations are in the form of geometric parameters such as the length and diameter ratios of the stem and branch sections. The traditional approach of this optimization accounts for the pressure drop across the stem and branch sections, however, ignores the pressure drop in the T-junction. In this paper, we conduct geometry optimization while including the effect of local junction losses in laminar flows. From the results, we are able to identify a non-dimensional parameter that can be used to predict the optimal geometric configurations. This parameter can also be used to identify the conditions in which the local junction losses can be ignored during the optimization.

Support vector machines optimization based theory, algorithms, and extensions

CERN Document Server

Deng, Naiyang; Zhang, Chunhua

2013-01-01

Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components of support vector machines (SVMs)-classification problems and regression problems. The book emphasizes the close connection between optimization theory and SVMs since optimization is one of the pillars on which SVMs are built.The authors share insight on many of their research achievements. They give a precise interpretation of statistical leaning theory for C-support vector classification. They also discuss regularized twi

Computational Approach to Profit Optimization of a Loss-Queueing System

Directory of Open Access Journals (Sweden)

Dinesh Kumar Yadav

2010-01-01

Full Text Available Objective of the paper is to deal with the profit optimization of a loss queueing system with the finite capacity. Here, we define and compute total expected cost (TEC, total expected revenue (TER and consequently we compute the total optimal profit (TOP of the system. In order to compute the total optimal profit of the system, a computing algorithm has been developed and a fast converging N-R method has been employed which requires least computing time and lesser memory space as compared to other methods. Sensitivity analysis and its observations based on graphics have added a significant value to this model.

Microgrids: Energy management by loss minimization technique

Energy Technology Data Exchange (ETDEWEB)

Basu, A.K. [Electrical Engineering Dept., Jadavpur University & 20/2, Khanpur Road, Kolkata 700047 (India); Chowdhury, S.; Chowdhury, S.P. [Electrical Engineering Department, University of Cape Town & Private Bag X3, Menzies Building, Room-517, Rondebosch, Cape Town 7701 (India)

2011-07-01

Energy management is a techno-economic issue, which dictates, in the context of microgrids, how optimal investment in technology front could bring optimal power quality and reliability (PQR) of supply to the consumers. Investment in distributed energy resources (DERs), with their connection to the utility grid at optimal locations and with optimal sizes, saves energy in the form of line loss reduction. Line loss reduction is the indirect benefit to the microgrid owner who may recover it as an incentive from utility. The present paper focuses on planning of optimal siting and sizing of DERs based on minimization of line loss. Optimal siting is done, here, on the loss sensitivity index (LSI) method and optimal sizing by differential evolution (DE) algorithms, which is, again, compared with particle swarm optimization (PSO) technique. Studies are conducted on 6-bus and 14-bus radial networks under islanded mode of operation with electric demand profile. Islanding helps planning of DER capacity of microgrid, which is self-sufficient to cater its own consumers without utility's support.

Optimism in prolonged grief and depression following loss: A three-wave longitudinal study.

Science.gov (United States)

Boelen, Paul A

2015-06-30

There is considerable evidence that optimism, the predisposition to have generalized favorable expectancies for the future, is associated with numerous desirable outcomes. Few studies have examined the association of optimism with emotional distress following the death of a loved one. Doing so is important, because optimism may be an important target for interventions for post-loss psychopathology. In the current study, we examined the degree to which optimism, assessed in the first year post-loss (Time 1, T1), was associated with symptom levels of prolonged grief and depression six months (Time 2, T2) and fifteen months (Time 3, T3) later, controlling for baseline symptoms and also taking into account positive automatic cognitions at T1. Findings showed that higher optimism at T1 was associated with lower concurrent prolonged grief and depression severity. Higher optimism at T1 was also inversely related with depression symptom severity at T2 and T3, but not prolonged grief severity at T2 and T3. Implications of these findings are discussed. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Energy loss optimization of run-off-road wheels applying imperialist competitive algorithm

Directory of Open Access Journals (Sweden)

Hamid Taghavifar

2014-08-01

Full Text Available The novel imperialist competitive algorithm (ICA has presented outstanding fitness on various optimization problems. Application of meta-heuristics has been a dynamic studying interest of the reliability optimization to determine idleness and reliability constituents. The application of a meta-heuristic evolutionary optimization method, imperialist competitive algorithm (ICA, for minimization of energy loss due to wheel rolling resistance in a soil bin facility equipped with single-wheel tester is discussed. The required data were collected thorough various designed experiments in the controlled soil bin environment. Local and global searching of the search space proposed that the energy loss could be reduced to the minimum amount of 15.46 J at the optimized input variable configuration of wheel load at 1.2 kN, tire inflation pressure of 296 kPa and velocity of 2 m/s. Meanwhile, genetic algorithm (GA, particle swarm optimization (PSO and hybridized GA–PSO approaches were benchmarked among the broad spectrum of meta-heuristics to find the outperforming approach. It was deduced that, on account of the obtained results, ICA can achieve optimum configuration with superior accuracy in less required computational time.

Optimizing Policymakers' Loss Functions in Crisis Prediction: Before, Within or After?

OpenAIRE

Sarlin, Peter; von Schweinitz, Gregor

2015-01-01

Early-warning models most commonly optimize signaling thresholds on crisis probabilities. The expost threshold optimization is based upon a loss function accounting for preferences between forecast errors, but comes with two crucial drawbacks: unstable thresholds in recursive estimations and an in-sample overfit at the expense of out-of-sample performance. We propose two alternatives for threshold setting: (i) including preferences in the estimation itself and (ii) setting thresholds ex-ante ...

Fuzzy-TLBO optimal reactive power control variables planning for energy loss minimization

International Nuclear Information System (INIS)

Moghadam, Ahmad; Seifi, Ali Reza

2014-01-01

Highlights: • A new approach to the problem of optimal reactive power control variables planning is proposed. • The energy loss minimization problem has been formulated by modeling the load of system as a Load Duration Curve. • To solving the energy loss problem, the classic methods and the evolutionary methods are used. • A new proposed fuzzy teaching–learning based algorithm is applied to energy loss problem. • Simulations are done to show the effectiveness and superiority of the proposed algorithm compared with other methods. - Abstract: This paper offers a new approach to the problem of optimal reactive power control variables planning (ORPVCP). The basic idea is division of Load Duration Curve (LDC) into several time intervals with constant active power demand in each interval and then solving the energy loss minimization (ELM) problem to obtain an optimal initial set of control variables of the system so that is valid for all time intervals and can be used as an initial operating condition of the system. In this paper, the ELM problem has been solved by the linear programming (LP) and fuzzy linear programming (Fuzzy-LP) and evolutionary algorithms i.e. MHBMO and TLBO and the results are compared with the proposed Fuzzy-TLBO method. In the proposed method both objective function and constraints are evaluated by membership functions. The inequality constraints are embedded into the fitness function by the membership function of the fuzzy decision and the problem is modeled by fuzzy set theory. The proposed Fuzzy-TLBO method is performed on the IEEE 30 bus test system by considering two different LDC; and it is shown that using this method has further minimized objective function than original TLBO and other optimization techniques and confirms its potential to solve the ORPCVP problem with considering ELM as the objective function

Optimism, Social Support, and Adjustment in African American Women with Breast Cancer

Science.gov (United States)

Shelby, Rebecca A.; Crespin, Tim R.; Wells-Di Gregorio, Sharla M.; Lamdan, Ruth M.; Siegel, Jamie E.; Taylor, Kathryn L.

2013-01-01

Past studies show that optimism and social support are associated with better adjustment following breast cancer treatment. Most studies have examined these relationships in predominantly non-Hispanic White samples. The present study included 77 African American women treated for nonmetastatic breast cancer. Women completed measures of optimism, social support, and adjustment within 10-months of surgical treatment. In contrast to past studies, social support did not mediate the relationship between optimism and adjustment in this sample. Instead, social support was a moderator of the optimism-adjustment relationship, as it buffered the negative impact of low optimism on psychological distress, well-being, and psychosocial functioning. Women with high levels of social support experienced better adjustment even when optimism was low. In contrast, among women with high levels of optimism, increasing social support did not provide an added benefit. These data suggest that perceived social support is an important resource for women with low optimism. PMID:18712591

Optimization of Monochromated TEM for Ultimate Resolution Imaging and Ultrahigh Resolution Electron Energy Loss Spectroscopy

KAUST Repository

Lopatin, Sergei; Cheng, Bin; Liu, Wei-Ting; Tsai, Meng-Lin; He, Jr-Hau; Chuvilin, Andrey

2017-01-01

The performance of a monochromated transmission electron microscope with Wien type monochromator is optimized to achieve an extremely narrow energy spread of electron beam and an ultrahigh energy resolution with spectroscopy. The energy spread in the beam is improved by almost an order of magnitude as compared to specified values. The optimization involves both the monochromator and the electron energy loss detection system. We demonstrate boosted capability of optimized systems with respect to ultra-low loss EELS and sub-angstrom resolution imaging (in a combination with spherical aberration correction).

Optimization of Monochromated TEM for Ultimate Resolution Imaging and Ultrahigh Resolution Electron Energy Loss Spectroscopy

KAUST Repository

Lopatin, Sergei

2017-09-01

The performance of a monochromated transmission electron microscope with Wien type monochromator is optimized to achieve an extremely narrow energy spread of electron beam and an ultrahigh energy resolution with spectroscopy. The energy spread in the beam is improved by almost an order of magnitude as compared to specified values. The optimization involves both the monochromator and the electron energy loss detection system. We demonstrate boosted capability of optimized systems with respect to ultra-low loss EELS and sub-angstrom resolution imaging (in a combination with spherical aberration correction).

Optimizing wind farm cable routing considering power losses

DEFF Research Database (Denmark)

Fischetti, Martina; Pisinger, David

2017-01-01

Wind energy is the fastest growing source of renewable energy, but as wind farms are getting larger and more remotely located, installation and infrastructure costs are rising. It is estimated that the expenses for electrical infrastructure account for 15-30% of the overall initial costs, hence...... that must be spent immediately in cable and installation costs, and the future reduced revenues due to power losses. The latter goal has not been addressed in previous work. We present a Mixed-Integer Linear Programming approach to optimize the routing using both exact and math-heuristic methods....... In the power losses computation, wind scenarios are handled eciently as part of the preprocessing, resulting in a MIP model of only slightly larger size. A library of real-life instances is introduced and made publicly available for benchmarking. Computational results on this testbed show the viability of our...

Optimizing wind farm cable routing considering power losses

DEFF Research Database (Denmark)

Fischetti, Martina; Pisinger, David

Wind energy is the fastest growing source of renewable energy, but as wind farms are getting larger and more remotely located, installation and infrastructure costs are rising. It is estimated that the expenses for electrical infrastructure account for 15-30% of the overall initial costs, hence...... that must be spent immediately in cable and installation costs, and the future reduced revenues due to power losses. The latter goal has not been addressed in previous work. We present a Mixed-Integer Linear Programming approach to optimize the routing using both exact and math-heuristic methods....... In the power losses computation, wind scenarios are handled eciently as part of the preprocessing, resulting in a MIP model of only slightly larger size. A library of real-life instances is introduced and made publicly available for benchmarking. Computational results on this testbed show the viability of our...

Enhanced GSA-Based Optimization for Minimization of Power Losses in Power System

Directory of Open Access Journals (Sweden)

Gonggui Chen

2015-01-01

Full Text Available Gravitational Search Algorithm (GSA is a heuristic method based on Newton’s law of gravitational attraction and law of motion. In this paper, to further improve the optimization performance of GSA, the memory characteristic of Particle Swarm Optimization (PSO is employed in GSAPSO for searching a better solution. Besides, to testify the prominent strength of GSAPSO, GSA, PSO, and GSAPSO are applied for the solution of optimal reactive power dispatch (ORPD of power system. Conventionally, ORPD is defined as a problem of minimizing the total active power transmission losses by setting control variables while satisfying numerous constraints. Therefore ORPD is a complicated mixed integer nonlinear optimization problem including many constraints. IEEE14-bus, IEEE30-bus, and IEEE57-bus test power systems are used to implement this study, respectively. The obtained results of simulation experiments using GSAPSO method, especially the power loss reduction rates, are compared to those yielded by the other modern artificial intelligence-based techniques including the conventional GSA and PSO methods. The results presented in this paper reveal the potential and effectiveness of the proposed method for solving ORPD problem of power system.

Optimism, social support, and mental health outcomes in patients with advanced cancer.

Science.gov (United States)

Applebaum, Allison J; Stein, Emma M; Lord-Bessen, Jennifer; Pessin, Hayley; Rosenfeld, Barry; Breitbart, William

2014-03-01

Optimism and social support serve as protective factors against distress in medically ill patients. Very few studies have specifically explored the ways in which these variables interact to impact quality of life (QOL), particularly among patients with advanced cancer. The present study examined the role of optimism as a moderator of the relationship between social support and anxiety, depression, hopelessness, and QOL among patients with advanced cancer. Participants (N = 168) completed self-report assessments of psychosocial, spiritual, and physical well-being, including social support, optimism, hopelessness, depressive and anxious symptoms, and QOL. Hierarchical multiple regression analyses were conducted to determine the extent to which social support and optimism were associated with depressive and anxious symptomatology, hopelessness and QOL, and the potential role of optimism as a moderator of the relationship between social support and these variables. Higher levels of optimism were significantly associated with fewer anxious and depressive symptoms, less hopelessness, and better QOL. Higher levels of perceived social support were also significantly associated with better QOL. Additionally, optimism moderated the relationship between social support and anxiety, such that there was a strong negative association between social support and anxiety for participants with low optimism. This study highlights the importance of optimism and social support in the QOL of patients with advanced cancer. As such, interventions that attend to patients' expectations for positive experiences and the expansion of social support should be the focus of future clinical and research endeavors. Copyright © 2013 John Wiley & Sons, Ltd.

A concurrent optimization model for supplier selection with fuzzy quality loss

International Nuclear Information System (INIS)

Rosyidi, C.; Murtisari, R.; Jauhari, W.

2017-01-01

The purpose of this research is to develop a concurrent supplier selection model to minimize the purchasing cost and fuzzy quality loss considering process capability and assembled product specification. Design/methodology/approach: This research integrates fuzzy quality loss in the model to concurrently solve the decision making in detailed design stage and manufacturing stage. Findings: The resulted model can be used to concurrently select the optimal supplier and determine the tolerance of the components. The model balances the purchasing cost and fuzzy quality loss. Originality/value: An assembled product consists of many components which must be purchased from the suppliers. Fuzzy quality loss is integrated in the supplier selection model to allow the vagueness in final assembly by grouping the assembly into several grades according to the resulted assembly tolerance.

A concurrent optimization model for supplier selection with fuzzy quality loss

Energy Technology Data Exchange (ETDEWEB)

Rosyidi, C.; Murtisari, R.; Jauhari, W.

2017-07-01

The purpose of this research is to develop a concurrent supplier selection model to minimize the purchasing cost and fuzzy quality loss considering process capability and assembled product specification. Design/methodology/approach: This research integrates fuzzy quality loss in the model to concurrently solve the decision making in detailed design stage and manufacturing stage. Findings: The resulted model can be used to concurrently select the optimal supplier and determine the tolerance of the components. The model balances the purchasing cost and fuzzy quality loss. Originality/value: An assembled product consists of many components which must be purchased from the suppliers. Fuzzy quality loss is integrated in the supplier selection model to allow the vagueness in final assembly by grouping the assembly into several grades according to the resulted assembly tolerance.

Optimal design of the cable metro with unified intermediate supports

Directory of Open Access Journals (Sweden)

Lagerev A.V.

2017-12-01

Full Text Available In article was formulated and solved the problem of conditional nonlinear technical and economic optimization of the distance between intermediate supports, uniform in height, during the design of the cable metro lines in highly urban-ized city environment. The optimization problem involves a single-criterion objective function that expresses the cost of construction of the cable metro line (total cost of intermediate supports and their foundations, traction and carrying steel cables and technical equipment. The specified objective function subject to minimization by finding the optimal combination of the distance between intermediate supports and tension carrying ropes with accounting constructive, modal, structural and planning constraints in the form of nonlinear inequalities. The optimization algorithm was based on the direct method of optimization type, Hooke-Jeeves, which was modified taking into account the need of varying the height of intermediate supports with a constant step equal to the step of unification. When constructing the objective function were considered three possible forms sagging of carrying ropes, which can be implemented for various values of the efforts of their tension. Analysis was done of the influence of the step unification and minimum size of interme-diate supports on their optimum step, the cost of intermediate supports, the cost of 1 km cable metro line for different values of the angle of the longitudinal slope of the surface relief along the cable metro line. The graph of height of uni-fied supports from the angle of the longitudinal slope of the surface relief has discrete-step type. With the increase of the step unify the discreteness increases: the width of the range of angles of the longitudinal slope of the surface relief within which the height of the supports remains constant, increases. The graph of step installation of unified supports along the cable metro line from the angle of the longitudinal

Derivative load voltage and particle swarm optimization to determine optimum sizing and placement of shunt capacitor in improving line losses

Directory of Open Access Journals (Sweden)

Mohamed Milad Baiek

2016-12-01

Full Text Available The purpose of this research is to study optimal size and placement of shunt capacitor in order to minimize line loss. Derivative load bus voltage was calculated to determine the sensitive load buses which further being optimum with the placement of shunt capacitor. Particle swarm optimization (PSO was demonstrated on the IEEE 14 bus power system to find optimum size of shunt capacitor in reducing line loss. The objective function was applied to determine the proper placement of capacitor and get satisfied solutions towards constraints. The simulation was run over Matlab under two scenarios namely base case and increasing 100% load. Derivative load bus voltage was simulated to determine the most sensitive load bus. PSO was carried out to determine the optimum sizing of shunt capacitor at the most sensitive bus. The results have been determined that the most sensitive bus was bus number 14 for the base case and increasing 100% load. The optimum sizing was 8.17 Mvar for the base case and 23.98 Mvar for increasing load about 100%. Line losses were able to reduce approximately 0.98% for the base case and increasing 100% load reduced about 3.16%. The proposed method was also proven as a better result compared with harmony search algorithm (HSA method. HSA method recorded loss reduction ratio about 0.44% for the base case and 2.67% when the load was increased by 100% while PSO calculated loss reduction ratio about 1.12% and 4.02% for the base case and increasing 100% load respectively. The result of this study will support the previous study and it is concluded that PSO was successfully able to solve some engineering problems as well as to find a solution in determining shunt capacitor sizing on the power system simply and accurately compared with other evolutionary optimization methods.

A Hybrid Optimization Method for Reactive Power and Voltage Control Considering Power Loss Minimization

DEFF Research Database (Denmark)

Liu, Chengxi; Qin, Nan; Bak, Claus Leth

2015-01-01

This paper proposes a hybrid optimization method to optimally control the voltage and reactive power with minimum power loss in transmission grid. This approach is used for the Danish automatic voltage control (AVC) system which is typically a non-linear non-convex problem mixed with both...

A Multivariate Quality Loss Function Approach for Optimization of Spinning Processes

Science.gov (United States)

Chakraborty, Shankar; Mitra, Ankan

2018-05-01

Recent advancements in textile industry have given rise to several spinning techniques, such as ring spinning, rotor spinning etc., which can be used to produce a wide variety of textile apparels so as to fulfil the end requirements of the customers. To achieve the best out of these processes, they should be utilized at their optimal parametric settings. However, in presence of multiple yarn characteristics which are often conflicting in nature, it becomes a challenging task for the spinning industry personnel to identify the best parametric mix which would simultaneously optimize all the responses. Hence, in this paper, the applicability of a new systematic approach in the form of multivariate quality loss function technique is explored for optimizing multiple quality characteristics of yarns while identifying the ideal settings of two spinning processes. It is observed that this approach performs well against the other multi-objective optimization techniques, such as desirability function, distance function and mean squared error methods. With slight modifications in the upper and lower specification limits of the considered quality characteristics, and constraints of the non-linear optimization problem, it can be successfully applied to other processes in textile industry to determine their optimal parametric settings.

Reducing support loss in micromechanical ring resonators using phononic band-gap structures

Energy Technology Data Exchange (ETDEWEB)

Hsu, Feng-Chia; Huang, Tsun-Che; Wang, Chin-Hung; Chang, Pin [Industrial Technology Research Institute-South, Tainan 709, Taiwan (China); Hsu, Jin-Chen, E-mail: fengchiahsu@itri.org.t, E-mail: hsujc@yuntech.edu.t [Department of Mechanical Engineering, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan (China)

2011-09-21

In micromechanical resonators, energy loss via supports into the substrates may lead to a low quality factor. To eliminate the support loss, in this paper a phononic band-gap structure is employed. We demonstrate a design of phononic-crystal (PC) strips used to support extensional wine-glass mode ring resonators to increase the quality factor. The PC strips are introduced to stop elastic-wave propagation by the band-gap and deaf-band effects. Analyses of resonant characteristics of the ring resonators and the dispersion relations, eigenmodes, and transmission properties of the PC strips are presented. With the proposed resonator architecture, the finite-element simulations show that the leaky power is effectively reduced and the stored energy inside the resonators is enhanced simultaneously as the operating frequencies of the resonators are within the band gap or deaf bands. Realization of a high quality factor micromechanical ring resonator with minimized support loss is expected.

Reducing support loss in micromechanical ring resonators using phononic band-gap structures

International Nuclear Information System (INIS)

Hsu, Feng-Chia; Huang, Tsun-Che; Wang, Chin-Hung; Chang, Pin; Hsu, Jin-Chen

2011-01-01

In micromechanical resonators, energy loss via supports into the substrates may lead to a low quality factor. To eliminate the support loss, in this paper a phononic band-gap structure is employed. We demonstrate a design of phononic-crystal (PC) strips used to support extensional wine-glass mode ring resonators to increase the quality factor. The PC strips are introduced to stop elastic-wave propagation by the band-gap and deaf-band effects. Analyses of resonant characteristics of the ring resonators and the dispersion relations, eigenmodes, and transmission properties of the PC strips are presented. With the proposed resonator architecture, the finite-element simulations show that the leaky power is effectively reduced and the stored energy inside the resonators is enhanced simultaneously as the operating frequencies of the resonators are within the band gap or deaf bands. Realization of a high quality factor micromechanical ring resonator with minimized support loss is expected.

Application of sensitivity analysis for optimized piping support design

International Nuclear Information System (INIS)

Tai, K.; Nakatogawa, T.; Hisada, T.; Noguchi, H.; Ichihashi, I.; Ogo, H.

1993-01-01

The objective of this study was to see if recent developments in non-linear sensitivity analysis could be applied to the design of nuclear piping systems which use non-linear supports and to develop a practical method of designing such piping systems. In the study presented in this paper, the seismic response of a typical piping system was analyzed using a dynamic non-linear FEM and a sensitivity analysis was carried out. Then optimization for the design of the piping system supports was investigated, selecting the support location and yield load of the non-linear supports (bi-linear model) as main design parameters. It was concluded that the optimized design was a matter of combining overall system reliability with the achievement of an efficient damping effect from the non-linear supports. The analysis also demonstrated sensitivity factors are useful in the planning stage of support design. (author)

Optimized support vector regression for drilling rate of penetration estimation

Science.gov (United States)

Bodaghi, Asadollah; Ansari, Hamid Reza; Gholami, Mahsa

2015-12-01

In the petroleum industry, drilling optimization involves the selection of operating conditions for achieving the desired depth with the minimum expenditure while requirements of personal safety, environment protection, adequate information of penetrated formations and productivity are fulfilled. Since drilling optimization is highly dependent on the rate of penetration (ROP), estimation of this parameter is of great importance during well planning. In this research, a novel approach called `optimized support vector regression' is employed for making a formulation between input variables and ROP. Algorithms used for optimizing the support vector regression are the genetic algorithm (GA) and the cuckoo search algorithm (CS). Optimization implementation improved the support vector regression performance by virtue of selecting proper values for its parameters. In order to evaluate the ability of optimization algorithms in enhancing SVR performance, their results were compared to the hybrid of pattern search and grid search (HPG) which is conventionally employed for optimizing SVR. The results demonstrated that the CS algorithm achieved further improvement on prediction accuracy of SVR compared to the GA and HPG as well. Moreover, the predictive model derived from back propagation neural network (BPNN), which is the traditional approach for estimating ROP, is selected for comparisons with CSSVR. The comparative results revealed the superiority of CSSVR. This study inferred that CSSVR is a viable option for precise estimation of ROP.

Quantum optimization for training support vector machines.

Science.gov (United States)

Anguita, Davide; Ridella, Sandro; Rivieccio, Fabio; Zunino, Rodolfo

2003-01-01

Refined concepts, such as Rademacher estimates of model complexity and nonlinear criteria for weighting empirical classification errors, represent recent and promising approaches to characterize the generalization ability of Support Vector Machines (SVMs). The advantages of those techniques lie in both improving the SVM representation ability and yielding tighter generalization bounds. On the other hand, they often make Quadratic-Programming algorithms no longer applicable, and SVM training cannot benefit from efficient, specialized optimization techniques. The paper considers the application of Quantum Computing to solve the problem of effective SVM training, especially in the case of digital implementations. The presented research compares the behavioral aspects of conventional and enhanced SVMs; experiments in both a synthetic and real-world problems support the theoretical analysis. At the same time, the related differences between Quadratic-Programming and Quantum-based optimization techniques are considered.

Definitions of apical vaginal support loss: a systematic review.

Science.gov (United States)

Meister, Melanie R L; Sutcliffe, Siobhan; Lowder, Jerry L

2017-03-01

We sought to identify and summarize definitions of apical support loss utilized for inclusion, success, and failure in surgical trials for treatment of apical vaginal prolapse. Pelvic organ prolapse is a common condition affecting more than 3 million women in the US, and the prevalence is increasing. Prolapse may occur in the anterior compartment, posterior compartment or at the apex. Apical support is considered paramount to overall female pelvic organ support, yet apical support loss is often underrecognized and there are no guidelines for when an apical support procedure should be performed or incorporated into a procedure designed to address prolapse. A systematic literature search was performed in 8 search engines: PubMed 1946-, Embase 1947-, Cochrane Database of Systematic Reviews, Cochrane Database of Abstracts of Review Effects, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, Proquest Dissertations and Theses, and FirstSearch Proceedings, using key words for apical pelvic organ prolapse and apical suspension procedures through April 2016. Searches were limited to human beings using human filters and articles published in English. Study authors (M.R.L.M., J.L.L.) independently reviewed publications for inclusion based on predefined variables. Articles were eligible for inclusion if they satisfied any of the following criteria: (1) apical support loss was an inclusion criterion in the original study, (2) apical support loss was a surgical indication, or (3) an apical support procedure was performed as part of the primary surgery. A total of 4469 publications were identified. After review, 35 articles were included in the analysis. Prolapse-related inclusion criteria were: (1) apical prolapse (n = 20, 57.1%); (2) overall prolapse (n = 8, 22.8%); or (3) both (n = 6, 17.1%). Definitions of apical prolapse (relative to the hymen) included: (1) apical prolapse >-1 cm (n = 13, 50.0%); (2) apical prolapse >+1 cm (n = 7, 26.9%); (3) apical

Systematic design of photonic crystal structures using topology optimization: Low-loss waveguide bends

DEFF Research Database (Denmark)

Jensen, Jakob Søndergaard; Sigmund, Ole

2004-01-01

Topology optimization is a promising method for systematic design of optical devices. As an example, we demonstrate how the method can be used to design a 90degrees bend in a two-dimensional photonic crystal waveguide with a transmission loss of less than 0.3% in almost the entire frequency range...... of the guided mode. The method can directly be applied to the design of other optical devices, e.g., multiplexers and wave splitters, with optimized performance. (C) 2004 American Institute of Physics....

Optimization of the outer support in the ITER lower cryostat thermal shield

International Nuclear Information System (INIS)

Noh, C.H.; Chung, W.; Lim, J.; Lee, B.C.

2016-01-01

Highlights: • Design methodology for the ITER lower cryostat thermal shield support is described. • Design optimization is performed using the kriging meta-model. • Single plate support design is proposed as an alternative design. • Proposed design has 24% reduced weight compared with the initial design. - Abstract: ITER Lower Cryostat Thermal Shield (LCTS) is fixed to the cryostat floor by a thin flexible plate support. Double plate made of titanium alloy is adopted as a reference design. Double plate is effective to get structural reliability for the high inertia load and buckling load. Thin plate with titanium alloy has good flexibility to the thermal movement and reduces conduction heat load from cryostat floor to the thermal shield. Double plate support has enough structural margin. In addition, titanium alloy requires high cost for fabrication. Design optimization is required to save manufacturing expenses. In addition to the mass minimization, design modification from double plate to single plate is proposed, because welding of double plate is difficult due to narrow gap between two plates. In this paper, design process to find optimal design of LCTS support is described. The sensitivities of the design variables such as thickness, height, width and gap between two plates are investigated. Optimal design solution is obtained by Sequential Quadratic Programming (SQP) algorithm based on the meta-model developed by randomly selected experimental samples. Through the design optimization process, optimal designs of the LCTS support are obtained. The weight of the support plates can be reduced to 24% compared with the initial design.

Optimization of the outer support in the ITER lower cryostat thermal shield

Energy Technology Data Exchange (ETDEWEB)

Noh, C.H., E-mail: chnoh@nfri.re.kr [National Fusion Research Institute, Daejeon, 305-333 (Korea, Republic of); Korea Advanced Institute of Science and Technology, Daejeon, 305-338 (Korea, Republic of); Chung, W., E-mail: whchung@nfri.re.kr [National Fusion Research Institute, Daejeon, 305-333 (Korea, Republic of); Lim, J., E-mail: jongmin.lim@kaist.ac.kr [Korea Advanced Institute of Science and Technology, Daejeon, 305-338 (Korea, Republic of); Lee, B.C., E-mail: bclee@kaist.ac.kr [Korea Advanced Institute of Science and Technology, Daejeon, 305-338 (Korea, Republic of)

2016-02-15

Highlights: • Design methodology for the ITER lower cryostat thermal shield support is described. • Design optimization is performed using the kriging meta-model. • Single plate support design is proposed as an alternative design. • Proposed design has 24% reduced weight compared with the initial design. - Abstract: ITER Lower Cryostat Thermal Shield (LCTS) is fixed to the cryostat floor by a thin flexible plate support. Double plate made of titanium alloy is adopted as a reference design. Double plate is effective to get structural reliability for the high inertia load and buckling load. Thin plate with titanium alloy has good flexibility to the thermal movement and reduces conduction heat load from cryostat floor to the thermal shield. Double plate support has enough structural margin. In addition, titanium alloy requires high cost for fabrication. Design optimization is required to save manufacturing expenses. In addition to the mass minimization, design modification from double plate to single plate is proposed, because welding of double plate is difficult due to narrow gap between two plates. In this paper, design process to find optimal design of LCTS support is described. The sensitivities of the design variables such as thickness, height, width and gap between two plates are investigated. Optimal design solution is obtained by Sequential Quadratic Programming (SQP) algorithm based on the meta-model developed by randomly selected experimental samples. Through the design optimization process, optimal designs of the LCTS support are obtained. The weight of the support plates can be reduced to 24% compared with the initial design.

On the optimization of a CAPM portfolio using lower partial moments as measure of risk and using the possibility of safeguarding its loss

Science.gov (United States)

Spreitzer, U. W.; Reznik, V.

2007-05-01

Using a portfolio built from bonds (investment without volatility) and shares (investment with volatility) corresponding to the CAPM we calculate the possible loss of this portfolio. The loss is measured by a so-called lower partial moment of the rate of return of the portfolio. Using this loss, we optimize the composition of the portfolio with respect to this loss. Also we investigate the optimization of the portfolio when the loss can be underwritten by an insurance. Concerning the premium of this insurance contract, we show that when the premium is defined inadequate, e.g. proportional to the investment or proportional to the amount of investment in shares, the optimal portfolio consists only of investment in shares. When the premium is defined more suitable, e.g. proportional to the loss, the optimal portfolio is built by an investment in bonds and shares.

Defining the Optimal Dietary Approach for Safe, Effective and Sustainable Weight Loss in Overweight and Obese Adults

Directory of Open Access Journals (Sweden)

Chrysi Koliaki

2018-06-01

Full Text Available Various dietary approaches with different caloric content and macronutrient composition have been recommended to treat obesity in adults. Although their safety and efficacy profile has been assessed in numerous randomized clinical trials, reviews and meta-analyses, the characteristics of the optimal dietary weight loss strategy remain controversial. This mini-review will provide general principles and practical recommendations for the dietary management of obesity and will further explore the components of the optimal dietary intervention. To this end, various dietary plans are critically discussed, including low-fat diets, low-carbohydrate diets, high-protein diets, very low-calorie diets with meal replacements, Mediterranean diet, and diets with intermittent energy restriction. As a general principle, the optimal diet to treat obesity should be safe, efficacious, healthy and nutritionally adequate, culturally acceptable and economically affordable, and should ensure long-term compliance and maintenance of weight loss. Setting realistic goals for weight loss and pursuing a balanced dietary plan tailored to individual needs, preferences, and medical conditions, are the key principles to facilitate weight loss in obese patients and most importantly reduce their overall cardiometabolic risk and other obesity-related comorbidities.

Optimally matching support and perceived spousal sensitivity.

Science.gov (United States)

Cutrona, Carolyn E; Shaffer, Philip A; Wesner, Kristin A; Gardner, Kelli A

2007-12-01

Partner sensitivity is an important antecedent of both intimacy (H. T. Reis & P. Shaver, 1988) and attachment (M. D. S. Ainsworth, 1989). On the basis of the optimal matching model of social support (C. E. Cutrona & D. Russell, 1990), support behaviors that "matched" the support goals of the stressed individual were predicted to lead to the perception of partner sensitivity. Predictions were tested with 59 married couples, who engaged in a videotaped self-disclosure task. Matching support was defined as the disclosure of emotions followed by emotional support or a request for information followed by informational support. Partial evidence was found for the predictions. Matching support following the disclosure of emotions was predictive of perceived partner sensitivity. Mismatched support following the disclosure of emotions predicted lower marital satisfaction, through the mediation of partner sensitivity. Matching support following a request for information was not predictive of perceived partner sensitivity, but negative partner responses (e.g., criticism or sarcasm) following a request for information negatively predicted perceptions of partner sensitivity. The importance of considering the context of support transactions is discussed.

Smoothing optimization of supporting quadratic surfaces with Zernike polynomials

Science.gov (United States)

Zhang, Hang; Lu, Jiandong; Liu, Rui; Ma, Peifu

2018-03-01

A new optimization method to get a smooth freeform optical surface from an initial surface generated by the supporting quadratic method (SQM) is proposed. To smooth the initial surface, a 9-vertex system from the neighbor quadratic surface and the Zernike polynomials are employed to establish a linear equation system. A local optimized surface to the 9-vertex system can be build by solving the equations. Finally, a continuous smooth optimization surface is constructed by stitching the above algorithm on the whole initial surface. The spot corresponding to the optimized surface is no longer discrete pixels but a continuous distribution.

An Improved Method for Reconfiguring and Optimizing Electrical Active Distribution Network Using Evolutionary Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Nur Faziera Napis

2018-05-01

Full Text Available The presence of optimized distributed generation (DG with suitable distribution network reconfiguration (DNR in the electrical distribution network has an advantage for voltage support, power losses reduction, deferment of new transmission line and distribution structure and system stability improvement. However, installation of a DG unit at non-optimal size with non-optimal DNR may lead to higher power losses, power quality problem, voltage instability and incremental of operational cost. Thus, an appropriate DG and DNR planning are essential and are considered as an objective of this research. An effective heuristic optimization technique named as improved evolutionary particle swarm optimization (IEPSO is proposed in this research. The objective function is formulated to minimize the total power losses (TPL and to improve the voltage stability index (VSI. The voltage stability index is determined for three load demand levels namely light load, nominal load, and heavy load with proper optimal DNR and DG sizing. The performance of the proposed technique is compared with other optimization techniques, namely particle swarm optimization (PSO and iteration particle swarm optimization (IPSO. Four case studies on IEEE 33-bus and IEEE 69-bus distribution systems have been conducted to validate the effectiveness of the proposed IEPSO. The optimization results show that, the best achievement is done by IEPSO technique with power losses reduction up to 79.26%, and 58.41% improvement in the voltage stability index. Moreover, IEPSO has the fastest computational time for all load conditions as compared to other algorithms.

Framatome ANP outage optimization support solutions

International Nuclear Information System (INIS)

Bombail, Jean Paul

2003-01-01

Over the last several years, leading plant operators have demonstrated that availability factors can be improved while safety and reliability can be enhanced on a long-term basis and operating costs reduced. Outage optimization is the new term being used to describe these long-term initiatives through which a variety of measures aimed at shortening scheduled plant outages have been developed and successfully implemented by these leaders working with their service providers who were introducing new technologies and process improvements. Following the leaders, all operators now have ambitious outage optimization plans and the median and average outage duration are decreasing world-wide. Future objectives are even more stringent and must include plant upgrades and component replacements being performed for life extension of plant operation. Outage optimization covers a broad range of activities from modifications of plant systems to faster cool down rates to human behavior improvements. It has been proven to reduce costs, avoid unplanned outages and thus support plant availability and help to ensure the utility's competitive position in the marketplace

Rotational loss of a ring-shaped flywheel supported by high Tc superconducting levitation

International Nuclear Information System (INIS)

Teshima, Hidekazu; Tawara, Taichi; Shimada, Ryuichi.

1997-01-01

This paper describes the experimental results for the rotational loss of a ring-shaped flywheel supported by high T c superconducting levitation. Superconducting levitation is appropriate for rotating a ring-shaped flywheel which has neither shaft nor hub because it is a non-contact and automatically stable levitation without any control systems. The rotational loss has been investigated using a small-scaled experimental machine consisting of 16 bulk superconductors 46 mm in diameter and a ring-shaped flywheel about 300 mm in diameter. The rotational loss decreased as the levitation gap height increased. In low-speed rotational regions, the rotational loss was in proportion to the rotation speed and depended more on the levitation gap. In high-speed rotational regions, the rotational loss was in proportion to the third power of the rotation speed and depended less on the levitation gap. The cubic rotational loss in He was reduced to one-fifth of that in air. The magnetic field pinned in bulk superconductors induces a loss in the materials composing the ring-shaped flywheel. The rotational loss of a ring-shaped flywheel supported by superconducting levitation can be reduced by improving the uniformity of the magnetic fields along the ring, enlargement of the bulk superconductor(s), and densely arranging the bulk superconductors. (author)

4500 V SPT+ IGBT optimization on static and dynamic losses

International Nuclear Information System (INIS)

Dai Qingyun; Tian Xiaoli; Zhang Wenliang; Lu Shuojin; Zhu Yangjun

2015-01-01

This paper concerns the need for improving the static and dynamic performance of the high voltage insulated gate bipolar transistor (HV IGBTs). A novel structure with a carrier stored layer on the cathode side, known as an enhanced planar IGBT of the 4500 V voltage class is investigated. With the adoption of a soft punch through (SPT) concept as the vertical structure and an enhanced planar concept as the top structure, signed as SPT + IGBT, the simulation results indicate the turn-off switching waveform of the 4500 V SPT + IGBT is soft and also realizes an improved trade-off relationship between on-state voltage drop (V on ) and turn-off loss (E off ) in comparison with the SPT IGBT. Attention is also paid to the influences caused by different carrier stored layer doping dose on static and dynamic performances, to optimize on-state and switching losses of SPT + IGBT. (paper)

Intelligent Decision Support in Proportional–Stop-Loss Reinsurance Using Multiple Attribute Decision-Making (MADM

Directory of Open Access Journals (Sweden)

Shirley Jie Xuan Wang

2017-11-01

Full Text Available This article addresses the possibility of incorporating intelligent decision support systems into reinsurance decision-making. This involves the insurance company and the reinsurance company, and is negotiated through reinsurance intermediaries. The article proposes a decision flow to model the reinsurance design and selection process. This article focuses on adopting more than one optimality criteria under a more generic combinational design of commonly used reinsurance products, i.e., proportional reinsurance and stop-loss reinsurance. In terms of methodology, the significant contribution of the study the incorporation of the well-established decision analysis tool multiple-attribute decision-making (MADM into the modelling of reinsurance selection. To illustrate the feasibility of incorporating intelligent decision supporting systems in the reinsurance market, the study includes a numerical case study using the simulation software @Risk in modeling insurance claims, as well as programming in MATLAB to realize MADM. A list of managerial implications could be drawn from the case study results. Most importantly, when choosing the most appropriate type of reinsurance, insurance companies should base their decisions on multiple measurements instead of single-criteria decision-making models so that their decisions may be more robust.

Watershed Management Optimization Support Tool (WMOST) v3: Theoretical Documentation

Science.gov (United States)

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that facilitates integrated water management at the local or small watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed context, accounting fo...

Measuring Information Loss in Managerial Decision

Czech Academy of Sciences Publication Activity Database

Volf, Petr

2016-01-01

Roč. 1, č. 1 (2016), s. 26-32 ISSN 2414-6498 R&D Projects: GA ČR GA13-14445S Institutional support: RVO:67985556 Keywords : stochastic optimization * Gini index * newsvendor problem * information loss Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2016/SI/volf-0456860.pdf

AngelStow: A Commercial Optimization-Based Decision Support Tool for Stowage Planning

DEFF Research Database (Denmark)

Delgado-Ortegon, Alberto; Jensen, Rune Møller; Guilbert, Nicolas

save port fees, optimize use of vessel capacity, and reduce bunker consumption. Stowage Coordinators (SCs) produce these plans manually with the help of graphical tools, but high-quality SPs are hard to generate with the limited support they provide. In this abstract, we introduce AngelStow which...... is a commercial optimization-based decision support tool for stowing container vessels developed in collaboration between Ange Optimization and The IT University of Copenhagen. The tool assists SCs in the process of generating SPs interactively, focusing on satisfying and optimizing constraints and objectives...... that are tedious to deal with for humans, while letting the SCs use their expertise to deal with hard combinatorial objectives and corner cases....

An Optimal Domestic Electric Vehicle Charging Strategy for Reducing Network Transmission Loss While Taking Seasonal Factors into Consideration

Directory of Open Access Journals (Sweden)

Yuancheng Zhao

2018-01-01

Full Text Available With the rapid growth of domestic electric vehicle charging loads, the peak-valley gap and power fluctuation rate of power systems increase sharply, which can lead to the increase of network losses and energy efficiency reduction. This paper tries to regulate network loads and reduce power system transmission loss by optimizing domestic electric vehicle charging loads. In this paper, a domestic electric vehicle charging loads model is first developed by analyzing the key factors that can affect users’ charging behavior. Subsequently, the Monte Carlo method is proposed to simulate the power consumption of a cluster of domestic electric vehicles. After that, an optimal electric vehicle charging strategy based on the 0-1 integer programming is presented to regulate network daily loads. Finally, by taking the IEEE33 distributed power system as an example, this paper tries to verify the efficacy of the proposed optimal charging strategy and the necessity for considering seasonal factors when scheduling electric vehicle charging loads. Simulation results show that the proposed 0-1 integer programming method does have good performance in reducing the network peak-valley gap, voltage fluctuation rate, and transmission loss. Moreover, it has some potential to further reduce power system transmission loss when seasonal factors are considered.

Reliability Based Optimization of Fire Protection

DEFF Research Database (Denmark)

Thoft-Christensen, Palle

fire protection (PFP) of firewalls and structural members. The paper is partly based on research performed within the EU supported research project B/E-4359 "Optimized Fire Safety of Offshore Structures" and partly on research supported by the Danish Technical Research Council (see Thoft-Christensen [1......]). Special emphasis is put on the optimization software developed within the project.......It is well known that fire is one of the major risks of serious damage or total loss of several types of structures such as nuclear installations, buildings, offshore platforms/topsides etc. This paper presents a methodology and software for reliability based optimization of the layout of passive...

Effect of perceived social support and dispositional optimism on the depression of burn patients.

Science.gov (United States)

He, Fei; Zhou, Qin; Zhao, Zhijing; Zhang, Yuan; Guan, Hao

2016-06-01

Burn wounds have a significant impact on the mental health of patients. This study aimed to investigate the impact of perceived social support and dispositional optimism on depression of burn patients. A total of 246 burn patients accomplished the Multidimensional Scale of Perceived Social Support, the Revised Life Orientation Test, and Depression Scale. The results revealed that both perceived social support and optimism were significantly correlated with depression. Structural equation modeling indicated that optimism partially mediated the relationship between perceived social support and depression. Implications for prevention of depression in burn patients were discussed. © The Author(s) 2014.

Short-Term Wind Speed Forecasting Using Support Vector Regression Optimized by Cuckoo Optimization Algorithm

Directory of Open Access Journals (Sweden)

Jianzhou Wang

2015-01-01

Full Text Available This paper develops an effectively intelligent model to forecast short-term wind speed series. A hybrid forecasting technique is proposed based on recurrence plot (RP and optimized support vector regression (SVR. Wind caused by the interaction of meteorological systems makes itself extremely unsteady and difficult to forecast. To understand the wind system, the wind speed series is analyzed using RP. Then, the SVR model is employed to forecast wind speed, in which the input variables are selected by RP, and two crucial parameters, including the penalties factor and gamma of the kernel function RBF, are optimized by various optimization algorithms. Those optimized algorithms are genetic algorithm (GA, particle swarm optimization algorithm (PSO, and cuckoo optimization algorithm (COA. Finally, the optimized SVR models, including COA-SVR, PSO-SVR, and GA-SVR, are evaluated based on some criteria and a hypothesis test. The experimental results show that (1 analysis of RP reveals that wind speed has short-term predictability on a short-term time scale, (2 the performance of the COA-SVR model is superior to that of the PSO-SVR and GA-SVR methods, especially for the jumping samplings, and (3 the COA-SVR method is statistically robust in multi-step-ahead prediction and can be applied to practical wind farm applications.

Optimal reconfiguration-based dynamic tariff for congestion management and line loss reduction in distribution networks

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei; Cheng, Lin

2016-01-01

This paper presents an optimal reconfiguration-based dynamic tariff (DT) method for congestion management and line loss reduction in distribution networks with high penetration of electric vehicles. In the proposed DT concept, feeder reconfiguration (FR) is employed through mixed integer programm...

Variation in body mass dynamics among sites in Black Brant Branta bernicla nigricans supports adaptivity of mass loss during moult

Science.gov (United States)

Fondell, Thomas F.; Flint, Paul L.; Schmutz, Joel A.; Schamber, Jason L.; Nicolai, Christopher A.

2013-01-01

Birds employ varying strategies to accommodate the energetic demands of moult, one important example being changes in body mass. To understand better their physiological and ecological significance, we tested three hypotheses concerning body mass dynamics during moult. We studied Black Brant in 2006 and 2007 moulting at three sites in Alaska which varied in food availability, breeding status and whether geese undertook a moult migration. First we predicted that if mass loss during moult were simply the result of inadequate food resources then mass loss would be highest where food was least available. Secondly, we predicted that if mass loss during moult were adaptive, allowing birds to reduce activity during moult, then birds would gain mass prior to moult where feeding conditions allowed and mass loss would be positively related to mass at moult initiation. Thirdly, we predicted that if mass loss during moult were adaptive, allowing birds to regain flight sooner, then across sites and groups, mass at the end of the flightless period would converge on a theoretical optimum, i.e. the mass that permits the earliest possible return to flight. Mass loss was greatest where food was most available and thus our results did not support the prediction that mass loss resulted from inadequate food availability. Mass at moult initiation was positively related to both food availability and mass loss. In addition, among sites and years, variation in mass was high at moult initiation but greatly reduced at the end of the flightless period, appearing to converge. Thus, our results supported multiple predictions that mass loss during moult was adaptive and that the optimal moulting strategy was to gain mass prior to the flightless period, then through behavioural modifications use these body reserves to reduce activity and in so doing also reduce wing loading. Geese that undertook a moult migration initiated moult at the highest mass, indicating that they were more than able to

The Great Recession and Job Loss Spillovers : Impact of Tradable Employment Shocks on Supporting Services

OpenAIRE

Nguyen, Ha; Rezaei, Shawheen

2016-01-01

This paper explores the spillover effects of job losses via input linkages during the Great Recession. Exploiting exogenous variation in tradable employment shocks across U.S. counties, the paper finds that job losses in the tradable sectors cause further job losses in local supporting services. The result is not due to reverse causation, construction job losses, or credit shortages. In ad...

A Method to Optimize Geometric Errors of Machine Tool based on SNR Quality Loss Function and Correlation Analysis

Directory of Open Access Journals (Sweden)

Cai Ligang

2017-01-01

Full Text Available Instead improving the accuracy of machine tool by increasing the precision of key components level blindly in the production process, the method of combination of SNR quality loss function and machine tool geometric error correlation analysis to optimize five-axis machine tool geometric errors will be adopted. Firstly, the homogeneous transformation matrix method will be used to build five-axis machine tool geometric error modeling. Secondly, the SNR quality loss function will be used for cost modeling. And then, machine tool accuracy optimal objective function will be established based on the correlation analysis. Finally, ISIGHT combined with MATLAB will be applied to optimize each error. The results show that this method is reasonable and appropriate to relax the range of tolerance values, so as to reduce the manufacturing cost of machine tools.

Chaotic improved PSO-based multi-objective optimization for minimization of power losses and L index in power systems

International Nuclear Information System (INIS)

Chen, Gonggui; Liu, Lilan; Song, Peizhu; Du, Yangwei

2014-01-01

Highlights: • New method for MOORPD problem using MOCIPSO and MOIPSO approaches. • Constrain-prior Pareto-dominance method is proposed to meet the constraints. • The limits of the apparent power flow of transmission line are considered. • MOORPD model is built up for MOORPD problem. • The achieved results by MOCIPSO and MOIPSO approaches are better than MOPSO method. - Abstract: Multi-objective optimal reactive power dispatch (MOORPD) seeks to not only minimize power losses, but also improve the stability of power system simultaneously. In this paper, the static voltage stability enhancement is achieved through incorporating L index in MOORPD problem. Chaotic improved PSO-based multi-objective optimization (MOCIPSO) and improved PSO-based multi-objective optimization (MOIPSO) approaches are proposed for solving complex multi-objective, mixed integer nonlinear problems such as minimization of power losses and L index in power systems simultaneously. In MOCIPSO and MOIPSO based optimization approaches, crossover operator is proposed to enhance PSO diversity and improve their global searching capability, and for MOCIPSO based optimization approach, chaotic sequences based on logistic map instead of random sequences is introduced to PSO for enhancing exploitation capability. In the two approaches, constrain-prior Pareto-dominance method (CPM) is proposed to meet the inequality constraints on state variables, the sorting and crowding distance methods are considered to maintain a well distributed Pareto optimal solutions, and moreover, fuzzy set theory is employed to extract the best compromise solution over the Pareto optimal curve. The proposed approaches have been examined and tested in the IEEE 30 bus and the IEEE 57 bus power systems. The performances of MOCIPSO, MOIPSO, and multi-objective PSO (MOPSO) approaches are compared with respect to multi-objective performance measures. The simulation results are promising and confirm the ability of MOCIPSO and

Social inequalities in adolescent depression: the role of parental social support and optimism.

Science.gov (United States)

Piko, Bettina F; Luszczynska, Aleksandra; Fitzpatrick, Kevin M

2013-08-01

Interpersonal theory suggests relationships between socio-economic status (SES) and adolescent psychopathology mediated by negative parenting. This study examines the role of perceived parental social support and optimism in understanding adolescents' depression and self-rated health among a sample of Hungarian youth. Using a self-administered questionnaire, data (N = 881) were collected from high-school students (14-20 years old) in Szeged, Hungary (a regional centre in the southeastern region, near to the Serbian border, with a population of 170,000 inhabitants). To analyse the overall structure of the relationship between objective/subjective SES, parental support, optimism and health outcomes (depression, self-perceived health), structural equation modelling (SEM) was employed. Findings suggest the following: (1) SES variables generate social inequalities in adolescent depression through parental social support, particularly maternal support; and (2) parents provide youths with different levels of social support that in turn may strengthen or weaken optimism during the socialization process. In addressing depression prevention and treatment, we may want to take into account socio-economic differences in social networks and levels of optimism, which may influence youths' psychosocial adjustment and development of psychopathology.

Optimal Tax-Timing and Asset Allocation when Tax Rebates on Capital Losses are Limited

DEFF Research Database (Denmark)

Marekwica, Marcel

2012-01-01

to realize capital gains immediately and pay capital gain taxes to regain the option to use potential future losses against a higher tax rate. This incentive adds an entirely new and as yet unstudied dimension to the portfolio problem. It causes risk averse investors to hold more equity and attain higher......This article studies the portfolio problem with realization-based capital gain taxation when limited amounts of losses qualify for tax rebate payments, as is the case under current US tax law. When the tax rate applicable to realized losses exceeds that on realized capital gains, it can be optimal...... welfare levels than is the case when trading under a tax system that seeks to collect the same amount of taxes, but does not allow for tax rebate payments. This is because the benefit to these investors from having their losses subsidized is greater than the suffering from having profits taxed at a higher...

A smartphone-supported weight loss program: design of the ENGAGED randomized controlled trial

Directory of Open Access Journals (Sweden)

Pellegrini Christine A

2012-11-01

Full Text Available Abstract Background Obesity remains a major public health challenge, demanding cost-effective and scalable weight management programs. Delivering key treatment components via mobile technology offers a potential way to reduce expensive in-person contact, thereby lowering the cost and burden of intensive weight loss programs. The ENGAGED study is a theory-guided, randomized controlled trial designed to examine the feasibility and efficacy of an abbreviated smartphone-supported weight loss program. Methods/design Ninety-six obese adults (BMI 30–39.9 kg/m2 will be randomized to one of three treatment conditions: (1 standard behavioral weight loss (STND, (2 technology-supported behavioral weight loss (TECH; or (3 self-guided behavioral weight loss (SELF. All groups will aim to achieve a 7% weight loss goal by reducing calorie and fat intake and progressively increasing moderate intensity physical activity to 175 minutes/week. STND and TECH will attend 8 group sessions and receive regular coaching calls during the first 6 months of the intervention; SELF will receive the Group Lifestyle Balance Program DVD’s and will not receive coaching calls. During months 1–6, TECH will use a specially designed smartphone application to monitor dietary intake, body weight, and objectively measured physical activity (obtained from a Blue-tooth enabled accelerometer. STND and SELF will self-monitor on paper diaries. Linear mixed modeling will be used to examine group differences on weight loss at months 3, 6, and 12. Self-monitoring adherence and diet and activity goal attainment will be tested as mediators. Discussion ENGAGED is an innovative weight loss intervention that integrates theory with emerging mobile technologies. We hypothesize that TECH, as compared to STND and SELF, will result in greater weight loss by virtue of improved behavioral adherence and goal achievement. Trial registration NCT01051713

Operator support through modern optimal estimation and control

International Nuclear Information System (INIS)

Burdick, G.R.

1980-01-01

Applications of Modern Optimal Estimation and Control Theories are late in coming to the nuclear industry. Some features of the theories that might be exploited in nuclear systems applications are described. Activities at the Idaho National Engineering Laboratory relating to operator support using those theories are identified and some implementation challenges are discussed

Rotational loss of a ring-shaped flywheel supported by high T{sub c} superconducting levitation

Energy Technology Data Exchange (ETDEWEB)

Teshima, Hidekazu [Nippon Steel Corp., Kawasaki, Kanagawa (Japan). Advanced Materials and Technology Research Labs.; Tawara, Taichi; Shimada, Ryuichi

1997-08-01

This paper describes the experimental results for the rotational loss of a ring-shaped flywheel supported by high T{sub c} superconducting levitation. Superconducting levitation is appropriate for rotating a ring-shaped flywheel which has neither shaft nor hub because it is a non-contact and automatically stable levitation without any control systems. The rotational loss has been investigated using a small-scaled experimental machine consisting of 16 bulk superconductors 46 mm in diameter and a ring-shaped flywheel about 300 mm in diameter. The rotational loss decreased as the levitation gap height increased. In low-speed rotational regions, the rotational loss was in proportion to the rotation speed and depended more on the levitation gap. In high-speed rotational regions, the rotational loss was in proportion to the third power of the rotation speed and depended less on the levitation gap. The cubic rotational loss in He was reduced to one-fifth of that in air. The magnetic field pinned in bulk superconductors induces a loss in the materials composing the ring-shaped flywheel. The rotational loss of a ring-shaped flywheel supported by superconducting levitation can be reduced by improving the uniformity of the magnetic fields along the ring, enlargement of the bulk superconductor(s), and densely arranging the bulk superconductors. (author)

Pipe support optimization in nuclear power plants

International Nuclear Information System (INIS)

Cleveland, A.B.; Kalyanam, N.

1984-01-01

A typical 1000 MWe nuclear power plant consists of 80,000 to 100,000 feet of piping which must be designed to withstand earthquake shock. For the required ground motion, seismic response spectra are developed for safety-related structures. These curves are used in the dynamic analysis of piping systems with pipe-stress analysis computer codes. To satisfy applicable Code requirements, the piping systems also require analysis for weight, thermal and possibly other lasting conditions. Bechtel Power Corporation has developed a design program called SLAM (Support Location Algorithm) for optimizing pipe support locations and types (rigid, spring, snubber, axial, lateral, etc.) while satisfying userspecified parameters such as locations, load combinations, stress and load allowables, pipe displacement and cost. This paper describes SLAM, its features, applications and benefits

Optimized evaporative cooling for sodium Bose-Einstein condensation against three-body loss

International Nuclear Information System (INIS)

Shobu, Takahiko; Yamaoka, Hironobu; Imai, Hiromitsu; Morinaga, Atsuo; Yamashita, Makoto

2011-01-01

We report on a highly efficient evaporative cooling optimized experimentally. We successfully created sodium Bose-Einstein condensates with 6.4x10 7 atoms starting from 6.6x10 9 thermal atoms trapped in a magnetic trap by employing a fast linear sweep of radio frequency at the final stage of evaporative cooling so as to overcome the serious three-body losses. The experimental results such as the cooling trajectory and the condensate growth quantitatively agree with the numerical simulations of evaporative cooling on the basis of the kinetic theory of a Bose gas carefully taking into account our specific experimental conditions. We further discuss theoretically a possibility of producing large condensates, more than 10 8 sodium atoms, by simply increasing the number of initial thermal trapped atoms and the corresponding optimization of evaporative cooling.

Sensitive parameters' optimization of the permanent magnet supporting mechanism

Energy Technology Data Exchange (ETDEWEB)

Liu, Yongguang; Gao, Xiaohui; Wang, Yixuan; Yang, Xiaowei [Beihang University, Beijing (China)

2014-07-15

The fast development of the ultra-high speed vertical rotor promotes the study and exploration for the supporting mechanism. It has become the focus of research that how to improve the speed and overcome the vibration when the rotors pass through the low-order critical frequencies. This paper introduces a kind of permanent magnet (PM) supporting mechanism and describes an optimization method of its sensitive parameters, which can make the vertical rotor system reach 80000 r/min smoothly. Firstly we find the sensitive parameters through analyzing the rotor's features in the process of achieving high-speed, then, study these sensitive parameters and summarize the regularities with the method of combining the experiment and the finite element method (FEM), at last, achieve the optimization method of these parameters. That will not only get a stable effect of raising speed and shorten the debugging time greatly, but also promote the extensive application of the PM supporting mechanism in the ultra-high speed vertical rotors.

Optimization-based decision support systems for planning problems in processing industries

NARCIS (Netherlands)

Claassen, G.D.H.

2014-01-01

Summary

Optimization-based decision support systems for planning problems in processing industries

Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in

Rural health professionals' perspectives on providing grief and loss support in cancer care.

Science.gov (United States)

Breen, L J; O'Connor, M

2013-11-01

Research demonstrates considerable inequalities in service delivery and health outcomes for people with cancer living outside large metropolitan cities. Semi-structured interviews with 11 professionals providing grief and loss support for people with cancer and their families in rural, regional, and remote areas Western Australia revealed the challenges they faced in delivering such support. The data are presented in four themes - Inequity of regional versus metropolitan services, Strain of the 'Jack of all trades' role, Constraints to accessing professional development, and Challenges in delivering post-bereavement services. These challenges are likely to be of growing concern given that populations are declining in rural areas as Australia becomes increasingly urban. The findings have implications in enhancing the loss and grief support services available in rural, regional, and remote Western Australia, including those grieving the death of a loved one through cancer. © 2013 John Wiley & Sons Ltd.

The solution of certain loss of contact between a plate and unilateral supports

Directory of Open Access Journals (Sweden)

Sompornjaroensuk Yos

2007-01-01

Full Text Available This paper examines the loss of contact between a square plate and the unilateral supports under uniformly distributed load. Since the plate is rested on the unilateral supports, it will have the regions of lost contact between a plate and the supports due to the absence of restraining corner force at the plate corners. This leads to the mixed boundary conditions and these conditions are then written in the form of dual-series equations which can further be reduced to a Fredholm integral equation by taking advantage of finite Hankel transform technique. Numerical results are given for the deflections of free edge and deflections along the middle line of the plate with deferent values of the Poisson’s ratio. In addition, the deflection surface is also presented. From the investigation, it can be indicated that the loss of contact is decreased upon the increasing Poisson’s ratio.

Can Hypocaloric, High-Protein Nutrition Support Be Used in Complicated Bariatric Patients to Promote Weight Loss?

Science.gov (United States)

Beebe, Mara Lee; Crowley, Nina

2015-08-01

Bariatric surgery, an effective treatment for morbid obesity, may result in complications that require nutrition support. Common goals for nutrition support in post-bariatric surgery patients include nutrition repletion, avoiding overfeeding, preserving lean body mass, and promoting wound healing. It is often questioned if continued weight loss can be part of the nutrition goals and if weight loss is safe for patients who become critically ill following bariatric surgery. Recent clinical practice guidelines from both the American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) and Society of Critical Care Medicine (SCCM) have recommended the use of hypocaloric, high-protein nutrition support in both critically and non-critically ill obese patients. Hypocaloric feedings of 50%-70% of estimated energy requirements based on predictive equations or obesity. Two small studies in complicated post-bariatric surgery patients requiring nutrition support have shown that the strategy of hypocaloric, high-protein feedings can result in positive outcomes, including positive nitrogen balance, wound healing, weight loss, and successful transition to oral diets. Additional research, including large, randomized studies, is still needed to validate these findings. However, based on a review of available clinical practice guidelines, predictive equations, indirect calorimetry, case studies, and systematic reviews, hypocaloric, high-protein nutrition support appears to at least be equal to eucaloric feedings and may be a useful tool for clinicians to achieve continued weight loss in complicated bariatric surgery patients requiring nutrition support. © 2015 American Society for Parenteral and Enteral Nutrition.

Optimal design of an in-situ bioremediation system using support vector machine and particle swarm optimization

Science.gov (United States)

ch, Sudheer; Kumar, Deepak; Prasad, Ram Kailash; Mathur, Shashi

2013-08-01

A methodology based on support vector machine and particle swarm optimization techniques (SVM-PSO) was used in this study to determine an optimal pumping rate and well location to achieve an optimal cost of an in-situ bioremediation system. In the first stage of the two stage methodology suggested for optimal in-situ bioremediation design, the optimal number of wells and their locations was determined from preselected candidate well locations. The pumping rate and well location in the first stage were subsequently optimized in the second stage of the methodology. The highly nonlinear system of equations governing in-situ bioremediation comprises the equations of flow and solute transport coupled with relevant biodegradation kinetics. A finite difference model was developed to simulate the process of in-situ bioremediation using an Alternate-Direction Implicit technique. This developed model (BIOFDM) yields the spatial and temporal distribution of contaminant concentration for predefined initial and boundary conditions. BIOFDM was later validated by comparing the simulated results with those obtained using BIOPLUME III for the case study of Shieh and Peralta (2005). The results were found to be in close agreement. Moreover, since the solution of the highly nonlinear equation otherwise requires significant computational effort, the computational burden in this study was managed within a practical time frame by replacing the BIOFDM model with a trained SVM model. Support Vector Machine which generates fast solutions in real time was considered to be a universal function approximator in the study. Apart from reducing the computational burden, this technique generates a set of near optimal solutions (instead of a single optimal solution) and creates a re-usable data base that could be used to address many other management problems. Besides this, the search for an optimal pumping pattern was directed by a simple PSO technique and a penalty parameter approach was adopted

Optimal design of an in-situ bioremediation system using support vector machine and particle swarm optimization.

Science.gov (United States)

ch, Sudheer; Kumar, Deepak; Prasad, Ram Kailash; Mathur, Shashi

2013-08-01

A methodology based on support vector machine and particle swarm optimization techniques (SVM-PSO) was used in this study to determine an optimal pumping rate and well location to achieve an optimal cost of an in-situ bioremediation system. In the first stage of the two stage methodology suggested for optimal in-situ bioremediation design, the optimal number of wells and their locations was determined from preselected candidate well locations. The pumping rate and well location in the first stage were subsequently optimized in the second stage of the methodology. The highly nonlinear system of equations governing in-situ bioremediation comprises the equations of flow and solute transport coupled with relevant biodegradation kinetics. A finite difference model was developed to simulate the process of in-situ bioremediation using an Alternate-Direction Implicit technique. This developed model (BIOFDM) yields the spatial and temporal distribution of contaminant concentration for predefined initial and boundary conditions. BIOFDM was later validated by comparing the simulated results with those obtained using BIOPLUME III for the case study of Shieh and Peralta (2005). The results were found to be in close agreement. Moreover, since the solution of the highly nonlinear equation otherwise requires significant computational effort, the computational burden in this study was managed within a practical time frame by replacing the BIOFDM model with a trained SVM model. Support Vector Machine which generates fast solutions in real time was considered to be a universal function approximator in the study. Apart from reducing the computational burden, this technique generates a set of near optimal solutions (instead of a single optimal solution) and creates a re-usable data base that could be used to address many other management problems. Besides this, the search for an optimal pumping pattern was directed by a simple PSO technique and a penalty parameter approach was adopted

Optimal Scheduling of Integrated Energy Systems with Combined Heat and Power Generation, Photovoltaic and Energy Storage Considering Battery Lifetime Loss

Directory of Open Access Journals (Sweden)

Yongli Wang

2018-06-01

Full Text Available Integrated energy systems (IESs are considered a trending solution for the energy crisis and environmental problems. However, the diversity of energy sources and the complexity of the IES have brought challenges to the economic operation of IESs. Aiming at achieving optimal scheduling of components, an IES operation optimization model including photovoltaic, combined heat and power generation system (CHP and battery energy storage is developed in this paper. The goal of the optimization model is to minimize the operation cost under the system constraints. For the optimization process, an optimization principle is conducted, which achieves maximized utilization of photovoltaic by adjusting the controllable units such as energy storage and gas turbine, as well as taking into account the battery lifetime loss. In addition, an integrated energy system project is taken as a research case to validate the effectiveness of the model via the improved differential evolution algorithm (IDEA. The comparison between IDEA and a traditional differential evolution algorithm shows that IDEA could find the optimal solution faster, owing to the double variation differential strategy. The simulation results in three different battery states which show that the battery lifetime loss is an inevitable factor in the optimization model, and the optimized operation cost in 2016 drastically decreased compared with actual operation data.

Development of Near Optimal Rule-Based Control for Plug-In Hybrid Electric Vehicles Taking into Account Drivetrain Component Losses

Directory of Open Access Journals (Sweden)

Hanho Son

2016-05-01

Full Text Available A near-optimal rule-based mode control (RBC strategy was proposed for a target plug-in hybrid electric vehicle (PHEV taking into account the drivetrain losses. Individual loss models were developed for drivetrain components including the gears, planetary gear (PG, bearings, and oil pump, based on experimental data and mathematical governing equations. Also, a loss model for the power electronic system was constructed, including loss from the motor-generator while rotating in the unloaded state. To evaluate the effect of the drivetrain losses on the operating mode control strategy, backward simulations were performed using dynamic programming (DP. DP selects the operating mode, which provides the highest efficiency for given driving conditions. It was found that the operating mode selection changes when drivetrain losses are included, depending on driving conditions. An operating mode schedule was developed with respect to the wheel power and vehicle speed, and based on the operating mode schedule, a RBC was obtained, which can be implemented in an on-line application. To evaluate the performance of the RBC, a forward simulator was constructed for the target PHEV. The simulation results show near-optimal performance of the RBC compared with dynamic-programming-based mode control in terms of the mode operation time and fuel economy. The RBC developed with drivetrain losses taken into account showed a 4%–5% improvement of the fuel economy over a similar RBC, which neglected the drivetrain losses.

Resource loss, self-efficacy, and family support predict posttraumatic stress symptoms: a 3-year study of earthquake survivors.

Science.gov (United States)

Warner, Lisa Marie; Gutiérrez-Doña, Benicio; Villegas Angulo, Maricela; Schwarzer, Ralf

2015-01-01

Social support and self-efficacy are regarded as coping resources that may facilitate readjustment after traumatic events. The 2009 Cinchona earthquake in Costa Rica serves as an example for such an event to study resources to prevent subsequent severity of posttraumatic stress symptoms. At Time 1 (1-6 months after the earthquake in 2009), N=200 survivors were interviewed, assessing resource loss, received family support, and posttraumatic stress response. At Time 2 in 2012, severity of posttraumatic stress symptoms and general self-efficacy beliefs were assessed. Regression analyses estimated the severity of posttraumatic stress symptoms accounted for by all variables. Moderator and mediator models were examined to understand the interplay of received family support and self-efficacy with posttraumatic stress symptoms. Baseline posttraumatic stress symptoms and resource loss (T1) accounted for significant but small amounts of the variance in the severity of posttraumatic stress symptoms (T2). The main effects of self-efficacy (T2) and social support (T1) were negligible, but social support buffered resource loss, indicating that only less supported survivors were affected by resource loss. Self-efficacy at T2 moderated the support-stress relationship, indicating that low levels of self-efficacy could be compensated by higher levels of family support. Receiving family support at T1 enabled survivors to feel self-efficacious, underlining the enabling hypothesis. Receiving social support from relatives shortly after an earthquake was found to be an important coping resource, as it alleviated the association between resource loss and the severity of posttraumatic stress response, compensated for deficits of self-efficacy, and enabled self-efficacy, which was in turn associated with more adaptive adjustment 3 years after the earthquake.

Optimism, Social Support, and Well-Being in Mothers of Children with Autism Spectrum Disorder

Science.gov (United States)

Ekas, Naomi V.; Lickenbrock, Diane M.; Whitman, Thomas L.

2010-01-01

This study used structural equation modeling to examine the relationship between multiple sources of social support (e.g., partner, family, and friends), optimism, and well-being among mothers of children with ASD. Social support was examined as a mediator and moderator of the optimism-maternal well-being relationship. Moreover, the role of…

Integrated Multidisciplinary Constrained Optimization of Offshore Support Structures

International Nuclear Information System (INIS)

Haghi, Rad; Molenaar, David P; Ashuri, Turaj; Van der Valk, Paul L C

2014-01-01

In the current offshore wind turbine support structure design method, the tower and foundation, which form the support structure are designed separately by the turbine and foundation designer. This method yields a suboptimal design and it results in a heavy, overdesigned and expensive support structure. This paper presents an integrated multidisciplinary approach to design the tower and foundation simultaneously. Aerodynamics, hydrodynamics, structure and soil mechanics are the modeled disciplines to capture the full dynamic behavior of the foundation and tower under different environmental conditions. The objective function to be minimized is the mass of the support structure. The model includes various design constraints: local and global buckling, modal frequencies, and fatigue damage along different stations of the structure. To show the usefulness of the method, an existing SWT-3.6-107 offshore wind turbine where its tower and foundation are designed separately is used as a case study. The result of the integrated multidisciplinary design optimization shows 12.1% reduction in the mass of the support structure, while satisfying all the design constraints

DECISION SUPPORT TOOL FOR RETAIL SHELF SPACE OPTIMIZATION

OpenAIRE

B. RAMASESHAN; N. R. ACHUTHAN; R. COLLINSON

2008-01-01

Efficient allocation of shelf space and product assortment can significantly improve a retailer's profitability. This paper addresses the problem from the perspective of an independent franchise retailer. A Category Management Decision Support Tool (CMDST) is proposed that efficiently generates optimal shelf space allocations and product assortments by using the existing scarce resources, resulting in increased profitability. CMDST utilizes two practical integrated category management models ...

Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization

Science.gov (United States)

Ma, Yuliang; Ding, Xiaohui; She, Qingshan; Luo, Zhizeng; Potter, Thomas; Zhang, Yingchun

2016-01-01

Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this study, we propose using a particle swarm optimization algorithm to optimize the selection of both the kernel and penalty parameters in order to improve the classification performance of support vector machines. The performance of the optimized classifier was evaluated with motor imagery EEG signals in terms of both classification and prediction. Results show that the optimized classifier can significantly improve the classification accuracy of motor imagery EEG signals. PMID:27313656

Optimized design of polarizers with low ohmic loss and any polarization state for the 28 GHz QUEST ECH/ECCD system

Energy Technology Data Exchange (ETDEWEB)

Tsujimura, Toru Ii, E-mail: tsujimura.tohru@nifs.ac.jp [National Institute for Fusion Science, National Institutes of Natural Sciences, Toki 509-5292 (Japan); Idei, Hiroshi [Research Institute for Applied Mechanics, Kyushu University, Kasuga 816-8580 (Japan); Kubo, Shin; Kobayashi, Sakuji [National Institute for Fusion Science, National Institutes of Natural Sciences, Toki 509-5292 (Japan)

2017-01-15

Highlights: • Ohmic loss was calculated on the grooved mirror surface in simulated polarizers. • Polarizers with a low ohmic loss feature were optimally designed for 28 GHz. • Smooth rounded-rectangular grooves were made by mechanical machining. • The designed polarizers can realize all polarization states. - Abstract: In a high-power long-pulse millimeter-wave transmission line for electron cyclotron heating and current drive (ECH/ECCD), the ohmic loss on the grooved mirror surface of polarizers is one of the important issues for reducing the transmission loss. In this paper, the ohmic loss on the mirror surface is evaluated in simulated real-scale polarizer miter bends for different groove parameters under a linearly-polarized incident wave excitation. The polarizers with low ohmic loss are optimally designed for a new 28 GHz transmission line on the QUEST spherical tokamak. The calculated optimum ohmic loss is restricted to only less than 1.5 times as large as the theoretical loss for a copper flat mirror at room temperature. The copper rounded-rectangular grooves of the polarizers were relatively easy to make smooth in mechanical machining and the resultant surface roughness was not more than 0.15 μm, which is only 0.38 times as large as the skin depth. The combination of the designed elliptical polarizer and the polarization rotator can also realize any polarization state of the reflected wave.

Method for optimal design of pipes for low-energy district heating, with focus on heat losses

DEFF Research Database (Denmark)

Dalla Rosa, Alessandro; Li, Hongwei; Svendsen, Svend

2011-01-01

The synergy between highly energy-efficient buildings and low-energy district heating (DH) systems is a promising concept for the optimal integration of energy-saving policies and energy supply systems based on renewable energy (RE). Network transmission and distribution heat loss is one of the k...

Effect of adherence to self-monitoring of diet and physical activity on weight loss in a technology-supported behavioral intervention

Directory of Open Access Journals (Sweden)

Wang J

2012-03-01

Full Text Available Jing Wang1, Susan M Sereika2,3, Eileen R Chasens2, Linda J Ewing4, Judith T Matthews2,5, Lora E Burke2,31School of Nursing, University of Texas Health Science Center at Houston, Houston, TX, 2School of Nursing, 3Graduate School of Public Health, 4School of Medicine, 5University Center for Social and Urban Research, University of Pittsburgh, Pittsburgh, PA, USABackground: Examination of mediating behavioral factors could explain how an intervention works and thus provide guidance to optimize behavioral weight-loss programs. This study examined the mediating role of adherence to self-monitoring of diet and physical activity on weight loss in a behavioral weight-loss trial testing the use of personal digital assistants (PDA for self-monitoring.Methods: Mediation analysis was conducted to examine the possible mediating role of adherence to self-monitoring of diet and physical activity between treatments using varying self-monitoring methods (paper record, PDA, and PDA with daily tailored feedback messages and weight loss.Findings: The sample (N = 210 was predominantly white (78% and female (85%. Compared to a paper record, using a PDA for self-monitoring diet (P = 0.027 and physical activity (P = 0.014 had significant direct effects on weight loss at 12 months, as well as a significant indirect effect on outcomes through improved adherence to self-monitoring (PS < 0.001. Receiving an automated daily feedback message via PDA only had a significant indirect effect on weight through self-monitoring adherence to diet (P = 0.004 and physical activity (P = 0.002.Conclusions: Adherence to self-monitoring of diet and physical activity is important as the underlying mechanism in this technology-supported behavioral weight-loss intervention.Keywords: behavioral intervention, self-monitoring, mobile technology, mediation analysis, weight loss, adherence 

Optimization-based decision support systems for planning problems in processing industries

OpenAIRE

Claassen, G.D.H.

2014-01-01

Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendous progress in hard- and software of the past decades was an important gateway for developing computerized systems that are able to support decision making on different levels within enterprises. T...

Social support for healthy behaviors: Scale psychometrics and prediction of weight loss among women in a behavioral program

Science.gov (United States)

Kiernan, Michaela; Moore, Susan D.; Schoffman, Danielle E.; Lee, Katherine; King, Abby C.; Taylor, C. Barr; Kiernan, Nancy Ellen; Perri, Michael G.

2015-01-01

Social support could be a powerful weight-loss treatment moderator or mediator but is rarely assessed. We assessed the psychometric properties, initial levels, and predictive validity of a measure of perceived social support and sabotage from friends and family for healthy eating and physical activity (eight subscales). Overweight/obese women randomized to one of two 6-month, group-based behavioral weight-loss programs (N=267; mean BMI 32.1±3.5; 66.3% White) completed subscales at baseline, and weight loss was assessed at 6 months. Internal consistency, discriminant validity, and content validity were excellent for support subscales and adequate for sabotage subscales; qualitative responses revealed novel deliberate instances not reflected in current sabotage items. Most women (>75%) “never” or “rarely” experienced support from friends or family. Using non-parametric classification methods, we identified two subscales—support from friends for healthy eating and support from family for physical activity—that predicted three clinically meaningful subgroups who ranged in likelihood of losing ≥5% of initial weight at 6 months. Women who “never” experienced family support were least likely to lose weight (45.7% lost weight) whereas women who experienced both frequent friend and family support were more likely to lose weight (71.6% lost weight). Paradoxically, women who “never” experienced friend support were most likely to lose weight (80.0% lost weight), perhaps because the group-based programs provided support lacking from friendships. Psychometrics for support subscales were excellent; initial support was rare; and the differential roles of friend versus family support could inform future targeted weight-loss interventions to subgroups at risk. PMID:21996661

Cancer Classification Based on Support Vector Machine Optimized by Particle Swarm Optimization and Artificial Bee Colony.

Science.gov (United States)

Gao, Lingyun; Ye, Mingquan; Wu, Changrong

2017-11-29

Intelligent optimization algorithms have advantages in dealing with complex nonlinear problems accompanied by good flexibility and adaptability. In this paper, the FCBF (Fast Correlation-Based Feature selection) method is used to filter irrelevant and redundant features in order to improve the quality of cancer classification. Then, we perform classification based on SVM (Support Vector Machine) optimized by PSO (Particle Swarm Optimization) combined with ABC (Artificial Bee Colony) approaches, which is represented as PA-SVM. The proposed PA-SVM method is applied to nine cancer datasets, including five datasets of outcome prediction and a protein dataset of ovarian cancer. By comparison with other classification methods, the results demonstrate the effectiveness and the robustness of the proposed PA-SVM method in handling various types of data for cancer classification.

Optimization of multiple performance characteristics in turning using Taguchi’s quality loss function: An experimental investigation

Directory of Open Access Journals (Sweden)

Tanmaya Mohanty

2013-06-01

Full Text Available Cutting force and chip reduction coefficient is the important index of machinability as it determines the power consumption and amount of energy invested in machining actions. It is primarily influenced by process parameters like cutting speed, feed and depth of cut. This paper presents the application of Taguchi’s parameter design to optimize the parameters for individual responses. For multi-response optimization, Taguchi’s quality loss function approach is proposed. In the present investigation, optimal values of cutting speed, feed and depth of cut are determined to minimize cutting force and chip reduction coefficient during orthogonal turning. The effectiveness of the proposed methodology is illustrated through an experimental investigation in turning mild steel workpiece using high speed steel tool.

Optimized VBM in patients with Alzheimer's disease: gray matter loss and its correlation with cognitive function

International Nuclear Information System (INIS)

Choi, Seon Hyeong; Moon, Won Jin; Chung, Eun Chul; Lee, Min Hee; Roh, Hong Gee; Park, Kwang Bo; Na, Duck Ryul

2005-01-01

To investigate the regional changes in gray matter volume by using optimized voxel based morphometry in the whole brain of patients with Alzheimer's disease (AD) and to determine its correlation with cognitive function. Nineteen patients with AD (mean mini mental state examination (MMSE) score = 20.4) and 19 age-matched control subjects (mean MMSE score 29) participated in this prospective study. T1-weighted 3D-SPGR scans were obtained for each subject. These T1-weighted images were spatially normalized into study-specific T1 template and segmented into gray matter, white matter and CSF. After the images were modulated and smoothed, all of the gray matter images were compared with control images by using voxel-wise statistical parametric test (two-sample-test). In patients with AD, total gray matter volume was significantly smaller than normal control (552 ± 39 mL vs. 632 ± 51 mL, ρ 0.001). Significant gray matter loss was seen in both the hippocampus and amygdala complexs, and the parahippocampi and frontoparietal cortices (ρ < 0.01, family wise error corrected). Left cerebral atrophy was more prominent than the right. Loss of gray matter volume in both the superior frontal gyri and left inferior temporal gyrus had a strong correlation with lower MMSE score. Optimized VBM was able to visualize pathologic changes of AD in vivo. In AD there was widespread gray matter volume loss in the frontoparietal lobes as well as the medial temporal lobes and had a strong correlation between volume loss of specific cortical areas and MMSE score

[Diagnosis and the technology for optimizing the medical support of a troop unit].

Science.gov (United States)

Korshever, N G; Polkovov, S V; Lavrinenko, O V; Krupnov, P A; Anastasov, K N

2000-05-01

The work is devoted to investigation of the system of military unit medical support with the use of principles and states of organizational diagnosis; development of the method allowing to assess its functional activity; and determination of optimization trends. Basing on the conducted organizational diagnosis and expert inquiry the informative criteria were determined which characterize the stages of functioning of the military unit medical support system. To evaluate the success of military unit medical support the complex multi-criteria pattern was developed and algorithm of this process optimization was substantiated. Using the results obtained, particularly realization of principles and states of decision taking theory in machine program it is possible to solve more complex problem of comparison between any number of military units: to dispose them according to priority decrease; to select the programmed number of the best and worst; to determine the trends of activity optimization in corresponding medical service personnel.

Daily Peak Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm

Directory of Open Access Journals (Sweden)

Shuyu Dai

2018-01-01

Full Text Available Daily peak load forecasting is an important part of power load forecasting. The accuracy of its prediction has great influence on the formulation of power generation plan, power grid dispatching, power grid operation and power supply reliability of power system. Therefore, it is of great significance to construct a suitable model to realize the accurate prediction of the daily peak load. A novel daily peak load forecasting model, CEEMDAN-MGWO-SVM (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, is proposed in this paper. Firstly, the model uses the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN algorithm to decompose the daily peak load sequence into multiple sub sequences. Then, the model of modified grey wolf optimization and support vector machine (MGWO-SVM is adopted to forecast the sub sequences. Finally, the forecasting sequence is reconstructed and the forecasting result is obtained. Using CEEMDAN can realize noise reduction for non-stationary daily peak load sequence, which makes the daily peak load sequence more regular. The model adopts the grey wolf optimization algorithm improved by introducing the population dynamic evolution operator and the nonlinear convergence factor to enhance the global search ability and avoid falling into the local optimum, which can better optimize the parameters of the SVM algorithm for improving the forecasting accuracy of daily peak load. In this paper, three cases are used to test the forecasting accuracy of the CEEMDAN-MGWO-SVM model. We choose the models EEMD-MGWO-SVM (Ensemble Empirical Mode Decomposition and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, MGWO-SVM (Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, GWO-SVM (Support Vector Machine Optimized by Grey Wolf Optimization Algorithm, SVM (Support Vector

Overview of NASA supported Stirling thermodynamic loss research

International Nuclear Information System (INIS)

Tew, R.C.; Geng, S.M.

1994-01-01

The National Aeronautics and Space Administration (NASA) is funding research to characterize Stirling machine thermodynamic losses. NASA's primary goal is to improve Stirling design codes to support engine development for space and terrestrial power. However, much of the fundamental data is applicable to Stirling cooler and heat pump applications. The research results are reviewed. Much has been learned about oscillating-flow hydrodynamics, including laminar/turbulent transition, and tabulated data has been documented for further analysis. Now, with a better understanding of the oscillator-flow field, it is time to begin measuring the effects of oscillating flow and oscillating pressure level on heat transfer in heat exchanger flow passages and in cylinders. This critical phase of the work is just beginning

A Cross-Layer Optimized Opportunistic Routing Scheme for Loss-and-Delay Sensitive WSNs

Science.gov (United States)

Xu, Xin; Yuan, Minjiao; Liu, Xiao; Cai, Zhiping; Wang, Tian

2018-01-01

In wireless sensor networks (WSNs), communication links are typically error-prone and unreliable, so providing reliable and timely data routing for loss- and delay-sensitive applications in WSNs it is a challenge issue. Additionally, with specific thresholds in practical applications, the loss and delay sensitivity implies requirements for high reliability and low delay. Opportunistic Routing (OR) has been well studied in WSNs to improve reliability for error-prone and unreliable wireless communication links where the transmission power is assumed to be identical in the whole network. In this paper, a Cross-layer Optimized Opportunistic Routing (COOR) scheme is proposed to improve the communication link reliability and reduce delay for loss-and-delay sensitive WSNs. The main contribution of the COOR scheme is making full use of the remaining energy in networks to increase the transmission power of most nodes, which will provide a higher communication reliability or further transmission distance. Two optimization strategies referred to as COOR(R) and COOR(P) of the COOR scheme are proposed to improve network performance. In the case of increasing the transmission power, the COOR(R) strategy chooses a node that has a higher communication reliability with same distance in comparison to the traditional opportunistic routing when selecting the next hop candidate node. Since the reliability of data transmission is improved, the delay of the data reaching the sink is reduced by shortening the time of communication between candidate nodes. On the other hand, the COOR(P) strategy prefers a node that has the same communication reliability with longer distance. As a result, network performance can be improved for the following reasons: (a) the delay is reduced as fewer hops are needed while the packet reaches the sink in longer transmission distance circumstances; (b) the reliability can be improved since it is the product of the reliability of every hop of the routing path

A Cross-Layer Optimized Opportunistic Routing Scheme for Loss-and-Delay Sensitive WSNs.

Science.gov (United States)

Xu, Xin; Yuan, Minjiao; Liu, Xiao; Liu, Anfeng; Xiong, Neal N; Cai, Zhiping; Wang, Tian

2018-05-03

In wireless sensor networks (WSNs), communication links are typically error-prone and unreliable, so providing reliable and timely data routing for loss- and delay-sensitive applications in WSNs it is a challenge issue. Additionally, with specific thresholds in practical applications, the loss and delay sensitivity implies requirements for high reliability and low delay. Opportunistic Routing (OR) has been well studied in WSNs to improve reliability for error-prone and unreliable wireless communication links where the transmission power is assumed to be identical in the whole network. In this paper, a Cross-layer Optimized Opportunistic Routing (COOR) scheme is proposed to improve the communication link reliability and reduce delay for loss-and-delay sensitive WSNs. The main contribution of the COOR scheme is making full use of the remaining energy in networks to increase the transmission power of most nodes, which will provide a higher communication reliability or further transmission distance. Two optimization strategies referred to as COOR(R) and COOR(P) of the COOR scheme are proposed to improve network performance. In the case of increasing the transmission power, the COOR(R) strategy chooses a node that has a higher communication reliability with same distance in comparison to the traditional opportunistic routing when selecting the next hop candidate node. Since the reliability of data transmission is improved, the delay of the data reaching the sink is reduced by shortening the time of communication between candidate nodes. On the other hand, the COOR(P) strategy prefers a node that has the same communication reliability with longer distance. As a result, network performance can be improved for the following reasons: (a) the delay is reduced as fewer hops are needed while the packet reaches the sink in longer transmission distance circumstances; (b) the reliability can be improved since it is the product of the reliability of every hop of the routing path

A Cross-Layer Optimized Opportunistic Routing Scheme for Loss-and-Delay Sensitive WSNs

Directory of Open Access Journals (Sweden)

Xin Xu

2018-05-01

Full Text Available In wireless sensor networks (WSNs, communication links are typically error-prone and unreliable, so providing reliable and timely data routing for loss- and delay-sensitive applications in WSNs it is a challenge issue. Additionally, with specific thresholds in practical applications, the loss and delay sensitivity implies requirements for high reliability and low delay. Opportunistic Routing (OR has been well studied in WSNs to improve reliability for error-prone and unreliable wireless communication links where the transmission power is assumed to be identical in the whole network. In this paper, a Cross-layer Optimized Opportunistic Routing (COOR scheme is proposed to improve the communication link reliability and reduce delay for loss-and-delay sensitive WSNs. The main contribution of the COOR scheme is making full use of the remaining energy in networks to increase the transmission power of most nodes, which will provide a higher communication reliability or further transmission distance. Two optimization strategies referred to as COOR(R and COOR(P of the COOR scheme are proposed to improve network performance. In the case of increasing the transmission power, the COOR(R strategy chooses a node that has a higher communication reliability with same distance in comparison to the traditional opportunistic routing when selecting the next hop candidate node. Since the reliability of data transmission is improved, the delay of the data reaching the sink is reduced by shortening the time of communication between candidate nodes. On the other hand, the COOR(P strategy prefers a node that has the same communication reliability with longer distance. As a result, network performance can be improved for the following reasons: (a the delay is reduced as fewer hops are needed while the packet reaches the sink in longer transmission distance circumstances; (b the reliability can be improved since it is the product of the reliability of every hop of the

Support optimization of the ring primary mirror of a 2m solar telescope

Science.gov (United States)

Yang, Dehua; Jin, Zhenyu; Liu, Zhong

2016-08-01

A special 2-m Ring Solar Telescope (2-m RST) is to be built by YNAO-Yunnan Astronomical Observatory, Kunming, China. Its distinct primary mirror is distinctively shaped in a ring with an outer diameter of 2.02 m and a ring width of 0.35 m. Careful calculation and optimization of the mirror support pattern have been carried out first of all to define optimum blank parameters in view of performance balance of support design, fabrication and cost. This paper is to review the special consideration and optimization of the support design for the unique ring mirror. Schott zerodur is the prevailing candidate for the primary mirror blank. Diverse support patterns with various blank thicknesses have been discussed by extensive calculation of axial support pattern of the mirror. We reached an optimum design of 36 axial supports for a blank thickness of 0.15 m with surface error of 5 nm RMS. Afterwards, lateral support scheme was figured out for the mirror with settled parameters. A classical push-and-pull scheme was used. Seeing the relative flexibility of the ring mirror, special consideration was taken to unusually set the acting direction of the support forces not in the mirror gravity plane, but along the gravity of the local virtual slices of the mirror blank. Nine couples of the lateral push-pull force are considered. When pointing to horizon, the mirror surface exhibits RMS error of 5 nm with three additional small force couples used to compensate for the predominant astigmatism introduced by lateral supports. Finally, error estimation has been performed to evaluate the surface degradation with introduced errors in support force and support position, respectively, for both axial and lateral supports. Monte Carlo approach was applied using unit seeds for amplitude and position of support forces. The comprehensive optimization and calculation suggests the support systems design meet the technic requirements of the ring mirror of the 2-m RST.

Associations between sensory loss and social networks, participation, support, and loneliness: Analysis of the Canadian Longitudinal Study on Aging.

Science.gov (United States)

Mick, Paul; Parfyonov, Maksim; Wittich, Walter; Phillips, Natalie; Kathleen Pichora-Fuller, M

2018-01-01

To determine if hearing loss, vision loss, and dual sensory loss were associated with social network diversity, social participation, availability of social support, and loneliness, respectively, in a population-based sample of older Canadians and to determine whether age or sex modified the associations. Cross-sectional population-based study. Canada. The sample included 21 241 participants in the Canadian Longitudinal Study on Aging tracking cohort. The sample was nationally representative of English- and French-speaking, non-institutionalized 45- to 89-year-old Canadians who did not live on First Nations reserves and who had normal cognition. Participants with missing data for any of the variables in the multivariable regression models were excluded from analysis. Hearing and vision loss were determined by self-report. Dual sensory loss was defined as reporting both hearing and vision loss. Univariate analyses were performed to assess cross-sectional associations between hearing, vision, and dual sensory loss, and social, demographic, and medical variables. Multivariable regression models were used to analyze cross-sectional associations between each type of sensory loss and social network diversity, social participation, availability of social support, and loneliness. Vision loss (in men) and dual sensory loss (in 65- to 85-year-olds) were independently associated with reduced social network diversity. Vision loss and dual sensory loss (in 65- to 85-year-olds) were each independently associated with reduced social participation. All forms of sensory loss were associated with both low availability of social support and loneliness. Sensory impairment is associated with reduced social function in older Canadians. Interventions and research that address the social needs of older individuals with sensory loss are needed. Copyright© the College of Family Physicians of Canada.

Optimal support systems for patients with stomas – an opinion piece

Directory of Open Access Journals (Sweden)

Burch J

2014-06-01

Full Text Available Jennie BurchSt Marks Hospital, Surgery, London, UKAbstract: Coping with a stoma is physically and emotionally difficult. This adaptation process can be hindered by various factors, including complications associated with the stoma, such as appliance leakage, and comorbidities, such as arthritis. There are many ways of learning to live successfully with a stoma, which may be influenced by family, health care professionals, and spiritual support. There is some evidence that a good social support network can result in a positive coping mechanism for people with a newly formed stoma. Difficulty in accepting the stoma has been shown to slow down the adaptation process. This article explores the basic issues related to stomas and the general preoperative and postoperative support that is supplied by health care professionals. There was no optimal support system protocol discovered in the review of the literature. However, some of the published data related to stoma care were extrapolated to enable the reader to understand the important role that support systems can play in the acceptance of the stoma. Health care professionals provide support in a variety of ways, including the provision of telephone advice, clinics, and “open days”, to assist the patient to come to terms with their newly formed stoma. Care includes training on the practical aspects of the stoma, supporting empowerment and self-efficacy of people with a stoma (ostomates, and providing assistance when problems arise. Other support systems that are available are support groups, which may be local or national. It can be seen that the adaptation process takes many months or longer, but by utilizing various means of support, people with a stoma can have a good quality of life. The optimal support systems for patients with a stoma are discussed in relation to the literature and the personal experience of the author.Keywords: colostomy, ileostomy, urostomy

Social Support and Optimism as Predictors of Life Satisfaction of College Students

Science.gov (United States)

Yalcin, Ilhan

2011-01-01

The purpose of this study was to investigate the predictive value of optimism, perceived support from family and perceived support from faculty in determining life satisfaction of college students in Turkey. One hundred and thirty three students completed the Satisfaction with Life Scale (Diener et al., Journal of Personality Assessment…

Implant and root supported overdentures - a literature review and some data on bone loss in edentulous jaws.

Science.gov (United States)

Carlsson, Gunnar E

2014-08-01

To present a literature review on implant overdentures after a brief survey of bone loss after extraction of all teeth. Papers on alveolar bone loss and implant overdentures have been studied for a narrative review. Bone loss of the alveolar process after tooth extraction occurs with great individual variation, impossible to predict at the time of extraction. The simplest way to prevent bone loss is to avoid extraction of all teeth. To keep a few teeth and use them or their roots for a tooth or root-supported overdenture substantially reduces bone loss. Jaws with implant-supported prostheses show less bone loss than jaws with conventional dentures. Mandibular 2-implant overdentures provide patients with better outcomes than do conventional dentures, regarding satisfaction, chewing ability and oral-health-related quality of life. There is no strong evidence for the superiority of one overdenture retention-system over the others regarding patient satisfaction, survival, peri-implant bone loss and relevant clinical factors. Mandibular single midline implant overdentures have shown promising results but long-term results are not yet available. For a maxillary overdenture 4 to 6 implants splinted with a bar provide high survival both for implants and overdenture. In edentulous mandibles, 2-implant overdentures provide excellent long-term success and survival, including patient satisfaction and improved oral functions. To further reduce the costs a single midline implant overdenture can be a promising option. In the maxilla, overdentures supported on 4 to 6 implants splinted with a bar have demonstrated good functional results.

Implant and root supported overdentures - a literature review and some data on bone loss in edentulous jaws

Science.gov (United States)

2014-01-01

PURPOSE To present a literature review on implant overdentures after a brief survey of bone loss after extraction of all teeth. MATERIALS AND METHODS Papers on alveolar bone loss and implant overdentures have been studied for a narrative review. RESULTS Bone loss of the alveolar process after tooth extraction occurs with great individual variation, impossible to predict at the time of extraction. The simplest way to prevent bone loss is to avoid extraction of all teeth. To keep a few teeth and use them or their roots for a tooth or root-supported overdenture substantially reduces bone loss. Jaws with implant-supported prostheses show less bone loss than jaws with conventional dentures. Mandibular 2-implant overdentures provide patients with better outcomes than do conventional dentures, regarding satisfaction, chewing ability and oral-health-related quality of life. There is no strong evidence for the superiority of one overdenture retention-system over the others regarding patient satisfaction, survival, peri-implant bone loss and relevant clinical factors. Mandibular single midline implant overdentures have shown promising results but long-term results are not yet available. For a maxillary overdenture 4 to 6 implants splinted with a bar provide high survival both for implants and overdenture. CONCLUSION In edentulous mandibles, 2-implant overdentures provide excellent long-term success and survival, including patient satisfaction and improved oral functions. To further reduce the costs a single midline implant overdenture can be a promising option. In the maxilla, overdentures supported on 4 to 6 implants splinted with a bar have demonstrated good functional results. PMID:25177466

Optimal Control Method for Wind Farm to Support Temporary Primary Frequency Control with Minimized Wind Energy Cost

DEFF Research Database (Denmark)

Wang, Haijiao; Chen, Zhe; Jiang, Quanyuan

2015-01-01

This study proposes an optimal control method for variable speed wind turbines (VSWTs) based wind farm (WF) to support temporary primary frequency control. This control method consists of two layers: temporary frequency support control (TFSC) of the VSWT, and temporary support power optimal...... dispatch (TSPOD) of the WF. With TFSC, the VSWT could temporarily provide extra power to support system frequency under varying and wide-range wind speed. In the WF control centre, TSPOD optimally dispatches the frequency support power orders to the VSWTs that operate under different wind speeds, minimises...... the wind energy cost of frequency support, and satisfies the support capabilities of the VSWTs. The effectiveness of the whole control method is verified in the IEEE-RTS built in MATLABSimulink, and compared with a published de-loading method....

Optimism and depression: a new look at social support as a mediator among women at risk for breast cancer.

Science.gov (United States)

Garner, Melissa J; McGregor, Bonnie A; Murphy, Karly M; Koenig, Alex L; Dolan, Emily D; Albano, Denise

2015-12-01

Breast cancer risk is a chronic stressor associated with depression. Optimism is associated with lower levels of depression among breast cancer survivors. However, to our knowledge, no studies have explored the relationship between optimism and depression among women at risk for breast cancer. We hypothesized that women at risk for breast cancer who have higher levels of optimism would report lower levels of depression and that social support would mediate this relationship. Participants (N = 199) with elevated distress were recruited from the community and completed self-report measures of depression, optimism, and social support. Participants were grouped based on their family history of breast cancer. Path analysis was used to examine the cross-sectional relationship between optimism, social support, and depressive symptoms in each group. Results indicated that the variance in depressive symptoms was partially explained through direct paths from optimism and social support among women with a family history of breast cancer. The indirect path from optimism to depressive symptoms via social support was significant (β = -.053; 90% CI = -.099 to -.011, p = .037) in this group. However, among individuals without a family history of breast cancer, the indirect path from optimism to depressive symptoms via social support was not significant. These results suggest that social support partially mediates the relationship between optimism and depression among women at risk for breast cancer. Social support may be an important intervention target to reduce depression among women at risk for breast cancer. Copyright © 2015 John Wiley & Sons, Ltd.

Finite time thermodynamic analysis and optimization of solar-dish Stirling heat engine with regenerative losses

Directory of Open Access Journals (Sweden)

Sharma Arjun

2011-01-01

Full Text Available The present study investigates the performance of the solar-driven Stirling engine system to maximize the power output and thermal efficiency using the non-linearized heat loss model of the solar dish collector and the irreversible cycle model of the Stirling engine. Finite time thermodynamic analysis has been done for combined system to calculate the finite-rate heat transfer, internal heat losses in the regenerator, conductive thermal bridging losses and finite regeneration process time. The results indicate that exergy efficiency of dish system increases as the effectiveness of regenerator increases but decreases with increase in regenerative time coefficient. It is also found that optimal range of collector temperature and corresponding concentrating ratio are 1000 K~1400 K and 1100~1400, respectively in order to get maximum value of exergy efficiency. It is reported that the exergy efficiency of this dish system can reach the maximum value when operating temperature and concentrating ratio are 1150 K and 1300, respectively.

Watershed Management Optimization Support Tool (WMOST) v2: User Manual and Case Studies

Science.gov (United States)

The Watershed Management Optimization Support Tool (WMOST) is a decision support tool that evaluates the relative cost-effectiveness of management practices at the local or watershed scale. WMOST models the environmental effects and costs of management decisions in a watershed c...

Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis

International Nuclear Information System (INIS)

Liu, Eva Sau Fan; Wu, Vincent Wing Cheung; Harris, Benjamin; Foote, Matthew; Lehman, Margot; Chan, Lawrence Wing Chi

2017-01-01

Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, following the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis while maintaining plan quality.

Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis

Energy Technology Data Exchange (ETDEWEB)

Liu, Eva Sau Fan [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Wu, Vincent Wing Cheung [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong); Harris, Benjamin [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); Foote, Matthew; Lehman, Margot [Department of Radiation Oncology, Princess Alexandra Hospital, Brisbane (Australia); School of Medicine, University of Queensland (Australia); Chan, Lawrence Wing Chi, E-mail: wing.chi.chan@polyu.edu.hk [Department of Health Technology and Informatics, The Hong Kong Polytechnic University (Hong Kong)

2017-07-01

Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, following the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis while maintaining plan quality.

Prediction of loss to follow-up in long-term supportive periodontal therapy in patients with chronic periodontitis.

Directory of Open Access Journals (Sweden)

Di Wu

Full Text Available This study examined the predictors of loss to follow-up in long-term supportive periodontal therapy in patients with chronic periodontitis.A total of 280 patients with moderate to severe chronic periodontitis in a tertiary care hospital in China were investigated and followed over the course of study. Questionnaires on clinical and demographic characteristics, self-efficacy for oral self-care and dental fear at baseline were completed. Participants were followed to determine whether they could adhere to long-term supportive periodontal therapy. Binary logistic regression analysis was used to examine the association between clinical and demographic characteristics, self-efficacy for oral self-care, dental fear and loss to follow-up in long-term supportive periodontal therapy.The loss to follow-up in long-term supportive periodontal therapy was significantly associated with age [adjusted OR = 1.042, 95% confidence interval (CI: 1.012-1.074, p = 0.006], severe periodontitis [adjusted OR = 4.892, 95%CI: 2.280-10.499, p<0.001], periodontal surgery [adjusted OR = 11.334, 95% CI: 2.235-57.472, p = 0.003], and middle and low-scoring of self-efficacy scale for self-care groups. The adjusted ORs of loss to follow-up for the middle- (54-59 and low-scoring groups (15-53 were 71.899 (95%CI: 23.926-216.062, p<0.001 and 4.800 (95% CI: 2.263-10.182, p<0.001, respectively, compared with the high-scoring SESS group (60-75.Age, severity of periodontitis, periodontal surgery and the level of self-efficacy for self-care may be effective predictors of loss to follow-up in long-term supportive periodontal therapy in patients with chronic periodontitis.

Project TEAMS (Talking about Eating, Activity, and Mutual Support: a randomized controlled trial of a theory-based weight loss program for couples

Directory of Open Access Journals (Sweden)

Amy A. Gorin

2017-09-01

Full Text Available Abstract Background Obesity risk is shared between spouses, yet existing weight loss programs focus on individuals and not the marital dyad. Given the interdependence of weight in couples, weight management outcomes might be improved by targeting joint weight loss and the creation of an interpersonal milieu that supports long-term behavior change. According to Self-Determination Theory (SDT, greater autonomous self-regulation of behaviors, and subsequently better treatment outcomes, are observed in needs supportive environments in which personally meaningful choice is supported and criticism and control are minimized. Correlational analyses confirm these pathways in weight management, with needs support from one’s spouse or partner emerging as a distinct predictor of weight loss success. Research is now needed to establish causal links and to develop and test weight loss interventions designed to facilitate the needs supportive behavior of spouses. Methods Project TEAMS (Talking about Eating, Activity, and Mutual Support is a randomized controlled trial testing a couples-based intervention, grounded in SDT, designed to change the social context of weight loss by training spouses to provide needs support for each other’s eating and physical activity behavior. Sixty-four couples will be randomized to either 6 months of behavioral weight loss treatment informed by SDT (SDT-WL or to 6 months of standard behavioral weight loss treatment (BWL. Couples will attend weekly sessions for 6 months and will be assessed at 0, 3, 6, and 12 months. By bolstering needs support, SDT-WL is predicted to increase autonomous self-regulation and perceived competence and produce greater weight loss and maintenance than standard behavioral treatment. Exploratory analyses will examine the SDT process model prediction that the influence of needs support on treatment outcomes will be mediated by autonomous self-regulation and perceived competence. Discussion This

Project TEAMS (Talking about Eating, Activity, and Mutual Support): a randomized controlled trial of a theory-based weight loss program for couples.

Science.gov (United States)

Gorin, Amy A; Powers, Theodore A; Gettens, Katelyn; Cornelius, Talea; Koestner, Richard; Mobley, Amy R; Pescatello, Linda; Medina, Tania Huedo

2017-09-29

Obesity risk is shared between spouses, yet existing weight loss programs focus on individuals and not the marital dyad. Given the interdependence of weight in couples, weight management outcomes might be improved by targeting joint weight loss and the creation of an interpersonal milieu that supports long-term behavior change. According to Self-Determination Theory (SDT), greater autonomous self-regulation of behaviors, and subsequently better treatment outcomes, are observed in needs supportive environments in which personally meaningful choice is supported and criticism and control are minimized. Correlational analyses confirm these pathways in weight management, with needs support from one's spouse or partner emerging as a distinct predictor of weight loss success. Research is now needed to establish causal links and to develop and test weight loss interventions designed to facilitate the needs supportive behavior of spouses. Project TEAMS (Talking about Eating, Activity, and Mutual Support) is a randomized controlled trial testing a couples-based intervention, grounded in SDT, designed to change the social context of weight loss by training spouses to provide needs support for each other's eating and physical activity behavior. Sixty-four couples will be randomized to either 6 months of behavioral weight loss treatment informed by SDT (SDT-WL) or to 6 months of standard behavioral weight loss treatment (BWL). Couples will attend weekly sessions for 6 months and will be assessed at 0, 3, 6, and 12 months. By bolstering needs support, SDT-WL is predicted to increase autonomous self-regulation and perceived competence and produce greater weight loss and maintenance than standard behavioral treatment. Exploratory analyses will examine the SDT process model prediction that the influence of needs support on treatment outcomes will be mediated by autonomous self-regulation and perceived competence. This study addresses the fundamental importance of interpersonal

NLP modeling for the optimization of LiBr-H_2O absorption refrigeration systems with exergy loss rate, heat transfer area, and cost as single objective functions

International Nuclear Information System (INIS)

Mussati, Sergio F.; Gernaey, Krist V.; Morosuk, Tatiana; Mussati, Miguel C.

2016-01-01

Highlights: • A NLP model is used for simultaneous optimization of sizes and operating conditions. • Total exergy loss rate and transfer area are optimized as single objective functions. • Theoretical and practical bounds for cost optimization problems are computed. • A systematic solution strategy is proposed for total annual cost optimization. • Relevance of components is ranked by heat transfer area, exergy loss rate, and cost. - Abstract: Based on a nonlinear mathematical programming model, the sizes and operating conditions of the process units of single-effect absorption refrigeration systems operating with a LiBr–H_2O solution are optimized for a specified cooling capacity by minimizing three single objective functions: the total exergy loss rate, the total heat transfer area, and the total annual cost of the system. It was found that the optimal solution obtained by minimization of the total exergy loss rate provides “theoretical” upper bounds not only for the total heat transfer area of the system but also for each process unit and all stream temperatures, while the optimal solution obtained by minimization of the total heat transfer area provides the lower bounds for these model variables, to solve a cost optimization problem. The minimization of the total exergy loss rate by varying parametrically the available total heat transfer area between these bounds was also performed, allowing to see how the optimal distribution of the available total heat transfer area among the system components, as well as the operating conditions (stream temperature, pressure, composition, and mass flow rate) and heat loads, vary qualitatively and quantitatively with increasing available total heat transfer area. These optimization results allowed to find a “practical” value of the total heat transfer area, i.e. no benefits can be obtained by increasing the available total heat transfer area above this value since the minimal total exergy loss value cannot

Need for Cost Optimization of Space Life Support Systems

Science.gov (United States)

Jones, Harry W.; Anderson, Grant

2017-01-01

As the nation plans manned missions that go far beyond Earth orbit to Mars, there is an urgent need for a robust, disciplined systems engineering methodology that can identify an optimized Environmental Control and Life Support (ECLSS) architecture for long duration deep space missions. But unlike the previously used Equivalent System Mass (ESM), the method must be inclusive of all driving parameters and emphasize the economic analysis of life support system design. The key parameter for this analysis is Life Cycle Cost (LCC). LCC takes into account the cost for development and qualification of the system, launch costs, operational costs, maintenance costs and all other relevant and associated costs. Additionally, an effective methodology must consider system technical performance, safety, reliability, maintainability, crew time, and other factors that could affect the overall merit of the life support system.

Optimal design of galvanic corrosion protection systems for offshore wind turbine support structures

DEFF Research Database (Denmark)

Sarhadi, Ali; Abrahamsen, Asger Bech; Stolpe, Mathias

2018-01-01

the optimized anodes on the support structure, and finally evaluating the protective potential on the structure during the lifetime by calling the finite element (FE) software COMSOL. An algorithm based on Sequential Quadratic Programming (SQP) is used for optimizing the number and dimensions of the anodes...... the electrical isolation degradation of the structure coating as well as the mass reduction of the anodes during the CP lifetime. The performance of the proposed optimization process is examined on a mono bucket inspired (with some simplifications) by the Dogger Bank metrological mast in England. The optimized......The current work addresses a mass/cost optimization procedure for galvanic anode cathodic protection (GACP) systems based on both cathodic protection (CP) standards and numerical simulation. An approach is developed for optimizing the number and dimensions of the galvanic anodes, distributing...

Relationships between depressive symptoms and perceived social support, self-esteem, & optimism in a sample of rural adolescents.

Science.gov (United States)

Weber, Scott; Puskar, Kathryn Rose; Ren, Dianxu

2010-09-01

Stress, developmental changes and social adjustment problems can be significant in rural teens. Screening for psychosocial problems by teachers and other school personnel is infrequent but can be a useful health promotion strategy. We used a cross-sectional survey descriptive design to examine the inter-relationships between depressive symptoms and perceived social support, self-esteem, and optimism in a sample of rural school-based adolescents. Depressive symptoms were negatively correlated with peer social support, family social support, self-esteem, and optimism. Findings underscore the importance for teachers and other school staff to provide health education. Results can be used as the basis for education to improve optimism, self-esteem, social supports and, thus, depression symptoms of teens.

A new global particle swarm optimization for the economic emission dispatch with or without transmission losses

International Nuclear Information System (INIS)

Zou, Dexuan; Li, Steven; Li, Zongyan; Kong, Xiangyong

2017-01-01

Highlights: • A new global particle swarm optimization (NGPSO) is proposed. • NGPSO has strong convergence and desirable accuracy. • NGPSO is used to handle the economic emission dispatch with or without transmission losses. • The equality constraint can be satisfied by solving a quadratic equation. • The inequality constraints can be satisfied by using penalty function method. - Abstract: A new global particle swarm optimization (NGPSO) algorithm is proposed to solve the economic emission dispatch (EED) problems in this paper. NGPSO is different from the traditional particle swarm optimization (PSO) algorithm in two aspects. First, NGPSO uses a new position updating equation which relies on the global best particle to guide the searching activities of all particles. Second, it uses the randomization based on the uniform distribution to slightly disturb the flight trajectories of particles during the late evolutionary process. The two steps enable NGPSO to effectively execute a number of global searches, and thus they increase the chance of exploring promising solution space, and reduce the probabilities of getting trapped into local optima for all particles. On the other hand, the two objective functions of EED are normalized separately according to all candidate solutions, and then they are incorporated into one single objective function. The transformation steps are very helpful in eliminating the difference caused by the different dimensions of the two functions, and thus they strike a balance between the fuel cost and emission. In addition, a simple and common penalty function method is employed to facilitate the satisfactions of EED’s constraints. Based on these improvements in PSO, objective functions and constraints handling, high-quality solutions can be obtained for EED problems. Five examples are chosen to testify the performance of three improved PSOs on solving EED problems with or without transmission losses. Experimental results show that

Optimization of offshore wind turbine support structures using analytical gradient-based method

OpenAIRE

Chew, Kok Hon; Tai, Kang; Ng, E.Y.K.; Muskulus, Michael

2015-01-01

Design optimization of the offshore wind turbine support structure is an expensive task; due to the highly-constrained, non-convex and non-linear nature of the design problem. This report presents an analytical gradient-based method to solve this problem in an efficient and effective way. The design sensitivities of the objective and constraint functions are evaluated analytically while the optimization of the structure is performed, subject to sizing, eigenfrequency, extreme load an...

Management of hair loss diseases

Directory of Open Access Journals (Sweden)

Manabu Ohyama

2010-12-01

Full Text Available The treatment of hair loss diseases is sometimes difficult because of insufficient efficacy and limited options. However, recent advances in understanding of the pathophysiology and development of new remedies have improved the treatment of refractory hair loss conditions. In this article, an update on the management of hair loss diseases is provided, especially focusing on recently reported therapeutic approaches for alopecia areata (AA. An accurate diagnosis is indispensable to optimize treatment. Dry dermoscopy represents new diagnostic techniques, which could enable the differentiation of barely indistinguishable alopecias, e.g. AA and trichotillomania. An organized scalp biopsy adopting both vertical and transverse sectioning approaches also provides a deep insight into the pathophysiology of ongoing alopecias. Among various treatments for AA, intraregional corticosteroid and contact immunotherapy have been recognized as first-line therapies. However, some AA cases are refractory to both treatments. Recent studies have demonstrated the efficacy of pulse corticosteroid therapy or the combination of oral psoralen ultraviolet A therapy and systemic corticosteroids for severe AA. Previous clinical observations have suggested the potential role of antihistamines as supportive medications for AA. Experimental evaluation using AA model mice further supports their effectiveness in AA treatment. Finasteride opens up new possibilities for the treatment of androgenetic alopecia. For androgenetic alopecia patients refractory to finasteride, the combination of finasteride with topical minoxidil or the administration of dutasteride, another 5 alpha-reductase inhibitor, may provide better outcomes. Scarring alopecia is the most difficult form of hair loss disorder to treat. The bulge stem cell area is destroyed by unnecessary immune reactions with resultant permanent loss of hair follicle structures in scarring alopecia. Currently, treatment options for

Optimism and benefit finding in parents of children with developmental disabilities: The role of positive reappraisal and social support.

Science.gov (United States)

Slattery, Éadaoin; McMahon, Jennifer; Gallagher, Stephen

2017-06-01

Researchers have consistently documented the relationship between optimism and benefit finding; however, there is a dearth of research on the psychological mechanisms mediating their association. This cross-sectional study sought to elucidate the mediating role of positive reappraisal and social support in the optimism-benefit finding relationship in parents caring for children with developmental disabilities by testing a parallel multiple mediation model. One hundred and forty-six parents caring for children with developmental disabilities completed an online survey assessing optimism, positive reappraisal, social support and benefit finding. Optimism was not directly related to benefit finding but rather influenced it indirectly through positive reappraisal and social support. Specifically, higher levels of optimism predicted greater positive reappraisal and social support, which in turn led to greater benefit finding in parents. These results underscore the importance of targeting parents' perceptions of benefits through both positive reappraisal and social support in order to help them cope with the demands of the caregiving context. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimization of Support Structures for Offshore Wind Turbines Using Genetic Algorithm with Domain-Trimming

Directory of Open Access Journals (Sweden)

Mohammad AlHamaydeh

2017-01-01

Full Text Available The powerful genetic algorithm optimization technique is augmented with an innovative “domain-trimming” modification. The resulting adaptive, high-performance technique is called Genetic Algorithm with Domain-Trimming (GADT. As a proof of concept, the GADT is applied to a widely used benchmark problem. The 10-dimensional truss optimization benchmark problem has well documented global and local minima. The GADT is shown to outperform several published solutions. Subsequently, the GADT is deployed onto three-dimensional structural design optimization for offshore wind turbine supporting structures. The design problem involves complex least-weight topology as well as member size optimizations. The GADT is applied to two popular design alternatives: tripod and quadropod jackets. The two versions of the optimization problem are nonlinearly constrained where the objective function is the material weight of the supporting truss. The considered design variables are the truss members end node coordinates, as well as the cross-sectional areas of the truss members, whereas the constraints are the maximum stresses in members and the maximum displacements of the nodes. These constraints are managed via dynamically modified, nonstationary penalty functions. The structures are subject to gravity, wind, wave, and earthquake loading conditions. The results show that the GADT method is superior in finding best discovered optimal solutions.

NLP modeling for the optimization of LiBr-H2O absorption refrigeration systems with exergy loss rate, heat transfer area, and cost as single objective functions

DEFF Research Database (Denmark)

Mussati, Sergio F.; Gernaey, Krist; Morosuk, Tatiana

2016-01-01

exergy loss rate, the total heat transfer area, and the total annual cost of the system. It was found that the optimal solution obtained by minimization of the total exergy loss rate provides “theoretical” upper bounds not only for the total heat transfer area of the system but also for each process unit...... and all stream temperatures, while the optimal solution obtained by minimization of the total heat transfer area provides the lower bounds for these model variables, to solve a cost optimization problem. The minimization of the total exergy loss rate by varying parametrically the available total heat...... transfer area between these bounds was also performed, allowing to see how the optimal distribution of the available total heat transfer area among the system components, as well as the operating conditions (stream temperature, pressure, composition, and mass flow rate) and heat loads, vary qualitatively...

Design and implementation of an interactive website to support long-term maintenance of weight loss.

Science.gov (United States)

Stevens, Victor J; Funk, Kristine L; Brantley, Phillip J; Erlinger, Thomas P; Myers, Valerie H; Champagne, Catherine M; Bauck, Alan; Samuel-Hodge, Carmen D; Hollis, Jack F

2008-01-25

For most individuals, long-term maintenance of weight loss requires long-term, supportive intervention. Internet-based weight loss maintenance programs offer considerable potential for meeting this need. Careful design processes are required to maximize adherence and minimize attrition. This paper describes the development, implementation and use of a Web-based intervention program designed to help those who have recently lost weight sustain their weight loss over 1 year. The weight loss maintenance website was developed over a 1-year period by an interdisciplinary team of public health researchers, behavior change intervention experts, applications developers, and interface designers. Key interactive features of the final site include social support, self-monitoring, written guidelines for diet and physical activity, links to appropriate websites, supportive tools for behavior change, check-in accountability, tailored reinforcement messages, and problem solving and relapse prevention training. The weight loss maintenance program included a reminder system (automated email and telephone messages) that prompted participants to return to the website if they missed their check-in date. If there was no log-in response to the email and telephone automated prompts, a staff member called the participant. We tracked the proportion of participants with at least one log-in per month, and analyzed log-ins as a result of automated prompts. The mean age of the 348 participants enrolled in an ongoing randomized trial and assigned to use the website was 56 years; 63% were female, and 38% were African American. While weight loss data will not be available until mid-2008, website use remained high during the first year with over 80% of the participants still using the website during month 12. During the first 52 weeks, participants averaged 35 weeks with at least one log-in. Email and telephone prompts appear to be very effective at helping participants sustain ongoing website use

Curtailment of renewable generation: Economic optimality and incentives

International Nuclear Information System (INIS)

Klinge Jacobsen, Henrik; Schröder, Sascha Thorsten

2012-01-01

The loss from curtailing generation based on renewable energy sources is generally seen as an unacceptable solution by the public. The main argument is that it is a loss of green energy and an economic loss to curtail generation with near zero marginal costs. However, this view could lead to overinvestment in grid infrastructure and underinvestment in renewable energy sources. This article argues that some curtailment of fluctuating (variable) generation is optimal. We address the possible contributions to total curtailment from involuntary and voluntary curtailment. The costs of curtailment in terms of lost generation are discussed based on market price and support levels including the rationale for compensating generators for losses. The extent of actual curtailment is illustrated by examples from different global markets. In general, both the value of the curtailed energy and the amount of curtailed energy relative to total fluctuating generation is low but rising. Single generators may be affected considerably if insufficient compensation measures are in place. In the future, optimal curtailment will increase along with an increased share of fluctuating renewable generation. Extending renewable generation comparatively cheaply can be achieved by the installation of additional capacity at offshore locations until optimal curtailment levels are reached. - Highlights: ► Curtailment of renewable generation can be optimal. ► Voluntary and involuntary curtailment categories. ► Compensation for involuntary curtailment should be provided. ► Asymmetrical balancing price provides incentive for voluntary curtailment. ► Network enforcement costs can be reduced per renewable generation.

Optimized VBM in patients with Alzheimer's disease: gray matter loss and its correlation with cognitive function

Energy Technology Data Exchange (ETDEWEB)

Choi, Seon Hyeong; Moon, Won Jin; Chung, Eun Chul; Lee, Min Hee; Roh, Hong Gee; Park, Kwang Bo; Na, Duck Ryul [Sungkyunkwan University School of Medicine, Seoul (Korea, Republic of)

2005-11-15

To investigate the regional changes in gray matter volume by using optimized voxel based morphometry in the whole brain of patients with Alzheimer's disease (AD) and to determine its correlation with cognitive function. Nineteen patients with AD (mean mini mental state examination (MMSE) score = 20.4) and 19 age-matched control subjects (mean MMSE score 29) participated in this prospective study. T1-weighted 3D-SPGR scans were obtained for each subject. These T1-weighted images were spatially normalized into study-specific T1 template and segmented into gray matter, white matter and CSF. After the images were modulated and smoothed, all of the gray matter images were compared with control images by using voxel-wise statistical parametric test (two-sample-test). In patients with AD, total gray matter volume was significantly smaller than normal control (552 {+-} 39 mL vs. 632 {+-} 51 mL, {rho} 0.001). Significant gray matter loss was seen in both the hippocampus and amygdala complexs, and the parahippocampi and frontoparietal cortices ({rho} < 0.01, family wise error corrected). Left cerebral atrophy was more prominent than the right. Loss of gray matter volume in both the superior frontal gyri and left inferior temporal gyrus had a strong correlation with lower MMSE score. Optimized VBM was able to visualize pathologic changes of AD in vivo. In AD there was widespread gray matter volume loss in the frontoparietal lobes as well as the medial temporal lobes and had a strong correlation between volume loss of specific cortical areas and MMSE score.

A Hybrid Least Square Support Vector Machine Model with Parameters Optimization for Stock Forecasting

Directory of Open Access Journals (Sweden)

Jian Chai

2015-01-01

Full Text Available This paper proposes an EMD-LSSVM (empirical mode decomposition least squares support vector machine model to analyze the CSI 300 index. A WD-LSSVM (wavelet denoising least squares support machine is also proposed as a benchmark to compare with the performance of EMD-LSSVM. Since parameters selection is vital to the performance of the model, different optimization methods are used, including simplex, GS (grid search, PSO (particle swarm optimization, and GA (genetic algorithm. Experimental results show that the EMD-LSSVM model with GS algorithm outperforms other methods in predicting stock market movement direction.

Optimal support vessel and access system selection for offshore wind farms

NARCIS (Netherlands)

Asgarpour, M.; Serraris, J.W.; Ridder, E. de; Broek, J. van den; Bos, J.E.

2016-01-01

Operation and maintenance (O&M) costs contribute to a significant part of Cost of Energy produced by offshore wind. In order to reduce the O&M costs and to guarantee safety and wellbeing of the maintenance technicians, for each individual wind farm an optimal set of support vessels and access

Optimization of the Hockey Fans in Training (Hockey FIT) weight loss and healthy lifestyle program for male hockey fans.

Science.gov (United States)

Blunt, Wendy; Gill, Dawn P; Sibbald, Shannon L; Riggin, Brendan; Pulford, Roseanne W; Scott, Ryan; Danylchuk, Karen; Gray, Cindy M; Wyke, Sally; Bunn, Christopher; Petrella, Robert J

2017-11-28

The health outcomes of men continue to be poorer than women globally. Challenges in addressing this problem include difficulties engaging men in weight loss programs as they tend to view these programs as contrary to the masculine narrative of independence and self-reliance. Researchers have been turning towards sports fans to engage men in health promotion programs as sports fans are typically male, and tend to have poor health habits. Developed from the highly successful gender-sensitized Football Fans in Training program, Hockey Fans in Training (Hockey FIT) recruited 80 male hockey fans of the London Knights and Sarnia Sting who were overweight or obese into a weekly, 90-minute classroom education and group exercise program held over 12 weeks; a 40-week minimally-supported phase followed. A process evaluation of the Hockey FIT program was completed alongside a pragmatic randomized controlled trial and outcome evaluation in order to fully explore the acceptability of the Hockey FIT program from the perspectives of coaches delivering and participants engaged in the program. Data sources included attendance records, participant focus groups, coach interviews, assessment of fidelity (program observations and post-session coach reflections), and 12-month participant interviews. Coaches enjoyed delivering the program and found it simple to deliver. Men valued being among others of similar body shape and similar weight loss goals, and found the knowledge they gained through the program helped them to make and maintain health behaviour changes. Suggested improvements include having more hockey-related information and activities, greater flexibility with timing of program delivery, and greater promotion of technology support tools. We confirmed Hockey FIT was an acceptable "gender-sensitized" health promotion program for male hockey fans who were overweight or obese. Minor changes were required for optimization, which will be evaluated in a future definitive trial

Investigation of optimal seismic design methodology for piping systems supported by elasto-plastic dampers. Part 1. Evaluation functions

International Nuclear Information System (INIS)

Ito, Tomohiro; Michiue, Masashi; Fujita, Katsuhisa

2009-01-01

In this study, the optimal seismic design methodology that can consider the structural integrity of not only the piping systems but also elasto-plastic supporting devices is developed. This methodology employs a genetic algorithm and can search the optimal conditions such as the supporting location, capacity and stiffness of the supporting devices. Here, a lead extrusion damper is treated as a typical elasto-plastic damper. Four types of evaluation functions are considered. It is found that the proposed optimal seismic design methodology is very effective and can be applied to the actual seismic design for piping systems supported by elasto-plastic dampers. The effectiveness of the evaluation functions is also clarified. (author)

Development and application of a decision support tool for reduction of product losses in the food-processing industry

NARCIS (Netherlands)

Akkerman, Renzo; van Donk, Dirk Pieter

2008-01-01

In food-processing industries, reduction of product losses is important for improving profitability and sustainability. This paper presents a decision support tool for analyzing the effects of planning decisions on the amount of product losses in the food-processing industry. We created a research

Relationships between Academic Stress, Social Support, Optimism-Pessimism and Self-Esteem in College Students

Science.gov (United States)

Fernández-González, L.; González-Hernández, A.; Trianes-Torres, M. V.

2015-01-01

Introduction: This research aims to analyse how optimism, self-esteem and social support help to predict academic stress. Method: The sample consisted of 123 students aged 20 to 31 years old, from the 3rd Year in the Psychology Degree. Students completed the Rosenberg Self-esteem Scale, the Life Orientation Optimism Questionnaire (LOT-R), the…

IEP (Individualized Educational Program) Co-operation between Optimal Support of Students with Special Needs

Science.gov (United States)

Ogoshi, Yasuhiro; Nakai, Akio; Ogoshi, Sakiko; Mitsuhashi, Yoshinori; Araki, Chikahiro

A key aspect of the optimal support of students with special needs is co-ordination and co-operation between school, home and specialized agencies. Communication between these entities is of prime importance and can be facilitated through the use of a support system implementing ICF guidelines as outlined. This communication system can be considered to be a preventative rather than allopathic support.

Coping with Loss Aversion in the Newsvendor Model

Directory of Open Access Journals (Sweden)

Jianwu Sun

2015-01-01

Full Text Available We introduce loss aversion into the decision framework of the newsvendor model. By introducing the loss aversion coefficient λ, we propose a novel utility function for the loss-averse newsvendor. First, we obtain the optimal order quantity to maximize the expected utility for the loss-averse newsvendor who is risk-neutral. It is found that this optimal order quantity is smaller than the expected profit maximization order quantity in the classical newsvendor model, which may help to explain the decision bias in the classical newsvendor model. Then, to reduce the risk which originates from the fluctuation in the market demand, we achieve the optimal order quantity to maximize CVaR about utility for the loss-averse newsvendor who is risk-averse. We find that this optimal order quantity is smaller than the optimal order quantity to maximize the expected utility above and is decreasing in the confidence level α. Further, it is proved that the expected utility under this optimal order quantity is decreasing in the confidence level α, which verifies that low risk implies low return. Finally, a numerical example is given to illustrate the obtained results and some management insights are suggested for the loss-averse newsvendor model.

Optimizing the District Heating Primary Network from the Perspective of Economic-Specific Pressure Loss

Directory of Open Access Journals (Sweden)

Haichao Wang

2017-07-01

Full Text Available A district heating (DH system is one of the most important components of infrastructures in cold areas. Proper DH network design should balance the initial investment and the heat distribution cost of the DH network. Currently, this design is often based on a recommended value for specific pressure loss (R = ∆P/L in the main lines. This will result in a feasible network design, but probably not be optimal in most cases. The paper develops a novel optimization model to facilitate the design by considering the initial investment in the pipes and the heat distribution costs. The model will generate all possible network scenarios consisting of different series of diameters for each pipe in the flow direction of the network. Then, the annuity on the initial investment, the heat distribution cost, and the total annual cost will be calculated for each network scenario, taking into account the uncertainties of the material prices and the yearly operating time levels. The model is applied to a sample DH network and the results indicate that the model works quite well, clearly identifying the optimal network design and demonstrating that the heat distribution cost is more important than the initial investment in DH network design.

Early Intervention for Children with Hearing Loss: Information Parents Receive about Supporting Children's Language

Science.gov (United States)

Decker, Kalli B.; Vallotton, Claire D.

2016-01-01

Family-centered early intervention for children with hearing loss is intended to strengthen families' interactions with their children to support children's language development, and should include providing parents with information they can use as part of their everyday routines. However, little is known about the information received by families…

Wearable devices and mobile technologies for supporting behavioral weight loss among people with serious mental illness.

Science.gov (United States)

Naslund, John A; Aschbrenner, Kelly A; Scherer, Emily A; McHugo, Gregory J; Marsch, Lisa A; Bartels, Stephen J

2016-10-30

Promoting physical activity is essential for addressing elevated cardiovascular risk and high obesity rates affecting people with serious mental illness. Numerous challenges interfere with exercise participation in this high-risk group including mental health symptoms, low motivation, and limited access to safe and affordable options for physical activity. Wearable devices and mobile health technologies may afford new opportunities for promoting physical activity and supporting behavioral weight loss efforts. This exploratory study examined whether daily step count measured using Fitbit wearable devices was associated with weight loss and improved fitness among individuals with serious mental illness enrolled in a 6-month lifestyle program. Participants (n=34) had a schizophrenia spectrum disorder (23.5%), major depression (50.0%), or bipolar disorder (26.5%), and wore Fitbits most of the days (M=86.2%; SD=18.4%) they were enrolled in the study. At 6-months, higher average daily step count was associated with greater weight loss (F=5.07; df=1,32; p=0.0314), but not improved fitness (F=1.92; df=1,31; p=0.176). These findings demonstrate that encouraging participants with serious mental illness enrolled in lifestyle interventions to collect more steps may contribute to greater weight loss. This suggests that wearable devices may offer a feasible and potentially effective strategy for supporting behavioral weight loss in community mental health settings. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entransy loss in thermodynamic processes and its application

International Nuclear Information System (INIS)

Cheng, Xuetao; Liang, Xingang

2012-01-01

The entransy theory has been developed for heat transfer optimization. This paper extends it to optimize thermodynamic processes. The entransy balance equation of thermodynamic processes is introduced, with which the concept of entransy loss is developed. For the Carnot cycle and the irreversible thermodynamic processes where the working fluid is heated by the streams with prescribed inlet temperatures and specific capacity flow rates, we find that the maximum entransy loss leads to the maximum output work, which is the maximum principle of entransy loss in thermodynamic processes. However, the entropy generation cannot describe the change of the output work for the Carnot cycle. Therefore, the concept of entransy loss could describe the performance of thermodynamic processes. Then, the principle is used to optimize the thermodynamic processes of heat exchanger groups and the design of the irreversible Brayton cycle. For these problems, the operation parameters are optimized to get the maximum output work by calculating the maximum entransy loss when the entransy loss induced by dumping the used streams into the environment is considered. The analysis of the air conditioning system for room heating with heat–work conversion processes demonstrates the entransy loss has a direct relation with the input heat. -- Highlights: ► The entransy balance equation of thermodynamic processes is introduced. ► The concept of entransy loss is developed. ► The maximum entransy loss corresponds to the maximum output work. ► Examples show that entransy loss can be used to optimize heat–work conversion.

Optimization of ITER Nb3Sn CICCs for coupling loss, transverse electromagnetic load and axial thermal contraction

International Nuclear Information System (INIS)

Nijhuis, A; Van Lanen, E P A; Rolando, G

2012-01-01

by the distinct difference in mechanical response of the cable during axial contraction for short and long pitches. For short pitches periodic bending in different directions with relatively short wavelength is imposed because of a lack of sufficient lateral restraint of radial pressure. This can lead to high bending strain and eventually buckling. Whereas for cables with long twist pitches, the strands are only able to react as coherent bundles, being tightly supported by the surrounding strands, providing sufficient lateral restraint of radial pressure in combination with enough slippage to avoid single strand bending along detrimental short wavelengths. Experimental evidence of good performance was already provided with the test of the long pitch TFPRO2-OST2, which is still until today, the best ITER-type cable to strand performance ever without any cyclic load (electromagnetic and thermal contraction) degradation. For reduction of the coupling loss, specific choices of the cabling twist sequence are needed to minimize the area of linked strands and bundles that are coupled and form loops with the applied changing magnetic field, instead of simply avoiding longer pitches. In addition we recommend increasing the wrap coverage of the CS conductor from 50% to at least 70%. A larger wrap coverage fraction enhances the overall strand bundle lateral restraint. The long pitch design seems the best solution to optimize the ITER CS conductor within the given restrictions of the present coil design envelope, only allowing marginal changes. The models predict significant improvement against strain sensitivity and substantial decrease of the AC coupling loss in Nb 3 Sn CICCs, but also for NbTi CICCs minimization of the coupling loss can obviously be achieved. Although the success of long pitches to transverse load degradation was already demonstrated, the prediction of the elegant innovative combination with low coupling loss needs to be validated by a short sample test.

Work, social support and leisure protect the elderly from functional loss: EPIDOSO study.

Science.gov (United States)

d'Orsi, Eleonora; Xavier, André Junqueira; Ramos, Luiz Roberto

2011-08-01

To identify risk factors for functional capacity loss in elderly people. Epidoso (Epidemiology of the Elderly) cohort study with elderly people living in São Paulo (Southeastern Brazil). A total of 326 participants in the first interview (1991-1992) who were independent or had mild dependence (one or two activities of daily living) were selected. Those who presented functional loss in the second (1994-1995) or third interviews (1998-1999) were compared to those who did not present it. The incidence of functional loss was calculated according to sociodemographic variables, life habits, cognitive status, morbidity, hospitalization, self-rated health, tooth loss, social support and leisure activities. Crude and adjusted relative risks with 95% confidence intervals were estimated through bivariate and multiple analyses with Poisson regression. The criterion for the inclusion of the variables in the model was p 0.10. The incidence of functional loss was 17.8% (13.6; 21.9). The risk factors in the final model were: age group 70-74 years RR=1.9 (0.9;3.9); age group 75-79 years RR=2.8 (1.4;5.5); age group 80 years or older RR=5.4 (3.0;9.6); score in the mini-mental state examination work RR=0.3 (0.1;1.0); monthly relationship with friends RR=0.5 (0.3;0.8); watching TV RR=0.5 (0.3;0.9); and handcrafting RR=0.7 (0.4;1.0). The prevention of functional loss should include adequate control of chronic diseases, like hypertension, asthma and diabetes, as well as cognitive stimulation. Work, leisure and relationships with friends should be valued due to their protective effect.

Optimization of CRISPR/Cas9 genome editing for loss-of-function in the early chick embryo.

Science.gov (United States)

Gandhi, Shashank; Piacentino, Michael L; Vieceli, Felipe M; Bronner, Marianne E

2017-12-01

The advent of CRISPR/Cas9 has made genome editing possible in virtually any organism, including those not previously amenable to genetic manipulations. Here, we present an optimization of CRISPR/Cas9 for application to early avian embryos with improved efficiency via a three-fold strategy. First, we employed Cas9 protein flanked with two nuclear localization signal sequences for improved nuclear localization. Second, we used a modified guide RNA (gRNA) scaffold that obviates premature termination of transcription and unstable Cas9-gRNA interactions. Third, we used a chick-specific U6 promoter that yields 4-fold higher gRNA expression than the previously utilized human U6. For rapid screening of gRNAs for in vivo applications, we also generated a chicken fibroblast cell line that constitutively expresses Cas9. As proof of principle, we performed electroporation-based loss-of-function studies in the early chick embryo to knock out Pax7 and Sox10, key transcription factors with known functions in neural crest development. The results show that CRISPR/Cas9-mediated deletion causes loss of their respective proteins and transcripts, as well as predicted downstream targets. Taken together, the results reveal the utility of this optimized CRISPR/Cas9 method for targeted gene knockout in chicken embryos in a manner that is reproducible, robust and specific. Copyright © 2017 Elsevier Inc. All rights reserved.

Soft sensor development and optimization of the commercial petrochemical plant integrating support vector regression and genetic algorithm

Directory of Open Access Journals (Sweden)

S.K. Lahiri

2009-09-01

Full Text Available Soft sensors have been widely used in the industrial process control to improve the quality of the product and assure safety in the production. The core of a soft sensor is to construct a soft sensing model. This paper introduces support vector regression (SVR, a new powerful machine learning methodbased on a statistical learning theory (SLT into soft sensor modeling and proposes a new soft sensing modeling method based on SVR. This paper presents an artificial intelligence based hybrid soft sensormodeling and optimization strategies, namely support vector regression – genetic algorithm (SVR-GA for modeling and optimization of mono ethylene glycol (MEG quality variable in a commercial glycol plant. In the SVR-GA approach, a support vector regression model is constructed for correlating the process data comprising values of operating and performance variables. Next, model inputs describing the process operating variables are optimized using genetic algorithm with a view to maximize the process performance. The SVR-GA is a new strategy for soft sensor modeling and optimization. The major advantage of the strategies is that modeling and optimization can be conducted exclusively from the historic process data wherein the detailed knowledge of process phenomenology (reaction mechanism, kinetics etc. is not required. Using SVR-GA strategy, a number of sets of optimized operating conditions were found. The optimized solutions, when verified in an actual plant, resulted in a significant improvement in the quality.

On scaling and optimization of high-intensity, low-beam-loss RF linacs for neutron source drivers

International Nuclear Information System (INIS)

Jameson, R.A.

1992-01-01

RF linacs providing cw proton beams of 30--250 mA at 800--1600 MeV, and cw deuteron beams of 100--250 mA at 35--40 MeV, are needed as drivers for factory neutron sources applied to radioactive waste transmutation, advanced energy production, materials testing facilities, and spallation neutron sources. The maintenance goals require very low beam loss along the linac. Optimization of such systems is complex; status of beam dynamics aspects presently being investigated is outlined

Multiplex protein pattern unmixing using a non-linear variable-weighted support vector machine as optimized by a particle swarm optimization algorithm.

Science.gov (United States)

Yang, Qin; Zou, Hong-Yan; Zhang, Yan; Tang, Li-Juan; Shen, Guo-Li; Jiang, Jian-Hui; Yu, Ru-Qin

2016-01-15

Most of the proteins locate more than one organelle in a cell. Unmixing the localization patterns of proteins is critical for understanding the protein functions and other vital cellular processes. Herein, non-linear machine learning technique is proposed for the first time upon protein pattern unmixing. Variable-weighted support vector machine (VW-SVM) is a demonstrated robust modeling technique with flexible and rational variable selection. As optimized by a global stochastic optimization technique, particle swarm optimization (PSO) algorithm, it makes VW-SVM to be an adaptive parameter-free method for automated unmixing of protein subcellular patterns. Results obtained by pattern unmixing of a set of fluorescence microscope images of cells indicate VW-SVM as optimized by PSO is able to extract useful pattern features by optimally rescaling each variable for non-linear SVM modeling, consequently leading to improved performances in multiplex protein pattern unmixing compared with conventional SVM and other exiting pattern unmixing methods. Copyright © 2015 Elsevier B.V. All rights reserved.

The Multidimensional Loss Scale: validating a cross-cultural instrument for measuring loss.

Science.gov (United States)

Vromans, Lyn; Schweitzer, Robert D; Brough, Mark

2012-04-01

The Multidimensional Loss Scale (MLS) represents the first instrument designed specifically to index Experience of Loss Events and Loss Distress across multiple domains (cultural, social, material, and intrapersonal) relevant to refugee settlement. Recently settled Burmese adult refugees (N = 70) completed a questionnaire battery, including MLS items. Analyses explored MLS internal consistency, convergent and divergent validity, and factor structure. Cronbach alphas indicated satisfactory internal consistency for Experience of Loss Events (0.85) and Loss Distress (0.92), reflecting a unitary construct of multidimensional loss. Loss Distress did not correlate with depression or anxiety symptoms and correlated moderately with interpersonal grief and trauma symptoms, supporting divergent and convergent validity. Factor analysis provided preliminary support for a five-factor model: Loss of Symbolic Self, Loss of Interdependence, Loss of Home, Interpersonal Loss, and Loss of Intrapersonal Integrity. Received well by participants, the new scale shows promise for application in future research and practice.

Improving support for parents of children with hearing loss: provider training on use of targeted communication strategies.

Science.gov (United States)

Muñoz, Karen; Nelson, Lauri; Blaiser, Kristina; Price, Tanner; Twohig, Michael

2015-02-01

When proper protocols are followed, children who are identified with a permanent hearing loss early in life have opportunities to develop language on par with their typical hearing peers. Young children with hearing loss are dependent on their parents to manage intervention during early years critical to their development, and parents' ability to effectively integrate recommendations in daily life is foundational for intervention success. Audiologists and early intervention professionals not only need to provide current evidence-based services, but also must address parents' emotional and learning needs related to their child's hearing loss. This study explored practice patterns related to education and support provided to parents of children with hearing loss and the influence of an in-service training on provider attitudes. This study used a prepost design with a self-report questionnaire to identify practice patterns related to communication skills and support used by providers when working with parents of children with hearing loss. A total of 45 participants (21 professionals and 24 graduate students) currently working with children completed the pretraining questionnaire, and 29 participants (13 professionals and 16 graduate students) completed the postquestionnaire. Data were collected using an online questionnaire before the training and 1 mo after training. Descriptive analyses were done to identify trends, and paired-samples t-tests were used to determine changes pretraining to posttraining. Findings revealed that professionals most frequently teach skills to mothers (91%) and infrequently teach skills to fathers (19%) and other caregivers (10%). Professionals reported frequently collaborating with other intervention providers (76%) and infrequently collaborating with primary care physicians (19%). One-third of the professionals reported addressing symptoms of depression and anxiety as an interfering factor with the ability to implement management

Loss-resistant unambiguous phase measurement

OpenAIRE

Dinani, Hossein T.; Berry, Dominic W.

2014-01-01

Entangled multi-photon states have the potential to provide improved measurement accuracy, but are sensitive to photon loss. It is possible to calculate ideal loss-resistant states that maximize the Fisher information, but it is unclear how these could be experimentally generated. Here we propose a set of states that can be obtained by processing the output from parametric down-conversion. Although these states are not optimal, they provide performance very close to that of optimal states for...

A quick earthquake disaster loss assessment method supported by dasymetric data for emergency response in China

Science.gov (United States)

Xu, Jinghai; An, Jiwen; Nie, Gaozong

2016-04-01

Improving earthquake disaster loss estimation speed and accuracy is one of the key factors in effective earthquake response and rescue. The presentation of exposure data by applying a dasymetric map approach has good potential for addressing this issue. With the support of 30'' × 30'' areal exposure data (population and building data in China), this paper presents a new earthquake disaster loss estimation method for emergency response situations. This method has two phases: a pre-earthquake phase and a co-earthquake phase. In the pre-earthquake phase, we pre-calculate the earthquake loss related to different seismic intensities and store them in a 30'' × 30'' grid format, which has several stages: determining the earthquake loss calculation factor, gridding damage probability matrices, calculating building damage and calculating human losses. Then, in the co-earthquake phase, there are two stages of estimating loss: generating a theoretical isoseismal map to depict the spatial distribution of the seismic intensity field; then, using the seismic intensity field to extract statistics of losses from the pre-calculated estimation data. Thus, the final loss estimation results are obtained. The method is validated by four actual earthquakes that occurred in China. The method not only significantly improves the speed and accuracy of loss estimation but also provides the spatial distribution of the losses, which will be effective in aiding earthquake emergency response and rescue. Additionally, related pre-calculated earthquake loss estimation data in China could serve to provide disaster risk analysis before earthquakes occur. Currently, the pre-calculated loss estimation data and the two-phase estimation method are used by the China Earthquake Administration.

A fast method for calculating reliable event supports in tree reconciliations via Pareto optimality.

Science.gov (United States)

To, Thu-Hien; Jacox, Edwin; Ranwez, Vincent; Scornavacca, Celine

2015-11-14

Given a gene and a species tree, reconciliation methods attempt to retrieve the macro-evolutionary events that best explain the discrepancies between the two tree topologies. The DTL parsimonious approach searches for a most parsimonious reconciliation between a gene tree and a (dated) species tree, considering four possible macro-evolutionary events (speciation, duplication, transfer, and loss) with specific costs. Unfortunately, many events are erroneously predicted due to errors in the input trees, inappropriate input cost values or because of the existence of several equally parsimonious scenarios. It is thus crucial to provide a measure of the reliability for predicted events. It has been recently proposed that the reliability of an event can be estimated via its frequency in the set of most parsimonious reconciliations obtained using a variety of reasonable input cost vectors. To compute such a support, a straightforward but time-consuming approach is to generate the costs slightly departing from the original ones, independently compute the set of all most parsimonious reconciliations for each vector, and combine these sets a posteriori. Another proposed approach uses Pareto-optimality to partition cost values into regions which induce reconciliations with the same number of DTL events. The support of an event is then defined as its frequency in the set of regions. However, often, the number of regions is not large enough to provide reliable supports. We present here a method to compute efficiently event supports via a polynomial-sized graph, which can represent all reconciliations for several different costs. Moreover, two methods are proposed to take into account alternative input costs: either explicitly providing an input cost range or allowing a tolerance for the over cost of a reconciliation. Our methods are faster than the region based method, substantially faster than the sampling-costs approach, and have a higher event-prediction accuracy on

Optimal siting of capacitors in radial distribution network using Whale Optimization Algorithm

Directory of Open Access Journals (Sweden)

D.B. Prakash

2017-12-01

Full Text Available In present days, continuous effort is being made in bringing down the line losses of the electrical distribution networks. Therefore proper allocation of capacitors is of utmost importance because, it will help in reducing the line losses and maintaining the bus voltage. This in turn results in improving the stability and reliability of the system. In this paper Whale Optimization Algorithm (WOA is used to find optimal sizing and placement of capacitors for a typical radial distribution system. Multi objectives such as operating cost reduction and power loss minimization with inequality constraints on voltage limits are considered and the proposed algorithm is validated by applying it on standard radial systems: IEEE-34 bus and IEEE-85 bus radial distribution test systems. The results obtained are compared with those of existing algorithms. The results show that the proposed algorithm is more effective in bringing down the operating costs and in maintaining better voltage profile. Keywords: Whale Optimization Algorithm (WOA, Optimal allocation and sizing of capacitors, Power loss reduction and voltage stability improvement, Radial distribution system, Operating cost minimization

Decision Support Model for Optimal Management of Coastal Gate

Science.gov (United States)

Ditthakit, Pakorn; Chittaladakorn, Suwatana

2010-05-01

The coastal areas are intensely settled by human beings owing to their fertility of natural resources. However, at present those areas are facing with water scarcity problems: inadequate water and poor water quality as a result of saltwater intrusion and inappropriate land-use management. To solve these problems, several measures have been exploited. The coastal gate construction is a structural measure widely performed in several countries. This manner requires the plan for suitably operating coastal gates. Coastal gate operation is a complicated task and usually concerns with the management of multiple purposes, which are generally conflicted one another. This paper delineates the methodology and used theories for developing decision support modeling for coastal gate operation scheduling. The developed model was based on coupling simulation and optimization model. The weighting optimization technique based on Differential Evolution (DE) was selected herein for solving multiple objective problems. The hydrodynamic and water quality models were repeatedly invoked during searching the optimal gate operations. In addition, two forecasting models:- Auto Regressive model (AR model) and Harmonic Analysis model (HA model) were applied for forecasting water levels and tide levels, respectively. To demonstrate the applicability of the developed model, it was applied to plan the operations for hypothetical system of Pak Phanang coastal gate system, located in Nakhon Si Thammarat province, southern part of Thailand. It was found that the proposed model could satisfyingly assist decision-makers for operating coastal gates under various environmental, ecological and hydraulic conditions.

Optimal Siting and Sizing of Multiple DG Units for the Enhancement of Voltage Profile and Loss Minimization in Transmission Systems Using Nature Inspired Algorithms

Directory of Open Access Journals (Sweden)

Ambika Ramamoorthy

2016-01-01

Full Text Available Power grid becomes smarter nowadays along with technological development. The benefits of smart grid can be enhanced through the integration of renewable energy sources. In this paper, several studies have been made to reconfigure a conventional network into a smart grid. Amongst all the renewable sources, solar power takes the prominent position due to its availability in abundance. Proposed methodology presented in this paper is aimed at minimizing network power losses and at improving the voltage stability within the frame work of system operation and security constraints in a transmission system. Locations and capacities of DGs have a significant impact on the system losses in a transmission system. In this paper, combined nature inspired algorithms are presented for optimal location and sizing of DGs. This paper proposes a two-step optimization technique in order to integrate DG. In a first step, the best size of DG is determined through PSO metaheuristics and the results obtained through PSO is tested for reverse power flow by negative load approach to find possible bus locations. Then, optimal location is found by Loss Sensitivity Factor (LSF and weak (WK bus methods and the results are compared. In a second step, optimal sizing of DGs is determined by PSO, GSA, and hybrid PSOGSA algorithms. Apart from optimal sizing and siting of DGs, different scenarios with number of DGs (3, 4, and 5 and PQ capacities of DGs (P alone, Q alone, and  P and Q both are also analyzed and the results are analyzed in this paper. A detailed performance analysis is carried out on IEEE 30-bus system to demonstrate the effectiveness of the proposed methodology.

Optimal Siting and Sizing of Multiple DG Units for the Enhancement of Voltage Profile and Loss Minimization in Transmission Systems Using Nature Inspired Algorithms.

Science.gov (United States)

Ramamoorthy, Ambika; Ramachandran, Rajeswari

2016-01-01

Power grid becomes smarter nowadays along with technological development. The benefits of smart grid can be enhanced through the integration of renewable energy sources. In this paper, several studies have been made to reconfigure a conventional network into a smart grid. Amongst all the renewable sources, solar power takes the prominent position due to its availability in abundance. Proposed methodology presented in this paper is aimed at minimizing network power losses and at improving the voltage stability within the frame work of system operation and security constraints in a transmission system. Locations and capacities of DGs have a significant impact on the system losses in a transmission system. In this paper, combined nature inspired algorithms are presented for optimal location and sizing of DGs. This paper proposes a two-step optimization technique in order to integrate DG. In a first step, the best size of DG is determined through PSO metaheuristics and the results obtained through PSO is tested for reverse power flow by negative load approach to find possible bus locations. Then, optimal location is found by Loss Sensitivity Factor (LSF) and weak (WK) bus methods and the results are compared. In a second step, optimal sizing of DGs is determined by PSO, GSA, and hybrid PSOGSA algorithms. Apart from optimal sizing and siting of DGs, different scenarios with number of DGs (3, 4, and 5) and PQ capacities of DGs (P alone, Q alone, and P and Q both) are also analyzed and the results are analyzed in this paper. A detailed performance analysis is carried out on IEEE 30-bus system to demonstrate the effectiveness of the proposed methodology.

How Positive Is Their Future? Assessing the Role of Optimism and Social Support in Understanding Mental Health Symptomatology among Homeless Adults.

Science.gov (United States)

Fitzpatrick, Kevin M

2017-04-01

Optimism has been noted as a primary protective factor in understanding mental health symptomatology in clinical and non-clinical settings. Any exploration of optimism has been absent in understanding mental health outcomes among homeless people. This study, using intensive interviews with 168 homeless adults in Northwest Arkansas, examines the role that social support and optimism play in lessening the negative impact of homeless circumstances/experiences on mental health symptomatology. Using OLS, findings support a mediating/protective role that social support and optimism play in lowering the negative effects of childhood life experiences on depressive symptoms among homeless persons. Despite the overwhelming conditions of homelessness, persons with higher levels of optimism and social support report lower depression and anxiety symptoms. The findings are discussed paying particular attention to the importance of developing and maintaining the perception of support and resiliency in preserving a positive outlook for the future among homeless persons facing often-debilitating circumstances. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Weight Loss Maintenance for 2 Years after a 6-Month Randomised Controlled Trial Comparing Education-Only and Group-Based Support in Japanese Adults

Directory of Open Access Journals (Sweden)

Yoshio Nakata

2014-11-01

Full Text Available Objective: Our previous study, a 6-month randomised controlled trial, demonstrated that a group-based support promoted weight loss as compared to an education-only intervention. The purpose of this study was to examine weight loss maintenance for 2 years. Methods: Originally, 188 overweight Japanese adults, aged 40-65 years, were randomly assigned to 3 groups: control, education-only or group-based support. After the 6-month intervention, 125 participants in the education-only and the group-based support groups were followed up for 2 years. The primary outcome was the amount of weight lost. The participants were retrospectively grouped into quartiles of percent weight loss for secondary analyses. Results: At the end of follow-up, the amount of weight lost in the education-only and the group-based support groups was the same (3.3 kg. Secondary analyses using data of those who completed the study (n = 100 revealed that the participants in the highest quartile of percent weight loss significantly increased their step counts and moderate-to-vigorous physical activity compared with the lowest quartile. No significant differences were observed in the energy intake among the four groups. Conclusion: The effects of group-based support disappear within 2 years. Increasing physical activity may be a crucial factor for successful maintenance of weight loss.

[Extraction Optimization of Rhizome of Curcuma longa by Response Surface Methodology and Support Vector Regression].

Science.gov (United States)

Zhou, Pei-pei; Shan, Jin-feng; Jiang, Jian-lan

2015-12-01

To optimize the optimal microwave-assisted extraction method of curcuminoids from Curcuma longa. On the base of single factor experiment, the ethanol concentration, the ratio of liquid to solid and the microwave time were selected for further optimization. Support Vector Regression (SVR) and Central Composite Design-Response Surface Methodology (CCD) algorithm were utilized to design and establish models respectively, while Particle Swarm Optimization (PSO) was introduced to optimize the parameters of SVR models and to search optimal points of models. The evaluation indicator, the sum of curcumin, demethoxycurcumin and bisdemethoxycurcumin by HPLC, were used. The optimal parameters of microwave-assisted extraction were as follows: ethanol concentration of 69%, ratio of liquid to solid of 21 : 1, microwave time of 55 s. On those conditions, the sum of three curcuminoids was 28.97 mg/g (per gram of rhizomes powder). Both the CCD model and the SVR model were credible, for they have predicted the similar process condition and the deviation of yield were less than 1.2%.

Optimization of Support Vector Machine (SVM) for Object Classification

Science.gov (United States)

Scholten, Matthew; Dhingra, Neil; Lu, Thomas T.; Chao, Tien-Hsin

2012-01-01

The Support Vector Machine (SVM) is a powerful algorithm, useful in classifying data into species. The SVMs implemented in this research were used as classifiers for the final stage in a Multistage Automatic Target Recognition (ATR) system. A single kernel SVM known as SVMlight, and a modified version known as a SVM with K-Means Clustering were used. These SVM algorithms were tested as classifiers under varying conditions. Image noise levels varied, and the orientation of the targets changed. The classifiers were then optimized to demonstrate their maximum potential as classifiers. Results demonstrate the reliability of SVM as a method for classification. From trial to trial, SVM produces consistent results.

Development of a fuzzy optimization model, supporting global warming decision-making

International Nuclear Information System (INIS)

Leimbach, M.

1996-01-01

An increasing number of models have been developed to support global warming response policies. The model constructors are facing a lot of uncertainties which limit the evidence of these models. The support of climate policy decision-making is only possible in a semi-quantitative way, as presented by a Fuzzy model. The model design is based on an optimization approach, integrated in a bounded risk decision-making framework. Given some regional emission-related and impact-related restrictions, optimal emission paths can be calculated. The focus is not only on carbon dioxide but on other greenhouse gases too. In the paper, the components of the model will be described. Cost coefficients, emission boundaries and impact boundaries are represented as Fuzzy parameters. The Fuzzy model will be transformed into a computational one by using an approach of Rommelfanger. In the second part, some problems of applying the model to computations will be discussed. This includes discussions on the data situation and the presentation, as well as interpretation of results of sensitivity analyses. The advantage of the Fuzzy approach is that the requirements regarding data precision are not so strong. Hence, the effort for data acquisition can be reduced and computations can be started earlier. 9 figs., 3 tabs., 17 refs., 1 appendix

Cognitive autonomy among adolescents with and without hearing loss: Associations with perceived social support.

Science.gov (United States)

Michael, Rinat; Attias, Joseph

2016-04-01

Cognitive autonomy is a skill which may help adolescents prepare for important decisions in adulthood. The current study examined the associations between cognitive autonomy and perceived social support among adolescents with and without hearing loss. Participants were 177 students: 55 were deaf and hard of hearing (dhh) and 122 were hearing. They completed the Cognitive Autonomy and Self-Evaluation Inventory, the Multidimensional Scale of Perceived Social Support, and a demographic questionnaire. Significant positive correlations were found between some of the cognitive autonomy variables and some of the perceived social support variables. However, among the dhh group, they were fewer and weaker. Family support was found to be a significant predictor of three out of the five cognitive autonomy variables. In addition, significant differences were found between the dhh and hearing participants in some of the cognitive autonomy variables, but not in perceived social support. Implications for theory and practice are discussed. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Social support, acculturation, and optimism: understanding positive health practices in Asian American college students.

Science.gov (United States)

Ayres, Cynthia G; Mahat, Ganga

2012-07-01

This study developed and tested a theory to better understand positive health practices (PHP) among Asian Americans aged 18 to 21 years. It tested theoretical relationships postulated between PHP and (a) social support (SS), (b) optimism, and (c) acculturation, and between SS and optimism and acculturation. Optimism and acculturation were also tested as possible mediators in the relationship between SS and PHP. A correlational study design was used. A convenience sample of 163 Asian college students in an urban setting completed four questionnaires assessing SS, PHP, optimism, and acculturation and one demographic questionnaire. There were statistically significant positive relationships between SS and optimism with PHP, between acculturation and PHP, and between optimism and SS. Optimism mediated the relationship between SS and PHP, whereas acculturation did not. Findings extend knowledge regarding these relationships to a defined population of Asian Americans aged 18 to 21 years. Findings contribute to a more comprehensive knowledge base regarding health practices among Asian Americans. The theoretical and empirical findings of this study provide the direction for future research as well. Further studies need to be conducted to identify and test other mediators in order to better understand the relationship between these two variables.

Optimal Placement and Sizing of PV-STATCOM in Power Systems Using Empirical Data and Adaptive Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Reza Sirjani

2018-03-01

Full Text Available Solar energy is a source of free, clean energy which avoids the destructive effects on the environment that have long been caused by power generation. Solar energy technology rivals fossil fuels, and its development has increased recently. Photovoltaic (PV solar farms can only produce active power during the day, while at night, they are completely idle. At the same time, though, active power should be supported by reactive power. Reactive power compensation in power systems improves power quality and stability. The use during the night of a PV solar farm inverter as a static synchronous compensator (or PV-STATCOM device has recently been proposed which can improve system performance and increase the utility of a PV solar farm. In this paper, a method for optimal PV-STATCOM placement and sizing is proposed using empirical data. Considering the objectives of power loss and cost minimization as well as voltage improvement, two sub-problems of placement and sizing, respectively, are solved by a power loss index and adaptive particle swarm optimization (APSO. Test results show that APSO not only performs better in finding optimal solutions but also converges faster compared with bee colony optimization (BCO and lightening search algorithm (LSA. Installation of a PV solar farm, STATCOM, and PV-STATCOM in a system are each evaluated in terms of efficiency and cost.

Opportunity Loss Minimization and Newsvendor Behavior

Directory of Open Access Journals (Sweden)

Xinsheng Xu

2017-01-01

Full Text Available To study the decision bias in newsvendor behavior, this paper introduces an opportunity loss minimization criterion into the newsvendor model with backordering. We apply the Conditional Value-at-Risk (CVaR measure to hedge against the potential risks from newsvendor’s order decision. We obtain the optimal order quantities for a newsvendor to minimize the expected opportunity loss and CVaR of opportunity loss. It is proven that the newsvendor’s optimal order quantity is related to the density function of market demand when the newsvendor exhibits risk-averse preference, which is inconsistent with the results in Schweitzer and Cachon (2000. The numerical example shows that the optimal order quantity that minimizes CVaR of opportunity loss is bigger than expected profit maximization (EPM order quantity for high-profit products and smaller than EPM order quantity for low-profit products, which is different from the experimental results in Schweitzer and Cachon (2000. A sensitivity analysis of changing the operation parameters of the two optimal order quantities is discussed. Our results confirm that high return implies high risk, while low risk comes with low return. Based on the results, some managerial insights are suggested for the risk management of the newsvendor model with backordering.

Multi-objective optimal operation of smart reconfigurable distribution grids

Directory of Open Access Journals (Sweden)

Abdollah Kavousi-Fard

2016-02-01

Full Text Available Reconfiguration is a valuable technique that can support the distribution grid from different aspects such as operation cost and loss reduction, reliability improvement, and voltage stability enhancement. An intelligent and efficient optimization framework, however, is required to reach the desired efficiency through the reconfiguration strategy. This paper proposes a new multi-objective optimization model to make use of the reconfiguration strategy for minimizing the power losses, improving the voltage profile, and enhancing the load balance in distribution grids. The proposed model employs the min-max fuzzy approach to find the most satisfying solution from a set of nondominated solutions in the problem space. Due to the high complexity and the discrete nature of the proposed model, a new optimization method based on harmony search (HS algorithm is further proposed. Moreover, a new modification method is suggested to increase the harmony memory diversity in the improvisation stage and increase the convergence ability of the algorithm. The feasibility and satisfying performance of the proposed model are examined on the IEEE 32-bus distribution system.

Career-Related Parental Support of Adolescents with Hearing Loss: Relationships with Parents' Expectations and Occupational Status

Science.gov (United States)

Rinat, Michael; Cinamon, Rachel Gali; Most, Tova

2015-01-01

The study examined the contribution of parents' occupational status and expectations regarding persons with hearing loss to career-related support they provide their deaf and hard of hearing (dhh) adolescent children. Thirty-eight parents completed the Evaluation of Occupational Competence Scale (Weisel & Cinamon, 2005), the Evaluation of…

Optimization of Synthesis Condition for Nanoscale Zero Valent Iron Immobilization on Granular Activated Carbon

DEFF Research Database (Denmark)

Mines, Paul D.; Andersen, Henrik Rasmus; Hwang, Yuhoon

2016-01-01

economical loss, but also potential risk to human health and environment. Thus, the immobilization onto coarse or structured support is essential. In this study, two representative processes for nZVI immobilization on granular activated carbon (GAC) were evaluated, and optimized conditions for synthesizing...

Customer demand prediction of service-oriented manufacturing using the least square support vector machine optimized by particle swarm optimization algorithm

Science.gov (United States)

Cao, Jin; Jiang, Zhibin; Wang, Kangzhou

2017-07-01

Many nonlinear customer satisfaction-related factors significantly influence the future customer demand for service-oriented manufacturing (SOM). To address this issue and enhance the prediction accuracy, this article develops a novel customer demand prediction approach for SOM. The approach combines the phase space reconstruction (PSR) technique with the optimized least square support vector machine (LSSVM). First, the prediction sample space is reconstructed by the PSR to enrich the time-series dynamics of the limited data sample. Then, the generalization and learning ability of the LSSVM are improved by the hybrid polynomial and radial basis function kernel. Finally, the key parameters of the LSSVM are optimized by the particle swarm optimization algorithm. In a real case study, the customer demand prediction of an air conditioner compressor is implemented. Furthermore, the effectiveness and validity of the proposed approach are demonstrated by comparison with other classical predication approaches.

Family support is associated with success in achieving weight loss in a group lifestyle intervention for diabetes prevention in Arab Americans.

Science.gov (United States)

Pinelli, Nicole R; Brown, Morton B; Herman, William H; Jaber, Linda A

2011-01-01

We have recently shown the feasibility of a community-based, culturally-specific, Diabetes Prevention Program-adapted, goal-oriented group lifestyle intervention targeting weight loss in Arab Americans. The objective of this study was to examine factors associated with weight-loss goal attainment at 24-weeks of the lifestyle intervention. We assessed the relationship among demographic, psychosocial, and behavioral measures and the attainment of > or =7% decrease of initial body weight among 71 lifestyle intervention participants. Weight loss goal of > or = 7% of body weight was achieved by 44% of study participants. Demographic and psychosocial factors were not associated with weight loss. Individuals attaining the weight loss goal were more likely to have family support during the core curriculum sessions (70% vs 30%; P=.0023). Decrease in body weight was positively correlated with attendance at sessions (r=.46; P=.0016) and physical activity minutes (r=.66; Pwomen; these trends were similar but not significant in men. Family support was an important predictor of attainment of the weight loss goal. Family-centered lifestyle interventions are likely to succeed in curtailing the rising epidemic of diabetes in the Arab-American Community.

Perceived overprotection: support gone bad?

Science.gov (United States)

Cimarolli, Verena R; Reinhardt, Joann P; Horowitz, Amy

2006-01-01

This article focuses on the effects of perceived overprotection, a potentially problematic aspect of receiving support, on the ability to adjust to a chronic impairment, specifically, age-related vision loss. Perceived overprotection is an especially critical issue in this population of chronically ill older adults because of the safety issues associated with vision impairment and because perceptions on the part of the older adult that the support providers are overprotective may lead to excess disability. Participants were 584 older men and women with age-related vision impairment who applied for services at a vision rehabilitation agency. Path analysis was used to examine the effects of perceived overprotection on two positive indicators of adjustment: vision-specific adaptation and environmental mastery. Moreover, antecedents of perceived overprotection were examined. Higher levels of perceived overprotection were associated with less optimal adjustment to age-related vision loss, with lower scores on measures of vision-specific adaptation and environmental mastery. Higher levels of functional disability and instrumental support received were associated with higher levels of perceived overprotection. Findings indicate that support providers of older adults with visual impairment as well as vision rehabilitation service providers need to be aware of the detrimental impact of perceived overprotection.

Artificial neural network to support thermohydraulic design optimization for an advanced nuclear heat removal system

International Nuclear Information System (INIS)

Ridluan, Artit; Tokuhiro, Akira; Linda, Ondrej; Manic, Milos

2009-01-01

The U.S. Department of Energy (DOE) is leading a number of initiatives, including one known as the Next Generation Nuclear Plant (NGNP) project. One of the NGNP nuclear system concepts is the Very High Temperature (gas-cooled) Reactor (VHTR) that may be coupled to a hydrogen generating plant to support the anticipated hydrogen economy. For the NGNP, an efficient power conversion system using an Intermediate Heat Exchanger (IHX) is key to electricity and/or process heat generation (hydrogen production). Ideally, it's desirable for the IHX to be compact and thermally efficient. However, traditional heat exchanger design practices do not assure that the design parameters are optimized. As part of NGNP heat exchanger design and optimization project, this research paper thus proposes developing a recurrent-type Artificial Neural Network (ANN), the Hopfield Network (HN) model, in which the activation function is modified, as a design optimization approach to support a NGNP thermal system candidate, the Printed Circuit Heat Exchanger (PCHE). Four quadratic functions, available in literature, were used to test the presented methodology. The results computed by an artificially intelligent approach were compared to another approach, the Genetic Algorithm (GA). The results show that the HN results are close to GA in optimization of multi-variable second-order equations. (author)

OPTIMIZING USABILITY OF AN ECONOMIC DECISION SUPPORT TOOL: PROTOTYPE OF THE EQUIPT TOOL.

Science.gov (United States)

Cheung, Kei Long; Hiligsmann, Mickaël; Präger, Maximilian; Jones, Teresa; Józwiak-Hagymásy, Judit; Muñoz, Celia; Lester-George, Adam; Pokhrel, Subhash; López-Nicolás, Ángel; Trapero-Bertran, Marta; Evers, Silvia M A A; de Vries, Hein

2018-01-01

Economic decision-support tools can provide valuable information for tobacco control stakeholders, but their usability may impact the adoption of such tools. This study aims to illustrate a mixed-method usability evaluation of an economic decision-support tool for tobacco control, using the EQUIPT ROI tool prototype as a case study. A cross-sectional mixed methods design was used, including a heuristic evaluation, a thinking aloud approach, and a questionnaire testing and exploring the usability of the Return of Investment tool. A total of sixty-six users evaluated the tool (thinking aloud) and completed the questionnaire. For the heuristic evaluation, four experts evaluated the interface. In total twenty-one percent of the respondents perceived good usability. A total of 118 usability problems were identified, from which twenty-six problems were categorized as most severe, indicating high priority to fix them before implementation. Combining user-based and expert-based evaluation methods is recommended as these were shown to identify unique usability problems. The evaluation provides input to optimize usability of a decision-support tool, and may serve as a vantage point for other developers to conduct usability evaluations to refine similar tools before wide-scale implementation. Such studies could reduce implementation gaps by optimizing usability, enhancing in turn the research impact of such interventions.

Topology optimization of two-dimensional waveguides

DEFF Research Database (Denmark)

Jensen, Jakob Søndergaard; Sigmund, Ole

2003-01-01

In this work we use the method of topology optimization to design two-dimensional waveguides with low transmission loss.......In this work we use the method of topology optimization to design two-dimensional waveguides with low transmission loss....

Role of vision loss, functional limitations and the supporting network in depression in a general population.

Science.gov (United States)

van Nispen, Ruth M A; Vreeken, Hilde L; Comijs, Hannie C; Deeg, Dorly J H; van Rens, Ger H M B

2016-02-01

Although the prevalence of depression in visually impaired older persons is high, the association between vision loss and depression seems to be influenced by factors other than visual impairment. In this study, the role of vision loss, functional limitations and social network characteristics in relation to depressive symptoms was investigated. Cross-sectional data (N = 1237) from the Longitudinal Aging Study Amsterdam were used to investigate the prevalence of depression (Center of Epidemiological Studies-Depression scale) within subgroups with increasing vision loss. In linear regression models, functional limitations and social network characteristics were examined as possible mediators in the association between vision loss and depression. Having a partner was considered to be a potential moderator. Although a significant linear trend was found in the presence of depressive symptoms with 14% in normally sighted, 23% in mild and 37% in severe vision loss (χ(2)(1) = 14.9; p depression. Mediators were functional limitations (p depression, a trend was found with increasing severity of vision loss, indicating the need for more attention in (mental) health care and low-vision rehabilitation. In the general older population, vision loss was not an independent determinant of depression but was mediated by functional limitations and social network size. Rather than receiving actual social support, the idea of having a social network to rely on when needed seemed to be associated with lower levels of depression. © 2015 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Optimization of fuel cycles: marginal loss values; Optimisation des cycles de combustibles: valeurs marginales des pertes

Energy Technology Data Exchange (ETDEWEB)

Gaussens, J [Commissariat a l' Energie Atomique, 75 - Paris (France); Lasteyrie, B de; Doumerc, J [Compagnie pour l' Etude et la Realisation de Combustibles Atomiques, 75 - Paris (France)

1965-07-01

Uranium processing from the pit to the fuel element rod entails metal losses at every step. These losses become more and more expensive with the elaboration of the metal. Some of the uranium must be accepted as definitely lost whilst the rest could be recovered and recycled. The high cost of these losses, whether they are recycled or not, and the fact that the higher the enrichment is the higher their costs are, make it necessary to take them into account when optimizing fuel cycles. It is therefore felt important to determine their most desirable level from an economic point of view at the various nuclear fuel processing stages. However, in France as in some other countries, fissile material production is a state concern, whilst fuel element fabrication is carried out by private enterprise. Optimization criteria and the economic value of losses are therefore different for each of the two links in the fabrication chain. One can try in spite of this to reach an optimum which would conform to public interest, without interfering with the firm's sales policy. This entails using the fact that for a given output marginal costs are equal at the optimum. One can therefore adjust the level of the losses to attain this equation of marginal costs, as these are easier to obtain from the firm than a justification of the actual prices. One notices moreover that, although mainly concerned with losses, this global analysis can bring both the state and the firm to a better use of other production factors. An account is given of the theory of this economic optimization method and practical applications in the field of natural uranium-graphite moderated and CO{sub 2} cooled reactor fuel element fabrication are offered. (authors) [French] L'elaboration de l'uranium, de la mine a la cartouche d'element combustible, s'accompagne, a tous les stades, de pertes, de plus en plus onereuses, a mesure que le metal devient plus elabore. Une certaine proportion de l'uranium doit etre consideree

Optimization of fuel cycles: marginal loss values; Optimisation des cycles de combustibles: valeurs marginales des pertes

Energy Technology Data Exchange (ETDEWEB)

Gaussens, J. [Commissariat a l' Energie Atomique, 75 - Paris (France); Lasteyrie, B. de; Doumerc, J. [Compagnie pour l' Etude et la Realisation de Combustibles Atomiques, 75 - Paris (France)

1965-07-01

Uranium processing from the pit to the fuel element rod entails metal losses at every step. These losses become more and more expensive with the elaboration of the metal. Some of the uranium must be accepted as definitely lost whilst the rest could be recovered and recycled. The high cost of these losses, whether they are recycled or not, and the fact that the higher the enrichment is the higher their costs are, make it necessary to take them into account when optimizing fuel cycles. It is therefore felt important to determine their most desirable level from an economic point of view at the various nuclear fuel processing stages. However, in France as in some other countries, fissile material production is a state concern, whilst fuel element fabrication is carried out by private enterprise. Optimization criteria and the economic value of losses are therefore different for each of the two links in the fabrication chain. One can try in spite of this to reach an optimum which would conform to public interest, without interfering with the firm's sales policy. This entails using the fact that for a given output marginal costs are equal at the optimum. One can therefore adjust the level of the losses to attain this equation of marginal costs, as these are easier to obtain from the firm than a justification of the actual prices. One notices moreover that, although mainly concerned with losses, this global analysis can bring both the state and the firm to a better use of other production factors. An account is given of the theory of this economic optimization method and practical applications in the field of natural uranium-graphite moderated and CO{sub 2} cooled reactor fuel element fabrication are offered. (authors) [French] L'elaboration de l'uranium, de la mine a la cartouche d'element combustible, s'accompagne, a tous les stades, de pertes, de plus en plus onereuses, a mesure que le metal devient plus elabore. Une certaine proportion de l

Optimization of spin-coated electrodes for electrolyte-supported solid oxide fuel cells

International Nuclear Information System (INIS)

Nobrega, Shayenne Diniz da; Monteiro, Natalia Kondo; Tabuti, Francisco; Fonseca, Fabio Coral; Florio, Daniel Zanetti de

2017-01-01

Electrodes for electrolyte-supported solid oxide fuel cells (SOFC’s) were fabricated by spin coating. Strontium-doped lanthanum manganite (LSM) cathode and nickel yttria-stabilized zirconia cermet anodes were synthesized and processed for enhanced deposition conditions. The influence of electrode microstructural parameters was investigated by a systematic experimental procedure aiming at optimized electrochemical performance of single cells. Polarization curves showed a strong dependence on both electrode thickness and sintering temperature. By a systematic control of such parameters, the performance of single cells was significantly enhanced due to decreasing of polarization resistance from 26 Ω cm² to 0.6 Ω cm² at 800°C. The results showed that spin-coated electrodes can be optimized for fast and cost effective fabrication of SOFCs. (author)

Optimization of spin-coated electrodes for electrolyte-supported solid oxide fuel cells

Energy Technology Data Exchange (ETDEWEB)

Nobrega, Shayenne Diniz da; Monteiro, Natalia Kondo; Tabuti, Francisco; Fonseca, Fabio Coral, E-mail: shaynnedn@hotmail.com, E-mail: nataliakm@usp.br, E-mail: fntabuti@ipen.br, E-mail: fabiocf@usp.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN-CNEN/SP), Sao Paulo, SP (Brazil); Florio, Daniel Zanetti de, E-mail: daniel.florio@ufabc.edu.br [Universidade Federal do ABC (UFABC), Santo Andre, SP (Brazil)

2017-01-15

Electrodes for electrolyte-supported solid oxide fuel cells (SOFC’s) were fabricated by spin coating. Strontium-doped lanthanum manganite (LSM) cathode and nickel yttria-stabilized zirconia cermet anodes were synthesized and processed for enhanced deposition conditions. The influence of electrode microstructural parameters was investigated by a systematic experimental procedure aiming at optimized electrochemical performance of single cells. Polarization curves showed a strong dependence on both electrode thickness and sintering temperature. By a systematic control of such parameters, the performance of single cells was significantly enhanced due to decreasing of polarization resistance from 26 Ω cm² to 0.6 Ω cm² at 800°C. The results showed that spin-coated electrodes can be optimized for fast and cost effective fabrication of SOFCs. (author)

HUBUNGAN RELIGIUSITAS, OPTIMISM, SOCIAL SUPPORT, DAN PSYCHOLOGICAL WELL-BEING PESERTA DIDIK MAN SE-KOTA MALANG

Directory of Open Access Journals (Sweden)

Muhammad Farid Ilhamuddin

2017-03-01

Full Text Available This study aims to know the relation between religiousity (X1 and psychological well being (Y, the relation between optimism (X2 and psychological well being (Y, as well as the relation between social support (X3 and psychological well being (Y of students of MAN in the entire Malang city. This study was a non-experimental study with causal relationship study plan. The result of this research showed that there was a positive significant between X1 and Y, X2 and Y, X3 and Y; X1, X2, X3 had strong linear relation with Y; the influence of the three independent     logical well being (Y, optimism (X2 dan psychological well being (Y, social support (X3 and psychological well being (Y student of MAN se-Kota Malang. Penelitian ini bertujuan untuk mengetahui hubungan religiusitas (X1 dan psychological well being (Y, optimis (X2 dan psychological well being (Y, social support (X3 dan psychological well being (Y peserta didik MAN se-kota Malang. Pendekatan yang digunakan adalah non experimental research dengan jenis penelitian causal relationship study. Hasil penelitian menunjukkan ada hubungan positif signifikan antara X1 dan Y, X2 dan Y, X3 dan Y; X1, X2, X3 memiliki hubungan linear yang kuat dengan Y; pengaruh ketiga variabel independen psychological well being (Y, optimism (X2 dan psychological well being (Y, social support (X3 dan psychological well being (Y peserta didik MAN se-Kota Malang.

Anxiety and Depression in Transgender Individuals: The Roles of Transition Status, Loss, Social Support, and Coping

Science.gov (United States)

Budge, Stephanie L.; Adelson, Jill L.; Howard, Kimberly A. S.

2013-01-01

Objective: The purpose of the current study was to examine facilitative and avoidant coping as mediators between distress and transition status, social support, and loss. Method: A total of 351 transgender individuals (n = 226 transgender women and n = 125 transgender men) participated in this study. Participants completed measures on transgender…

Recovery of insulin sensitivity and optimal body composition after rapid weight loss in obese dogs fed a high-protein medium-carbohydrate diet.

Science.gov (United States)

André, A; Leriche, I; Chaix, G; Thorin, C; Burger, M; Nguyen, P

2017-06-01

This study investigated the effects of an experimental high-protein medium-carbohydrate diet (protein level, 46% metabolizable energy, ME). First, postprandial plasma glucose and insulin kinetics were determined in steady-state overweight/obese Beagle dogs (28%-41% excess body weight) for an experimental high-protein medium-carbohydrate diet (protein level, 46% ME) and a commercial high-carbohydrate medium-protein diet (protein level, 24%ME) in obese dogs. Secondly, all the dogs were included in a weight loss programme. They were fed the high-protein medium-carbohydrate diet, and the energy allocation was gradually reduced until they reached their optimal body weight. Insulin sensitivity and body composition were evaluated before and after weight loss using a euglycaemic-hyperinsulinaemic clamp and the deuterium oxide dilution technique respectively. For statistical analysis, linear mixed effect models were used with a significance level of 5%. Postprandial plasma glucose and insulin concentrations were substantially lower with the high-protein medium-carbohydrate diet than the high-carbohydrate medium-protein diet. These differences can be explained mainly by the difference in carbohydrate content between the two diets. Energy restriction (35% lower energy intake than in the obese state) resulted in a 2.23 ± 0.05% loss in body weight/week, and the dogs reached their optimal body weight in 12-16 weeks. Weight loss was associated with a significant increase in insulin sensitivity. The high-protein medium-carbohydrate diet allowed fat-free mass preservation despite a relatively high rate of weekly weight loss. The increase in insulin sensitivity indicated improved control of carbohydrate metabolism, possible due to weight loss and to the nature of the diet. Thus, a high-protein medium-carbohydrate diet is a good nutritional solution for managing the weight of overweight dogs. This diet may improve glycaemic control, which could be beneficial for preventing or

Heat loss analysis-based design of a 12 MW wind power generator module having an HTS flux pump exciter

International Nuclear Information System (INIS)

Sung, Hae-Jin; Go, Byeong-Soo; Jiang, Zhenan; Park, Minwon; Yu, In-Keun

2016-01-01

Highlights: • A large-scale HTS generator module has been suggested to avoid issues such as a huge vacuum vessel and higher reliability. • The challenging heat loss analysis of a large-scale HTS generator has successfully been performed, enabling the design of an optimal support structure having a total heat loss of 43 W/400 kW. • The results prove the potential of a large-scale superconducting wind-power generator to operate efficiently, and support further development of the concept. - Abstract: The development of an effective high-temperature superconducting (HTS) generator is currently a research focus; however, the reduction of heat loss of a large-scale HTS generator is a challenge. This study deals with a heat loss analysis-based design of a 12 MW wind power generator module having an HTS flux pump exciter. The generator module consists of an HTS rotor of the generator and an HTS flux pump exciter. The specifications of the module were described, and the detailed configuration of the module was illustrated. For the heat loss analysis of the module, the excitation loss of the flux pump exciter, eddy current loss of all of the structures in the module, radiation loss, and conduction loss of an HTS coil supporter were assessed using a 3D finite elements method program. In the case of the conduction loss, different types of the supporters were compared to find out the supporter of the lowest conduction loss in the module. The heat loss analysis results of the module were reflected in the design of the generator module and discussed in detail. The results will be applied to the design of large-scale superconducting generators for wind turbines including a cooling system.

Heat loss analysis-based design of a 12 MW wind power generator module having an HTS flux pump exciter

Energy Technology Data Exchange (ETDEWEB)

Sung, Hae-Jin, E-mail: haejin0216@gmail.com [Changwon National University, 20 Changwondaehak-ro, Changwon, 641-773 (Korea, Republic of); Go, Byeong-Soo [Changwon National University, 20 Changwondaehak-ro, Changwon, 641-773 (Korea, Republic of); Jiang, Zhenan [Robinson Research Institute, Victoria University of Wellington, PO Box 33436 (New Zealand); Park, Minwon [Changwon National University, 20 Changwondaehak-ro, Changwon, 641-773 (Korea, Republic of); Yu, In-Keun, E-mail: yuik@changwon.ac.kr [Changwon National University, 20 Changwondaehak-ro, Changwon, 641-773 (Korea, Republic of)

2016-11-15

Highlights: • A large-scale HTS generator module has been suggested to avoid issues such as a huge vacuum vessel and higher reliability. • The challenging heat loss analysis of a large-scale HTS generator has successfully been performed, enabling the design of an optimal support structure having a total heat loss of 43 W/400 kW. • The results prove the potential of a large-scale superconducting wind-power generator to operate efficiently, and support further development of the concept. - Abstract: The development of an effective high-temperature superconducting (HTS) generator is currently a research focus; however, the reduction of heat loss of a large-scale HTS generator is a challenge. This study deals with a heat loss analysis-based design of a 12 MW wind power generator module having an HTS flux pump exciter. The generator module consists of an HTS rotor of the generator and an HTS flux pump exciter. The specifications of the module were described, and the detailed configuration of the module was illustrated. For the heat loss analysis of the module, the excitation loss of the flux pump exciter, eddy current loss of all of the structures in the module, radiation loss, and conduction loss of an HTS coil supporter were assessed using a 3D finite elements method program. In the case of the conduction loss, different types of the supporters were compared to find out the supporter of the lowest conduction loss in the module. The heat loss analysis results of the module were reflected in the design of the generator module and discussed in detail. The results will be applied to the design of large-scale superconducting generators for wind turbines including a cooling system.

Shape optimization of 3D curved slots and its application to the squirrel-cage elastic support design

Science.gov (United States)

Wang, Dan; Zhang, Weihong; Wang, Zhenpei; Zhu, Jihong

2010-10-01

The squirrel-cage elastic support is one of the most important components of an aero-engine rotor system. A proper structural design will favor the static and dynamic performances of the system. In view of the deficiency of the current shape optimization techniques, a new mapping approach is proposed to define shape design variables based on the parametric equations of 3D curves and surfaces. It is then applied for the slot shape optimization of a squirrel-cage elastic support. To this end, an automatic design procedure that integrates the Genetic Algorithm (GA) is developed to solve the problem. Two typical examples with different shape constraints are considered. Numerical results provide reasonable optimum designs for the improvement of stiffness and strength of the squirrel-cage elastic support.

Decision Support System for Optimized Herbicide Dose in Spring Barley

DEFF Research Database (Denmark)

Sønderskov, Mette; Kudsk, Per; Mathiassen, Solvejg K

2014-01-01

Crop Protection Online (CPO) is a decision support system, which integrates decision algorithms quantifying the requirement for weed control and a herbicide dose model. CPO was designed to be used by advisors and farmers to optimize the choice of herbicide and dose. The recommendations from CPO...... as the Treatment Frequency Index (TFI)) compared to a high level of required weed control. The observations indicated that the current level of weed control required is robust for a range of weed scenarios. Weed plant numbers 3 wk after spraying indicated that the growth of the weed species were inhibited...

Coordination of a Random Yield Supply Chain with a Loss-Averse Supplier

Directory of Open Access Journals (Sweden)

Jiarong Luo

2015-01-01

Full Text Available This paper investigates the coordination of a supply chain consisting of a loss-averse supplier and a risk-neutral buyer who orders products from the supplier who suffers from random yield to meet a deterministic demand. We derive the risk-neutral buyer’s optimal order policy and the loss-averse supplier’s optimal production policy under shortage-penalty-surplus-subsidy (SPSS contracts. We also analyze the impacts of loss aversion on the loss-averse supplier’s production decision making and find that the loss-averse supplier may produce less than, equal to, or more than the risk-neutral supplier. Then, we provide explicit conditions on which the random yield supply chain with a loss-averse supplier can be coordinated under SPSS contracts. Finally, adopting numerical examples, we find that when the shortage penalty is low, the buyer’s optimal order quantity will increase, while the supplier’s optimal production quantity will first decrease and then increase as the loss aversion level increases. When the shortage penalty is high, the buyer’s optimal order quantity will decrease but the supplier’s optimal production quantity will always increase as the loss aversion level increases. Furthermore, the numerical examples provide strong evidence for the view that SPSS contracts can effectively improve the performance of the whole supply chain.

Control strategies for wind farm power optimization: LES study

Science.gov (United States)

Ciri, Umberto; Rotea, Mario; Leonardi, Stefano

2017-11-01

Turbines in wind farms operate in off-design conditions as wake interactions occur for particular wind directions. Advanced wind farm control strategies aim at coordinating and adjusting turbine operations to mitigate power losses in such conditions. Coordination is achieved by controlling on upstream turbines either the wake intensity, through the blade pitch angle or the generator torque, or the wake direction, through yaw misalignment. Downstream turbines can be adapted to work in waked conditions and limit power losses, using the blade pitch angle or the generator torque. As wind conditions in wind farm operations may change significantly, it is difficult to determine and parameterize the variations of the coordinated optimal settings. An alternative is model-free control and optimization of wind farms, which does not require any parameterization and can track the optimal settings as conditions vary. In this work, we employ a model-free optimization algorithm, extremum-seeking control, to find the optimal set-points of generator torque, blade pitch and yaw angle for a three-turbine configuration. Large-Eddy Simulations are used to provide a virtual environment to evaluate the performance of the control strategies under realistic, unsteady incoming wind. This work was supported by the National Science Foundation, Grants No. 1243482 (the WINDINSPIRE project) and IIP 1362033 (I/UCRC WindSTAR). TACC is acknowledged for providing computational time.

Fruit fly optimization based least square support vector regression for blind image restoration

Science.gov (United States)

Zhang, Jiao; Wang, Rui; Li, Junshan; Yang, Yawei

2014-11-01

The goal of image restoration is to reconstruct the original scene from a degraded observation. It is a critical and challenging task in image processing. Classical restorations require explicit knowledge of the point spread function and a description of the noise as priors. However, it is not practical for many real image processing. The recovery processing needs to be a blind image restoration scenario. Since blind deconvolution is an ill-posed problem, many blind restoration methods need to make additional assumptions to construct restrictions. Due to the differences of PSF and noise energy, blurring images can be quite different. It is difficult to achieve a good balance between proper assumption and high restoration quality in blind deconvolution. Recently, machine learning techniques have been applied to blind image restoration. The least square support vector regression (LSSVR) has been proven to offer strong potential in estimating and forecasting issues. Therefore, this paper proposes a LSSVR-based image restoration method. However, selecting the optimal parameters for support vector machine is essential to the training result. As a novel meta-heuristic algorithm, the fruit fly optimization algorithm (FOA) can be used to handle optimization problems, and has the advantages of fast convergence to the global optimal solution. In the proposed method, the training samples are created from a neighborhood in the degraded image to the central pixel in the original image. The mapping between the degraded image and the original image is learned by training LSSVR. The two parameters of LSSVR are optimized though FOA. The fitness function of FOA is calculated by the restoration error function. With the acquired mapping, the degraded image can be recovered. Experimental results show the proposed method can obtain satisfactory restoration effect. Compared with BP neural network regression, SVR method and Lucy-Richardson algorithm, it speeds up the restoration rate and

Loss-resistant unambiguous phase measurement

Science.gov (United States)

Dinani, Hossein T.; Berry, Dominic W.

2014-08-01

Entangled multiphoton states have the potential to provide improved measurement accuracy, but are sensitive to photon loss. It is possible to calculate ideal loss-resistant states that maximize the Fisher information, but it is unclear how these could be experimentally generated. Here we propose a set of states that can be obtained by processing the output from parametric down-conversion. Although these states are not optimal, they provide performance very close to that of optimal states for a range of parameters. Moreover, we show how to use sequences of such states in order to obtain an unambiguous phase measurement that beats the standard quantum limit. We consider the optimization of parameters in order to minimize the final phase variance, and find that the optimum parameters are different from those that maximize the Fisher information.

Text Message Support for Weight Loss in Patients With Prediabetes: A Randomized Clinical Trial.

Science.gov (United States)

Fischer, Henry H; Fischer, Ilana P; Pereira, Rocio I; Furniss, Anna L; Rozwadowski, Jeanne M; Moore, Susan L; Durfee, Michael J; Raghunath, Silvia G; Tsai, Adam G; Havranek, Edward P

2016-08-01

Although the benefits of in-person Diabetes Prevention Program (DPP) classes for diabetes prevention have been demonstrated in trials, effectiveness in clinical practice is limited by low participation rates. This study explores whether text message support enhances weight loss in patients offered DPP classes. English- and Spanish-speaking patients with prediabetes (n = 163) were randomized to the control group, which only received an invitation to DPP classes as defined by the Centers for Disease Control and Prevention, or to the text message-augmented intervention group, which also received text messages adapted from the DPP curriculum for 12 months. Mean weight decreased 0.6 pounds (95% CI -2.7 to 1.6) in the control group and 2.6 pounds (95% CI -5.5 to 0.2) in the intervention group (P value 0.05). Three percent weight loss was achieved by 21.5% of participants in the control group (95% CI 12.5-30.6), compared with 38.5% in the intervention group (95% CI 27.7-49.3) (absolute difference 17.0%; P value 0.02). Mean glycated hemoglobin (HbA1c) increased by 0.19% or 2.1 mmol/mol (95% CI -0.1 to 0.5%) and decreased by 0.09% or 1.0 mmol/mol (95% CI -0.2 to 0.0%) in the control group and intervention participants, respectively (absolute difference 0.28%; P value 0.07). Stratification by language demonstrated a significant treatment effect in Spanish speakers but not in English speakers. Text message support can lead to clinically significant weight loss in patients with prediabetes. Further study assessing effect by primary language and in an operational setting is warranted. © 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.

Marginal Loss Calculations for the DCOPF

Energy Technology Data Exchange (ETDEWEB)

Eldridge, Brent [Federal Energy Regulatory Commission, Washington, DC (United States); Johns Hopkins Univ., Baltimore, MD (United States); O' Neill, Richard P. [Federal Energy Regulatory Commission, Washington, DC (United States); Castillo, Andrea R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-12-05

The purpose of this paper is to explain some aspects of including a marginal line loss approximation in the DCOPF. The DCOPF optimizes electric generator dispatch using simplified power flow physics. Since the standard assumptions in the DCOPF include a lossless network, a number of modifications have to be added to the model. Calculating marginal losses allows the DCOPF to optimize the location of power generation, so that generators that are closer to demand centers are relatively cheaper than remote generation. The problem formulations discussed in this paper will simplify many aspects of practical electric dispatch implementations in use today, but will include sufficient detail to demonstrate a few points with regard to the handling of losses.

DGA-based VAR rescheduling for transmission loss reduction

Energy Technology Data Exchange (ETDEWEB)

Mishra, S. [Indian Inst. of Technology, Delhi (India); Taylor, G.A. [Brunel Univ., London (United Kingdom). Brunel Inst. of Power Systems; Reddy, J.B.V. [Government of India, New Delhi (India). Dept. of Science and Technology; Naeem, M.H. [Multimedia Univ. (Malaysia). Faculty of Engineering

2009-07-01

Power losses in power transmission lines can be minimized by adjusting transformer taps and switchable VAR sources. Optimal power flow (OPF) is a static, nonlinear, multi-objective optimization challenge in which the optimal settings of control variables must be determined for minimizing the cost of generation, emissions, transmission losses and voltage and power flow deviations. OPF is important in power system operation because a small savings per hour can mean a large annual savings. This paper presented a method to reduce transmission power losses using a Differential Genetic Algorithm (DGA) for VAR rescheduling. The New England 39-bus power system was used as a test case. Power losses were minimized by changing the tap settings of various transformers and by varying the injected reactive power. The paper showed that certain buses in the system can improve the voltage profile and reduce transmission losses through reactive power injections from capacitor banks. In this study, minimum reactive power output of generators was maintained at zero to ensure that the generators did not draw reactive power. The DGA was shown to produce better results than the Conventional Genetic Algorithm in terms of power loss minimization. 12 refs., 1 tab., 2 figs.

Cortical correlations support optimal sequence memory

OpenAIRE

Helias, Moritz; Schuecker, Jannis; Dahmen, David; Goedeke, Sven

2017-01-01

The brain processes time-varying input, but is it not known if its dynamical state is optimal for this task. Indeed, recurrent and randomly coupled networks of rate neurons display a rich internal dynamics near the transition to chaos [1], which has been associated with optimal information processing capabilities [2, 3, 4]. In particular, the dynamics becomes arbitrarily slow at the onset of chaos similar to ‘critical slowing down’. The interplay between time-dependent input signals, network ...

Long term performance degradation analysis and optimization of anode supported solid oxide fuel cell stacks

International Nuclear Information System (INIS)

Parhizkar, Tarannom; Roshandel, Ramin

2017-01-01

Highlights: • A degradation based optimization framework is developed. • The cost of electricity based on degradation of solid oxide fuel cells is minimized. • The effects of operating conditions on degradation mechanisms are investigated. • Results show 7.12% lower cost of electricity in comparison with base case. • Degradation based optimization is a beneficial concept for long term analysis. - Abstract: The main objective of this work is minimizing the cost of electricity of solid oxide fuel cell stacks by decelerating degradation mechanisms rate in long term operation for stationary power generation applications. The degradation mechanisms in solid oxide fuel cells are caused by microstructural changes, reactions between lanthanum strontium manganite and electrolyte, poisoning by chromium, carburization on nickel particles, formation of nickel sulfide, nickel coarsening, nickel oxidation, loss of conductivity and crack formation in the electrolyte. The rate of degradation mechanisms depends on the cell operating conditions (cell voltage and fuel utilization). In this study, the degradation based optimization framework is developed which determines optimum operating conditions to achieve a minimum cost of electricity. To show the effectiveness of the developed framework, optimization results are compared with the case that system operates at its design point. Results illustrate optimum operating conditions decrease the cost of electricity by 7.12%. The performed study indicates that degradation based optimization is a beneficial concept for long term performance degradation analysis of energy conversion systems.

A Linear Programming Model to Optimize Various Objective Functions of a Foundation Type State Support Program.

Science.gov (United States)

Matzke, Orville R.

The purpose of this study was to formulate a linear programming model to simulate a foundation type support program and to apply this model to a state support program for the public elementary and secondary school districts in the State of Iowa. The model was successful in producing optimal solutions to five objective functions proposed for…

Theory and experimental verifications of the resonator Q and equivalent electrical parameters due to viscoelastic and mounting supports losses.

Science.gov (United States)

Yong, Yook-Kong; Patel, Mihir S; Tanaka, Masako

2010-08-01

A novel analytical/numerical method for calculating the resonator Q and its equivalent electrical parameters due to viscoelastic, conductivity, and mounting supports losses is presented. The method presented will be quite useful for designing new resonators and reducing the time and costs of prototyping. There was also a necessity for better and more realistic modeling of the resonators because of miniaturization and the rapid advances in the frequency ranges of telecommunication. We present new 3-D finite elements models of quartz resonators with viscoelasticity, conductivity, and mounting support losses. The losses at the mounting supports were modeled by perfectly matched layers (PMLs). A previously published theory for dissipative anisotropic piezoelectric solids was formulated in a weak form for finite element (FE) applications. PMLs were placed at the base of the mounting supports to simulate the energy losses to a semi-infinite base substrate. FE simulations were carried out for free vibrations and forced vibrations of quartz tuning fork and AT-cut resonators. Results for quartz tuning fork and thickness shear AT-cut resonators were presented and compared with experimental data. Results for the resonator Q and the equivalent electrical parameters were compared with their measured values. Good equivalences were found. Results for both low- and high-Q AT-cut quartz resonators compared well with their experimental values. A method for estimating the Q directly from the frequency spectrum obtained for free vibrations was also presented. An important determinant of the quality factor Q of a quartz resonator is the loss of energy from the electrode area to the base via the mountings. The acoustical characteristics of the plate resonator are changed when the plate is mounted onto a base substrate. The base affects the frequency spectra of the plate resonator. A resonator with a high Q may not have a similarly high Q when mounted on a base. Hence, the base is an

Prediction of Skin Sensitization with a Particle Swarm Optimized Support Vector Machine

Directory of Open Access Journals (Sweden)

Chenzhong Cao

2009-07-01

Full Text Available Skin sensitization is the most commonly reported occupational illness, causing much suffering to a wide range of people. Identification and labeling of environmental allergens is urgently required to protect people from skin sensitization. The guinea pig maximization test (GPMT and murine local lymph node assay (LLNA are the two most important in vivo models for identification of skin sensitizers. In order to reduce the number of animal tests, quantitative structure-activity relationships (QSARs are strongly encouraged in the assessment of skin sensitization of chemicals. This paper has investigated the skin sensitization potential of 162 compounds with LLNA results and 92 compounds with GPMT results using a support vector machine. A particle swarm optimization algorithm was implemented for feature selection from a large number of molecular descriptors calculated by Dragon. For the LLNA data set, the classification accuracies are 95.37% and 88.89% for the training and the test sets, respectively. For the GPMT data set, the classification accuracies are 91.80% and 90.32% for the training and the test sets, respectively. The classification performances were greatly improved compared to those reported in the literature, indicating that the support vector machine optimized by particle swarm in this paper is competent for the identification of skin sensitizers.

Prediction of Skin Sensitization with a Particle Swarm Optimized Support Vector Machine

Science.gov (United States)

Yuan, Hua; Huang, Jianping; Cao, Chenzhong

2009-01-01

Skin sensitization is the most commonly reported occupational illness, causing much suffering to a wide range of people. Identification and labeling of environmental allergens is urgently required to protect people from skin sensitization. The guinea pig maximization test (GPMT) and murine local lymph node assay (LLNA) are the two most important in vivo models for identification of skin sensitizers. In order to reduce the number of animal tests, quantitative structure-activity relationships (QSARs) are strongly encouraged in the assessment of skin sensitization of chemicals. This paper has investigated the skin sensitization potential of 162 compounds with LLNA results and 92 compounds with GPMT results using a support vector machine. A particle swarm optimization algorithm was implemented for feature selection from a large number of molecular descriptors calculated by Dragon. For the LLNA data set, the classification accuracies are 95.37% and 88.89% for the training and the test sets, respectively. For the GPMT data set, the classification accuracies are 91.80% and 90.32% for the training and the test sets, respectively. The classification performances were greatly improved compared to those reported in the literature, indicating that the support vector machine optimized by particle swarm in this paper is competent for the identification of skin sensitizers. PMID:19742136

An 8-Week Web-Based Weight Loss Challenge With Celebrity Endorsement and Enhanced Social Support: Observational Study

Science.gov (United States)

Collins, Clare E; Morgan, Philip J; Callister, Robin

2013-01-01

Background Initial engagement and weight loss within Web-based weight loss programs may predict long-term success. The integration of persuasive Web-based features may boost engagement and therefore weight loss. Objective To determine whether an 8-week challenge within a commercial Web-based weight loss program influenced weight loss, website use, and attrition in the short term, when compared to the standard program. Methods De-identified data for participants (mean age 36.7±10.3 years; 86% female) who enrolled in the Biggest Loser Club (BLC) (n=952) and the BLC’s Shannan Ponton Fast Track Challenge (SC) for 8 weeks (n=381) were compared. The BLC program used standard evidence-based website features, with individualized calorie and exercise targets to facilitate a weight loss of 0.5-1 kg per week (–500kcal/day less than estimated energy expenditure). SC used the same website features but in addition promoted greater initial weight loss using a 1200 kcal/day energy intake target and physical activity energy expenditure of 600 kcal/day. SC used persuasive features to facilitate greater user engagement, including offering additional opportunities for social support (eg, webinar meetings with a celebrity personal trainer and social networking) endorsed by a celebrity personal trainer. Self-reported weekly weight records were used to determine weight change after 8 weeks. A primary analysis was undertaken using a generalized linear mixed model (GLMM) with all available weight records for all participants included. Dropout (participants who cancelled their subscription) and nonusage (participants who stopped using the Web-based features) attrition rates at 8 weeks were calculated. The number of participants who accessed each website feature and the total number of days each feature was used were calculated. The difference between attrition rates and website use for the two programs were tested using chi-square and Wilcoxon Rank Sum tests, respectively. Results

An 8-week web-based weight loss challenge with celebrity endorsement and enhanced social support: observational study.

Science.gov (United States)

Hutchesson, Melinda J; Collins, Clare E; Morgan, Philip J; Callister, Robin

2013-07-04

Initial engagement and weight loss within Web-based weight loss programs may predict long-term success. The integration of persuasive Web-based features may boost engagement and therefore weight loss. To determine whether an 8-week challenge within a commercial Web-based weight loss program influenced weight loss, website use, and attrition in the short term, when compared to the standard program. De-identified data for participants (mean age 36.7±10.3 years; 86% female) who enrolled in the Biggest Loser Club (BLC) (n=952) and the BLC's Shannan Ponton Fast Track Challenge (SC) for 8 weeks (n=381) were compared. The BLC program used standard evidence-based website features, with individualized calorie and exercise targets to facilitate a weight loss of 0.5-1 kg per week (-500kcal/day less than estimated energy expenditure). SC used the same website features but in addition promoted greater initial weight loss using a 1200 kcal/day energy intake target and physical activity energy expenditure of 600 kcal/day. SC used persuasive features to facilitate greater user engagement, including offering additional opportunities for social support (eg, webinar meetings with a celebrity personal trainer and social networking) endorsed by a celebrity personal trainer. Self-reported weekly weight records were used to determine weight change after 8 weeks. A primary analysis was undertaken using a generalized linear mixed model (GLMM) with all available weight records for all participants included. Dropout (participants who cancelled their subscription) and nonusage (participants who stopped using the Web-based features) attrition rates at 8 weeks were calculated. The number of participants who accessed each website feature and the total number of days each feature was used were calculated. The difference between attrition rates and website use for the two programs were tested using chi-square and Wilcoxon Rank Sum tests, respectively. Using GLMM, including weight data for all

Multiobjective Optimization of Aircraft Maintenance in Thailand Using Goal Programming: A Decision-Support Model

Directory of Open Access Journals (Sweden)

Yuttapong Pleumpirom

2012-01-01

Full Text Available The purpose of this paper is to develop the multiobjective optimization model in order to evaluate suppliers for aircraft maintenance tasks, using goal programming. The authors have developed a two-step process. The model will firstly be used as a decision-support tool for managing demand, by using aircraft and flight schedules to evaluate and generate aircraft-maintenance requirements, including spare-part lists. Secondly, they develop a multiobjective optimization model by minimizing cost, minimizing lead time, and maximizing the quality under various constraints in the model. Finally, the model is implemented in the actual airline's case.

Optimal Operation of the Integrated Electrical and Heating Systems to Accommodate the Intermittent Renewable Sources

DEFF Research Database (Denmark)

Li, Jinghua; Fang, Jiakun; Zeng, Qing

2016-01-01

The integration of electrical and heating systems has great potential to enhance the flexibility of power systems to accommodate more renewable power such as the wind and solar. This study was to investigate an optimal way to integrate the energy of both systems in urban areas. The amount of energy...... the effectiveness of the proposed solution. The results showed that coordinated optimization of the energy distribution have significant benefits for reducing wind curtailment, operation cost, and energy losses. The proposed model and methodology could help system operators with decision support in the emerging...... conversion between the electrical system and heating system was optimally decided so that the demand within both systems could be met at the least operational cost. Besides, the best node to join with the electrical system and heating system was chosen by consideration of the energy transmission loss...

Watershed Management Optimization Support Tool (WMOST) v1: User Manual and Case Study Examples

Science.gov (United States)

The Watershed Management Optimization Support Tool (WMOST) is intended to be used as a screening tool as part of an integrated watershed management process such as that described in EPA’s watershed planning handbook (EPA 2008).1 The objective of WMOST is to serve as a public-doma...

Hair Loss Myths.

Science.gov (United States)

DiMarco, Gabriella; McMichael, Amy

2017-07-01

INTRODUCTION: Hair loss is a common complaint seen in dermatology clinics. From frustration and attempts at self-help, patients with hair loss may present to the dermatologist with false beliefs, or myths, about the causes of their condition and what treatments are effective. METHODS: We identified 12 common myths about hair loss, categorized as myths about minoxidil treatment, vitamin and mineral supplements, natural topical treatments, and hair care practices. We performed a PubMed search to find evidence to support or refute each myth. RESULTS: We found that there is little evidence to support many of these common hair loss myths. In some cases, randomized controlled trials have investigated the effects of particular therapies and point to the effectiveness of certain hair loss treatments. DISCUSSION: In many cases, there have not been sufficient randomized controlled trials to evaluate the effect of different therapies and hair care practices on hair loss. It is best to guide patients toward treatments with a long track record of efficacy and away from those where little is known scientifically. J Drugs Dermatol. 2017;16(7):690-694..

Analysis of power loss data for the 200 Area Tank Farms in support of K Basin SAR work

International Nuclear Information System (INIS)

Shultz, M.V. Jr.

1994-12-01

An analysis of power loss data for the 200 Area Tank Farms was performed in support of K Basin safety analysis report work. The purpose of the analysis was to establish a relationship between the length of a power outage and its yearly frequency. This relationship can be used to determine whether the duration of a specific power loss is a risk concern. The information was developed from data contained in unusual occurrence reports (UORs) spanning a continuous period of 19.75 years. The average frequency of power loss calculated from the UOR information is 1.22 events per year. The mean of the power loss duration is 32.5 minutes an the median duration is 2 minutes. Nine events resulted in loss of power to both 200 East and 200 West areas simultaneously. Seven events (not necessarily the same events that resulted in loss of power to both 200 areas) resulted in outage durations exceeding 5 minutes. Approximately one-half of the events were caused by human error. The other half resulted from natural phenomena or equipment failures. None of the outages were reported to have any adverse effect on the tank farms

Implant-supported overdentures, a prevention of bone loss in edentulous mandibles? A 5-year follow-up study

DEFF Research Database (Denmark)

von Wowern, N; Gotfredsen, K

2001-01-01

The purpose of this study were to analyse 1) the changes in the bone mineral content (BMC) in mandibles with implant-supported overdentures when compared with the physiologic age-related mandibular BMC loss, 2) whether the BMC changes were different in groups without or with a bar connecting...

Career-related parental support of adolescents with hearing loss: relationships with parents' expectations and occupational status.

Science.gov (United States)

Michael, Rinat; Cinamon, Rachel Gali; Most, Tova

2015-01-01

The study examined the contribution of parents' occupational status and expectations regarding persons with hearing loss to career-related support they provide their deaf and hard of hearing (dhh) adolescent children. Thirty-eight parents completed the Evaluation of Occupational Competence Scale (Weisel & Cinamon, 2005), the Evaluation of Family Competence Scale (Caprara, Regalia, Scabini, Barbaranelli, & Bandura, 2004), the Career-Related Parent Support Scale (Turner, Alliman-Brissett, Lapan, Udipi, & Ergun, 2003), and a background questionnaire. Parents' occupational expectations were positively correlated with their family expectations regarding deaf persons. Parents' occupational status contributed to expectations of success for deaf persons in prestigious occupations with high communication demands. Different types of expectations contributed to career-related parental support. Implications for theory and practice are discussed.

Tooth loss in well-maintained patients with chronic periodontitis during long-term supportive therapy in Brazil.

Science.gov (United States)

Chambrone, Luiz A; Chambrone, Leandro

2006-10-01

The objective of this retrospective study was to assess the reasons for tooth loss in a sample of patients who underwent periodontal therapy and supportive periodontal therapy (SPT) in a Brazilian private periodontal practice. A sample of 120 subjects who had been treated and maintained for 10 years or longer was selected from patients attending a periodontal practice. All patients followed a similar treatment: basic procedures, re-evaluation and periodontal surgery where indicated. Reasons for tooth loss were categorized as periodontal, caries, endodontal, root fractures and extraction of retained or partially erupted third molars. Of the 2927 teeth present at the completion of active periodontal treatment, 53 (1.8%) were lost due to periodontal disease, 16 (0.5%) for root fracture, six (0.2%) to caries, five (0.2%) for endodontic reasons and 31 (1.0%) were lost to extraction of retained or partially erupted third molars. Logistic regression analysis was performed to investigate the association between five independent variables with tooth loss due to periodontitis. Only age (> 60 years) and smoking were statistically significant (p < 0.05). The findings of this survey were consistent with previous studies. Older subjects and smokers were more susceptible to periodontal tooth loss. In addition, patients with generalized chronic periodontitis were treated and maintained for long-term periods with low rates of tooth loss.

Analytical study of optimal design and gain parameters of double-slot plasmonic waveguides

International Nuclear Information System (INIS)

Handapangoda, Dayan; Rukhlenko, Ivan D; Premaratne, Malin

2013-01-01

We theoretically analyze guided modes in optically active and passive double-slot plasmonic waveguides. We show that for one of the two different mode symmetries supported by the waveguide, a most productive guiding condition can be realized by adjusting the thicknesses of the layers to optimal values. We also derive approximate analytic expressions to calculate the optimal geometrical parameters of the waveguide. Interestingly, our analysis shows that the propagation losses associated with the inverse mode symmetry of the double-slot waveguide are comparatively low, regardless of the dimensions of the waveguide. We further show that the propagation losses become the smallest in the limiting case of a single-slot (metal–dielectric–metal (MDM)) waveguide. For both double- and single-slot waveguides, we show that the gain required to overcome the losses can be reduced by choosing a dielectric with a low refractive index. We also derive accurate analytical expressions to readily estimate the critical gain and modal gain of the waveguides. (paper)

Optimal placement of capacito

Directory of Open Access Journals (Sweden)

N. Gnanasekaran

2016-06-01

Full Text Available Optimal size and location of shunt capacitors in the distribution system plays a significant role in minimizing the energy loss and the cost of reactive power compensation. This paper presents a new efficient technique to find optimal size and location of shunt capacitors with the objective of minimizing cost due to energy loss and reactive power compensation of distribution system. A new Shark Smell Optimization (SSO algorithm is proposed to solve the optimal capacitor placement problem satisfying the operating constraints. The SSO algorithm is a recently developed metaheuristic optimization algorithm conceptualized using the shark’s hunting ability. It uses a momentum incorporated gradient search and a rotational movement based local search for optimization. To demonstrate the applicability of proposed method, it is tested on IEEE 34-bus and 118-bus radial distribution systems. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

Technologies for Decreasing Mining Losses

Science.gov (United States)

Valgma, Ingo; Väizene, Vivika; Kolats, Margit; Saarnak, Martin

2013-12-01

In case of stratified deposits like oil shale deposit in Estonia, mining losses depend on mining technologies. Current research focuses on extraction and separation possibilities of mineral resources. Selective mining, selective crushing and separation tests have been performed, showing possibilities of decreasing mining losses. Rock crushing and screening process simulations were used for optimizing rock fractions. In addition mine backfilling, fine separation, and optimized drilling and blasting have been analyzed. All tested methods show potential and depend on mineral usage. Usage in addition depends on the utilization technology. The questions like stability of the material flow and influences of the quality fluctuations to the final yield are raised.

Optimal placement of FACTS devices using optimization techniques: A review

Science.gov (United States)

Gaur, Dipesh; Mathew, Lini

2018-03-01

Modern power system is dealt with overloading problem especially transmission network which works on their maximum limit. Today’s power system network tends to become unstable and prone to collapse due to disturbances. Flexible AC Transmission system (FACTS) provides solution to problems like line overloading, voltage stability, losses, power flow etc. FACTS can play important role in improving static and dynamic performance of power system. FACTS devices need high initial investment. Therefore, FACTS location, type and their rating are vital and should be optimized to place in the network for maximum benefit. In this paper, different optimization methods like Particle Swarm Optimization (PSO), Genetic Algorithm (GA) etc. are discussed and compared for optimal location, type and rating of devices. FACTS devices such as Thyristor Controlled Series Compensator (TCSC), Static Var Compensator (SVC) and Static Synchronous Compensator (STATCOM) are considered here. Mentioned FACTS controllers effects on different IEEE bus network parameters like generation cost, active power loss, voltage stability etc. have been analyzed and compared among the devices.

Optimal compensation for neuron loss

Science.gov (United States)

Barrett, David GT; Denève, Sophie; Machens, Christian K

2016-01-01

The brain has an impressive ability to withstand neural damage. Diseases that kill neurons can go unnoticed for years, and incomplete brain lesions or silencing of neurons often fail to produce any behavioral effect. How does the brain compensate for such damage, and what are the limits of this compensation? We propose that neural circuits instantly compensate for neuron loss, thereby preserving their function as much as possible. We show that this compensation can explain changes in tuning curves induced by neuron silencing across a variety of systems, including the primary visual cortex. We find that compensatory mechanisms can be implemented through the dynamics of networks with a tight balance of excitation and inhibition, without requiring synaptic plasticity. The limits of this compensatory mechanism are reached when excitation and inhibition become unbalanced, thereby demarcating a recovery boundary, where signal representation fails and where diseases may become symptomatic. DOI: http://dx.doi.org/10.7554/eLife.12454.001 PMID:27935480

Joint Inventory, Pricing, and Advertising Decisions with Surplus and Stockout Loss Aversions

Directory of Open Access Journals (Sweden)

Bing-Bing Cao

2016-01-01

Full Text Available The newsvendor models considering decision-makers’ behavioral factors remain a fruitful research area in operation management field in past decade. In this paper, we further extend the current literatures to look into joint inventory, pricing, and advertising decisions considering loss aversion effects under the newsvendor setting. The purpose is to explore how the loss aversions affect the optimal policy of order quantity, price, and advertising effort level. We present an integrated utility model to measure both economic payoff and loss aversion utility of the newsvendor, where surplus loss aversion and stockout loss aversion are first separately defined and quantified. Then, we analyze the optimal solution conditions of the integrated model under exogenous and endogenous price cases, respectively. Under exogenous price case, we find that the uniquely optimal policy exists and is presented in the closed form. Under endogenous price case, the optimal policy is determined under mild conditions; we also provide the solutions when order quantity factor or advertising effort level is fixed in this case. In addition, the sensitivity analysis shows that the loss aversions affect the optimal decisions of order quantity, price, and advertising effort level in a systematic way.

Preventive Biomechanics Optimizing Support Systems for the Human Body in the Lying and Sitting Position

CERN Document Server

Silber, Gerhard

2013-01-01

How can we optimize a bedridden patient’s mattress? How can we make a passenger seat on a long distance flight or ride more comfortable? What qualities should a runner’s shoes have? To objectively address such questions using engineering and scientific methods, adequate virtual human body models for use in computer simulation of loading scenarios are required. The authors have developed a novel method incorporating subject studies, magnetic resonance imaging, 3D-CAD-reconstruction, continuum mechanics, material theory and the finite element method. The focus is laid upon the mechanical in vivo-characterization of human soft tissue, which is indispensable for simulating its mechanical interaction with, for example, medical bedding or automotive and airplane seating systems. Using the examples of arbitrary body support systems, the presented approach provides visual insight into simulated internal mechanical body tissue stress and strain, with the goal of biomechanical optimization of body support systems. ...

Tool Support for Software Lookup Table Optimization

Directory of Open Access Journals (Sweden)

Chris Wilcox

2011-01-01

Full Text Available A number of scientific applications are performance-limited by expressions that repeatedly call costly elementary functions. Lookup table (LUT optimization accelerates the evaluation of such functions by reusing previously computed results. LUT methods can speed up applications that tolerate an approximation of function results, thereby achieving a high level of fuzzy reuse. One problem with LUT optimization is the difficulty of controlling the tradeoff between performance and accuracy. The current practice of manual LUT optimization adds programming effort by requiring extensive experimentation to make this tradeoff, and such hand tuning can obfuscate algorithms. In this paper we describe a methodology and tool implementation to improve the application of software LUT optimization. Our Mesa tool implements source-to-source transformations for C or C++ code to automate the tedious and error-prone aspects of LUT generation such as domain profiling, error analysis, and code generation. We evaluate Mesa with five scientific applications. Our results show a performance improvement of 3.0× and 6.9× for two molecular biology algorithms, 1.4× for a molecular dynamics program, 2.1× to 2.8× for a neural network application, and 4.6× for a hydrology calculation. We find that Mesa enables LUT optimization with more control over accuracy and less effort than manual approaches.

The Efficacy of Supportive Peri-Implant Therapies in Preventing Peri-Implantitis and Implant Loss: a Systematic Review of the Literature

Directory of Open Access Journals (Sweden)

Ausra Ramanauskaite

2016-09-01

Full Text Available Objectives: To study the efficacy of supportive peri-implant therapies in preventing clinical and radiological signs of peri-implantitis and implant loss. Material and Methods: Longitudinal human studies, published between January 1, 2006, and February 1, 2016, were included based on an electronic search using MEDLINE and EMBASE databases and complemented by a manual search. Articles were included only if 1 they comprised a group of patients involved in/adhering to regular supportive peri-implant therapies (SPTs and a control group without such therapies or with poor adherence to them, 2 the protocol of the SPTs was clearly described and 3 the outcome was indicated by means of clinical/radiological changes or implant loss. Results: After initially identifying a total of 710 titles and abstracts, 12 full text articles were selected for eligibility assessment. Seven studies, three prospective and four retrospective, fulfilled the inclusion criteria for this review. The frequency of recall visits varied between the studies from a minimum of one visit every three months to an individually tailored regimen. In all the studies a lack of SPTs or poor adherence to them resulted in significantly higher frequencies of sites with mucosal bleeding, deepened peri-implant pockets or alveolar bone loss. In line with the above, a lack of/poor adherence to SPTs was associated with higher implant loss. Conclusions: To prevent peri-implantitis, an individually tailored supportive programme based on patient motivation and re-instruction in oral hygiene measures combined with professional implant cleaning seem to be crucial.

Application of Hybrid HS and Tabu Search Algorithm for Optimal Location of FACTS Devices to Reduce Power Losses in Power Systems

Directory of Open Access Journals (Sweden)

Z. Masomi Zohrabad

2016-12-01

Full Text Available Power networks continue to grow following the annual growth of energy demand. As constructing new energy generation facilities bears a high cost, minimizing power grid losses becomes essential to permit low cost energy transmission in larger distances and additional areas. This study aims to model an optimization problem for an IEEE 30-bus power grid using a Tabu search algorithm based on an improved hybrid Harmony Search (HS method to reduce overall grid losses. The proposed algorithm is applied to find the best location for the installation of a Unified Power Flow Controller (UPFC. The results obtained from installation of the UPFC in the grid are presented by displaying outputs.

The effect of topography on the choice of optimal step intermediate supports along the line of the cable metro

Directory of Open Access Journals (Sweden)

Lagerev A.V.

2017-09-01

Full Text Available In article was formulated and solved the problem of conditional nonlinear optimization of the distance between inter-mediate supports during the design of the cable metro lines in highly urbanized environment, taking into account not the horizontal surface of the terrain. The optimization problem involves a single-criterion objective function that expresses the cost of construction of the cable metro line (total cost of intermediate supports and their foundations, traction and carrying steel cables and technical equipment. The specified objective function subject to minimization by finding the optimal combination of the distance between intermediate supports and tension carrying ropes with accounting con-structive, modal, structural and planning constraints in the form of nonlinear inequalities. When constructing the objec-tive function were considered three possible forms sagging of carrying ropes, which can be implemented for various values of the efforts of their tension. Analysis was done of the influence of the angle of the longitudinal slope of the surface relief along the line of the cable metro on the value of the optimal distance between intermediate supports de-pending on the design and cost of intermediate supports and at the cost of 1 km line of the cable metro. Quantitative calculations showed that with the increase of the longitudinal slope of the surface construction cost also increases with nonlinear increasing rate. The dependence of the cost of 1 km of line underground cable metro from the parameters of the relief is of extreme character with a pronounced minimum at small angles of inclination of the terrain surface about 3...60 degrees. The position of the minimum is quite stable and only slightly changes when enough significant change in the cost of intermediate supports and installed on them technological equipment. The most effective conditions for the construction of the cable metro is the terrain with considerable

Topology Optimized Photonic Wire Splitters

DEFF Research Database (Denmark)

Frandsen, Lars Hagedorn; Borel, Peter Ingo; Jensen, Jakob Søndergaard

2006-01-01

Photonic wire splitters have been designed using topology optimization. The splitters have been fabricated in silicon-on-insulator material and display broadband low-loss 3dB splitting in a bandwidth larger than 100 nm.......Photonic wire splitters have been designed using topology optimization. The splitters have been fabricated in silicon-on-insulator material and display broadband low-loss 3dB splitting in a bandwidth larger than 100 nm....

Particle swarm optimization based support vector machine for damage level prediction of non-reshaped berm breakwater

Digital Repository Service at National Institute of Oceanography (India)

Harish, N.; Mandal, S.; Rao, S.; Patil, S.G.

breakwater. Soft computing tools like Artificial Neural Network, Fuzzy Logic, Support Vector Machine (SVM), etc, are successfully used to solve complex problems. In the present study, SVM and hybrid of Particle Swarm Optimization (PSO) with SVM (PSO...

Reduced Cost of Reactive Power in Doubly Fed Induction Generator Wind Turbine System with Optimized Grid Filter

DEFF Research Database (Denmark)

Zhou, Dao; Blaabjerg, Frede; Franke, Toke

2014-01-01

The modern grid requirement has caused that the wind power system behaves more like conventional rotating generators and it is able to support certain amount of the reactive power. For a typical doubly-fed induction generator wind turbine system, the reactive power can be supported either through...... for the generator and the wind power converter in terms of the reactive power done by the rotor-side converter or the grid-side converter with various grid filters. Afterwards, the annual energy loss is also estimated based on yearly wind profile. Finally, experimental results of the loss distribution are performed...... the rotor-side converter or the grid-side converter. This paper firstly compares the current ripples and supportive reactive power ranges between the conventional L and optimized LCL filter, if the reactive power is injected from the grid-side converter. Then, the loss distribution is evaluated both...

Reduced Cost of Reactive Power in Doubly Fed Induction Generator Wind Turbine System With Optimized Grid Filter

DEFF Research Database (Denmark)

Zhou, Dao; Blaabjerg, Frede; Franke, Toke

2015-01-01

The modern grid requirement has caused that the wind power system behaves more like conventional rotating generators, and it is able to support certain amount of the reactive power. For a typical doubly fed induction generator (DFIG) wind turbine system, the reactive power can be supported either...... for the generator and the wind power converter in terms of the reactive power done by the rotor-side converter or the grid-side converter with various grid filters. Afterward, the annual energy loss is also estimated based on yearly wind profile. Finally, experimental results of the loss distribution are performed...... through the rotor-side converter or the grid-side converter. This paper first compares the current ripples and supportive reactive power ranges between the conventional L and optimized LCL filter, if the reactive power is injected from the grid-side converter. Then, the loss distribution is evaluated both...

Optimal Design of a Center Support Quadruple Mass Gyroscope (CSQMG

Directory of Open Access Journals (Sweden)

Tian Zhang

2016-04-01

Full Text Available This paper reports a more complete description of the design process of the Center Support Quadruple Mass Gyroscope (CSQMG, a gyro expected to provide breakthrough performance for flat structures. The operation of the CSQMG is based on four lumped masses in a circumferential symmetric distribution, oscillating in anti-phase motion, and providing differential signal extraction. With its 4-fold symmetrical axes pattern, the CSQMG achieves a similar operation mode to Hemispherical Resonant Gyroscopes (HRGs. Compared to the conventional flat design, four Y-shaped coupling beams are used in this new pattern in order to adjust mode distribution and enhance the synchronization mechanism of operation modes. For the purpose of obtaining the optimal design of the CSQMG, a kind of applicative optimization flow is developed with a comprehensive derivation of the operation mode coordination, the pseudo mode inhibition, and the lumped mass twisting motion elimination. The experimental characterization of the CSQMG was performed at room temperature, and the center operation frequency is 6.8 kHz after tuning. Experiments show an Allan variance stability 0.12°/h (@100 s and a white noise level about 0.72°/h/√Hz, which means that the CSQMG possesses great potential to achieve navigation grade performance.

Mechanistic modeling of cyclic voltammetry: A helpful tool for understanding biosensor principles and supporting design optimization

DEFF Research Database (Denmark)

Semenova, Daria; Zubov, Alexandr; Silina, Yuliya E.

2018-01-01

Abstract Design, optimization and integration of biosensors hold a great potential for the development of cost-effective screening and point-of-care technologies. However, significant progress in this field can still be obtained on condition that sufficiently accurate mathematical models......, oxidized/reduced forms of the mediator - Prussian Blue/Prussian White). Furthermore, the developed model was applied under various operating conditions as a crucial tool for biosensor design optimization. The obtained qualitative and quantitative dependencies towards amperometric biosensors design...... optimization were independently supported by results of cyclic voltammetry and multi-analytical studies, such as scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Remarkably, a linear...

Structure optimization of a grain impact piezoelectric sensor and its application for monitoring separation losses on tangential-axial combine harvesters.

Science.gov (United States)

Liang, Zhenwei; Li, Yaoming; Zhao, Zhan; Xu, Lizhang

2015-01-14

Grain separation losses is a key parameter to weigh the performance of combine harvesters, and also a dominant factor for automatically adjusting their major working parameters. The traditional separation losses monitoring method mainly rely on manual efforts, which require a high labor intensity. With recent advancements in sensor technology, electronics and computational processing power, this paper presents an indirect method for monitoring grain separation losses in tangential-axial combine harvesters in real-time. Firstly, we developed a mathematical monitoring model based on detailed comparative data analysis of different feeding quantities. Then, we developed a grain impact piezoelectric sensor utilizing a YT-5 piezoelectric ceramic as the sensing element, and a signal process circuit designed according to differences in voltage amplitude and rise time of collision signals. To improve the sensor performance, theoretical analysis was performed from a structural vibration point of view, and the optimal sensor structural has been selected. Grain collide experiments have shown that the sensor performance was greatly improved. Finally, we installed the sensor on a tangential-longitudinal axial combine harvester, and grain separation losses monitoring experiments were carried out in North China, which results have shown that the monitoring method was feasible, and the biggest measurement relative error was 4.63% when harvesting rice.

Structure Optimization of a Grain Impact Piezoelectric Sensor and Its Application for Monitoring Separation Losses on Tangential-Axial Combine Harvesters

Science.gov (United States)

Liang, Zhenwei; Li, Yaoming; Zhao, Zhan; Xu, Lizhang

2015-01-01

Grain separation losses is a key parameter to weigh the performance of combine harvesters, and also a dominant factor for automatically adjusting their major working parameters. The traditional separation losses monitoring method mainly rely on manual efforts, which require a high labor intensity. With recent advancements in sensor technology, electronics and computational processing power, this paper presents an indirect method for monitoring grain separation losses in tangential-axial combine harvesters in real-time. Firstly, we developed a mathematical monitoring model based on detailed comparative data analysis of different feeding quantities. Then, we developed a grain impact piezoelectric sensor utilizing a YT-5 piezoelectric ceramic as the sensing element, and a signal process circuit designed according to differences in voltage amplitude and rise time of collision signals. To improve the sensor performance, theoretical analysis was performed from a structural vibration point of view, and the optimal sensor structural has been selected. Grain collide experiments have shown that the sensor performance was greatly improved. Finally, we installed the sensor on a tangential-longitudinal axial combine harvester, and grain separation losses monitoring experiments were carried out in North China, which results have shown that the monitoring method was feasible, and the biggest measurement relative error was 4.63% when harvesting rice. PMID:25594592

Injection optimization in a heavy-ion synchrotron using genetic algorithms

Energy Technology Data Exchange (ETDEWEB)

Appel, S., E-mail: s.appel@gsi.de [GSI, Helmholtzzentrum für Schwerionenforschung GmbH, Planckstraße 1, 64291 Darmstadt (Germany); Boine-Frankenheim, O. [GSI, Helmholtzzentrum für Schwerionenforschung GmbH, Planckstraße 1, 64291 Darmstadt (Germany); Technische Universität Darmstadt, Schlossgartenstraße 8, 64289 Darmstadt (Germany); Petrov, F. [Technische Universität Darmstadt, Schlossgartenstraße 8, 64289 Darmstadt (Germany)

2017-04-21

The control of the beam loss induced dynamic pressure is one of the most challenging problems for synchrotrons operated with high intensity beams of intermediate charge state ions. This loss-induced vacuum degradation and associated life-time reduction is one of the key intensity limiting factors. Beam loss during Multi-Turn Injection (MTI) can trigger the pressure bump instability. An optimized injection can relax the dynamic vacuum problem, but is also crucial to fill the available machine acceptance. A numerical model has been developed to describe the intensity limitation due to loss-induced vacuum degradation. In order to optimize the multi-turn injection for given initial losses, a genetic algorithm based optimization has been performed. For the SIS18 synchrotron at GSI the optimization resulted in a significant improvement of MTI performance and subsequent transmission for intense beams. A range of suitable injector brilliances for given initial loss could be defined. This information is crucial for the layout of the injector upgrade for FAIR. The effect of transverse space charge force on MTI has been included in the optimization studies.

PMSVM: An Optimized Support Vector Machine Classification Algorithm Based on PCA and Multilevel Grid Search Methods

Directory of Open Access Journals (Sweden)

Yukai Yao

2015-01-01

Full Text Available We propose an optimized Support Vector Machine classifier, named PMSVM, in which System Normalization, PCA, and Multilevel Grid Search methods are comprehensively considered for data preprocessing and parameters optimization, respectively. The main goals of this study are to improve the classification efficiency and accuracy of SVM. Sensitivity, Specificity, Precision, and ROC curve, and so forth, are adopted to appraise the performances of PMSVM. Experimental results show that PMSVM has relatively better accuracy and remarkable higher efficiency compared with traditional SVM algorithms.

A process insight repository supporting process optimization

OpenAIRE

Vetlugin, Andrey

2012-01-01

Existing solutions for analysis and optimization of manufacturing processes, such as online analysis processing or statistical calculations, have shortcomings that limit continuous process improvements. In particular, they lack means of storing and integrating the results of analysis. This makes the valuable information that can be used for process optimizations used only once and then disposed. The goal of the Advanced Manufacturing Analytics (AdMA) research project is to design an integrate...

Investigation of optimal seismic design methodology for piping systems supported by elasto-plastic dampers. Part. 2. Applicability for seismic waves with various frequency characteristics

International Nuclear Information System (INIS)

Ito, Tomohiro; Michiue, Masashi; Fujita, Katsuhisa

2010-01-01

In this study, the applicability of a previously developed optimal seismic design methodology, which can consider the structural integrity of not only piping systems but also elasto-plastic supporting devices, is studied for seismic waves with various frequency characteristics. This methodology employs a genetic algorithm and can search the optimal conditions such as the supporting location and the capacity and stiffness of the supporting devices. Here, a lead extrusion damper is treated as a typical elasto-plastic damper. Numerical simulations are performed using a simple piping system model. As a result, it is shown that the proposed optimal seismic design methodology is applicable to the seismic design of piping systems subjected to seismic waves with various frequency characteristics. The mechanism of optimization is also clarified. (author)

Latent classes of resilience and psychological response among only-child loss parents in China.

Science.gov (United States)

Wang, An-Ni; Zhang, Wen; Zhang, Jing-Ping; Huang, Fei-Fei; Ye, Man; Yao, Shu-Yu; Luo, Yuan-Hui; Li, Zhi-Hua; Zhang, Jie; Su, Pan

2017-10-01

Only-child loss parents in China recently gained extensive attention as a newly defined social group. Resilience could be a probable solution out of the psychological dilemma. Using a sample of 185 only-child loss people, this study employed latent class analysis (a) to explore whether different classes of resilience could be identified, (b) to determine socio-demographic characteristics of each class, and (c) to compare the depression and the subjective well-being of each class. The results supported a three-class solution, defined as 'high tenacity-strength but moderate optimism class', 'moderate resilience but low self-efficacy class' and 'low tenacity but moderate adaption-dependence class'. Parents with low income and medical insurance of low reimbursement type and without endowment insurance occupied more proportions in the latter two classes. The latter two classes also had a significant higher depression scores and lower subjective well-being scores than high tenacity-strength but moderate optimism class. Future work should care those socio-economically vulnerable bereaved parents, and an elastic economic assistance policy was needed. To develop targeted resilience interventions, the emphasis of high tenacity-strength but moderate optimism class should be the optimism. Moderate resilience but low self-efficacy class should be self-efficacy, and low tenacity but moderate adaption-dependence class should be tenacity. Copyright © 2016 John Wiley & Sons, Ltd.

A Fast Optimization Method for General Binary Code Learning.

Science.gov (United States)

Shen, Fumin; Zhou, Xiang; Yang, Yang; Song, Jingkuan; Shen, Heng; Tao, Dacheng

2016-09-22

Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely-used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this work, we propose a novel binary code optimization method, dubbed Discrete Proximal Linearized Minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this work by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised `2 loss encodes the whole NUS-WIDE database into 64-bit binary codes within 10 seconds on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale datasets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.

Performance and optimization of support vector machines in high-energy physics classification problems

International Nuclear Information System (INIS)

Sahin, M.Ö.; Krücker, D.; Melzer-Pellmann, I.-A.

2016-01-01

In this paper we promote the use of Support Vector Machines (SVM) as a machine learning tool for searches in high-energy physics. As an example for a new-physics search we discuss the popular case of Supersymmetry at the Large Hadron Collider. We demonstrate that the SVM is a valuable tool and show that an automated discovery-significance based optimization of the SVM hyper-parameters is a highly efficient way to prepare an SVM for such applications.

Performance and optimization of support vector machines in high-energy physics classification problems

Energy Technology Data Exchange (ETDEWEB)

Sahin, Mehmet Oezguer; Kruecker, Dirk; Melzer-Pellmann, Isabell [DESY, Hamburg (Germany)

2016-07-01

In this talk, the use of Support Vector Machines (SVM) is promoted for new-physics searches in high-energy physics. We developed an interface, called SVM HEP Interface (SVM-HINT), for a popular SVM library, LibSVM, and introduced a statistical-significance based hyper-parameter optimization algorithm for the new-physics searches. As example case study, a search for Supersymmetry at the Large Hadron Collider is given to demonstrate the capabilities of SVM using SVM-HINT.

Performance and optimization of support vector machines in high-energy physics classification problems

Energy Technology Data Exchange (ETDEWEB)

Sahin, M.Ö., E-mail: ozgur.sahin@desy.de; Krücker, D., E-mail: dirk.kruecker@desy.de; Melzer-Pellmann, I.-A., E-mail: isabell.melzer@desy.de

2016-12-01

In this paper we promote the use of Support Vector Machines (SVM) as a machine learning tool for searches in high-energy physics. As an example for a new-physics search we discuss the popular case of Supersymmetry at the Large Hadron Collider. We demonstrate that the SVM is a valuable tool and show that an automated discovery-significance based optimization of the SVM hyper-parameters is a highly efficient way to prepare an SVM for such applications.

Decision support systems for recovery of endangered species

International Nuclear Information System (INIS)

Armstrong, C.E.

1995-01-01

The listing of a species as endangered under the Endangered Species Act invokes a suite of responses to help improve conditions for the recovery of that species, to include identification of stressors contributing to population loss, decision analysis of the impacts of proposed recovery options, and implementation of optimal recovery measures. The ability of a decision support system to quantify inherent stressor uncertainties and to identify the key stressors that can be controlled or eliminated becomes key to ensuring the recovery of an endangered species. The listing of the Snake River sockeye, spring/summer chinook, and fall chinook salmon species in the Snake River as endangered provides a vivid example of the importance of sophisticated decision support systems. Operational and physical changes under consideration at eight of the hydroelectric dams along the Columbia and Lower Snake River pose significant financial impacts to a variety of stakeholders involved in the salmon population recovery process and carry significant uncertainties of outcome. A decision support system is presented to assist in the identification of optimal recovery actions for this example that includes the following: creation of datamarts of information on environmental, engineering, and ecological values that influence species survival; incorporation of decision analysis tools to determine optimal decision policies; and the use of geographic information systems (GIS) to provide a context for decision analysis and to communicate the impacts of decision policies

Ecological optimization for generalized irreversible Carnot refrigerators

International Nuclear Information System (INIS)

Chen Lingen; Zhu Xiaoqin; Sun Fengrui; Wu Chih

2005-01-01

The optimal ecological performance of a Newton's law generalized irreversible Carnot refrigerator with the losses of heat resistance, heat leakage and internal irreversibility is derived by taking an ecological optimization criterion as the objective, which consists of maximizing a function representing the best compromise between the exergy output rate and exergy loss rate (entropy production rate) of the refrigerator. Numerical examples are given to show the effects of heat leakage and internal irreversibility on the optimal performance of generalized irreversible refrigerators

Cognitive Development Optimization Algorithm Based Support Vector Machines for Determining Diabetes

Directory of Open Access Journals (Sweden)

Utku Kose

2016-03-01

Full Text Available The definition, diagnosis and classification of Diabetes Mellitus and its complications are very important. First of all, the World Health Organization (WHO and other societies, as well as scientists have done lots of studies regarding this subject. One of the most important research interests of this subject is the computer supported decision systems for diagnosing diabetes. In such systems, Artificial Intelligence techniques are often used for several disease diagnostics to streamline the diagnostic process in daily routine and avoid misdiagnosis. In this study, a diabetes diagnosis system, which is formed via both Support Vector Machines (SVM and Cognitive Development Optimization Algorithm (CoDOA has been proposed. Along the training of SVM, CoDOA was used for determining the sigma parameter of the Gauss (RBF kernel function, and eventually, a classification process was made over the diabetes data set, which is related to Pima Indians. The proposed approach offers an alternative solution to the field of Artificial Intelligence-based diabetes diagnosis, and contributes to the related literature on diagnosis processes.

A gain-loss framework based on ensemble flow forecasts to switch the urban drainage-wastewater system management towards energy optimization during dry periods

Science.gov (United States)

Courdent, Vianney; Grum, Morten; Munk-Nielsen, Thomas; Mikkelsen, Peter S.

2017-05-01

Precipitation is the cause of major perturbation to the flow in urban drainage and wastewater systems. Flow forecasts, generated by coupling rainfall predictions with a hydrologic runoff model, can potentially be used to optimize the operation of integrated urban drainage-wastewater systems (IUDWSs) during both wet and dry weather periods. Numerical weather prediction (NWP) models have significantly improved in recent years, having increased their spatial and temporal resolution. Finer resolution NWP are suitable for urban-catchment-scale applications, providing longer lead time than radar extrapolation. However, forecasts are inevitably uncertain, and fine resolution is especially challenging for NWP. This uncertainty is commonly addressed in meteorology with ensemble prediction systems (EPSs). Handling uncertainty is challenging for decision makers and hence tools are necessary to provide insight on ensemble forecast usage and to support the rationality of decisions (i.e. forecasts are uncertain and therefore errors will be made; decision makers need tools to justify their choices, demonstrating that these choices are beneficial in the long run). This study presents an economic framework to support the decision-making process by providing information on when acting on the forecast is beneficial and how to handle the EPS. The relative economic value (REV) approach associates economic values with the potential outcomes and determines the preferential use of the EPS forecast. The envelope curve of the REV diagram combines the results from each probability forecast to provide the highest relative economic value for a given gain-loss ratio. This approach is traditionally used at larger scales to assess mitigation measures for adverse events (i.e. the actions are taken when events are forecast). The specificity of this study is to optimize the energy consumption in IUDWS during low-flow periods by exploiting the electrical smart grid market (i.e. the actions are taken

Wake losses optimization of offshore wind farms with moveable floating wind turbines

International Nuclear Information System (INIS)

Rodrigues, S.F.; Teixeira Pinto, R.; Soleimanzadeh, M.; Bosman, Peter A.N.; Bauer, P.

2015-01-01

Highlights: • We present a layout optimization framework for wind farms with moveable turbines. • Using moveable wind turbines in optimized layouts maximizes energy production. • Turbine and wind farm designers should cooperate to optimize offshore wind projects. - Abstract: In the future, floating wind turbines could be used to harvest energy in deep offshore areas where higher wind mean speeds are observed. Currently, several floating turbine concepts are being designed and tested in small scale projects; in particular, one concept allows the turbine to move after installation. This article presents a novel layout optimization framework for wind farms composed of moveable floating turbines. The proposed framework uses an evolutionary optimization strategy in a nested configuration which simultaneously optimizes the anchoring locations and the wind turbine position within the mooring lines for each individual wind direction. The results show that maximum energy production is obtained when moveable wind turbines are deployed in an optimized layout. In conclusion, the framework represents a new design optimization tool for future offshore wind farms composed of moveable floating turbines

Short-Term Load Forecasting Based on Wavelet Transform and Least Squares Support Vector Machine Optimized by Fruit Fly Optimization Algorithm

Directory of Open Access Journals (Sweden)

Wei Sun

2015-01-01

Full Text Available Electric power is a kind of unstorable energy concerning the national welfare and the people’s livelihood, the stability of which is attracting more and more attention. Because the short-term power load is always interfered by various external factors with the characteristics like high volatility and instability, a single model is not suitable for short-term load forecasting due to low accuracy. In order to solve this problem, this paper proposes a new model based on wavelet transform and the least squares support vector machine (LSSVM which is optimized by fruit fly algorithm (FOA for short-term load forecasting. Wavelet transform is used to remove error points and enhance the stability of the data. Fruit fly algorithm is applied to optimize the parameters of LSSVM, avoiding the randomness and inaccuracy to parameters setting. The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system.

Perceived Academic Control: Mediating the Effects of Optimism and Social Support on College Students' Psychological Health

Science.gov (United States)

Ruthig, Joelle C.; Haynes, Tara L.; Stupnisky, Robert H.; Perry, Raymond P.

2009-01-01

The first year of college presents numerous challenges experienced as overwhelming by some freshmen who may become overly stressed and depressed. This longitudinal study examined perceived academic control (PAC) as a mediator of optimism and social support's buffering effects on freshman students' psychological health. Multiple regressions…

Long-Term Effect of Interactive Online Dietician Weight Loss Advice in General Practice (LIVA) Protocol for a Randomized Controlled Trial

DEFF Research Database (Denmark)

Brandt, Carl J; Brandt, Vibeke; Pedersen, Mathilde

2014-01-01

Background. Internet-based complex interventions aiming to promote weight loss and optimize healthy behaviors have attracted much attention. However, evidence for effect is lacking. Obesity is a growing problem, resulting in an increasing demand for cost efficient weight loss programs suitable...... for use on a large scale, for example, as part of standard primary care. In a previous pilot project by Brandt et al. (2011) without a control group, we examined the effects of online dietician counseling and found an average weight loss of 7.0 kg (95% CI: 4.6 to 9.3 kg) after 20 months. Aims and Methods....... To analyze the effects of a complex intervention using trained dieticians in a general practice setting combined with internet-based interactive and personalized weight management support compared with conventional advice with a noninteractive internet support as placebo treatment in 340 overweight patients...

Thermally induced diffraction losses for a Gaussian pump beam and optimization of the mode-to-pump ratio in an end-pumped Nd:GdVO4 laser

International Nuclear Information System (INIS)

Wang, Y T; Li, W J; Pan, L L; Yu, J T; Zhang, R H

2013-01-01

The analytical model of thermally induced diffraction losses for a Gaussian pump beam are derived as functions of the mode-to-pump ratio and pump power in end-pumped Nd-doped lasers considering the energy transfer upconversion effects. The mode-to-pump ratio is optimized based on it. The results show that the optimum mode-to-pump ratio with the thermally induced diffraction losses is less than 0.65, and it is less than the results in which the thermally induced diffraction losses are neglected. The theoretical model is applied to a diode-end-pumped Nd:GdVO 4 laser operating at 1342 nm, and the theoretical calculations are in good agreement with the experimental results. (paper)

Probability Weighting and Loss Aversion in Futures Hedging

NARCIS (Netherlands)

Mattos, F.; Garcia, P.; Pennings, J.M.E.

2008-01-01

We analyze how the introduction of probability weighting and loss aversion in a futures hedging model affects decision making. Analytical findings indicate that probability weighting alone always affects optimal hedge ratios, while loss and risk aversion only have an impact when probability

Cancer Cachexia: Beyond Weight Loss.

Science.gov (United States)

Bruggeman, Andrew R; Kamal, Arif H; LeBlanc, Thomas W; Ma, Joseph D; Baracos, Vickie E; Roeland, Eric J

2016-11-01

Cancer cachexia is a multifactorial syndrome characterized by skeletal muscle loss leading to progressive functional impairment. Despite the ubiquity of cachexia in clinical practice, prevention, early identification, and intervention remain challenging. The impact of cancer cachexia on quality of life, treatment-related toxicity, physical function, and mortality are well established; however, establishing a clinically meaningful definition has proven challenging because of the focus on weight loss alone. Attempts to more comprehensively define cachexia through body composition, physical functioning, and molecular biomarkers, while promising, are yet to be routinely incorporated into clinical practice. Pharmacologic agents that have not been approved by the US Food and Drug Administration but that are currently used in cancer cachexia (ie, megestrol, dronabinol) may improve weight but not outcomes of interest such as muscle mass, physical activity, or mortality. Their routine use is limited by adverse effects. For the practicing oncologist, early identification and management of cachexia is critical. Oncologists must recognize cachexia beyond weight loss alone, focusing instead on body composition and physical functioning. In fact, becoming emaciated is a late sign of cachexia that characterizes its refractory stage. Given that cachexia is a multifactorial syndrome, it requires early identification and polymodal intervention, including optimal cancer therapy, symptom management, nutrition, exercise, and psychosocial support. Consequently, oncologists have a role in ensuring that these resources are available to their patients. In addition, in light of the promising investigational agents, it remains imperative to refer patients with cachexia to clinical trials so that available options can be expanded to effectively treat this pervasive problem.

Improved Reliability-Based Optimization with Support Vector Machines and Its Application in Aircraft Wing Design

Directory of Open Access Journals (Sweden)

Yu Wang

2015-01-01

Full Text Available A new reliability-based design optimization (RBDO method based on support vector machines (SVM and the Most Probable Point (MPP is proposed in this work. SVM is used to create a surrogate model of the limit-state function at the MPP with the gradient information in the reliability analysis. This guarantees that the surrogate model not only passes through the MPP but also is tangent to the limit-state function at the MPP. Then, importance sampling (IS is used to calculate the probability of failure based on the surrogate model. This treatment significantly improves the accuracy of reliability analysis. For RBDO, the Sequential Optimization and Reliability Assessment (SORA is employed as well, which decouples deterministic optimization from the reliability analysis. The improved SVM-based reliability analysis is used to amend the error from linear approximation for limit-state function in SORA. A mathematical example and a simplified aircraft wing design demonstrate that the improved SVM-based reliability analysis is more accurate than FORM and needs less training points than the Monte Carlo simulation and that the proposed optimization strategy is efficient.

Vulnerability Analysis of Soft Caving Tunnel Support System and Surrounding Rock Optimal Control Technology Research

Directory of Open Access Journals (Sweden)

Ming Ji

2014-01-01

Full Text Available The vulnerability assessment model, composed by 11 vulnerability factors, is established with the introduction of the concept of “vulnerability” into the assessment of tunnel support system. Analytic hierarchy process is utilized to divide these 11 factors into human attributes and natural attributes, and define the weight of these factors for the model. The “vulnerability” applied io the assessment of the tunnel support system model is reached. The vulnerability assessment model was used for evaluating and modifying the haulage tunnel #3207 of Bo-fang mine panel #2. The results decreased the vulnerability of the tunnel support system and demonstrated acceptable effects. Furthermore, the results show that the impact of human attributes on tunnel support systems is dramatic under the condition that natural attributes are permanent, and the “vulnerability” is exactly a notable factor to manifest the transformation during this process. The results also indicate that optimizing human attributes can attenuate vulnerability in tunnel support systems. As a result, enhancement of stability of tunnel support systems can be achieved.

Revisiting support optimization at the Driskos tunnel using a quantitative risk approach

Directory of Open Access Journals (Sweden)

J. Connor Langford

2016-04-01

Full Text Available With the scale and cost of geotechnical engineering projects increasing rapidly over the past few decades, there is a clear need for the careful consideration of calculated risks in design. While risk is typically dealt with subjectively through the use of conservative design parameters, with the advent of reliability-based methods, this no longer needs to be the case. Instead, a quantitative risk approach can be considered that incorporates uncertainty in ground conditions directly into the design process to determine the variable ground response and support loads. This allows for the optimization of support on the basis of both worker safety and economic risk. This paper presents the application of such an approach to review the design of the initial lining system along a section of the Driskos twin tunnels as part of the Egnatia Odos highway in northern Greece. Along this section of tunnel, weak rock masses were encountered as well as high in situ stress conditions, which led to excessive deformations and failure of the as built temporary support. Monitoring data were used to validate the rock mass parameters selected in this area and a risk approach was used to determine, in hindsight, the most appropriate support category with respect to the cost of installation and expected cost of failure. Different construction sequences were also considered in the context of both convenience and risk cost.

Rational risk-based decision support for drinking water well managers by optimized monitoring designs

Science.gov (United States)

Enzenhöfer, R.; Geiges, A.; Nowak, W.

2011-12-01

Advection-based well-head protection zones are commonly used to manage the contamination risk of drinking water wells. Considering the insufficient knowledge about hazards and transport properties within the catchment, current Water Safety Plans recommend that catchment managers and stakeholders know, control and monitor all possible hazards within the catchments and perform rational risk-based decisions. Our goal is to supply catchment managers with the required probabilistic risk information, and to generate tools that allow for optimal and rational allocation of resources between improved monitoring versus extended safety margins and risk mitigation measures. To support risk managers with the indispensable information, we address the epistemic uncertainty of advective-dispersive solute transport and well vulnerability (Enzenhoefer et al., 2011) within a stochastic simulation framework. Our framework can separate between uncertainty of contaminant location and actual dilution of peak concentrations by resolving heterogeneity with high-resolution Monte-Carlo simulation. To keep computational costs low, we solve the reverse temporal moment transport equation. Only in post-processing, we recover the time-dependent solute breakthrough curves and the deduced well vulnerability criteria from temporal moments by non-linear optimization. Our first step towards optimal risk management is optimal positioning of sampling locations and optimal choice of data types to reduce best the epistemic prediction uncertainty for well-head delineation, using the cross-bred Likelihood Uncertainty Estimator (CLUE, Leube et al., 2011) for optimal sampling design. Better monitoring leads to more reliable and realistic protection zones and thus helps catchment managers to better justify smaller, yet conservative safety margins. In order to allow an optimal choice in sampling strategies, we compare the trade-off in monitoring versus the delineation costs by accounting for ill

Support vector regression for porosity prediction in a heterogeneous reservoir: A comparative study

Science.gov (United States)

Al-Anazi, A. F.; Gates, I. D.

2010-12-01

In wells with limited log and core data, porosity, a fundamental and essential property to characterize reservoirs, is challenging to estimate by conventional statistical methods from offset well log and core data in heterogeneous formations. Beyond simple regression, neural networks have been used to develop more accurate porosity correlations. Unfortunately, neural network-based correlations have limited generalization ability and global correlations for a field are usually less accurate compared to local correlations for a sub-region of the reservoir. In this paper, support vector machines are explored as an intelligent technique to correlate porosity to well log data. Recently, support vector regression (SVR), based on the statistical learning theory, have been proposed as a new intelligence technique for both prediction and classification tasks. The underlying formulation of support vector machines embodies the structural risk minimization (SRM) principle which has been shown to be superior to the traditional empirical risk minimization (ERM) principle employed by conventional neural networks and classical statistical methods. This new formulation uses margin-based loss functions to control model complexity independently of the dimensionality of the input space, and kernel functions to project the estimation problem to a higher dimensional space, which enables the solution of more complex nonlinear problem optimization methods to exist for a globally optimal solution. SRM minimizes an upper bound on the expected risk using a margin-based loss function ( ɛ-insensitivity loss function for regression) in contrast to ERM which minimizes the error on the training data. Unlike classical learning methods, SRM, indexed by margin-based loss function, can also control model complexity independent of dimensionality. The SRM inductive principle is designed for statistical estimation with finite data where the ERM inductive principle provides the optimal solution (the

Cuckoo search with Lévy flights for weighted Bayesian energy functional optimization in global-support curve data fitting.

Science.gov (United States)

Gálvez, Akemi; Iglesias, Andrés; Cabellos, Luis

2014-01-01

The problem of data fitting is very important in many theoretical and applied fields. In this paper, we consider the problem of optimizing a weighted Bayesian energy functional for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to other common approaches in CAD/CAM and computer graphics driven by piecewise functions (such as B-splines and NURBS) that provide local control of the shape of the curve. Our method applies a powerful nature-inspired metaheuristic algorithm called cuckoo search, introduced recently to solve optimization problems. A major advantage of this method is its simplicity: cuckoo search requires only two parameters, many fewer than other metaheuristic approaches, so the parameter tuning becomes a very simple task. The paper shows that this new approach can be successfully used to solve our optimization problem. To check the performance of our approach, it has been applied to five illustrative examples of different types, including open and closed 2D and 3D curves that exhibit challenging features, such as cusps and self-intersections. Our results show that the method performs pretty well, being able to solve our minimization problem in an astonishingly straightforward way.

DCS cabinet power loss analysis for CPR1000 nuclear power plant

International Nuclear Information System (INIS)

Zhou Liang; Zhao Yanfeng; Sun Yongbin

2014-01-01

The DCS overall structure of CRP1000 nuclear power plant was introduced. Based on the RPC, the signal interface character and signal processing mechanism on the key root were analyzed. By the power loss analyzing of RPC, the RPC loss power may lead reactor trip signal from anticipated transient without scram (ATWS) system. The results indicate that it is necessary to search DCS cabinet power loss analysis. Optimizing and assigning the main water flow signals can avoid trigger reactor trip signal by mistake. The DCS cabinet power loss analysis can optimize the I and C (instrumentation and control) design and increase the nuclear plant's reliability. (authors)

Graph-related optimization and decision support systems

CERN Document Server

Krichen, Saoussen

2014-01-01

Constrained optimization is a challenging branch of operations research that aims to create a model which has a wide range of applications in the supply chain, telecommunications and medical fields. As the problem structure is split into two main components, the objective is to accomplish the feasible set framed by the system constraints. The aim of this book is expose optimization problems that can be expressed as graphs, by detailing, for each studied problem, the set of nodes and the set of edges.  This graph modeling is an incentive for designing a platform that integrates all optimizatio

Optimizing Support Vector Machine Parameters with Genetic Algorithm for Credit Risk Assessment

Science.gov (United States)

Manurung, Jonson; Mawengkang, Herman; Zamzami, Elviawaty

2017-12-01

Support vector machine (SVM) is a popular classification method known to have strong generalization capabilities. SVM can solve the problem of classification and linear regression or nonlinear kernel which can be a learning algorithm for the ability of classification and regression. However, SVM also has a weakness that is difficult to determine the optimal parameter value. SVM calculates the best linear separator on the input feature space according to the training data. To classify data which are non-linearly separable, SVM uses kernel tricks to transform the data into a linearly separable data on a higher dimension feature space. The kernel trick using various kinds of kernel functions, such as : linear kernel, polynomial, radial base function (RBF) and sigmoid. Each function has parameters which affect the accuracy of SVM classification. To solve the problem genetic algorithms are proposed to be applied as the optimal parameter value search algorithm thus increasing the best classification accuracy on SVM. Data taken from UCI repository of machine learning database: Australian Credit Approval. The results show that the combination of SVM and genetic algorithms is effective in improving classification accuracy. Genetic algorithms has been shown to be effective in systematically finding optimal kernel parameters for SVM, instead of randomly selected kernel parameters. The best accuracy for data has been upgraded from kernel Linear: 85.12%, polynomial: 81.76%, RBF: 77.22% Sigmoid: 78.70%. However, for bigger data sizes, this method is not practical because it takes a lot of time.

Systematic design of loss-engineered slow-light waveguides

DEFF Research Database (Denmark)

Wang, Fengwen; Jensen, Jakob Søndergaard; Mørk, Jesper

2012-01-01

This paper employs topology optimization to systematically design free-topology loss-engineered slow-light waveguides with enlarged group index bandwidth product (GBP). The propagation losses of guided modes are evaluated by the imaginary part of eigenvalues in complex band structure calculations......, where the scattering losses due to manufacturing imperfections are represented by an edge-related effective dissipation. The loss engineering of slow-light waveguides is realized by minimizing the propagation losses of design modes. Numerical examples illustrate that the propagation losses of free......-topology dispersion-engineered waveguides can be significantly suppressed by loss engineering. Comparisons between fixed- and free-topology loss-engineered waveguides demonstrate that the GBP can be enhanced significantly by the free-topology loss-engineered waveguides with a small increase of the propagation losses....

Parameter optimization via cuckoo optimization algorithm of fuzzy controller for energy management of a hybrid power system

International Nuclear Information System (INIS)

Berrazouane, S.; Mohammedi, K.

2014-01-01

Highlights: • Optimized fuzzy logic controller (FLC) for operating a standalone hybrid power system based on cuckoo search algorithm. • Comparison between optimized fuzzy logic controller based on cuckoo search and swarm intelligent. • Loss of power supply probability and levelized energy cost are introduced. - Abstract: This paper presents the development of an optimized fuzzy logic controller (FLC) for operating a standalone hybrid power system based on cuckoo search algorithm. The FLC inputs are batteries state of charge (SOC) and net power flow, FLC outputs are the power rate of batteries, photovoltaic and diesel generator. Data for weekly solar irradiation, ambient temperature and load profile are used to tune the proposed controller by using cuckoo search algorithm. The optimized FLC is able to minimize loss of power supply probability (LPSP), excess energy (EE) and levelized energy cost (LEC). Moreover, the results of CS optimization are better than of particle swarm optimization PSO for fuzzy system controller

42 CFR 403.256 - Loss ratio supporting data.

Science.gov (United States)

2010-10-01

... individual or a group policy. (2) The earliest age at which policyholders can purchase the policy. (3) The... service. (vi) Interest. (vii) Expected distribution, by age and sex, of persons who will purchase the...) The past loss ratio experience for the policy, including the experience of all riders and endorsements...

Diffraction measurements using the LHC Beam Loss Monitoring System

Science.gov (United States)

Kalliokoski, Matti

2017-03-01

The Beam Loss Monitoring (BLM) system of the Large Hadron Collider protects the machine from beam induced damage by measuring the absorbed dose rates of beam losses, and by triggering beam dump if the rates increase above the allowed threshold limits. Although the detection time scales are optimized for multi-turn losses, information on fast losses can be recovered from the loss data. In this paper, methods in using the BLM system in diffraction studies are discussed.

Time is on my side: optimism in intertemporal choice

NARCIS (Netherlands)

Berndsen, M.; van der Pligt, J.

2001-01-01

The present research, using data from 163 undergraduates, examines the role of optimism on time preferences for both losses and gains. It is argued that optimism has asymmetric effects on time preferences for gains versus losses: one reason why decision makers prefer immediate gains is because they

The New Multipoint Relays Selection in OLSR using Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Razali Ngah

2012-06-01

Full Text Available The standard Optimized Link State Routing (OLSR introduces an interesting concept, the multipoint relays (MPRs, to mitigate message overhead during the flooding process. We propose a new algorithm for MPRs selection to enhance the performance of OLSR using Particle Swarm Optimization Sigmoid Increasing Inertia Weight (PSOSIIW. The sigmoid increasing inertia weight has significance improve the particle swarm optimization (PSO in terms of simplicity and quick convergence towards optimum solution. The new fitness function of PSO-SIIW, packet delay of each node and degree of willingness are introduced to support MPRs selection in OLSR. We examine the throughput, packet loss and end-to-end delay of the proposed method using network simulator 2 (ns2.  Overall results indicate that OLSR-PSOSIIW has shown good performance compared to the standard OLSR and OLSR-PSO, particularly for the throughput and end-to-end delay. Generally the proposed OLSR-PSOSIIW shows advantage of using PSO for optimizing routing paths in the MPRs selection algorithm.

The EVOTION Decision Support System: Utilizing It for Public Health Policy-Making in Hearing Loss.

Science.gov (United States)

Katrakazas, Panagiotis; Trenkova, Lyubov; Milas, Josip; Brdaric, Dario; Koutsouris, Dimitris

2017-01-01

As Decision Support Systems start to play a significant role in decision making, especially in the field of public-health policy making, we present an initial attempt to formulate such a system in the concept of public health policy making for hearing loss related problems. Justification for the system's conceptual architecture and its key functionalities are presented. The introduction of the EVOTION DSS sets a key innovation and a basis for paradigm shift in policymaking, by incorporating relevant models, big data analytics and generic demographic data. Expected outcomes for this joint effort are discussed from a public-health point of view.

Break-down of Losses in High Performing Metal-Supported Solid Oxide Fuel Cells

DEFF Research Database (Denmark)

Kromp, Alexander; Nielsen, Jimmi; Blennow Tullmar, Peter

2012-01-01

Metal supported SOFC designs offer competitive advantages such as reduced material costs and improved mechanical robustness. On the other hand, disadvantages might arise due to possible corrosion of the porous metal parts during processing and operation at high fuel utilization. In this paper we...... in hydrogen. The electrochemically active parts were applied by infiltrating CGO-Ni precursor solution into the porous metal and anode backbone and screenprinting (La,Sr)(Co,Fe)O3-based cathodes. To prevent a solid state reaction between cathode and zirconia electrolyte, CGO buffer layers were applied...... in between cathode and electrolyte. The detailed electrochemical characterization by means of impedance spectroscopy and a subsequent data analysis by the distribution of relaxation times enabled us to separate the different loss contributions in the cell. Based on an appropriate equivalent circuit model...

A nonlinear support vector machine model with hard penalty function based on glowworm swarm optimization for forecasting daily global solar radiation

International Nuclear Information System (INIS)

Jiang, He; Dong, Yao

2016-01-01

Highlights: • Eclat data mining algorithm is used to determine the possible predictors. • Support vector machine is converted into a ridge regularization problem. • Hard penalty selects the number of radial basis functions to simply the structure. • Glowworm swarm optimization is utilized to determine the optimal parameters. - Abstract: For a portion of the power which is generated by grid connected photovoltaic installations, an effective solar irradiation forecasting approach must be crucial to ensure the quality and the security of power grid. This paper develops and investigates a novel model to forecast 30 daily global solar radiation at four given locations of the United States. Eclat data mining algorithm is first presented to discover association rules between solar radiation and several meteorological factors laying a theoretical foundation for these correlative factors as input vectors. An effective and innovative intelligent optimization model based on nonlinear support vector machine and hard penalty function is proposed to forecast solar radiation by converting support vector machine into a regularization problem with ridge penalty, adding a hard penalty function to select the number of radial basis functions, and using glowworm swarm optimization algorithm to determine the optimal parameters of the model. In order to illustrate our validity of the proposed method, the datasets at four sites of the United States are split to into training data and test data, separately. The experiment results reveal that the proposed model delivers the best forecasting performances comparing with other competitors.

Design, Analysis and Optimization of a Solar Dish/Stirling System

Directory of Open Access Journals (Sweden)

Seyyed Danial Nazemi

2016-02-01

Full Text Available In this paper, a mathematical model by which the thermal and physical behavior of a solar dish/Stirling system was investigated, then the system was designed, analysed and optimized. In this regard, all of heat losses in a dish/Stirling system were calculated, then, the output net-work of the Stirling engine was computed, and accordingly, the system efficiency was worked out. These heat losses include convection and conduction heat losses, radiation heat losses by emission in the cavity receiver, reflection heat losses of solar energy in the parabolic dish, internal and external conduction heat losses, energy dissipation by pressure drops, and energy losses by shuttle effect in displacer piston in the Stirling engine. All of these heat losses in the parabolic dish, cavity receiver and Stirling engine were calculated using mathematical modeling in MatlabTM software. For validation of the proposed model, a 10 kW solar dish/Stirling system was designed and the simulation results were compared with the Eurodish system data with a reasonable degree of agreement. This model is used to investigate the effect of geometric and thermodynamic parameters including the aperture diameter of the parabolic dish and the cavity receiver, and the pressure of the compression space of the Stirling engine, on the system performance. By using the PSO method, which is an intelligent optimization technique, the total design was optimized and the optimal values of decision-making parameters were determined. The optimization has been done in two scenarios. In the first scenario, the optimal value of each designed parameter has been changed when the other parameters are equal to the designed case study parameters. In the second scenario, all of parameters were assumed in their optimal values. By optimization of the modeled dish/Stirling system, the total efficiency of the system improved to 0.60% in the first scenario and it increased from 21.69% to 22.62% in the second

Dietary protein considerations to support active aging.

Science.gov (United States)

Wall, Benjamin T; Cermak, Naomi M; van Loon, Luc J C

2014-11-01

Given our rapidly aging world-wide population, the loss of skeletal muscle mass with healthy aging (sarcopenia) represents an important societal and public health concern. Maintaining or adopting an active lifestyle alleviates age-related muscle loss to a certain extent. Over time, even small losses of muscle tissue can hinder the ability to maintain an active lifestyle and, as such, contribute to the development of frailty and metabolic disease. Considerable research focus has addressed the application of dietary protein supplementation to support exercise-induced gains in muscle mass in younger individuals. In contrast, the role of dietary protein in supporting the maintenance (or gain) of skeletal muscle mass in active older persons has received less attention. Older individuals display a blunted muscle protein synthetic response to dietary protein ingestion. However, this reduced anabolic response can largely be overcome when physical activity is performed in close temporal proximity to protein consumption. Moreover, recent evidence has helped elucidate the optimal type and amount of dietary protein that should be ingested by the older adult throughout the day in order to maximize the skeletal muscle adaptive response to physical activity. Evidence demonstrates that when these principles are adhered to, muscle maintenance or hypertrophy over prolonged periods can be further augmented in active older persons. The present review outlines the current understanding of the role that dietary protein occupies in the lifestyle of active older adults as a means to increase skeletal muscle mass, strength and function, and thus support healthier aging.

Efficiency Optimization in Class-D Audio Amplifiers

DEFF Research Database (Denmark)

Yamauchi, Akira; Knott, Arnold; Jørgensen, Ivan Harald Holger

2015-01-01

This paper presents a new power efficiency optimization routine for designing Class-D audio amplifiers. The proposed optimization procedure finds design parameters for the power stage and the output filter, and the optimum switching frequency such that the weighted power losses are minimized under...... the given constraints. The optimization routine is applied to minimize the power losses in a 130 W class-D audio amplifier based on consumer behavior investigations, where the amplifier operates at idle and low power levels most of the time. Experimental results demonstrate that the optimization method can...... lead to around 30 % of efficiency improvement at 1.3 W output power without significant effects on both audio performance and the efficiency at high power levels....

The self-concept and conjugal loss: evidence for structural change.

Science.gov (United States)

Montpetit, Mignon A; Bergeman, C S; Bisconti, Toni L

2010-08-01

The self-concept is often considered to be a personal resource that individuals may use to cope with life stressors, but little is known about how this entity might itself change in response to profound stress. The present study examines structural change in self-concept following conjugal loss in later life. Analyses were conducted on data collected from 57 widows every 4 months over the first 2 years post-loss. The first objective was to explore the adequacy of an operational definition of the self-concept as a latent construct lying at the confluence of self-esteem, perceived environmental mastery, and optimism. Because confirmatory factor analysis (CFA) supported this theoretically based conceptualization, the second objective of the study was to model stability and change in the structure of the self-concept over the 2-year study period. Results suggested that there is both stability and change in the self-system during the adjustment to major life stress.

Estimating conditional quantiles with the help of the pinball loss

International Nuclear Information System (INIS)

Steinwart, Ingo

2008-01-01

Using the so-called pinball loss for estimating conditional quantiles is a well-known tool in both statistics and machine learning. So far, however, only little work has been done to quantify the efficiency of this tool for non-parametric (modified) empirical risk minimization approaches. The goal of this work is to fill this gap by establishing inequalities that describe how close approximate pinball risk minimizers are to the corresponding conditional quantile. These inequalities, which hold under mild assumptions on the data-generating distribution, are then used to establish so-called variance bounds which recently turned out to play an important role in the statistical analysis of (modified) empirical risk minimization approaches. To illustrate the use of the established inequalities, we then use them to establish an oracle inequality for support vector machines that use the pinball loss. Here, it turns out that we obtain learning rates which are optimal in a min-max sense under some standard assumptions on the regularity of the conditional quantile function

The Weighted Support Vector Machine Based on Hybrid Swarm Intelligence Optimization for Icing Prediction of Transmission Line

Directory of Open Access Journals (Sweden)

Xiaomin Xu

2015-01-01

Full Text Available Not only can the icing coat on transmission line cause the electrical fault of gap discharge and icing flashover but also it will lead to the mechanical failure of tower, conductor, insulators, and others. It will bring great harm to the people’s daily life and work. Thus, accurate prediction of ice thickness has important significance for power department to control the ice disaster effectively. Based on the analysis of standard support vector machine, this paper presents a weighted support vector machine regression model based on the similarity (WSVR. According to the different importance of samples, this paper introduces the weighted support vector machine and optimizes its parameters by hybrid swarm intelligence optimization algorithm with the particle swarm and ant colony (PSO-ACO, which improves the generalization ability of the model. In the case study, the actual data of ice thickness and climate in a certain area of Hunan province have been used to predict the icing thickness of the area, which verifies the validity and applicability of this proposed method. The predicted results show that the intelligent model proposed in this paper has higher precision and stronger generalization ability.

'Are you still on that stupid diet?': women's experiences of societal pressure and support regarding weight loss, and attitudes towards health policy intervention.

Science.gov (United States)

Whale, Katie; Gillison, Fiona B; Smith, Paula C

2014-12-01

This study investigated how people's attitudes and motivations towards losing weight are influenced by societal pressures surrounding weight loss, their interaction with the obesogenic environment and individuals' attitudes and motivations towards weight. Semi-structured qualitative interviews were conducted with 10 women currently attending commercial weight-loss programmes. Participants experienced conflicting messages regarding weight norms, with the media portraying powerful social norms relating to thinness and beauty, and changes to the food environment and interactions with family and friends commonly undermining weight-loss activities and promoting increased consumption. Providing social and environmental support for the behaviours needed to produce weight loss may need to be a primary focus for obesity policy. © The Author(s) 2013.

Performance and optimization of support vector machines in high-energy physics classification problems

Energy Technology Data Exchange (ETDEWEB)

Sahin, M.Oe.; Kruecker, D.; Melzer-Pellmann, I.A.

2016-01-15

In this paper we promote the use of Support Vector Machines (SVM) as a machine learning tool for searches in high-energy physics. As an example for a new-physics search we discuss the popular case of Supersymmetry at the Large Hadron Collider. We demonstrate that the SVM is a valuable tool and show that an automated discovery-significance based optimization of the SVM hyper-parameters is a highly efficient way to prepare an SVM for such applications. A new C++ LIBSVM interface called SVM-HINT is developed and available on Github.

Performance and optimization of support vector machines in high-energy physics classification problems

International Nuclear Information System (INIS)

Sahin, M.Oe.; Kruecker, D.; Melzer-Pellmann, I.A.

2016-01-01

In this paper we promote the use of Support Vector Machines (SVM) as a machine learning tool for searches in high-energy physics. As an example for a new-physics search we discuss the popular case of Supersymmetry at the Large Hadron Collider. We demonstrate that the SVM is a valuable tool and show that an automated discovery-significance based optimization of the SVM hyper-parameters is a highly efficient way to prepare an SVM for such applications. A new C++ LIBSVM interface called SVM-HINT is developed and available on Github.

Software Support for Optimizing Layout Solution in Lean Production

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Naqib Daneshjo

2018-02-01

Full Text Available As progressive managerial styles, the techniques based on "lean thinking" are being increasingly promoted. They are focused on applying lean production concepts to all phases of product lifecycle and also to business environment. This innovative approach strives to eliminate any wasting of resources and shortens the time to respond to customer requirements, including redesigning the structure of the organization’ supply chain. A lean organization is created mainly by employees, their creative potential, knowledge, self-realization and motivation for continuous improvement of the processes and the production systems. A set of tools, techniques and methods of lean production is basically always very similar. Only a form of their presentation or classification into individual phases of the product lifecycle may differ. The authors present the results of their research from the designing phases of production systems to optimize their dispositional solution with software support and 3D simulation and visualization. Modelling is based on use of Tecnomatix's and Photomodeler's progressive software tools and a dynamic model for capacitive dimensioning of more intelligent production system

Multi-Objective Distribution Network Operation Based on Distributed Generation Optimal Placement Using New Antlion Optimizer Considering Reliability

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KHANBABAZADEH Javad

2016-10-01

Full Text Available Distribution network designers and operators are trying to deliver electrical energy with high reliability and quality to their subscribers. Due to high losses in the distribution systems, using distributed generation can improves reliability, reduces losses and improves voltage profile of distribution network. Therefore, the choice of the location of these resources and also determining the amount of their generated power to maximize the benefits of this type of resource is an important issue which is discussed from different points of view today. In this paper, a new multi-objective optimal location and sizing of distributed generation resources is performed to maximize its benefits on the 33 bus distribution test network considering reliability and using a new Antlion Optimizer (ALO. The benefits for DG are considered as system losses reduction, system reliability improvement and benefits from the sale electricity and voltage profile improvement. For each of the mentioned benefits, the ALO algorithm is used to optimize the location and sizing of distributed generation resources. In order to verify the proposed approach, the obtained results have been analyzed and compared with the results of particle swarm optimization (PSO algorithm. The results show that the ALO has shown better performance in optimization problem solution versus PSO.

Tax-Optimal Step-Up and Imperfect Loss Offset

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Markus Diller

2012-05-01

Full Text Available In the field of mergers and acquisitions, German and international tax law allow for several opportunities to step up a firm's assets, i.e., to revaluate the assets at fair market values. When a step-up is performed the taxpayer recognizes a taxable gain, but also obtains tax benefits in the form of higher future depreciation allowances associated with stepping up the tax base of the assets. This tax-planning problem is well known in taxation literature and can also be applied to firm valuation in the presence of taxation. However, the known models usually assume a perfect loss offset. If this assumption is abandoned, the depreciation allowances may lose value as they become tax effective at a later point in time, or even never if there are not enough cash flows to be offset against. This aspect is especiallyrelevant if future cash flows are assumed to be uncertain. This paper shows that a step-up may be disadvantageous or a firm overvalued if these aspects are not integrated into the basic calculus. Compared to the standard approach, assets should be stepped up only in a few cases and - under specific conditions - at a later point in time. Firm values may be considerably lower under imperfect loss offset.

Risk-Averse Suppliers’ Optimal Pricing Strategies in a Two-Stage Supply Chain

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Rui Shen

2013-01-01

Full Text Available Risk-averse suppliers’ optimal pricing strategies in two-stage supply chains under competitive environment are discussed. The suppliers in this paper focus more on losses as compared to profits, and they care their long-term relationship with their customers. We introduce for the suppliers a loss function, which covers both current loss and future loss. The optimal wholesale price is solved under situations of risk neutral, risk averse, and a combination of minimizing loss and controlling risk, respectively. Besides, some properties of and relations among these optimal wholesale prices are given as well. A numerical example is given to illustrate the performance of the proposed method.

Relationships among optimism, well-being, self-transcendence, coping, and social support in women during treatment for breast cancer.

Science.gov (United States)

Matthews, Ellyn E; Cook, Paul F

2009-07-01

The impact of diagnosis and treatment for breast cancer, stressors that affect emotional well-being, is influenced by several psychosocial factors and the relationships among them. The purpose of this study was to investigate the relationship between optimism and emotional well-being (EWB) and the individual and combined mediation of this relationship by perceived social support (SS), problem focused coping (PFC), and self-transcendence in women with breast cancer during radiation therapy. Ninety-three women receiving radiation treatment for breast cancer completed questionnaires that measured EWB, optimism, SS, PFC, and self-transcendence. Correlational and multiple regression analysis revealed that optimism was positively related to EWB. Of the three mediators, self-transcendence alone was found to partially mediate the relationship between optimism and EWB. The relationship between optimism and PFC was not significant. Optimism was related to SS, but its indirect effect on EWB through SS did not reach significance. During breast cancer treatment, the positive effects of optimism on EWB are partially mediated by a woman's level of self-transcendence. Brief screening of women's optimism may help identify women at risk for psychological distress. Early detection and interventions to promote psychological adjustment throughout the cancer trajectory (e.g. enhancing self-transcendence) should receive attention in future research. (c) 2008 John Wiley & Sons, Ltd.

Clustering Algorithm As A Planning Support Tool For Rural Electrification Optimization

Directory of Open Access Journals (Sweden)

Ronaldo Pornillosa Parreno Jr

2015-08-01

Full Text Available Abstract In this study clustering algorithm was developed to optimize electrification plans by screening and grouping potential customers to be supplied with electricity. The algorithm provided adifferent approach in clustering problem which combines conceptual and distance-based clustering algorithmsto analyze potential clusters using spanning tree with the shortest possible edge weight and creating final cluster trees based on the test of inconsistency for the edges. The clustering criteria consists of commonly used distance measure with the addition of household information as basis for the ability to pay ATP value. The combination of these two parameters resulted to a more significant and realistic clusters since distance measure alone could not take the effect of the household characteristics in screening the most sensible groupings of households. In addition the implications of varying geographical features were incorporated in the algorithm by using routing index across the locations of the households. This new approach of connecting the households in an area was applied in an actual case study of one village or barangay that was not yet energized. The results of clustering algorithm generated cluster trees which could becomethetheoretical basis for power utilities to plan the initial network arrangement of electrification. Scenario analysis conducted on the two strategies of clustering the households provideddifferent alternatives for the optimization of the cost of electrification. Futhermorethe benefits associated with the two strategies formulated from the two scenarios was evaluated using benefit cost ratio BC to determine which is more economically advantageous. The results of the study showed that clustering algorithm proved to be effective in solving electrification optimization problem and serves its purpose as a planning support tool which can facilitate electrification in rural areas and achieve cost-effectiveness.

Tension optimization of the conductor-and-support cable elements during stranding process

Directory of Open Access Journals (Sweden)

I.M. Chayun

2016-12-01

Full Text Available Steel lifting ropes, cables and other similar products are rod statically undeterminable prestressed structures. Preliminary deformations of their elements (wires are caused by their manufacturing technology. Wires suffer stretching, bending with torsion in a stage of elastoplastic deformation. In this work the mechanic-mathematical model of residual forces determination in the wires of polymetallic conductor-and-support cable is offered. Aim: The aim of the work is studying of the mechanical and mathematical model defining residual forces in the wires of conductor-and-support cable and also the optimization of parameters of a twist by the criterion of residual forces lack after production process finishing. Materials and methods: The method developed by the authors earlier to the study the strain-stressed state of twisted wire products off-loading from technological internal forces has been applied to assess the impact of the approximate value of the longitudinal stiffness of the product. In this paper, each wire is considered as an element of the product individually. This is necessary to investigate the impact of uneven wire tensions on defects of conductor-and-support cable (out-of-straight in a free state and stripping-down. Results: On the basis of the conducted deformation studies of conductor-and-support cable during off-loading process from twist tension of its elements the dependencies of residual forces on the level and interrelation of elements tension has been determined. The condition of ensuring of zero residual forces in the wires of conductor-and-support cable after production is formulated. It was found that calculated values of residual forces are almost identical when using of the approximate and exact values of longitudinal stiffness of conductor-and-support cable.

Particle swarm optimization-based support vector machine for forecasting dissolved gases content in power transformer oil

Energy Technology Data Exchange (ETDEWEB)

Fei, Sheng-wei; Wang, Ming-Jun; Miao, Yu-bin; Tu, Jun; Liu, Cheng-liang [School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200240 (China)

2009-06-15

Forecasting of dissolved gases content in power transformer oil is a complicated problem due to its nonlinearity and the small quantity of training data. Support vector machine (SVM) has been successfully employed to solve regression problem of nonlinearity and small sample. However, the practicability of SVM is effected due to the difficulty of selecting appropriate SVM parameters. Particle swarm optimization (PSO) is a new optimization method, which is motivated by social behaviour of organisms such as bird flocking and fish schooling. The method not only has strong global search capability, but also is very easy to implement. Thus, the proposed PSO-SVM model is applied to forecast dissolved gases content in power transformer oil in this paper, among which PSO is used to determine free parameters of support vector machine. The experimental data from several electric power companies in China is used to illustrate the performance of proposed PSO-SVM model. The experimental results indicate that the PSO-SVM method can achieve greater forecasting accuracy than grey model, artificial neural network under the circumstances of small sample. (author)

Particle swarm optimization-based support vector machine for forecasting dissolved gases content in power transformer oil

Energy Technology Data Exchange (ETDEWEB)

Fei Shengwei [School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200240 (China)], E-mail: feishengwei@sohu.com; Wang Mingjun; Miao Yubin; Tu Jun; Liu Chengliang [School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200240 (China)

2009-06-15

Forecasting of dissolved gases content in power transformer oil is a complicated problem due to its nonlinearity and the small quantity of training data. Support vector machine (SVM) has been successfully employed to solve regression problem of nonlinearity and small sample. However, the practicability of SVM is effected due to the difficulty of selecting appropriate SVM parameters. Particle swarm optimization (PSO) is a new optimization method, which is motivated by social behaviour of organisms such as bird flocking and fish schooling. The method not only has strong global search capability, but also is very easy to implement. Thus, the proposed PSO-SVM model is applied to forecast dissolved gases content in power transformer oil in this paper, among which PSO is used to determine free parameters of support vector machine. The experimental data from several electric power companies in China is used to illustrate the performance of proposed PSO-SVM model. The experimental results indicate that the PSO-SVM method can achieve greater forecasting accuracy than grey model, artificial neural network under the circumstances of small sample.

Optimizing the Nutritional Support of Adult Patients in the Setting of Cirrhosis.

Science.gov (United States)

Perumpail, Brandon J; Li, Andrew A; Cholankeril, George; Kumari, Radhika; Ahmed, Aijaz

2017-10-13

The aim of this work is to develop a pragmatic approach in the assessment and management strategies of patients with cirrhosis in order to optimize the outcomes in this patient population. A systematic review of literature was conducted through 8 July 2017 on the PubMed Database looking for key terms, such as malnutrition, nutrition, assessment, treatment, and cirrhosis. Articles and studies looking at associations between nutrition and cirrhosis were reviewed. An assessment of malnutrition should be conducted in two stages: the first, to identify patients at risk for malnutrition based on the severity of liver disease, and the second, to perform a complete multidisciplinary nutritional evaluation of these patients. Optimal management of malnutrition should focus on meeting recommended daily goals for caloric intake and inclusion of various nutrients in the diet. The nutritional goals should be pursued by encouraging and increasing oral intake or using other measures, such as oral supplementation, enteral nutrition, or parenteral nutrition. Although these strategies to improve nutritional support have been well established, current literature on the topic is limited in scope. Further research should be implemented to test if this enhanced approach is effective.

Optimizing the Nutritional Support of Adult Patients in the Setting of Cirrhosis

Directory of Open Access Journals (Sweden)

Brandon J. Perumpail

2017-10-01

Full Text Available Aim: The aim of this work is to develop a pragmatic approach in the assessment and management strategies of patients with cirrhosis in order to optimize the outcomes in this patient population. Method: A systematic review of literature was conducted through 8 July 2017 on the PubMed Database looking for key terms, such as malnutrition, nutrition, assessment, treatment, and cirrhosis. Articles and studies looking at associations between nutrition and cirrhosis were reviewed. Results: An assessment of malnutrition should be conducted in two stages: the first, to identify patients at risk for malnutrition based on the severity of liver disease, and the second, to perform a complete multidisciplinary nutritional evaluation of these patients. Optimal management of malnutrition should focus on meeting recommended daily goals for caloric intake and inclusion of various nutrients in the diet. The nutritional goals should be pursued by encouraging and increasing oral intake or using other measures, such as oral supplementation, enteral nutrition, or parenteral nutrition. Conclusions: Although these strategies to improve nutritional support have been well established, current literature on the topic is limited in scope. Further research should be implemented to test if this enhanced approach is effective.

Multi-model ensembles for assessment of flood losses and associated uncertainty

Science.gov (United States)

Figueiredo, Rui; Schröter, Kai; Weiss-Motz, Alexander; Martina, Mario L. V.; Kreibich, Heidi

2018-05-01

Flood loss modelling is a crucial part of risk assessments. However, it is subject to large uncertainty that is often neglected. Most models available in the literature are deterministic, providing only single point estimates of flood loss, and large disparities tend to exist among them. Adopting any one such model in a risk assessment context is likely to lead to inaccurate loss estimates and sub-optimal decision-making. In this paper, we propose the use of multi-model ensembles to address these issues. This approach, which has been applied successfully in other scientific fields, is based on the combination of different model outputs with the aim of improving the skill and usefulness of predictions. We first propose a model rating framework to support ensemble construction, based on a probability tree of model properties, which establishes relative degrees of belief between candidate models. Using 20 flood loss models in two test cases, we then construct numerous multi-model ensembles, based both on the rating framework and on a stochastic method, differing in terms of participating members, ensemble size and model weights. We evaluate the performance of ensemble means, as well as their probabilistic skill and reliability. Our results demonstrate that well-designed multi-model ensembles represent a pragmatic approach to consistently obtain more accurate flood loss estimates and reliable probability distributions of model uncertainty.

The mediating role of social support, cognitive appraisal, and quality health care in black mothers' stress-resilience process following loss to gun violence.

Science.gov (United States)

Bailey, Annette; Sharma, Manoj; Jubin, Michelle

2013-01-01

Although much attention has been granted to the perpetrators and victims of gun violence, limitations exist in our understanding of the psychological well-being of parents grieving children lost to gun violence. The purpose of this study was to examine the mediating effects of social support, cognitive appraisal, and quality health care on the relationship between traumatic stress and resilience among Black mothers bereaving children to gun violence. A cross-sectional design and network sampling method were used to recruit 48 Black mothers living in a large Canadian city. Participants completed a survey either by phone or in person. Social support and positive appraisal were found to be protective factors of resilience for study participants. The traumatic stress experienced by the sample decreased with increased social support (beta = -.291, p = .045), leading to an increase of their resilience (beta = .297, p = .032). With positive appraisal of the loss, the stress levels of study participants decreased (beta = -.334, p = .023), leading to increased resilience (beta = .441, p = .003). Quality health care showed a significant positive relationship with the resilience of the women (beta = .313, p = .023) but did not mediate the relationship between their stress and resilience. For Black mothers who experience loss of a child to gun violence, policy and social change efforts should focus on strengthening their access to formal and informal supports and improving their abilities to find meaning in their loss.

Low losses left-handed materials with optimized electric and magnetic resonance

Science.gov (United States)

Zhou, Xin; Liu, Yahong; Zhao, Xiaopeng

2010-03-01

We propose that the losses in left-handed materials (LHMs) can be significantly affected by changing the coupling relationship between electric and magnetic resonance. A double bowknot shaped structure (DBS) is used to construct the LHMs. And the magnetic resonance of the DBS, which resonated in the case of lower and higher frequencies than the electric resonant dip, is studied in simulation and experiment by tailoring the structural parameters. The case of magnetic resonance located at low electric resonance frequencies band is confirmed to have relatively low losses. Using full wave simulation of prism shaped structure composed of DBS unit cells, we prove the negative refraction behavior in such a frame. This study can serve as a guide for designing other similar metal-dielectric-metal (MDM) in low losses at terahertz or higher frequencies.

Predicting loss of evolutionary history: Where are we?

Science.gov (United States)

Veron, Simon; Davies, T Jonathan; Cadotte, Marc W; Clergeau, Philippe; Pavoine, Sandrine

2017-02-01

The Earth's evolutionary history is threatened by species loss in the current sixth mass extinction event in Earth's history. Such extinction events not only eliminate species but also their unique evolutionary histories. Here we review the expected loss of Earth's evolutionary history quantified by phylogenetic diversity (PD) and evolutionary distinctiveness (ED) at risk. Due to the general paucity of data, global evolutionary history losses have been predicted for only a few groups, such as mammals, birds, amphibians, plants, corals and fishes. Among these groups, there is now empirical support that extinction threats are clustered on the phylogeny; however this is not always a sufficient condition to cause higher loss of phylogenetic diversity in comparison to a scenario of random extinctions. Extinctions of the most evolutionarily distinct species and the shape of phylogenetic trees are additional factors that can elevate losses of evolutionary history. Consequently, impacts of species extinctions differ among groups and regions, and even if global losses are low within large groups, losses can be high among subgroups or within some regions. Further, we show that PD and ED are poorly protected by current conservation practices. While evolutionary history can be indirectly protected by current conservation schemes, optimizing its preservation requires integrating phylogenetic indices with those that capture rarity and extinction risk. Measures based on PD and ED could bring solutions to conservation issues, however they are still rarely used in practice, probably because the reasons to protect evolutionary history are not clear for practitioners or due to a lack of data. However, important advances have been made in the availability of phylogenetic trees and methods for their construction, as well as assessments of extinction risk. Some challenges remain, and looking forward, research should prioritize the assessment of expected PD and ED loss for more taxonomic

Novel optimization technique of isolated microgrid with hydrogen energy storage.

Science.gov (United States)

Beshr, Eman Hassan; Abdelghany, Hazem; Eteiba, Mahmoud

2018-01-01

This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs), Diesel Generator (DG), a Wind Turbine Generator (WTG), Photovoltaic (PV) arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm.

Novel optimization technique of isolated microgrid with hydrogen energy storage.

Directory of Open Access Journals (Sweden)

Eman Hassan Beshr

Full Text Available This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs, Diesel Generator (DG, a Wind Turbine Generator (WTG, Photovoltaic (PV arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm.

Low-order model of the Loss-of-Fluid Test (LOFT) reactor plant for use in Kalman filter-based optimal estimators

International Nuclear Information System (INIS)

Tylee, J.L.

1980-01-01

A low-order, nonlinear model of the Loss-of-Fluid Test (LOFT) reactor plant, for use in Kalman filter estimators, is developed, described, and evaluated. This model consists of 31 differential equations and represents all major subsystems of both the primary and secondary sides of the LOFT plant. Comparisons between model calculations and available LOFT power range testing transients demonstrate the accuracy of the low-order model. The nonlinear model is numerically linearized for future implementation in Kalman filter and optimal control algorithms. The linearized model is shown to be an adequate representation of the nonlinear plant dynamics

Signal Enhancement as Minimization of Relevant Information Loss

OpenAIRE

Geiger, Bernhard C.; Kubin, Gernot

2012-01-01

We introduce the notion of relevant information loss for the purpose of casting the signal enhancement problem in information-theoretic terms. We show that many algorithms from machine learning can be reformulated using relevant information loss, which allows their application to the aforementioned problem. As a particular example we analyze principle component analysis for dimensionality reduction, discuss its optimality, and show that the relevant information loss can indeed vanish if the r...

Wavelet entropy and directed acyclic graph support vector machine for detection of patients with unilateral hearing loss in MRI scanning

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Shuihua Wang

2016-10-01

Full Text Available (Aim Sensorineural hearing loss (SNHL is correlated to many neurodegenerative disease. Now more and more computer vision based methods are using to detect it in an automatic way. (Materials We have in total 49 subjects, scanned by 3.0T MRI (Siemens Medical Solutions, Erlangen, Germany. The subjects contain 14 patients with right-sided hearing loss (RHL, 15 patients with left-sided hearing loss (LHL, and 20 healthy controls (HC. (Method We treat this as a three-class classification problem: RHL, LHL, and HC. Wavelet entropy (WE was selected from the magnetic resonance images of each subjects, and then submitted to a directed acyclic graph support vector machine (DAG-SVM. (Results The 10 repetition results of 10-fold cross validation shows 3-level decomposition will yield an overall accuracy of 95.10% for this three-class classification problem, higher than feedforward neural network, decision tree, and naive Bayesian classifier. (Conclusions This computer-aided diagnosis system is promising. We hope this study can attract more computer vision method for detecting hearing loss.

Control of Refrigeration Systems for Trade-off between Energy Consumption and Food Quality Loss

DEFF Research Database (Denmark)

Cai, Junping

In supermarkets, control strategies determine both the energy consumption of refrigeration systems and the quality loss of refrigerated foodstuffs. The question is, what can be done to optimize the balance between quality loss and energy consumption? This thesis tries to answer this question...... by applying two main optimization strategies to traditional refrigeration systems. The first strategy is a new defrost-on-demand scheme, which based on an objective function between quality loss and energy consumption, continuously seeks an optimal time interval for defrosting in dynamic situation. The second...... strategy is through utilization of the thermal mass of the refrigerated foodstuffs, the day-night temperature variation and the capacity control of the compressor, to realize a trade-off between system energy consumption and food quality loss....

Optimalization of IGBT Communication

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Pavol Spanik

2002-01-01

Full Text Available The paper presents IGBT switch off process in order to reduce power loss in the structure. The soft switching method using switch-off after current reduction is used. Process mentioned above is optimized to minimize the power loss that is determined by experiment. Results obtained in the experiment can be helpful in a converter and controller design process.

Effectiveness of web-based self-disclosure peer-to-peer support for weight loss: randomized controlled trial.

Science.gov (United States)

Imanaka, Mie; Ando, Masahiko; Kitamura, Tetsuhisa; Kawamura, Takashi

2013-07-09

Obesity is one of the most common public health problems in the industrialized world as a cause of noncommunicable diseases. Although primarily used for one-on-one communication, email is available for uninterrupted support for weight loss, but little is known about the effects of dietitian group counseling for weight control via the Internet. We developed a Web-based self-disclosure health support (WSHS) system for weight loss. This study aims to compare the effect of weight change between those using the WSHS and those using the email health support (EHS). This study was designed as an open prospective individual randomized controlled trial. Eligible participants were aged 35 to 65 years with a body mass index (BMI) of ≥25.0 in their latest health examination. Participants were randomly assigned to either the WSHS group or the EHS group. Thirteen registered dietitians under the direction of a principal dietitian each instructed 6 to 8 participants from the respective groups. All participants in the WSHS group could receive nutritional advice and calculate their nutritive intake from a photograph of a meal on their computer screen from the Internet sent to them by their dietitian, receive supervision from the registered dietitian, and view fellow participants' weight changes and lifestyle modifications. In the EHS group, a participant could receive one-on-one nutritional advice and calculate his/her nutritive intake from the photograph of a meal on computer screen sent by email from his/her dietitian, without being able to view fellow participants' status. The follow-up period was 12 weeks for both groups. The primary outcome measure was change in body weight. The secondary outcome measure included changes in BMI and waist circumference. The intergroup comparison of the changes before and after intervention was evaluated using analysis of covariance. A total of 193 participants were randomly assigned to either the WSHS group (n=97) or the EHS group (n=96). Ten

Chaotic particle swarm optimization algorithm in a support vector regression electric load forecasting model

International Nuclear Information System (INIS)

Hong, W.-C.

2009-01-01

Accurate forecasting of electric load has always been the most important issues in the electricity industry, particularly for developing countries. Due to the various influences, electric load forecasting reveals highly nonlinear characteristics. Recently, support vector regression (SVR), with nonlinear mapping capabilities of forecasting, has been successfully employed to solve nonlinear regression and time series problems. However, it is still lack of systematic approaches to determine appropriate parameter combination for a SVR model. This investigation elucidates the feasibility of applying chaotic particle swarm optimization (CPSO) algorithm to choose the suitable parameter combination for a SVR model. The empirical results reveal that the proposed model outperforms the other two models applying other algorithms, genetic algorithm (GA) and simulated annealing algorithm (SA). Finally, it also provides the theoretical exploration of the electric load forecasting support system (ELFSS)

Efficiency optimized control of medium-size induction motor drives

DEFF Research Database (Denmark)

Abrahamsen, F.; Blaabjerg, Frede; Pedersen, John Kim

2000-01-01

The efficiency of a variable speed induction motor drive can be optimized by adaption of the motor flux level to the load torque. In small drives (<10 kW) this can be done without considering the relatively small converter losses, but for medium-size drives (10-1000 kW) the losses can not be disr......The efficiency of a variable speed induction motor drive can be optimized by adaption of the motor flux level to the load torque. In small drives (... not be disregarded without further analysis. The importance of the converter losses on efficiency optimization in medium-size drives is analyzed in this paper. Based on the experiments with a 90 kW drive it is found that it is not critical if the converter losses are neglected in the control, except...... that the robustness towards load disturbances may unnecessarily be reduced. Both displacement power factor and model-based efficiency optimizing control methods perform well in medium-size drives. The last strategy is also tested on a 22 kW drive with good results....

Effective Loss Minimization and Allocation of Unbalanced Distribution Network

Directory of Open Access Journals (Sweden)

Manvir Kaur

2017-11-01

Full Text Available An efficient distribution network must be able to supply power with good voltage profile. The main objective of the proposed work is to allocate losses of the unbalanced distribution network by the firefly algorithm in regulated and deregulated environments before and after loss minimization. Reconfiguration is one of the methods for loss reduction of unbalanced distribution network. Further, optimal placement of distributed generation and capacitor in the reconfigured unbalanced distribution network can further reduce the loss. The results of reconfigured unbalanced distribution network in regulated environment have already been reported. In this paper reconfiguration of an unbalanced distribution network in a deregulated environment is also carried out using an established Fuzzy Firefly algorithm. Loss sensitivity factor of unbalanced distribution networks is used to get the appropriate location of distributed generation and capacitor to be placed in the unbalanced distribution network. Their ratings have been found out by using bacteria foraging optimization algorithm (BFOA. The suggested loss allocation method using Firefly algorithm is implemented at first on 13 node unbalanced distribution network to check the performance of the proposed loss allocation method when compared to other available method. Finally the proposed method has been implemented on 25 node unbalanced distribution network. Both of the implementations are carried out under MATLAB environment.

Operation Characteristics Optimization of Low Power Three-Phase Asynchronous Motors

Directory of Open Access Journals (Sweden)

VLAD, I.

2014-02-01

Full Text Available Most published papers on low power asynchronous motors were aimed to achieve better operational performances in different operating conditions. The optimal design of the general-purpose motors requires searching and selecting an electric machine to meet minimum operating costs criterion and certain customer imposed restrictive conditions. In this paper, there are many significant simulations providing qualitative and quantitative information on reducing active and reactive energy losses in motors, and on parameters and constructive solution. The optimization study applied the minimal operating costs criterion, and it took into account the starting restrictive conditions. Thirteen variables regarding electromagnetic stresses and main constructive dimensions were considered. The operating costs of the optimized motor decreased with 25.6%, as compared to the existing solution. This paper can be a practical and theoretical support for the development and implementation of modern design methods, based on theoretical and experimental study of stationary and transient processes in low power motors, to increase efficiency and power factor.

A simulation-optimization model for Stone column-supported embankment stability considering rainfall effect

International Nuclear Information System (INIS)

Deb, Kousik; Dhar, Anirban; Purohit, Sandip

2016-01-01

Landslide due to rainfall has been and continues to be one of the most important concerns of geotechnical engineering. The paper presents the variation of factor of safety of stone column-supported embankment constructed over soft soil due to change in water level for an incessant period of rainfall. A combined simulation-optimization based methodology has been proposed to predict the critical surface of failure of the embankment and to optimize the corresponding factor of safety under rainfall conditions using an evolutionary genetic algorithm NSGA-II (Non-Dominated Sorted Genetic Algorithm-II). It has been observed that the position of water table can be reliably estimated with varying periods of infiltration using developed numerical method. The parametric study is presented to study the optimum factor of safety of the embankment and its corresponding critical failure surface under the steady-state infiltration condition. Results show that in case of floating stone columns, period of infiltration has no effect on factor of safety. Even critical failure surfaces for a particular floating column length remain same irrespective of rainfall duration

A simulation-optimization model for Stone column-supported embankment stability considering rainfall effect

Energy Technology Data Exchange (ETDEWEB)

Deb, Kousik, E-mail: kousik@civil.iitkgp.ernet.in [Associate Professor, Department of Civil Engineering, IIT Kharagpur, Kharagpur-721302 (India); Dhar, Anirban, E-mail: anirban@civil.iitkgp.ernet.in [Assistant Professor, Department of Civil Engineering, IIT Kharagpur, Kharagpur-721302 (India); Purohit, Sandip, E-mail: sandip.purohit91@gmail.com [Former B.Tech Student, Department of Civil Engineering, NIT Rourkela, Rourkela (India)

2016-02-01

Landslide due to rainfall has been and continues to be one of the most important concerns of geotechnical engineering. The paper presents the variation of factor of safety of stone column-supported embankment constructed over soft soil due to change in water level for an incessant period of rainfall. A combined simulation-optimization based methodology has been proposed to predict the critical surface of failure of the embankment and to optimize the corresponding factor of safety under rainfall conditions using an evolutionary genetic algorithm NSGA-II (Non-Dominated Sorted Genetic Algorithm-II). It has been observed that the position of water table can be reliably estimated with varying periods of infiltration using developed numerical method. The parametric study is presented to study the optimum factor of safety of the embankment and its corresponding critical failure surface under the steady-state infiltration condition. Results show that in case of floating stone columns, period of infiltration has no effect on factor of safety. Even critical failure surfaces for a particular floating column length remain same irrespective of rainfall duration.

AIP Diffraction measurements using the LHC Beam Loss Monitoring System

CERN Document Server

Kalliokoski, Matti

2017-01-01

The Beam Loss Monitoring (BLM) system of the Large Hadron Collider protects the machine from beam induced damage by measuring the absorbed dose rates of beam losses, and by triggering beam dump if the rates increase above the allowed threshold limits. Although the detection time scales are optimized for multi-turn losses, information on fast losses can be recovered from the loss data. In this paper, methods in using the BLM system in di ff raction studies are discussed.

Prohibitions against Mourning in Childhood Sibling Loss.

Science.gov (United States)

Rosen, Helen

1985-01-01

Presents findings from a research study on sibling loss in childhood which support the idea that the loss of a sibling in childhood may be an especially significant loss for a child, in that both internal, family, and societal influences prohibit the opportunity to mourn the loss. (Author/NRB)

Supporting families in neonatal loss: relationship and faith key to comfort.

Science.gov (United States)

Holston, Jane Treadwell

2015-01-01

Around 20,000 neonatal deaths occur each year, many from congenital heart defects such as hypoplastic left heart syndrome. Nurses are on the frontline of caring for families experiencing neonatal loss. Careful spiritual and cultural assessment, attention to beliefs, focusing on relationship, and helping families create legacy can assist with grieving and making meaning out of loss.

Grid-Optimization Program for Photovoltaic Cells

Science.gov (United States)

Daniel, R. E.; Lee, T. S.

1986-01-01

CELLOPT program developed to assist in designing grid pattern of current-conducting material on photovoltaic cell. Analyzes parasitic resistance losses and shadow loss associated with metallized grid pattern on both round and rectangular solar cells. Though performs sensitivity studies, used primarily to optimize grid design in terms of bus bar and grid lines by minimizing power loss. CELLOPT written in APL.

Resolution and reconciliation of non-binary gene trees with transfers, duplications and losses.

Science.gov (United States)

Jacox, Edwin; Weller, Mathias; Tannier, Eric; Scornavacca, Celine

2017-04-01

Gene trees reconstructed from sequence alignments contain poorly supported branches when the phylogenetic signal in the sequences is insufficient to determine them all. When a species tree is available, the signal of gains and losses of genes can be used to correctly resolve the unsupported parts of the gene history. However finding a most parsimonious binary resolution of a non-binary tree obtained by contracting the unsupported branches is NP-hard if transfer events are considered as possible gene scale events, in addition to gene origination, duplication and loss. We propose an exact, parameterized algorithm to solve this problem in single-exponential time, where the parameter is the number of connected branches of the gene tree that show low support from the sequence alignment or, equivalently, the maximum number of children of any node of the gene tree once the low-support branches have been collapsed. This improves on the best known algorithm by an exponential factor. We propose a way to choose among optimal solutions based on the available information. We show the usability of this principle on several simulated and biological datasets. The results are comparable in quality to several other tested methods having similar goals, but our approach provides a lower running time and a guarantee that the produced solution is optimal. Our algorithm has been integrated into the ecceTERA phylogeny package, available at http://mbb.univ-montp2.fr/MBB/download_sources/16__ecceTERA and which can be run online at http://mbb.univ-montp2.fr/MBB/subsection/softExec.php?soft=eccetera . celine.scornavacca@umontpellier.fr. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

A Conjunction Method of Wavelet Transform-Particle Swarm Optimization-Support Vector Machine for Streamflow Forecasting

Directory of Open Access Journals (Sweden)

Fanping Zhang

2014-01-01

Full Text Available Streamflow forecasting has an important role in water resource management and reservoir operation. Support vector machine (SVM is an appropriate and suitable method for streamflow prediction due to its best versatility, robustness, and effectiveness. In this study, a wavelet transform particle swarm optimization support vector machine (WT-PSO-SVM model is proposed and applied for streamflow time series prediction. Firstly, the streamflow time series were decomposed into various details (Ds and an approximation (A3 at three resolution levels (21-22-23 using Daubechies (db3 discrete wavelet. Correlation coefficients between each D subtime series and original monthly streamflow time series are calculated. Ds components with high correlation coefficients (D3 are added to the approximation (A3 as the input values of the SVM model. Secondly, the PSO is employed to select the optimal parameters, C, ε, and σ, of the SVM model. Finally, the WT-PSO-SVM models are trained and tested by the monthly streamflow time series of Tangnaihai Station located in Yellow River upper stream from January 1956 to December 2008. The test results indicate that the WT-PSO-SVM approach provide a superior alternative to the single SVM model for forecasting monthly streamflow in situations without formulating models for internal structure of the watershed.

Adaptive optimization for active queue management supporting TCP flows

NARCIS (Netherlands)

Baldi, S.; Kosmatopoulos, Elias B.; Pitsillides, Andreas; Lestas, Marios; Ioannou, Petros A.; Wan, Y.; Chiu, George; Johnson, Katie; Abramovitch, Danny

2016-01-01

An adaptive decentralized strategy for active queue management of TCP flows over communication networks is presented. The proposed strategy solves locally, at each link, an optimal control problem, minimizing a cost composed of residual capacity and buffer queue size. The solution of the optimal

Optimization and Control for Sharing of the ITER Vacuum Vessel Support Force

International Nuclear Information System (INIS)

Rozov, V.

2006-01-01

The ITER Vacuum Vessel (VV) is a complex body supported in 9 points below lower ports by restraints in the radial, toroidal and vertical directions. The applied load produces a combination of reaction forces, which must be consistent with the design of the supported object. A reasonable sharing of the load among the supports is important for overall performance of the structure and helps to avoid excessive stress at the joints between the VV and lower ports. Optimization has been performed of the sharing of the total horizontal load applied to the ITER VV between radial and toroidal restraints. An effective method of finding simple parametric relationships between the design parameters of supports and the balance of the reaction forces has been developed. This allows purely analytical prediction of the sharing of the reaction forces for any desired stiffness of the applied restraints with no need for finite element structural analysis, and also allows control of the sharing by a proper selection of parameters of the supports. The method is based on the use of elementary mono-directional schemes - equivalent oscillators built for the main global modes, in static problems. The types of schemes and parameters of their members, related to the a-priori unknown stiffness of the VV structure under the supports, are found from consideration of the free vibration problem for the object using a 3D model of the VV with mass simulators - a series of simple eigenvalue analyses with variation of stiffness of the external restraints, that demands quite moderate computational resources. The equivalent schemes for the main modes not only enable simple one-line analytical calculation of the natural frequencies at any desired stiffness of the supports, but also indicate the contributions and balance of stiffness, to be considered in the static problem. The results of assessments of the reaction forces by direct static structural analyses for several cases are in agreement with values

Cuckoo Search with Lévy Flights for Weighted Bayesian Energy Functional Optimization in Global-Support Curve Data Fitting

Directory of Open Access Journals (Sweden)

Akemi Gálvez

2014-01-01

for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to other common approaches in CAD/CAM and computer graphics driven by piecewise functions (such as B-splines and NURBS that provide local control of the shape of the curve. Our method applies a powerful nature-inspired metaheuristic algorithm called cuckoo search, introduced recently to solve optimization problems. A major advantage of this method is its simplicity: cuckoo search requires only two parameters, many fewer than other metaheuristic approaches, so the parameter tuning becomes a very simple task. The paper shows that this new approach can be successfully used to solve our optimization problem. To check the performance of our approach, it has been applied to five illustrative examples of different types, including open and closed 2D and 3D curves that exhibit challenging features, such as cusps and self-intersections. Our results show that the method performs pretty well, being able to solve our minimization problem in an astonishingly straightforward way.

Surrogate losses: Understandings of pregnancy loss and assisted reproduction among surrogate mothers.

Science.gov (United States)

Berend, Zsuzsa

2010-06-01

I explore surrogate mothers' narrative construction of pregnancy loss on surrogacy support websites. Communicating via the Internet, women construct the public online world of surrogacy. Drawing on anthropological and sociological literature I investigate the connections between conceptualizations of loss and understandings of technological practices and the consequences of these understandings for assisted reproduction. Surrogate mothers define loss broadly, ranging from failure to conceive to miscarriage and stillbirth; loss means the failure to give a baby to the intended parents. Assisted reproductive technologies contribute to loss by raising expectations of success, by attempting to maximize results through the transfer of multiple fertilized ova, and by early monitoring and testing. However, surrogates collectively understand technology as a positive force and advocate for reproductive technology. Surrogates' resolve to "give the gift of life" makes them vulnerable to failure and loss, yet also informs repeated efforts to bear children for others with technological assistance.

Topology optimization of two-dimensional elastic wave barriers

DEFF Research Database (Denmark)

Van Hoorickx, C.; Sigmund, Ole; Schevenels, M.

2016-01-01

harmonic sources at a frequency in a given range, a uniform reduction of the response over a frequency range is pursued. The minimal insertion loss over the frequency range of interest is maximized. The resulting design contains features at depth leading to a reduction of the insertion loss at the lowest...... frequencies and features close to the surface leading to a reduction at the highest frequencies. For broadband sources, the average insertion loss in a frequency range is optimized. This leads to designs that especially reduce the response at high frequencies. The designs optimized for the frequency averaged...

Adipose-derived stromal cells enhance auditory neuron survival in an animal model of sensory hearing loss.

Science.gov (United States)

Schendzielorz, Philipp; Vollmer, Maike; Rak, Kristen; Wiegner, Armin; Nada, Nashwa; Radeloff, Katrin; Hagen, Rudolf; Radeloff, Andreas

2017-10-01

A cochlear implant (CI) is an electronic prosthesis that can partially restore speech perception capabilities. Optimum information transfer from the cochlea to the central auditory system requires a proper functioning auditory nerve (AN) that is electrically stimulated by the device. In deafness, the lack of neurotrophic support, normally provided by the sensory cells of the inner ear, however, leads to gradual degeneration of auditory neurons with undesirable consequences for CI performance. We evaluated the potential of adipose-derived stromal cells (ASCs) that are known to produce neurotrophic factors to prevent neural degeneration in sensory hearing loss. For this, co-cultures of ASCs with auditory neurons have been studied, and autologous ASC transplantation has been performed in a guinea pig model of gentamicin-induced sensory hearing loss. In vitro ASCs were neuroprotective and considerably increased the neuritogenesis of auditory neurons. In vivo transplantation of ASCs into the scala tympani resulted in an enhanced survival of auditory neurons. Specifically, peripheral AN processes that are assumed to be the optimal activation site for CI stimulation and that are particularly vulnerable to hair cell loss showed a significantly higher survival rate in ASC-treated ears. ASC transplantation into the inner ear may restore neurotrophic support in sensory hearing loss and may help to improve CI performance by enhanced AN survival. Copyright © 2017 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

The Impact of Impulsivity on Weight Loss Four Years after Bariatric Surgery

Directory of Open Access Journals (Sweden)

Kathrin Schag

2016-11-01

Full Text Available Bariatric surgery has serious implications on metabolic health. The reasons for a failure of bariatric surgery, i.e., limited weight loss, are multifactorial and include psychological factors. We established a theoretical model of how impulsivity is related to weight loss outcome. We propose that depressive symptoms act as a mediator between impulsivity and pathological eating behavior, and that pathological eating behavior has a direct impact on weight loss outcome. We calculated excessive weight loss (%EWL and assessed self-reported impulsivity (using the Baratt Impulsiveness Scale (BIS-15 total score, depressive symptoms (the Patient Health Questionnaire (PHQ-9 score, and pathological eating behavior (the Eating Disorder Inventory 2 (EDI-2 total score in 65 patients four years after laparoscopic sleeve gastrectomy. Regression and mediation analyses were computed to validate the theoretical model. The BIS-15, PHQ-9, and EDI-2 have medium to high correlations between each other, and EDI-2 correlated with %EWL. The mediation analysis yielded that the PHQ-9 represents a significant mediator between BIS-15 and EDI-2. The regression model between EDI-2 and %EWL was also significant. These results support our theoretical model, i.e., suggest that impulsivity has an indirect impact on weight loss outcome after bariatric surgery, mediated by depression and transferred through pathological eating behavior. Thus, the underlying psychological factors should be addressed in post-operative care to optimize weight loss outcome.

Optimal Design of Magnetic ComponentsinPlasma Cutting Power Supply

Science.gov (United States)

Jiang, J. F.; Zhu, B. R.; Zhao, W. N.; Yang, X. J.; Tang, H. J.

2017-10-01

Phase-shifted transformer and DC reactor are usually needed in chopper plasma cutting power supply. Because of high power rate, the loss of magnetic components may reach to several kilowatts, which seriously affects the conversion efficiency. Therefore, it is necessary to research and design low loss magnetic components by means of efficient magnetic materials and optimal design methods. The main task in this paper is to compare the core loss of different magnetic material, to analyze the influence of transformer structure, winding arrangement and wire structure on the characteristics of magnetic component. Then another task is to select suitable magnetic material, structure and wire in order to reduce the loss and volume of magnetic components. Based on the above outcome, the optimization design process of transformer and dc reactor are proposed in chopper plasma cutting power supply with a lot of solutions. These solutions are analyzed and compared before the determination of the optimal solution in order to reduce the volume and power loss of the two magnetic components and improve the conversion efficiency of plasma cutting power supply.

Information Support of Optimal Control of Modes of Electric Systems with Renewable Energy Sources

Directory of Open Access Journals (Sweden)

Michalina Gryniewicz-Jaworska

2017-12-01

Full Text Available To provide necessary quality of electric energy and reliable supply and reduce environmental contamination as a result of energy units operation, renewable sources of energy (RSE, in particular solar electric stations (SES, wind electric stations (WES and small hydropower stations (SHES are intensively developed. The paper considers the conditions of optimality of renewable sources of energy (RSE functioning in electric systems, controllability of which is limited by the impact of non-stable weather conditions. The influence of control system information support on the efficiency of RSE usage is shown.

Optimization-based decision support to assist in logistics planning for hospital evacuations.

Science.gov (United States)

Glick, Roger; Bish, Douglas R; Agca, Esra

2013-01-01

The evacuation of the hospital is a very complex process and evacuation planning is an important part of a hospital's emergency management plan. There are numerous factors that affect the evacuation plan including the nature of threat, availability of resources and staff the characteristics of the evacuee population, and risk to patients and staff. The safety and health of patients is of fundamental importance, but safely moving patients to alternative care facilities while under threat is a very challenging task. This article describes the logistical issues and complexities involved in planning and execution of hospital evacuations. Furthermore, this article provides examples of how optimization-based decision support tools can help evacuation planners to better plan for complex evacuations by providing real-world solutions to various evacuation scenarios.

On the optimization of support positioning and stiffness for piping systems in power plants

International Nuclear Information System (INIS)

Collina, A.; Zanaboni, P.; Belloli, M.

2005-01-01

The optimal location of supports for the reduction of vibration in piping systems is an interesting structural problem, that can be approached also with the methods used in the updating parameters problems, especially when the cause of the vibration is due to a resonance or a ineffective damping level, and the shift of a critical frequency is an effective remedy. In the proposed paper a frequency domain method of Finite Element model updating is used in order to properly locate the natural frequencies of a given piping system, starting from the nominal condition. The method considers modal parameters, and enables to directly update the physical quantities of the finite element model, i.e., in the considered application, the stiffness and damping of the supporting devices. The model of the structure is made up by beam finite elements, lumped springs and masses, and rigid links. The general procedure is applied here updating the stiffness and location of the supports of the piping according to the comparison among the current frequencies of the piping systems structure and the ones that are required, according to specific requirements. Application to a system similar to a portion of an actual AP1000 (a new Advanced Passive Nuclear Reactor) piping-support layout is presented. (authors)

Long-run savings and investment strategy optimization.

Science.gov (United States)

Gerrard, Russell; Guillén, Montserrat; Nielsen, Jens Perch; Pérez-Marín, Ana M

2014-01-01

We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor's risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.

Long-Run Savings and Investment Strategy Optimization

Directory of Open Access Journals (Sweden)

Russell Gerrard

2014-01-01

Full Text Available We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor’s risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.

Expanding the PACS archive to support clinical review, research, and education missions

Science.gov (United States)

Honeyman-Buck, Janice C.; Frost, Meryll M.; Drane, Walter E.

1999-07-01

Designing an image archive and retrieval system that supports multiple users with many different requirements and patterns of use without compromising the performance and functionality required by diagnostic radiology is an intellectual and technical challenge. A diagnostic archive, optimized for performance when retrieving diagnostic images for radiologists needed to be expanded to support a growing clinical review network, the University of Florida Brain Institute's demands for neuro-imaging, Biomedical Engineering's imaging sciences, and an electronic teaching file. Each of the groups presented a different set of problems for the designers of the system. In addition, the radiologists did not want to see nay loss of performance as new users were added.

Locomotor training with body weight support in SCI : EMG improvement is more optimally expressed at a low testing speed

NARCIS (Netherlands)

Meyns, P.; Van de Crommert, H. W. A. A.; Rijken, H.; van Kuppevelt, D. H. J. M.; Duysens, J.

2014-01-01

Study design: Case series. Objectives: To determine the optimal testing speed at which the recovery of the EMG (electromyographic) activity should be assessed during and after body weight supported (BWS) locomotor training. Setting: Tertiary hospital, Sint Maartenskliniek, Nijmegen, The Netherlands.

Hidden loss

DEFF Research Database (Denmark)

Kieffer-Kristensen, Rikke; Johansen, Karen Lise Gaardsvig

2013-01-01

to participate. RESULTS: All children were affected by their parents' ABI and the altered family situation. The children's expressions led the authors to identify six themes, including fear of losing the parent, distress and estrangement, chores and responsibilities, hidden loss, coping and support. The main......PRIMARY OBJECTIVE: The purpose of this study was to listen to and learn from children showing high levels of post-traumatic stress symptoms after parental acquired brain injury (ABI), in order to achieve an in-depth understanding of the difficulties the children face in their everyday lives...... finding indicates that the children experienced numerous losses, many of which were often suppressed or neglected by the children to protect the ill parents. CONCLUSIONS: The findings indicated that the children seemed to make a special effort to hide their feelings of loss and grief in order to protect...

Theories on coping with loss: the impact of social support and self-esteem on adjustment to emotional and social loneliness following a partner's death in later life.

Science.gov (United States)

van Baarsen, Berna

2002-01-01

This longitudinal study focused on the role of self-esteem and social support in adjustment to loneliness experienced by bereaved elderly persons. This study also examined the contributions of a general and a specific coping theory toward explaining loneliness. A distinction has been made between emotional loneliness and social loneliness/perceived support. The theory of mental incongruity predicts that the presence of more favorable conditions, such as higher self-esteem or more social support, results in less loneliness (i.e., less incongruity). According to the theory of relational loneliness, the partner's death leads to a loss of identity, thus increasing emotional loneliness, and social support does not mitigate emotional loneliness following a loss. In total, 101 participants, aged 55-89 years, were interviewed before and after their partners' deaths. Findings were ambiguous with regard to both theories. As hypothesized, partner loss lowered self-esteem, resulting in higher emotional loneliness and social loneliness, that is, perception of less support. Supportive personal relations reduced emotional loneliness. The presence of close friends, however, seemed to increase emotional and social loneliness (i.e., decrease perceived support) in the long term, particularly among bereaved participants with lower self-esteem. The findings highlight the need to integrate theoretical concepts. In explaining adjustment to a partner's death, attention should be paid to underlying mechanisms relevant to the restoration process (e.g., identity change) and the ways in which the adjustment process can be improved (e.g., intimate relationships) or impeded (e.g., dependency-sustaining relationships).

Predicting Taxi-Out Time at Congested Airports with Optimization-Based Support Vector Regression Methods

Directory of Open Access Journals (Sweden)

Guan Lian

2018-01-01

Full Text Available Accurate prediction of taxi-out time is significant precondition for improving the operationality of the departure process at an airport, as well as reducing the long taxi-out time, congestion, and excessive emission of greenhouse gases. Unfortunately, several of the traditional methods of predicting taxi-out time perform unsatisfactorily at congested airports. This paper describes and tests three of those conventional methods which include Generalized Linear Model, Softmax Regression Model, and Artificial Neural Network method and two improved Support Vector Regression (SVR approaches based on swarm intelligence algorithm optimization, which include Particle Swarm Optimization (PSO and Firefly Algorithm. In order to improve the global searching ability of Firefly Algorithm, adaptive step factor and Lévy flight are implemented simultaneously when updating the location function. Six factors are analysed, of which delay is identified as one significant factor in congested airports. Through a series of specific dynamic analyses, a case study of Beijing International Airport (PEK is tested with historical data. The performance measures show that the proposed two SVR approaches, especially the Improved Firefly Algorithm (IFA optimization-based SVR method, not only perform as the best modelling measures and accuracy rate compared with the representative forecast models, but also can achieve a better predictive performance when dealing with abnormal taxi-out time states.

Minimization of Distribution Grid Losses by Consumption Coordination

DEFF Research Database (Denmark)

Juelsgaard, Morten; Andersen, Palle; Wisniewski, Rafal

2013-01-01

for coordinating consumption of electrical energy within the community, with the purpose of reducing grid loading and active power losses. For this we present a simplified model of the electrical grid, including system losses and capacity constraints. Coordination is performed in a distributed fashion, where each...... are obeyed. These objectives are enforced by coordinating consumers through nonlinear tariffs on power consumption. We present simulation test-cases, illustrating that significant reduction of active losses, can be obtained by such coordination. The distributed optimization algorithm, employs the alternating...

Optimizing the supply chain of biomass and biogas for a single plant considering mass and energy losses

DEFF Research Database (Denmark)

Jensen, Ida Græsted; Münster, Marie; Pisinger, David

2017-01-01

plants. In this paper, a mixed integer programming (MIP) model for finding the optimal production and investment plan for a biogas supply chain is presented to ensure better economy for the full chain hopefully stimulating future investments in biogas. The model makes use of step-wise linear functions...... to represent capital and operational expenditures at the biogas plant; considers the chain from the farmer to the end market; and includes changes of mass and energy content along the chain by modeling the losses and gains for all processes in the chain. Biomass inputs are scheduled on a weekly basis whereas...... energy outputs are scheduled on an hourly basis to better capture the changes of energy prices and potentially take advantage of these changes. The model is tested on a case study with co-digestion of straw, sugar beet and manure, considering natural gas, heat, and electricity as end products. The model...

Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

Science.gov (United States)

Abdulameer, Mohammed Hasan; Othman, Zulaiha Ali

2014-01-01

Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584

Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Mohammed Hasan Abdulameer

2014-01-01

Full Text Available Existing face recognition methods utilize particle swarm optimizer (PSO and opposition based particle swarm optimizer (OPSO to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM. In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented.

Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

Directory of Open Access Journals (Sweden)

Maolong Xi

2016-01-01

Full Text Available This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO for cancer feature gene selection, coupling support vector machine (SVM for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV. Finally, the BQPSO coupling SVM (BQPSO/SVM, binary PSO coupling SVM (BPSO/SVM, and genetic algorithm coupling SVM (GA/SVM are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms.

Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

Science.gov (United States)

Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

2016-01-01

This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV). Finally, the BQPSO coupling SVM (BQPSO/SVM), binary PSO coupling SVM (BPSO/SVM), and genetic algorithm coupling SVM (GA/SVM) are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms. PMID:27642363

Optimization of accelerator control

International Nuclear Information System (INIS)

Vasiljev, N.D.; Mozin, I.V.; Shelekhov, V.A.; Efremov, D.V.

1992-01-01

Expensive exploitation of charged particle accelerators is inevitably concerned with requirements of effectively obtaining of the best characteristics of accelerated beams for physical experiments. One of these characteristics is intensity. Increase of intensity is hindered by a number of effects, concerned with the influence of the volume charge field on a particle motion dynamics in accelerator's chamber. However, ultimate intensity, determined by a volume charge, is almost not achieved for the most of the operating accelerators. This fact is caused by losses of particles during injection, at the initial stage of acceleration and during extraction. These losses are caused by deviations the optimal from real characteristics of the accelerating and magnetic system. This is due to a number of circumstances, including technological tolerances on structural elements of systems, influence of measuring and auxiliary equipment and beam consumers' installations, placed in the closed proximity to magnets, and instability in operation of technological systems of accelerator. Control task consists in compensation of deviations of characteristics of magnetic and electric fields by optimal selection of control actions. As for technical means, automatization of modern accelerators allows to solve optimal control problems in real time. Therefore, the report is devoted to optimal control methods and experimental results. (J.P.N.)

A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-25

This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.

Global optimization of silicon nanowires for efficient parametric processes

DEFF Research Database (Denmark)

Vukovic, Dragana; Xu, Jing; Mørk, Jesper

2013-01-01

We present a global optimization of silicon nanowires for parametric single-pump mixing. For the first time, the effect of surface roughness-induced loss is included in the analysis, significantly influencing the optimum waveguide dimensions.......We present a global optimization of silicon nanowires for parametric single-pump mixing. For the first time, the effect of surface roughness-induced loss is included in the analysis, significantly influencing the optimum waveguide dimensions....

Optimal placement of distributed generation in distribution networks ...

African Journals Online (AJOL)

This paper proposes the application of Particle Swarm Optimization (PSO) technique to find the optimal size and optimum location for the placement of DG in the radial distribution networks for active power compensation by reduction in real power losses and enhancement in voltage profile. In the first segment, the optimal ...

Loss Model and Efficiency Analysis of Tram Auxiliary Converter Based on a SiC Device

Directory of Open Access Journals (Sweden)

Hao Liu

2017-12-01

Full Text Available Currently, the auxiliary converter in the auxiliary power supply system of a modern tram adopts Si IGBT as its switching device and with the 1700 V/225 A SiC MOSFET module commercially available from Cree, an auxiliary converter using all SiC devices is now possible. A SiC auxiliary converter prototype is developed during this study. The author(s derive the loss calculation formula of the SiC auxiliary converter according to the system topology and principle and each part loss in this system can be calculated based on the device datasheet. Then, the static and dynamic characteristics of the SiC MOSFET module used in the system are tested, which aids in fully understanding the performance of the SiC devices and provides data support for the establishment of the PLECS loss simulation model. Additionally, according to the actual circuit parameters, the PLECS loss simulation model is set up. This simulation model can simulate the actual operating conditions of the auxiliary converter system and calculate the loss of each switching device. Finally, the loss of the SiC auxiliary converter prototype is measured and through comparison it is found that the loss calculation theory and PLECS loss simulation model is valuable. Furthermore, the thermal images of the system can prove the conclusion about loss distribution to some extent. Moreover, these two methods have the advantages of less variables and fast calculation for high power applications. The loss models may aid in optimizing the switching frequency and improving the efficiency of the system.

An MR Brain Images Classifier System via Particle Swarm Optimization and Kernel Support Vector Machine

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Yudong Zhang

2013-01-01

Full Text Available Automated abnormal brain detection is extremely of importance for clinical diagnosis. Over last decades numerous methods had been presented. In this paper, we proposed a novel hybrid system to classify a given MR brain image as either normal or abnormal. The proposed method first employed digital wavelet transform to extract features then used principal component analysis (PCA to reduce the feature space. Afterwards, we constructed a kernel support vector machine (KSVM with RBF kernel, using particle swarm optimization (PSO to optimize the parameters C and σ. Fivefold cross-validation was utilized to avoid overfitting. In the experimental procedure, we created a 90 images dataset brain downloaded from Harvard Medical School website. The abnormal brain MR images consist of the following diseases: glioma, metastatic adenocarcinoma, metastatic bronchogenic carcinoma, meningioma, sarcoma, Alzheimer, Huntington, motor neuron disease, cerebral calcinosis, Pick’s disease, Alzheimer plus visual agnosia, multiple sclerosis, AIDS dementia, Lyme encephalopathy, herpes encephalitis, Creutzfeld-Jakob disease, and cerebral toxoplasmosis. The 5-folded cross-validation classification results showed that our method achieved 97.78% classification accuracy, higher than 86.22% by BP-NN and 91.33% by RBF-NN. For the parameter selection, we compared PSO with those of random selection method. The results showed that the PSO is more effective to build optimal KSVM.

Optimization of refrigeration machinery

Energy Technology Data Exchange (ETDEWEB)

Wall, Goeran [University Coll. of Eskilstuna/Vaesteraas (SE)

1991-11-01

This paper reports the application of thermoeconomics to the optimization of a heat pump. The method is suited for application to thermodynamic processes and yields exergy losses. The marginal cost of an arbitary variable can also be calculated. The efficiencies of the compressor, condenser, evaporator and electric motor are chosen as variables to be optimized. Parameters such as the price of electricity and the temperature of the delivered heat may vary between optimizations, and results are presented for different parameter values. The results show that the efficiency of the electric motor is the most important variable. (author).

Modified Monkey Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem

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Kanagasabai Lenin

2015-04-01

Full Text Available In this paper, a novel approach Modified Monkey optimization (MMO algorithm for solving optimal reactive power dispatch problem has been presented. MMO is a population based stochastic meta-heuristic algorithm and it is inspired by intelligent foraging behaviour of monkeys. This paper improves both local leader and global leader phases.  The proposed (MMO algorithm has been tested in standard IEEE 30 bus test system and simulation results show the worthy performance of the proposed algorithm in reducing the real power loss.

Frequency of intron loss correlates with processed pseudogene abundance: a novel strategy to test the reverse transcriptase model of intron loss.

Science.gov (United States)

Zhu, Tao; Niu, Deng-Ke

2013-03-05

Although intron loss in evolution has been described, the mechanism involved is still unclear. Three models have been proposed, the reverse transcriptase (RT) model, genomic deletion model and double-strand-break repair model. The RT model, also termed mRNA-mediated intron loss, suggests that cDNA molecules reverse transcribed from spliced mRNA recombine with genomic DNA causing intron loss. Many studies have attempted to test this model based on its predictions, such as simultaneous loss of adjacent introns, 3'-side bias of intron loss, and germline expression of intron-lost genes. Evidence either supporting or opposing the model has been reported. The mechanism of intron loss proposed in the RT model shares the process of reverse transcription with the formation of processed pseudogenes. If the RT model is correct, genes that have produced more processed pseudogenes are more likely to undergo intron loss. In the present study, we observed that the frequency of intron loss is correlated with processed pseudogene abundance by analyzing a new dataset of intron loss obtained in mice and rats. Furthermore, we found that mRNA molecules of intron-lost genes are mostly translated on free cytoplasmic ribosomes, a feature shared by mRNA molecules of the parental genes of processed pseudogenes and long interspersed elements. This feature is likely convenient for intron-lost gene mRNA molecules to be reverse transcribed. Analyses of adjacent intron loss, 3'-side bias of intron loss, and germline expression of intron-lost genes also support the RT model. Compared with previous evidence, the correlation between the abundance of processed pseudogenes and intron loss frequency more directly supports the RT model of intron loss. Exploring such a correlation is a new strategy to test the RT model in organisms with abundant processed pseudogenes.

Is There an Optimal Diet for Weight Management and Metabolic Health?

Science.gov (United States)

Thom, George; Lean, Mike

2017-05-01

Individuals can lose body weight and improve health status on a wide range of energy (calorie)-restricted dietary interventions. In this paper, we have reviewed the effectiveness of the most commonly utilized diets, including low-fat, low-carbohydrate, and Mediterranean approaches, in addition to commercial slimming programs, meal replacements, and newly popularized intermittent fasting diets. We also consider the role of artificial sweeteners in weight management. Low-fat diets tend to improve low-density lipoprotein cholesterol the most, while lower-carbohydrate diets may preferentially improve triglycerides and high-density lipoprotein cholesterol. However, differences between diets are marginal. Weight loss improves almost all obesity-related co-morbidities and metabolic markers, regardless of the macronutrient composition of the diet, but individuals do vary in preferences and ability to adhere to different diets. Optimizing adherence is the most important factor for weight loss success, and this is enhanced by regular professional contact and supportive behavioral change programs. Maintaining weight losses in the long term remains the biggest challenge, and is undermined by an "obesogenic" environment and biological adaptations that accompany weight loss. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

Optimal Control for Bufferbloat Queue Management Using Indirect Method with Parametric Optimization

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Amr Radwan

2016-01-01

Full Text Available Because memory buffers become larger and cheaper, they have been put into network devices to reduce the number of loss packets and improve network performance. However, the consequences of large buffers are long queues at network bottlenecks and throughput saturation, which has been recently noticed in research community as bufferbloat phenomenon. To address such issues, in this article, we design a forward-backward optimal control queue algorithm based on an indirect approach with parametric optimization. The cost function which we want to minimize represents a trade-off between queue length and packet loss rate performance. Through the integration of an indirect approach with parametric optimization, our proposal has advantages of scalability and accuracy compared to direct approaches, while still maintaining good throughput and shorter queue length than several existing queue management algorithms. All numerical analysis, simulation in ns-2, and experiment results are provided to solidify the efficiency of our proposal. In detailed comparisons to other conventional algorithms, the proposed procedure can run much faster than direct collocation methods while maintaining a desired short queue (≈40 packets in simulation and 80 (ms in experiment test.

Evaluation of levee setbacks for flood-loss reduction, Middle Mississippi River, USA

Science.gov (United States)

Dierauer, Jennifer; Pinter, Nicholas; Remo, Jonathan W. F.

2012-07-01

SummaryOne-dimensional hydraulic modeling and flood-loss modeling were used to test the effectiveness of levee setbacks for flood-loss reduction along the Middle Mississippi River (MMR). Four levee scenarios were assessed: (1) the present-day levee configuration, (2) a 1000 m levee setback, (3) a 1500 m levee setback, and (4) an optimized setback configuration. Flood losses were estimated using FEMA's Hazus-MH (Hazards US Multi-Hazard) loss-estimation software on a structure-by-structure basis for a range of floods from the 2- to the 500-year events. These flood-loss estimates were combined with a levee-reliability model to calculate probability-weighted damage estimates. In the simplest case, the levee setback scenarios tested here reduced flood losses compared to current conditions for large, infrequent flooding events but increased flood losses for smaller, more frequent flood events. These increases occurred because levee protection was removed for some of the existing structures. When combined with buyouts of unprotected structures, levee setbacks reduced flood losses for all recurrence intervals. The "optimized" levee setback scenario, involving a levee configuration manually planned to protect existing high-value infrastructure, reduced damages with or without buyouts. This research shows that levee setbacks in combination with buyouts are an economically viable approach for flood-risk reduction along the study reach and likely elsewhere where levees are widely employed for flood control. Designing a levee setback around existing high-value infrastructure can maximize the benefit of the setback while simultaneously minimizing the costs. The optimized levee setback scenario analyzed here produced payback periods (costs divided by benefits) of less than 12 years. With many aging levees failing current inspections across the US, and flood losses spiraling up over time, levee setbacks are a viable solution for reducing flood exposure and flood levels.

A simulation based optimization approach to model and design life support systems for manned space missions

Science.gov (United States)

Aydogan, Selen

This dissertation considers the problem of process synthesis and design of life-support systems for manned space missions. A life-support system is a set of technologies to support human life for short and long-term spaceflights, via providing the basic life-support elements, such as oxygen, potable water, and food. The design of the system needs to meet the crewmember demand for the basic life-support elements (products of the system) and it must process the loads generated by the crewmembers. The system is subject to a myriad of uncertainties because most of the technologies involved are still under development. The result is high levels of uncertainties in the estimates of the model parameters, such as recovery rates or process efficiencies. Moreover, due to the high recycle rates within the system, the uncertainties are amplified and propagated within the system, resulting in a complex problem. In this dissertation, two algorithms have been successfully developed to help making design decisions for life-support systems. The algorithms utilize a simulation-based optimization approach that combines a stochastic discrete-event simulation and a deterministic mathematical programming approach to generate multiple, unique realizations of the controlled evolution of the system. The timelines are analyzed using time series data mining techniques and statistical tools to determine the necessary technologies, their deployment schedules and capacities, and the necessary basic life-support element amounts to support crew life and activities for the mission duration.

Bayesian optimal experimental design for priors of compact support

KAUST Repository

Long, Quan

2016-01-08

In this study, we optimize the experimental setup computationally by optimal experimental design (OED) in a Bayesian framework. We approximate the posterior probability density functions (pdf) using truncated Gaussian distributions in order to account for the bounded domain of the uniform prior pdf of the parameters. The underlying Gaussian distribution is obtained in the spirit of the Laplace method, more precisely, the mode is chosen as the maximum a posteriori (MAP) estimate, and the covariance is chosen as the negative inverse of the Hessian of the misfit function at the MAP estimate. The model related entities are obtained from a polynomial surrogate. The optimality, quantified by the information gain measures, can be estimated efficiently by a rejection sampling algorithm against the underlying Gaussian probability distribution, rather than against the true posterior. This approach offers a significant error reduction when the magnitude of the invariants of the posterior covariance are comparable to the size of the bounded domain of the prior. We demonstrate the accuracy and superior computational efficiency of our method for shock-tube experiments aiming to measure the model parameters of a key reaction which is part of the complex kinetic network describing the hydrocarbon oxidation. In the experiments, the initial temperature and fuel concentration are optimized with respect to the expected information gain in the estimation of the parameters of the target reaction rate. We show that the expected information gain surface can change its shape dramatically according to the level of noise introduced into the synthetic data. The information that can be extracted from the data saturates as a logarithmic function of the number of experiments, and few experiments are needed when they are conducted at the optimal experimental design conditions.

Method of Retention Control for Compromised Periodontal Bone Support Abutment of Conical Crown Retained Denture

Directory of Open Access Journals (Sweden)

Chau-Hsiang Wang

2010-08-01

Full Text Available Conical crown-retained dentures (CCRD show a higher survival rate and greater patient satisfaction than transitional removable partial dentures during long-term follow-up. However, unsustainable denture retention force on supporting abutments after initial delivery and loss retention are frequently seen in long-term follow-up of clinical cases. The main causes are insufficient information concerning denture retention designs and the retention-tolerance of the supporting abutments. Monitoring by dental technicians of the quality of dental prostheses is critical. This case report describes an optimal method for CCRD construction that determines and distributes an optimal denture retention force on the supporting abutments to allow the patient to easily remove the denture while ensuring that the CCRD remains in place during physiologic activities. Oral rehabilitation with CCRD should consider the condition of the abutment periodontal support, the interarch occlusal relationship, supplemental fatigue of the terminal abutment, and patient's estimated bite force. The effects of friction on the abutment's inner crown were based on an optimal a angle. The dental laboratory used these measurements to fabricate a CCRD using a Koni-Meter to adjust the retention of the inner crown. This method protects the abutments and reduces the wear between the inner and outer crowns. The CCRD achieved good esthetic results and physiologic functions. Periodic long-term follow-up of the patient and CCRD after initial placement is recommended.

Optimal support techniques when providing mechanical ventilation to patients with acute respiratory distress syndrome.

Science.gov (United States)

Parissopoulos, Stelios; Mpouzika, Meropi DA; Timmins, Fiona

2017-01-01

Adult respiratory distress syndrome (ARDS) is a type of acute diffuse lung injury characterized by severe inflammation, increased pulmonary vascular permeability and a loss of aerated lung tissue. The effects of high fraction of inspired oxygen (FiO 2 ) include oxygen toxicity manifested by damage to the lung parenchyma in the acute phase of lung injury. There is still a high mortality rate among this group of patients, so clinically sensitive evidence-based interventions are paramount to maximize survival chances during critical care. The aim of this article is to explore the current opinion concerning optimal mechanical ventilation support techniques for patients with acute respiratory distress syndrome. A literature search of clinical trials and observation studies, reviews, discussion papers, meta-analyses and clinical guidelines written in English up to 2015, derived from the databases of Scopus, CINAHL, Cochrane Library databases and PubMed was conducted. Low tidal volume, pressure limitation and prone positioning in severe ARDS patients appear to be of some benefit. More research is required and further development and use of standardized protocols is an important strategy for reducing practice variations across disciplines, as well as giving clear guidelines to nurses practising in critical care. There is also evidence that this syndrome is under-diagnosed and the utilization of lung protective ventilation is still variable. It is important that nurses have underlying knowledge of both aetiology of ARDS and ventilation management, and that they monitor patients very closely. The adoption of a low tidal ventilation protocol, which is based on quality evidence guidelines, the value of rescue therapies and patient observation practices in the overall patient management, and the need to place emphasis on long-term patient outcomes, all these emerge as key factors for consideration and future research. However, there is also a need for more research that would

Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm

Directory of Open Access Journals (Sweden)

M. Balasubbareddy

2015-12-01

Full Text Available A novel optimization algorithm is proposed to solve single and multi-objective optimization problems with generation fuel cost, emission, and total power losses as objectives. The proposed method is a hybridization of the conventional cuckoo search algorithm and arithmetic crossover operations. Thus, the non-linear, non-convex objective function can be solved under practical constraints. The effectiveness of the proposed algorithm is analyzed for various cases to illustrate the effect of practical constraints on the objectives' optimization. Two and three objective multi-objective optimization problems are formulated and solved using the proposed non-dominated sorting-based hybrid cuckoo search algorithm. The effectiveness of the proposed method in confining the Pareto front solutions in the solution region is analyzed. The results for single and multi-objective optimization problems are physically interpreted on standard test functions as well as the IEEE-30 bus test system with supporting numerical and graphical results and also validated against existing methods.

Decision support model for establishing the optimal energy retrofit strategy for existing multi-family housing complexes

International Nuclear Information System (INIS)

Hong, Taehoon; Koo, Choongwan; Kim, Hyunjoong; Seon Park, Hyo

2014-01-01

The number of multi-family housing complexes (MFHCs) over 15 yr old in South Korea is expected to exceed 5 million by 2015. Accordingly, the demand for energy retrofit in the deteriorating MFHCs is rapidly increasing. This study aimed to develop a decision support model for establishing the optimal energy retrofit strategy for existing MFHCs. It can provide clear criteria for establishing the carbon emissions reduction target (CERT) and allow efficient budget allocation for conducting the energy retrofit. The CERT for “S” MFHC, one of MFHCs located in Seoul, as a case study, was set at 23.0% (electricity) and 27.9% (gas energy). In the economic and environmental assessment, it was determined that scenario #12 was the optimal scenario (ranked second with regard to NPV 40 (net present value at year 40) and third with regard to SIR 40 (saving to investment ratio at year 40). The proposed model could be useful for owners, construction managers, or policymakers in charge of establishing energy retrofit strategy for existing MFHCs. It could allow contractors in a competitive bidding process to rationally establish the CERT and select the optimal energy retrofit strategy. It can be also applied to any other country or sector in a global environment. - Highlights: • The proposed model was developed to establish the optimal energy retrofit strategy. • Advanced case-based reasoning was applied to establish the community-based CERT. • Energy simulation was conducted to analyze the effects of energy retrofit strategy. • The optimal strategy can be finally selected based on the LCC and LCCO 2 analysis. • It could be extended to any other country or sector in the global environment

Chemical effects head-loss research in support of generic safety issue 191.

Energy Technology Data Exchange (ETDEWEB)

Park, J. H.; Kasza, K.; Fisher, B.; Oras, J.; Natesan, K.; Shack, W. J.; Nuclear Engineering Division

2006-10-31

This summary report describes studies conducted at Argonne National Laboratory on the potential for chemical effects on head loss across sump screens. Three different buffering solutions were used for these tests: trisodium phosphate (TSP), sodium hydroxide, and sodium tetraborate. These pH control agents used following a LOCA at a nuclear power plant show various degrees of interaction with the insulating materials Cal-Sil and NUKON. Results for Cal-Sil dissolution tests in TSP solutions, settling rate tests of calcium phosphate precipitates, and benchmark tests in chemically inactive environments are also presented. The dissolution tests were intended to identify important environmental variables governing both calcium dissolution and subsequent calcium phosphate formation over a range of simulated sump pool conditions. The results from the dissolution testing were used to inform both the head loss and settling test series. The objective of the head loss tests was to assess the head loss produced by debris beds created by Cal-Sil, fibrous debris, and calcium phosphate precipitates. The effects of both the relative arrival time of the precipitates and insulation debris and the calcium phosphate formation process were specifically evaluated. The debris loadings, test loop flow rates, and test temperature were chosen to be reasonably representative of those expected in plants with updated sump screen configurations, although the approach velocity of 0.1 ft/s used for most of the tests is 3-10 times that expected in plants with large screens . Other variables were selected with the intent to reasonably bound the head loss variability due to arrival time and calcium phosphate formation uncertainty. Settling tests were conducted to measure the settling rates of calcium phosphate precipitates (formed by adding dissolved Ca to boric acid and TSP solutions) in water columns having no bulk directional flow. For PWRs where NaOH and sodium tetraborate are used to control

Integrated Medical Model (IMM) Optimization Version 4.0 Functional Improvements

Science.gov (United States)

Arellano, John; Young, M.; Boley, L.; Garcia, Y.; Saile, L.; Walton, M.; Kerstman, E.; Reyes, D.; Goodenow, D. A.; Myers, J. G.

2016-01-01

The IMMs ability to assess mission outcome risk levels relative to available resources provides a unique capability to provide guidance on optimal operational medical kit and vehicle resources. Post-processing optimization allows IMM to optimize essential resources to improve a specific model outcome such as maximization of the Crew Health Index (CHI), or minimization of the probability of evacuation (EVAC) or the loss of crew life (LOCL). Mass and or volume constrain the optimized resource set. The IMMs probabilistic simulation uses input data on one hundred medical conditions to simulate medical events that may occur in spaceflight, the resources required to treat those events, and the resulting impact to the mission based on specific crew and mission characteristics. Because IMM version 4.0 provides for partial treatment for medical events, IMM Optimization 4.0 scores resources at the individual resource unit increment level as opposed to the full condition-specific treatment set level, as done in version 3.0. This allows the inclusion of as many resources as possible in the event that an entire set of resources called out for treatment cannot satisfy the constraints. IMM Optimization version 4.0 adds capabilities that increase efficiency by creating multiple resource sets based on differing constraints and priorities, CHI, EVAC, or LOCL. It also provides sets of resources that improve mission-related IMM v4.0 outputs with improved performance compared to the prior optimization. The new optimization represents much improved fidelity that will improve the utility of the IMM 4.0 for decision support.

Early weight loss while on lorcaserin, diet, and exercise as a predictor of week 52 weight-loss outcomes

DEFF Research Database (Denmark)

Smith, Steven R; O'Neil, Patrick M; Astrup, Arne

2014-01-01

OBJECTIVE: To identify an early treatment milestone that optimizes sensitivity and specificity for predicting ≥5% weight loss at Week (W) 52 in patients with and without type 2 diabetes on lorcaserin or placebo. METHODS: Post hoc area under the curve for receiver operating characteristic analyses...

Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study).

Science.gov (United States)

Thomas, Diana M; Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A

2015-03-01

Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing model. The AUC statistic quantified the ROC curve's capacity to classify participants likely to lose models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. © 2015 American Society for Nutrition.

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Human Space Flight Missions

Science.gov (United States)

Kerstman, Eric L.; Minard, Charles; FreiredeCarvalho, Mary H.; Walton, Marlei E.; Myers, Jerry G., Jr.; Saile, Lynn G.; Lopez, Vilma; Butler, Douglas J.; Johnson-Throop, Kathy A.

2011-01-01

This slide presentation reviews the Integrated Medical Model (IMM) and its use as a risk assessment and decision support tool for human space flight missions. The IMM is an integrated, quantified, evidence-based decision support tool useful to NASA crew health and mission planners. It is intended to assist in optimizing crew health, safety and mission success within the constraints of the space flight environment for in-flight operations. It uses ISS data to assist in planning for the Exploration Program and it is not intended to assist in post flight research. The IMM was used to update Probability Risk Assessment (PRA) for the purpose of updating forecasts for the conditions requiring evacuation (EVAC) or Loss of Crew Life (LOC) for the ISS. The IMM validation approach includes comparison with actual events and involves both qualitative and quantitaive approaches. The results of these comparisons are reviewed. Another use of the IMM is to optimize the medical kits taking into consideration the specific mission and the crew profile. An example of the use of the IMM to optimize the medical kits is reviewed.

Optimal power flow by particle swarm optimization with an aging ...

African Journals Online (AJOL)

In this paper, a particle swarm optimization (PSO) with an aging leader and challengers (ALC-PSO) is applied for the solution of OPF problem of power system. This study is implemented on modified IEEE 30-bus test power system with different objectives that reflect minimization of either fuel cost or active power loss or sum ...

ANALYTICAL CALCULATION OF THE BASIC ELECTROMAGNETIC LOSSES OF THE ENERGY OF THE FREQUENCY-REGULATED ASYNCHRONOUS ENGINE IN POSITIONING

Directory of Open Access Journals (Sweden)

V. O. Volkov

2018-02-01

Full Text Available Purpose. Obtaining analytical dependencies for the calculation of the main electromagnetic energy losses of a frequency-controlled induction motor in positioning modes with small displacements for various types (linear, parabolic and quasi-optimal of its velocity variation. Methodology. Similarity methods, differential and integral calculus, analytical interpolation, mathematical analysis. Findings. Analytical dependencies for calculation of current electromagnetic power losses and basic electromagnetic energy losses of a frequency-controlled asynchronous motor in the modes of positioning with small displacements for various types (linear, parabolic and quasi-optimal of its velocity are obtained. A universal form of the analytical dependence for calculating the optimal acceleration and deceleration times for a frequency-controlled asynchronous motor for positioning with small displacements, corresponding to minimization of the main electromagnetic energy losses of this engine with the indicated positioning for various species (linear, parabolic and quasi-optimal, is obtained. A comparative quantitative assessment of the change is made: the optimum values of the main electromagnetic energy losses of the frequency-controlled asynchronous engine and the corresponding maximum speed and optimal acceleration and deceleration times, in the function of the set prescribed small displacements for the various engine speed trajectories under consideration. Originality. For the first time, analytical dependencies for the calculation of the main electromagnetic energy losses of a frequency-controlled asynchronous motor are obtained for positioning with small displacements as a function of the set values of the movement of the motor shaft and the set values of its acceleration and deceleration times for the specified specified displacements. For the first time, dependences are obtained for a quantitative estimate of the minimum fundamental electromagnetic

Optimization of TTEthernet Networks to Support Best-Effort Traffic

DEFF Research Database (Denmark)

Tamas-Selicean, Domitian; Pop, Paul

2014-01-01

This paper focuses on the optimization of the TTEthernet communication protocol, which offers three traffic classes: time-triggered (TT), sent according to static schedules, rate-constrained (RC) that has bounded end-to-end latency, and best-effort (BE), the classic Ethernet traffic, with no timing...... guarantees. In our earlier work we have proposed an optimization approach named DOTTS that performs the routing, scheduling and packing / fragmenting of TT and RC messages, such that the TT and RC traffic is schedulable. Although backwards compatibility with classic Ethernet networks is one of TTEthernet...

Optimal learning with Bernstein online aggregation

DEFF Research Database (Denmark)

Wintenberger, Olivier

2017-01-01

batch version achieves the fast rate of convergence log (M) / n in deviation. The BOA procedure is the first online algorithm that satisfies this optimal fast rate. The second order refinement is required to achieve the optimality in deviation as the classical exponential weights cannot be optimal, see...... is shown to be sufficiently small to assert the fast rate in the iid setting when the loss is Lipschitz and strongly convex. We also introduce a multiple learning rates version of BOA. This fully adaptive BOA procedure is also optimal, up to a log log (n) factor....

Reduction of fatigue loads on jacket substructure through blade design optimization for multimegawatt wind turbines at 50 m water depths

DEFF Research Database (Denmark)

NJOMO WANDJI, Wilfried; Pavese, Christian; Natarajan, Anand

2016-01-01

This paper addresses the reduction of the fore-aft damage equivalent moment at the tower base for multi-megawatt offshore wind turbines mounted on jacket type substructures at 50 m water depths. The study investigates blade design optimization of a reference 10 MW wind turbine under standard wind...... conditions of onshore sites. The blade geometry and structure is optimized to yield a design that minimizes tower base fatigue loads without significant loss of power production compared to that of the reference setup. The resulting blade design is then mounted on a turbine supported by a jacket and placed...

Optimization as investment decision support in a Swedish medium-sized iron foundry - A move beyond traditional energy auditing

International Nuclear Information System (INIS)

Thollander, Patrik; Mardan, Nawzad; Karlsson, Magnus

2009-01-01

Due to increased globalisation, industries are facing greater competition that is pressing companies into decreasing their expenses in order to increase their profits. As regards Swedish industry, it has been faced with substantial increases in energy prices in recent years. Barriers to energy efficiency such as imperfect information inhibit investments in energy efficiency measures, energy audits being one means of reducing barriers and overcoming imperfect information. However, an evaluation of such energy audits in Sweden reveals that it is chiefly low-cost measures that are undertaken as a result of an audit. Moreover, these audits often tend to focus on support processes such as ventilation, lighting, air compressors etc., while measures impacting production processes are often not as extensively covered, which underlines the need for further support in addition to energy audits. Decision support is practised in a variety of different disciplines such as optimization and simulation and the aim of this paper is to explore whether investment decision support practices may be used successfully towards small and medium-sized manufacturers in Sweden when complex production-related investment decisions are taken. The optimization results from the different cases, involving a foundry's investment in a new melting unit, indicate that with no electricity price fluctuations over the day, the investment seems sound as it lowers the overall energy costs. However, with fluctuating electricity prices, there are no large differences in energy costs between the option of retaining the existing five melting furnaces at the foundry and investing in a twin furnace and removing the holding furnaces - which was the initial investment plan for the foundry in the study. It would not have been possible to achieve this outcome without the use of investment decision support such as MIND. One of the main conclusions in this paper is that investment decision support, when strategic

Optimization and approximation

CERN Document Server

Pedregal, Pablo

2017-01-01

This book provides a basic, initial resource, introducing science and engineering students to the field of optimization. It covers three main areas: mathematical programming, calculus of variations and optimal control, highlighting the ideas and concepts and offering insights into the importance of optimality conditions in each area. It also systematically presents affordable approximation methods. Exercises at various levels have been included to support the learning process.

Mitigation of numerical noise for beam loss simulations

CERN Document Server

Kesting, Frederik

2017-01-01

Numerical noise emerges in self-consistent simulations of charged particles, and its mitigation is investigated since the first numerical studies in plasma physics. In accelerator physics, recent studies find an artificial diffusion of the particle beam due to numerical noise in particle-in-cell tracking, which is of particular importance for high intensity machines with a long storage time, as the SIS100 at FAIR or in context of the LIU upgrade at CERN. In beam loss simulations for these projects artificial effects must be distinguished from physical beam loss. Therefore, it is important to relate artificial diffusion to artificial beam loss, and to choose simulation parameters such that physical beam loss is well resolved. As a practical tool, we therefore suggest a scaling law to find optimal simulation parameters for a given maximum percentage of acceptable artificial beam loss.

Modeling and optimization of proton-conducting solid oxide electrolysis cell: Conversion of CO2 into value-added products

Science.gov (United States)

Namwong, Lawit; Authayanun, Suthida; Saebea, Dang; Patcharavorachot, Yaneeporn; Arpornwichanop, Amornchai

2016-11-01

Proton-conducting solid oxide electrolysis cells (SOEC-H+) are a promising technology that can utilize carbon dioxide to produce syngas. In this work, a detailed electrochemical model was developed to predict the behavior of SOEC-H+ and to prove the assumption that the syngas is produced through a reversible water gas-shift (RWGS) reaction. The simulation results obtained from the model, which took into account all of the cell voltage losses (i.e., ohmic, activation, and concentration losses), were validated using experimental data to evaluate the unknown parameters. The developed model was employed to examine the structural and operational parameters. It is found that the cathode-supported SOEC-H+ is the best configuration because it requires the lowest cell potential. SOEC-H+ operated favorably at high temperatures and low pressures. Furthermore, the simulation results revealed that the optimal S/C molar ratio for syngas production, which can be used for methanol synthesis, is approximately 3.9 (at a constant temperature and pressure). The SOEC-H+ was optimized using a response surface methodology, which was used to determine the optimal operating conditions to minimize the cell potential and maximize the carbon dioxide flow rate.

Resource Loss and Gain, Life Satisfaction, and Health Among Retirees in Spain.

Science.gov (United States)

Topa, Gabriela; Jiménez, Irene; Valero, Encarna; Ovejero, Anastasio

2017-04-01

This article focuses on retirement transition from the Conservation of Resources (COR) perspective to better understand how aged participants' perceptions of retirement losses and gains significantly explain retirement well-being. In this article, the mediation of social support in the losses-well-being relationship is explored. The study was conducted with a two-wave longitudinal design. Participants at T1 were aged Spanish workers (>64 years) and at T2 were retirees, with a final sample of 275, who had retired during the previous 6 months. Findings supported the assertion that losses better explain well-being than gains. In addition, specific losses revealed a higher explaining power of life satisfaction and health complaints depending on their content. Social support mediated between perceived losses and well-being. This study suggests that both perceived losses and gains associated with retirement and social support during retirement should be taken into account when addressing postretirement well-being.

Ultra-low loss nano-taper coupler for Silicon-on-Insulator ridge waveguide

DEFF Research Database (Denmark)

Pu, Minhao; Liu, Liu; Ou, Haiyan

2010-01-01

A nano-taper coupler is optimized specially for the transverse-magnetic mode for interfacing light between a silicon-on-insulator ridge waveguide and a single-mode fiber. An ultra-low coupling loss of ~0.36dB is achieved for the nano-taper coupler.......A nano-taper coupler is optimized specially for the transverse-magnetic mode for interfacing light between a silicon-on-insulator ridge waveguide and a single-mode fiber. An ultra-low coupling loss of ~0.36dB is achieved for the nano-taper coupler....

Optimism in prolonged grief and depression following loss : A three-wave longitudinal study

NARCIS (Netherlands)

Boelen, Paul A

2015-01-01

There is considerable evidence that optimism, the predisposition to have generalized favorable expectancies for the future, is associated with numerous desirable outcomes. Few studies have examined the association of optimism with emotional distress following the death of a loved one. Doing so is

The influence of optimism, social support and anxiety on aggression in a sample of dermatology patients: an analysis of cross-sectional data.

Science.gov (United States)

Coneo, A M C; Thompson, A R; Lavda, A

2017-05-01

Individuals with visible skin conditions often experience stigmatization and discrimination. This may trigger maladaptive responses such as feelings of anger and hostility, with negative consequences to social interactions and relationships. To identify psychosocial factors contributing to aggression levels in dermatology patients. Data were obtained from 91 participants recruited from outpatient clinics in the north of England, U.K. This study used dermatology-specific data extracted from a large U.K. database of medical conditions collected by The Appearance Research Collaboration. This study looked at the impact of optimism, perceptions of social support and social acceptance, fear of negative evaluation, appearance concern, appearance discrepancy, social comparison and well-being on aggression levels in a sample of dermatology patients. In order to assess the relationship between variables, a hierarchical regression analysis was performed. Dispositional style (optimism) was shown to have a strong negative relationship with aggression (β = -0·37, t = -2·97, P = 0·004). Higher levels of perceived social support were significantly associated with lower levels of aggression (β = -0·26, t = -2·26, P = 0·02). Anxiety was also found to have a significant positive relationship with aggression (β = 0·36, t = 2·56, P = 0·01). This study provides evidence for the importance of perceived social support and optimism in psychological adjustment to skin conditions. Psychosocial interventions provided to dermatology patients might need to address aggression levels and seek to enhance social support and the ability to be optimistic. © 2016 British Association of Dermatologists.

Effect of different economic support policies on the optimal synthesis and operation of a distributed energy supply system with renewable energy sources for an industrial area

International Nuclear Information System (INIS)

Casisi, Melchiorre; De Nardi, Alberto; Pinamonti, Piero; Reini, Mauro

2015-01-01

Highlights: • MILP model optimization identifies best structure and operation of an energy system. • Total cost of the system is minimized according to industrial stakeholders wills. • Effects of the adoption of economic support policies on the system are evaluated. • Social cost of incentives is comparted with correspondent CO 2 emission reduction. • Support schemes that promote an actual environmental benefit are highlighted. - Abstract: Economic support policies are widely adopted in European countries in order to promote a more efficient energy usage and the growth of renewable energy technologies. On one hand these schemes allow us to reduce the overall pollutant emissions and the total cost from the point of view of the energy systems, but on the other hand their social impact in terms of economic investment needs to be evaluated. The aim of this paper is to compare the social cost of the application of each incentive with the correspondent CO 2 emission reduction and overall energy saving. A Mixed Integer Linear Programming optimization procedure is used to evaluate the effect of different economic support policies on the optimal configuration and operation of a distributed energy supply system of an industrial area located in the north-east of Italy. The minimized objective function is the total annual cost for owning, operating and maintaining the whole energy system. The expectation is that a proper mix of renewable energy technologies and cogeneration systems will be included in the optimal solution, depending on the amount and nature of the supporting policies, highlighting the incentives that promote a real environmental benefit

Sleep As A Strategy For Optimizing Performance.

Science.gov (United States)

Yarnell, Angela M; Deuster, Patricia

2016-01-01

Recovery is an essential component of maintaining, sustaining, and optimizing cognitive and physical performance during and after demanding training and strenuous missions. Getting sufficient amounts of rest and sleep is key to recovery. This article focuses on sleep and discusses (1) why getting sufficient sleep is important, (2) how to optimize sleep, and (3) tools available to help maximize sleep-related performance. Insufficient sleep negatively impacts safety and readiness through reduced cognitive function, more accidents, and increased military friendly-fire incidents. Sufficient sleep is linked to better cognitive performance outcomes, increased vigor, and better physical and athletic performance as well as improved emotional and social functioning. Because Special Operations missions do not always allow for optimal rest or sleep, the impact of reduced rest and sleep on readiness and mission success should be minimized through appropriate preparation and planning. Preparation includes periods of "banking" or extending sleep opportunities before periods of loss, monitoring sleep by using tools like actigraphy to measure sleep and activity, assessing mental effectiveness, exploiting strategic sleep opportunities, and consuming caffeine at recommended doses to reduce fatigue during periods of loss. Together, these efforts may decrease the impact of sleep loss on mission and performance. 2016.

Dielectric loss of strontium titanate thin films

Science.gov (United States)

Dalberth, Mark Joseph

1999-12-01

Interest in strontium titanate (STO) thin films for microwave device applications continues to grow, fueled by the telecommunications industry's interest in phase shifters and tunable filters. The optimization of these devices depends upon increasing the phase or frequency tuning and decreasing the losses in the films. Currently, the dielectric response of thin film STO is poorly understood through lack of data and a theory to describe it. We have studied the growth of STO using pulsed laser deposition and single crystal substrates like lanthanum aluminate and neodymium gallate. We have researched ways to use ring resonators to accurately measure the dielectric response as a function of temperature, electric field, and frequency from low radio frequencies to a few gigahertz. Our films grown on lanthanum aluminate show marked frequency dispersion in the real part of the dielectric constant and hints of thermally activated loss behavior. We also found that films grown with conditions that optimized the dielectric constant showed increased losses. In an attempt to simplify the system, we developed a technique called epitaxial lift off, which has allowed us to study films removed from their growth substrates. These free standing films have low losses and show obvious thermally activated behavior. The "amount of tuning," as measured by a figure of merit, KE, is greater in these films than in the films still attached to their growth substrates. We have developed a theory that describes the real and imaginary parts of the dielectric constant. The theory models the real part using a mean field description of the ionic motion in the crystal and includes the loss by incorporating the motion of charged defects in the films.

Reliability-Based Optimal Design for Very Large Floating Structure

Institute of Scientific and Technical Information of China (English)

ZHANG Shu-hua(张淑华); FUJIKUBO Masahiko

2003-01-01

Costs and losses induced by possible future extreme environmental conditions and difficulties in repairing post-yielding damage strongly suggest the need for proper consideration in design rather than just life loss prevention. This can be addressed through the development of design methodology that balances the initial cost of the very large floating structure (VLFS) against the expected potential losses resulting from future extreme wave-induced structural damage. Here, the development of a methodology for determining optimal, cost-effective design will be presented and applied to a VLFS located in the Tokyo bay. Optimal design criteria are determined based on the total expected life-cycle cost and acceptable damage probability and curvature of the structure, and a set of sizes of the structure are obtained. The methodology and applications require expressions of the initial cost and the expected life-cycle damage cost as functions of the optimal design variables. This study includes the methodology, total life-cycle cost function, structural damage modeling, and reliability analysis.

Theoretical proposal of a low-loss wide-bandwidth silicon photonic crystal fiber for supporting 30 orbital angular momentum modes.

Directory of Open Access Journals (Sweden)

Xun Xu

Full Text Available We propose a novel four-ring hollow-core silicon photonic crystal fiber (PCF, and we systematically and theoretically investigate the properties of their vector modes. Our PCF can stably support 30 OAM states from the wavelength of 1.5 μm to 2.4 μm, with a large effective refractive index separation of above 1×10-4. The confinement loss is less than 1×10-9 dB/m at the wavelength of 1.55 μm, and the average confinement loss is less than 1×10-8 dB/m from the wavelength of 1.2 μm to 2.4 μm. Moreover, the curve of the dispersion tends to flatten as the wavelength increases. In addition, we comparably investigate PCFs with different hole spacing. This kind of fiber structure will be a potential candidate for high-capacity optical fiber communications and OAM sensing applications using fibers.

Pythran: enabling static optimization of scientific Python programs

Science.gov (United States)

Guelton, Serge; Brunet, Pierrick; Amini, Mehdi; Merlini, Adrien; Corbillon, Xavier; Raynaud, Alan

2015-01-01

Pythran is an open source static compiler that turns modules written in a subset of Python language into native ones. Assuming that scientific modules do not rely much on the dynamic features of the language, it trades them for powerful, possibly inter-procedural, optimizations. These optimizations include detection of pure functions, temporary allocation removal, constant folding, Numpy ufunc fusion and parallelization, explicit thread-level parallelism through OpenMP annotations, false variable polymorphism pruning, and automatic vector instruction generation such as AVX or SSE. In addition to these compilation steps, Pythran provides a C++ runtime library that leverages the C++ STL to provide generic containers, and the Numeric Template Toolbox for Numpy support. It takes advantage of modern C++11 features such as variadic templates, type inference, move semantics and perfect forwarding, as well as classical idioms such as expression templates. Unlike the Cython approach, Pythran input code remains compatible with the Python interpreter. Output code is generally as efficient as the annotated Cython equivalent, if not more, but without the backward compatibility loss.

Identifying the optimal supply temperature in district heating networks - A modelling approach

DEFF Research Database (Denmark)

Mohammadi, Soma; Bojesen, Carsten

2014-01-01

of this study is to develop a model for thermo-hydraulic calculation of low temperature DH system. The modelling is performed with emphasis on transient heat transfer in pipe networks. The pseudo-dynamic approach is adopted to model the District Heating Network [DHN] behaviour which estimates the temperature...... dynamically while the flow and pressure are calculated on the basis of steady state conditions. The implicit finite element method is applied to simulate the transient temperature behaviour in the network. Pipe network heat losses, pressure drop in the network and return temperature to the plant...... are calculated in the developed model. The model will serve eventually as a basis to find out the optimal supply temperature in an existing DHN in later work. The modelling results are used as decision support for existing DHN; proposing possible modifications to operate at optimal supply temperature....

Enhanced Co-Worker Social Support in Isolated Work Groups and Its Mitigating Role on the Work-Family Conflict-Depression Loss Spiral

Directory of Open Access Journals (Sweden)

Wesley P. McTernan

2016-03-01

Full Text Available This paper examines a loss spiral model (i.e., reciprocal relationships between work-family conflict and depression, moderated by co-worker support. We expected that the moderation effect due to co-worker support would be evident among those working in isolation (i.e., mining workers due to a greater level of intragroup attraction and saliency attributable to the proximity effects. We used a two wave panel study and data from a random population sample of Australian employees (n = 2793, [n = 112 mining, n = 2681 non-mining]. Using structural equation modelling we tested the reciprocal three way interaction effects. In line with our theory, co-worker support buffered the reciprocal relationship between WFC and depression, showing a protective effect in both pathways. These moderation effects were found in the mining industry only suggesting a proximity component moderates the social support buffer hypothesis (i.e., a three way interaction effect. The present paper integrates previous theoretical perspectives of stress and support, and provides insight into the changing dynamics of workplace relationships.

Enhanced Co-Worker Social Support in Isolated Work Groups and Its Mitigating Role on the Work-Family Conflict-Depression Loss Spiral.

Science.gov (United States)

McTernan, Wesley P; Dollard, Maureen F; Tuckey, Michelle R; Vandenberg, Robert J

2016-03-29

This paper examines a loss spiral model (i.e., reciprocal relationships) between work-family conflict and depression, moderated by co-worker support. We expected that the moderation effect due to co-worker support would be evident among those working in isolation (i.e., mining workers) due to a greater level of intragroup attraction and saliency attributable to the proximity effects. We used a two wave panel study and data from a random population sample of Australian employees (n = 2793, [n = 112 mining, n = 2681 non-mining]). Using structural equation modelling we tested the reciprocal three way interaction effects. In line with our theory, co-worker support buffered the reciprocal relationship between WFC and depression, showing a protective effect in both pathways. These moderation effects were found in the mining industry only suggesting a proximity component moderates the social support buffer hypothesis (i.e., a three way interaction effect). The present paper integrates previous theoretical perspectives of stress and support, and provides insight into the changing dynamics of workplace relationships.

Individual Differences in Loss Aversion: Conscientiousness Predicts How Life Satisfaction Responds to Losses Versus Gains in Income.

Science.gov (United States)

Boyce, Christopher J; Wood, Alex M; Ferguson, Eamonn

2016-04-01

Loss aversion is considered a general pervasive bias occurring regardless of the context or the person making the decision. We hypothesized that conscientiousness would predict an aversion to losses in the financial domain. We index loss aversion by the relative impact of income losses and gains on life satisfaction. In a representative German sample (N = 105,558; replicated in a British sample, N = 33,848), with conscientiousness measured at baseline, those high on conscientiousness have the strongest reactions to income losses, suggesting a pronounced loss aversion effect, whereas for those moderately unconscientious, there is no loss aversion effect. Our research (a) provides the first evidence of personality moderation of any loss aversion phenomena, (b) supports contextual perspectives that both personality and situational factors need to be examined in combination, (c) shows that the small but robust relationship between income and life satisfaction is driven primarily by a subset of people experiencing highly impactful losses. © 2016 by the Society for Personality and Social Psychology, Inc.

Application of support vector regression for optimization of vibration flow field of high-density polyethylene melts characterized by small angle light scattering

Science.gov (United States)

Xian, Guangming

2018-03-01

In this paper, the vibration flow field parameters of polymer melts in a visual slit die are optimized by using intelligent algorithm. Experimental small angle light scattering (SALS) patterns are shown to characterize the processing process. In order to capture the scattered light, a polarizer and an analyzer are placed before and after the polymer melts. The results reported in this study are obtained using high-density polyethylene (HDPE) with rotation speed at 28 rpm. In addition, support vector regression (SVR) analytical method is introduced for optimization the parameters of vibration flow field. This work establishes the general applicability of SVR for predicting the optimal parameters of vibration flow field.

Full body photography in the massive weight loss population: an inquiry to optimize patient-centered care.

Science.gov (United States)

Wasicek, Philip; Kaswan, Sumesh; Messing, Susan; Gusenoff, Jeffrey A

2013-11-01

Medical photography of body contouring patients often requires complete nudity, placing patients in a vulnerable situation. We investigated patient perspectives on full body photography in an effort to better protect the patients and enhance comfort with the photography process. Sixty-five massive weight loss patients were identified who underwent body contouring surgery with full body photography. Photographs were taken at the time of initial consult, time of marking, and postoperatively. A retrospective chart review was performed to assess body mass indices and comorbidities, and a telephone survey inquired about several aspects of the photographic process. Fifty-six (86%) patients participated. Patients were more comfortable at the time of markings (P = 0.0004) and at the postoperative session (P = 0.0009). Patients' perception of positive body image increased after body contouring surgery (P photography improves quickly as they move through the surgical process. Maintaining professionalism is the most important factor in achieving patient trust and comfort. Limiting the number of observers in the room, providing explicit details of the photography process, and having at least 1 person of the same sex in the room can optimize patient safety and comfort.

Optimal Allocation of Power-Electronic Interfaced Wind Turbines Using a Genetic Algorithm - Monte Carlo Hybrid Optimization Method

DEFF Research Database (Denmark)

Chen, Peiyuan; Siano, Pierluigi; Chen, Zhe

2010-01-01

determined by the wind resource and geographic conditions, the location of wind turbines in a power system network may significantly affect the distribution of power flow, power losses, etc. Furthermore, modern WTs with power-electronic interface have the capability of controlling reactive power output...... limit requirements. The method combines the Genetic Algorithm (GA), gradient-based constrained nonlinear optimization algorithm and sequential Monte Carlo simulation (MCS). The GA searches for the optimal locations and capacities of WTs. The gradient-based optimization finds the optimal power factor...... setting of WTs. The sequential MCS takes into account the stochastic behaviour of wind power generation and load. The proposed hybrid optimization method is demonstrated on an 11 kV 69-bus distribution system....

Joint-layer encoder optimization for HEVC scalable extensions

Science.gov (United States)

Tsai, Chia-Ming; He, Yuwen; Dong, Jie; Ye, Yan; Xiu, Xiaoyu; He, Yong

2014-09-01

Scalable video coding provides an efficient solution to support video playback on heterogeneous devices with various channel conditions in heterogeneous networks. SHVC is the latest scalable video coding standard based on the HEVC standard. To improve enhancement layer coding efficiency, inter-layer prediction including texture and motion information generated from the base layer is used for enhancement layer coding. However, the overall performance of the SHVC reference encoder is not fully optimized because rate-distortion optimization (RDO) processes in the base and enhancement layers are independently considered. It is difficult to directly extend the existing joint-layer optimization methods to SHVC due to the complicated coding tree block splitting decisions and in-loop filtering process (e.g., deblocking and sample adaptive offset (SAO) filtering) in HEVC. To solve those problems, a joint-layer optimization method is proposed by adjusting the quantization parameter (QP) to optimally allocate the bit resource between layers. Furthermore, to make more proper resource allocation, the proposed method also considers the viewing probability of base and enhancement layers according to packet loss rate. Based on the viewing probability, a novel joint-layer RD cost function is proposed for joint-layer RDO encoding. The QP values of those coding tree units (CTUs) belonging to lower layers referenced by higher layers are decreased accordingly, and the QP values of those remaining CTUs are increased to keep total bits unchanged. Finally the QP values with minimal joint-layer RD cost are selected to match the viewing probability. The proposed method was applied to the third temporal level (TL-3) pictures in the Random Access configuration. Simulation results demonstrate that the proposed joint-layer optimization method can improve coding performance by 1.3% for these TL-3 pictures compared to the SHVC reference encoder without joint-layer optimization.

Annual Electric Load Forecasting by a Least Squares Support Vector Machine with a Fruit Fly Optimization Algorithm

Directory of Open Access Journals (Sweden)

Bao Wang

2012-11-01

Full Text Available The accuracy of annual electric load forecasting plays an important role in the economic and social benefits of electric power systems. The least squares support vector machine (LSSVM has been proven to offer strong potential in forecasting issues, particularly by employing an appropriate meta-heuristic algorithm to determine the values of its two parameters. However, these meta-heuristic algorithms have the drawbacks of being hard to understand and reaching the global optimal solution slowly. As a novel meta-heuristic and evolutionary algorithm, the fruit fly optimization algorithm (FOA has the advantages of being easy to understand and fast convergence to the global optimal solution. Therefore, to improve the forecasting performance, this paper proposes a LSSVM-based annual electric load forecasting model that uses FOA to automatically determine the appropriate values of the two parameters for the LSSVM model. By taking the annual electricity consumption of China as an instance, the computational result shows that the LSSVM combined with FOA (LSSVM-FOA outperforms other alternative methods, namely single LSSVM, LSSVM combined with coupled simulated annealing algorithm (LSSVM-CSA, generalized regression neural network (GRNN and regression model.

Incorporation of β-glucans in meat emulsions through an optimal mixture modeling systems.

Science.gov (United States)

Vasquez Mejia, Sandra M; de Francisco, Alicia; Manique Barreto, Pedro L; Damian, César; Zibetti, Andre Wüst; Mahecha, Hector Suárez; Bohrer, Benjamin M

2018-05-22

The effects of β-glucans (βG) in beef emulsions with carrageenan and starch were evaluated using an optimal mixture modeling system. The best mathematical models to describe the cooking loss, color, and textural profile analysis (TPA) were selected and optimized. The cubic models were better to describe the cooking loss, color, and TPA parameters, with the exception of springiness. Emulsions with greater levels of βG and starch had less cooking loss (54 and <62), and greater hardness, cohesiveness and springiness values. Subsequently, during the optimization phase, the use of carrageenan was eliminated. The optimized emulsion contained 3.13 ± 0.11% βG, which could cover the intake daily of βG recommendations. However, the hardness of the optimized emulsion was greater (60,224 ± 1025 N) than expected. The optimized emulsion had a homogeneous structure and normal thermal behavior by DSC and allowed for the manufacture of products with high amounts of βG and desired functional attributes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimization of mobile IPv6-based handovers to support VoIP services in wireless heterogeneous networks

DEFF Research Database (Denmark)

Fathi, Hanane; Chakraborty, Shyam; Prasad, Ramjee

2007-01-01

The support of the voice over Internet Protocol (VoIP) services in next-generation wireless systems requires the coupling of mobility with quality of service. The mobile node can experience disruptions or even intermittent disconnections of an ongoing real-time session due to handovers. The durat......The support of the voice over Internet Protocol (VoIP) services in next-generation wireless systems requires the coupling of mobility with quality of service. The mobile node can experience disruptions or even intermittent disconnections of an ongoing real-time session due to handovers...... at layer 3. Using analytical models, the authors evaluate MIPv4, MIPv6, fast MIPv6 (FMIPv6), and hierarchical MIPv6 (HMIPv6) and compare their performances in terms of handover delay for VoIP services. To optimize the handover delay, the authors propose to use the adaptive retransmission timer described...

Product demand forecasts using wavelet kernel support vector machine and particle swarm optimization in manufacture system

Science.gov (United States)

Wu, Qi

2010-03-01

Demand forecasts play a crucial role in supply chain management. The future demand for a certain product is the basis for the respective replenishment systems. Aiming at demand series with small samples, seasonal character, nonlinearity, randomicity and fuzziness, the existing support vector kernel does not approach the random curve of the sales time series in the space (quadratic continuous integral space). In this paper, we present a hybrid intelligent system combining the wavelet kernel support vector machine and particle swarm optimization for demand forecasting. The results of application in car sale series forecasting show that the forecasting approach based on the hybrid PSOWv-SVM model is effective and feasible, the comparison between the method proposed in this paper and other ones is also given, which proves that this method is, for the discussed example, better than hybrid PSOv-SVM and other traditional methods.

Distribution Loss Reduction by Household Consumption Coordination in Smart Grids

DEFF Research Database (Denmark)

Juelsgaard, Morten; Andersen, Palle; Wisniewski, Rafal

2014-01-01

for coordinating consumption of electrical energy within the community, with the purpose of reducing grid loading and active power losses. For this we present a simplified model of the electrical grid, including system losses and capacity constraints. Coordination is performed in a distributed fashion, where each...... are obeyed. These objectives are enforced by coordinating consumers through a nonlinear penalty on power consumption. We present simulation test-cases, illustrating that significant reduction of active losses, can be obtained by such coordination. The distributed optimization algorithm employs...

Taxable and Tax-deferred Investing with the Limited Use of Losses

DEFF Research Database (Denmark)

Fischer, Marcel; Gallmeyer, Michael

2017-01-01

We study the impact of the different tax treatment of capital gains and losses on the optimal location of assets in taxable and tax-deferred accounts. The classical result of Black (1980) and Tepper (1981) suggests that investors should follow a strict pecking order asset location rule and hold...... those assets that are subject to the highest tax rate preferentially in tax-deferred accounts. We show that with the different tax treatment of realized gains and losses, only tax-efficient equity mutual funds are optimally held in taxable accounts, whereas mutual funds with average tax......-(in)efficiency are preferentially held in tax-deferred accounts....

Contingency Contractor Optimization Phase 3 Sustainment Software Design Document - Contingency Contractor Optimization Tool - Prototype

Energy Technology Data Exchange (ETDEWEB)

Durfee, Justin David; Frazier, Christopher Rawls; Bandlow, Alisa; Jones, Katherine A

2016-05-01

This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATL Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.

Exergy Losses in the Szewalski Binary Vapor Cycle

Directory of Open Access Journals (Sweden)

Tomasz Kowalczyk

2015-10-01

Full Text Available In this publication, we present an energy and exergy analysis of the Szewalski binary vapor cycle based on a model of a supercritical steam power plant. We used energy analysis to conduct a preliminary optimization of the cycle. Exergy loss analysis was employed to perform a comparison of heat-transfer processes, which are essential for hierarchical cycles. The Szewalski binary vapor cycle consists of a steam cycle bottomed with an organic Rankine cycle installation. This coupling has a negative influence on the thermal efficiency of the cycle. However, the primary aim of this modification is to reduce the size of the power unit by decreasing the low-pressure steam turbine cylinder and the steam condenser. The reduction of the “cold end” of the turbine is desirable from economic and technical standpoints. We present the Szewalski binary vapor cycle in addition to a mathematical model of the chosen power plant’s thermodynamic cycle. We elaborate on the procedure of the Szewalski cycle design and its optimization in order to attain an optimal size reduction of the power unit and limit exergy loss.

Forecasting of Power Grid Investment in China Based on Support Vector Machine Optimized by Differential Evolution Algorithm and Grey Wolf Optimization Algorithm

Directory of Open Access Journals (Sweden)

Shuyu Dai

2018-04-01

Full Text Available In recent years, the construction of China’s power grid has experienced rapid development, and its scale has leaped into the first place in the world. Accurate and effective prediction of power grid investment can not only help pool funds and rationally arrange investment in power grid construction, but also reduce capital costs and economic risks, which plays a crucial role in promoting power grid investment planning and construction process. In order to forecast the power grid investment of China accurately, firstly on the basis of analyzing the influencing factors of power grid investment, the influencing factors system for China’s power grid investment forecasting is constructed in this article. The method of grey relational analysis is used for screening the main influencing factors as the prediction model input. Then, a novel power grid investment prediction model based on DE-GWO-SVM (support vector machine optimized by differential evolution and grey wolf optimization algorithm is proposed. Next, two cases are taken for empirical analysis to prove that the DE-GWO-SVM model has strong generalization capacity and has achieved a good prediction effect for power grid investment forecasting in China. Finally, the DE-GWO-SVM model is adopted to forecast power grid investment in China from 2018 to 2022.

Modeling and Compensation of Random Drift of MEMS Gyroscopes Based on Least Squares Support Vector Machine Optimized by Chaotic Particle Swarm Optimization.

Science.gov (United States)

Xing, Haifeng; Hou, Bo; Lin, Zhihui; Guo, Meifeng

2017-10-13

MEMS (Micro Electro Mechanical System) gyroscopes have been widely applied to various fields, but MEMS gyroscope random drift has nonlinear and non-stationary characteristics. It has attracted much attention to model and compensate the random drift because it can improve the precision of inertial devices. This paper has proposed to use wavelet filtering to reduce noise in the original data of MEMS gyroscopes, then reconstruct the random drift data with PSR (phase space reconstruction), and establish the model for the reconstructed data by LSSVM (least squares support vector machine), of which the parameters were optimized using CPSO (chaotic particle swarm optimization). Comparing the effect of modeling the MEMS gyroscope random drift with BP-ANN (back propagation artificial neural network) and the proposed method, the results showed that the latter had a better prediction accuracy. Using the compensation of three groups of MEMS gyroscope random drift data, the standard deviation of three groups of experimental data dropped from 0.00354°/s, 0.00412°/s, and 0.00328°/s to 0.00065°/s, 0.00072°/s and 0.00061°/s, respectively, which demonstrated that the proposed method can reduce the influence of MEMS gyroscope random drift and verified the effectiveness of this method for modeling MEMS gyroscope random drift.

Analysis of the internal heat losses in a thermoelectric generator

DEFF Research Database (Denmark)

Bjørk, Rasmus; Christensen, Dennis Valbjørn; Eriksen, Dan

2014-01-01

and radiative heat losses, including surface to surface radiation. For radiative heat losses it is shown that for the temperatures considered here, surface to ambient radiation is a good approximation of the heat loss. For conductive heat transfer the module efficiency is shown to be comparable to the case...... of radiative losses. Finally, heat losses due to internal natural convection in the module is shown to be negligible for the millimetre sized modules considered here. The combined case of radiative and conductive heat transfer resulted in the lowest efficiency. The optimized load resistance is found...... to decrease for increased heat loss. The leg dimensions are varied for all heat losses cases and it is shown that the ideal way to construct a TEG module with minimal heat losses and maximum efficiency is to either use a good insulating material between the legs or evacuate the module completely, and use...

Optimal Control of Wind Farms for Coordinated TSO-DSO Reactive Power Management

Directory of Open Access Journals (Sweden)

David Sebastian Stock

2018-01-01

Full Text Available The growing importance of renewable generation connected to distribution grids requires an increased coordination between transmission system operators (TSOs and distribution system operators (DSOs for reactive power management. This work proposes a practical and effective interaction method based on sequential optimizations to evaluate the reactive flexibility potential of distribution networks and to dispatch them along with traditional synchronous generators, keeping to a minimum the information exchange. A modular optimal power flow (OPF tool featuring multi-objective optimization is developed for this purpose. The proposed method is evaluated for a model of a real German 110 kV grid with 1.6 GW of installed wind power capacity and a reduced order model of the surrounding transmission system. Simulations show the benefit of involving wind farms in reactive power support reducing losses both at distribution and transmission level. Different types of setpoints are investigated, showing the feasibility for the DSO to fulfill also individual voltage and reactive power targets over multiple connection points. Finally, some suggestions are presented to achieve a fair coordination, combining both TSO and DSO requirements.

Can Sophie's choice be adequately captured by cold computation of minimizing losses? An fMRI study of vital loss decisions.

Directory of Open Access Journals (Sweden)

Qi Li

Full Text Available The vast majority of decision-making research is performed under the assumption of the value maximizing principle. This principle implies that when making decisions, individuals try to optimize outcomes on the basis of cold mathematical equations. However, decisions are emotion-laden rather than cool and analytic when they tap into life-threatening considerations. Using functional magnetic resonance imaging (fMRI, this study investigated the neural mechanisms underlying vital loss decisions. Participants were asked to make a forced choice between two losses across three conditions: both losses are trivial (trivial-trivial, both losses are vital (vital-vital, or one loss is trivial and the other is vital (vital-trivial. Our results revealed that the amygdala was more active and correlated positively with self-reported negative emotion associated with choice during vital-vital loss decisions, when compared to trivial-trivial loss decisions. The rostral anterior cingulate cortex was also more active and correlated positively with self-reported difficulty of choice during vital-vital loss decisions. Compared to the activity observed during trivial-trivial loss decisions, the orbitofrontal cortex and ventral striatum were more active and correlated positively with self-reported positive emotion of choice during vital-trivial loss decisions. Our findings suggest that vital loss decisions involve emotions and cannot be adequately captured by cold computation of minimizing losses. This research will shed light on how people make vital loss decisions.

Particle swarm optimization-based least squares support vector regression for critical heat flux prediction

International Nuclear Information System (INIS)

Jiang, B.T.; Zhao, F.Y.

2013-01-01

Highlights: ► CHF data are collected from the published literature. ► Less training data are used to train the LSSVR model. ► PSO is adopted to optimize the key parameters to improve the model precision. ► The reliability of LSSVR is proved through parametric trends analysis. - Abstract: In view of practical importance of critical heat flux (CHF) for design and safety of nuclear reactors, accurate prediction of CHF is of utmost significance. This paper presents a novel approach using least squares support vector regression (LSSVR) and particle swarm optimization (PSO) to predict CHF. Two available published datasets are used to train and test the proposed algorithm, in which PSO is employed to search for the best parameters involved in LSSVR model. The CHF values obtained by the LSSVR model are compared with the corresponding experimental values and those of a previous method, adaptive neuro fuzzy inference system (ANFIS). This comparison is also carried out in the investigation of parametric trends of CHF. It is found that the proposed method can achieve the desired performance and yields a more satisfactory fit with experimental results than ANFIS. Therefore, LSSVR method is likely to be suitable for other parameters processing such as CHF

Low-loss hollow-core silica fibers with adjacent nested anti-resonant tubes

DEFF Research Database (Denmark)

Habib, Selim; Bang, Ole; Bache, Morten

2015-01-01

We report on numerical design optimization of hollow-core antiresonant fibers with the aim of reducing transmission losses. We show that re-arranging the nested anti-resonant tubes in the cladding to be adjacent has the effect of significantly reducing leakage as well as bending losses, and for r...

EXPLOT - decision support system for optimization of oil exploitation; EXPLOT - sistema de apoio a decisao para a otimizacao da explotacao de petroleo

Energy Technology Data Exchange (ETDEWEB)

Tupac Valdivia, Yvan Jesus; Almeida, Luciana Faletti; Pacheco, Marco Aurelio Cavalcanti; Vellasco, Marley Maria Bernardes Rebuzzi [Pontificia Universidade Catolica do Rio de Janeiro (PUC-Rio), RJ (Brazil). Dept. de Engenharia Eletrica. Lab. de Inteligencia Computacional], e-mail: yvantv@ele.puc-rio.br, e-mail: faletti@ele.puc-rio.br, e-mail: marco@ele.puc-rio.br, e-mail: marley@ele.puc-rio.br

2007-06-15

The present work offers a decision supporting system, integrated in different techniques (genetic algorithms, cultural algorithms, co-evolution, neural networks, neuro fuzzy model and distributed processing) for optimization of exploitation of oil reservoirs. The EXPLOT system identifies exploitation alternatives and determines the quantity, position, type (producers or injectors) and structure (horizontal or vertical) of wells, that maximize the present net value of the alternative (VPL). The EXPLOT system is composed of three main modules: the optimizer (genetic algorithms, cultural algorithms and co-evolution), the Production Curves Obtention (approximator neuro fuzzy-NFHB of the production curve) and the present net value calculation. To estimate the VPL of each developmental alternative, the system utilizes a reservoir simulator, specifically the IMEX, although other simulators may be utilized. In addition to these technologies, the system also utilizes distributed processing, based on the CORBA architecture for distributed execution of the reservoir simulator in a computer network, which significantly reduces the total optimization time. The EXPLOT system was already tested in different examples of oil fields. Results obtained so far are considered consistent according to the opinion of specialists, who consider the system as a new decision support tool concept in the area. The differences of EXPLOT are not only to be found in its efficient optimization model, but also in its interface, through which the specialists interact with the system, introducing project recommendations (e.g., five-spot wells), commanding a localized search for best solutions, sizing the simulation network and monitoring simulation distribution by means of available networks. The EXPLOT system is the result of joint research between CENPES and the Applied Computational Intelligence Lab, PUC-Rio, accomplished during the past three years. The continuation of this research project expands

Systemic causes of hair loss.

Science.gov (United States)

Lin, Richard L; Garibyan, Lilit; Kimball, Alexandra B; Drake, Lynn A

2016-09-01

Hair loss is both a common chief complaint by patients and a clinical challenge for physicians, especially general practitioners, yet few dermatological problems yield as much patient satisfaction when resolved as hair loss. The diagnosis is often attributed to androgen-related hair loss, while other causes, some of which are life-threatening but treatable, are overlooked. We searched for relevant literature on hair loss and supported these findings with our clinical experience to identify seven major systemic etiologies of hair loss, ranging from infectious agents to consumption of unsafe supplements. Many causes are only described in the literature through case studies, though some original articles and meta-analyses are available. Careful history taking, proper examination techniques, and judicious use of laboratory tests are essential to reach at the correct diagnosis in a cost-effective manner when performing patient work-up. Such methodical evaluation of hair loss can result in the appropriate treatment plan and provide significant patient satisfaction. Key messages Hair loss is a common chief complaint and a difficult challenge for both general practitioners and dermatology consultants. We identified seven major categories of systemic hair loss etiology and present a framework for their clinical evaluation. A methodical approach to hair loss can result in the appropriate treatment plan and provide significant patient satisfaction.

Multi-objective optimization for the maximization of the operating share of cogeneration system in District Heating Network

International Nuclear Information System (INIS)

Franco, Alessandro; Versace, Michele

2017-01-01

Highlights: • Combined Heat and Power plants and civil/residential energy uses. • CHP plant supported by auxiliary boilers and thermal energy storage. • Definition of optimal operational strategies for cogeneration plants for District Heating. • Optimal-sized Thermal Energy Storage and a hybrid operational strategy. • Maximization of cogeneration share and reduction of time of operation of auxiliary boilers. - Abstract: The aim of the paper is to define optimal operational strategies for Combined Heat and Power plants connected to civil/residential District Heating Networks. The role of a reduced number of design variables, including a Thermal Energy Storage system and a hybrid operational strategy dependent on the storage level, is considered. The basic principle is to reach maximum efficiency of the system operation through the utilization of an optimal-sized Thermal Energy Storage. Objective functions of both energetic and combined energetic and economic can be considered. In particular, First and Second Law Efficiency, thermal losses of the storage, number of starts and stops of the combined heat and power unit are considered. Constraints are imposed to nullify the waste of heat and to operate the unit at its maximum efficiency for the highest possible number of consecutive operating hours, until the thermal tank cannot store more energy. The methodology is applied to a detailed case study: a medium size district heating system, in an urban context in the northern Italy, powered by a combined heat and power plant supported by conventional auxiliary boilers. The issues involving this type of thermal loads are also widely investigated in the paper. An increase of Second Law Efficiency of the system of 26% (from 0.35 to 0.44) can be evidenced, while the First Law Efficiency shifts from about 0.74 to 0.84. The optimization strategy permits of combining the economic benefit of cogeneration with the idea of reducing the energy waste and exergy losses.

Power loss analysis in altered tooth-sum spur gearing

Directory of Open Access Journals (Sweden)

Sachidananda H. K.

2018-01-01

Full Text Available The main cause of power loss or dissipation of heat in case of meshed gears is due to friction existing between gear tooth mesh and is a major concern in low rotational speed gears, whereas in case of high operating speed the power loss taking place due to compression of air-lubricant mixture (churning losses and windage losses due to aerodynamic trial of air lubricant mixture which controls the total efficiency needs to be considered. Therefore, in order to improve mechanical efficiency it is necessary for gear designer during gear tooth optimization to consider these energy losses. In this research paper the power loss analysis for a tooth-sum of 100 altered by ±4% operating between a specified center distance is considered. The results show that negative altered tooth-sum gearing performs better as compared to standard and positive altered tooth-sum gearing.

Hearing loss in Usher syndrome type II is nonprogressive.

Science.gov (United States)

Reisser, Christoph F V; Kimberling, William J; Otterstedde, Christian R

2002-12-01

Usher syndrome is an autosomal recessive disorder characterized by sensorineural hearing loss and progressive visual loss secondary to retinitis pigmentosa. In the literature, a possible progression of the moderate to severe hearing loss in Usher syndrome type II (Usher II) is controversial. We studied the development of the hearing loss of 125 patients with a clinical diagnosis of Usher syndrome type II intraindividually and interindividually by repeatedly performing complete audiological and neuro-otologic examinations. Our data show a very characteristic slope of the hearing curve in all Usher II patients and no clinically relevant progression of the hearing loss over up to 17 years. The subjective impression of a deterioration of the communicative abilities of Usher II patients must therefore be attributed to the progressive visual loss. The patients should be reassured that changes in their hearing abilities are unlikely and should be provided with optimally fitted modern hearing aids.

A hybrid system dynamics and optimization approach for supporting sustainable water resources planning in Zhengzhou City, China

Science.gov (United States)

Li, Zhi; Li, Chunhui; Wang, Xuan; Peng, Cong; Cai, Yanpeng; Huang, Weichen

2018-01-01

Problems with water resources restrict the sustainable development of a city with water shortages. Based on system dynamics (SD) theory, a model of sustainable utilization of water resources using the STELLA software has been established. This model consists of four subsystems: population system, economic system, water supply system and water demand system. The boundaries of the four subsystems are vague, but they are closely related and interdependent. The model is applied to Zhengzhou City, China, which has a serious water shortage. The difference between the water supply and demand is very prominent in Zhengzhou City. The model was verified with data from 2009 to 2013. The results show that water demand of Zhengzhou City will reach 2.57 billion m3 in 2020. A water resources optimization model is developed based on interval-parameter two-stage stochastic programming. The objective of the model is to allocate water resources to each water sector and make the lowest cost under the minimum water demand. Using the simulation results, decision makers can easily weigh the costs of the system, the water allocation objectives, and the system risk. The hybrid system dynamics method and optimization model is a rational try to support water resources management in many cities, particularly for cities with potential water shortage and it is solidly supported with previous studies and collected data.

SU-F-T-209: Multicriteria Optimization Algorithm for Intensity Modulated Radiation Therapy Using Pencil Proton Beam Scanning

Energy Technology Data Exchange (ETDEWEB)

Beltran, C; Kamal, H [Mayo Clinic, Rochester, MN (United States)

2016-06-15

Purpose: To provide a multicriteria optimization algorithm for intensity modulated radiation therapy using pencil proton beam scanning. Methods: Intensity modulated radiation therapy using pencil proton beam scanning requires efficient optimization algorithms to overcome the uncertainties in the Bragg peaks locations. This work is focused on optimization algorithms that are based on Monte Carlo simulation of the treatment planning and use the weights and the dose volume histogram (DVH) control points to steer toward desired plans. The proton beam treatment planning process based on single objective optimization (representing a weighted sum of multiple objectives) usually leads to time-consuming iterations involving treatment planning team members. We proved a time efficient multicriteria optimization algorithm that is developed to run on NVIDIA GPU (Graphical Processing Units) cluster. The multicriteria optimization algorithm running time benefits from up-sampling of the CT voxel size of the calculations without loss of fidelity. Results: We will present preliminary results of Multicriteria optimization for intensity modulated proton therapy based on DVH control points. The results will show optimization results of a phantom case and a brain tumor case. Conclusion: The multicriteria optimization of the intensity modulated radiation therapy using pencil proton beam scanning provides a novel tool for treatment planning. Work support by a grant from Varian Inc.

SU-F-T-209: Multicriteria Optimization Algorithm for Intensity Modulated Radiation Therapy Using Pencil Proton Beam Scanning

International Nuclear Information System (INIS)

Beltran, C; Kamal, H

2016-01-01

Purpose: To provide a multicriteria optimization algorithm for intensity modulated radiation therapy using pencil proton beam scanning. Methods: Intensity modulated radiation therapy using pencil proton beam scanning requires efficient optimization algorithms to overcome the uncertainties in the Bragg peaks locations. This work is focused on optimization algorithms that are based on Monte Carlo simulation of the treatment planning and use the weights and the dose volume histogram (DVH) control points to steer toward desired plans. The proton beam treatment planning process based on single objective optimization (representing a weighted sum of multiple objectives) usually leads to time-consuming iterations involving treatment planning team members. We proved a time efficient multicriteria optimization algorithm that is developed to run on NVIDIA GPU (Graphical Processing Units) cluster. The multicriteria optimization algorithm running time benefits from up-sampling of the CT voxel size of the calculations without loss of fidelity. Results: We will present preliminary results of Multicriteria optimization for intensity modulated proton therapy based on DVH control points. The results will show optimization results of a phantom case and a brain tumor case. Conclusion: The multicriteria optimization of the intensity modulated radiation therapy using pencil proton beam scanning provides a novel tool for treatment planning. Work support by a grant from Varian Inc.

Optimal capacitor placement and sizing using combined fuzzy ...

African Journals Online (AJOL)

Then the sizing of the capacitors is modeled as an optimization problem and the objective function (loss minimization) is solved using Hybrid Particle Swarm Optimization (HPSO) technique. A case study with an IEEE 34 bus distribution feeder is presented to illustrate the applicability of the algorithm. A comparison is made ...

Seeking optimality in fruit pulping schedules: A case study*

Directory of Open Access Journals (Sweden)

J.H. Van Vuuren

2014-01-01

Full Text Available The process of scheduling fruit pulping for the production of fruit juices is of great importance in the beverage industry. Decisions have to be made regarding available processing time, the disposal of fruit that will not be pulped before stock loss due to spoilage, the fulfilment of customer demand and an optimal financial position. Sheduling depends on the capacity of the work force, pulping machine limitations and delivery deadlines. However, the situation is often encountered where the plant manager has to decide which fruit batches (usually from stock piles of overwhelming proportions during the harvesting season are to be pulped in order to minimize losses due to fruit deterioration. Such decisions are usually done manually, based on intuition and experience. A mathematical model is presented here which constructs a pulping strategy while minimising cascading financial losses associated with fruit grade drops within the stock pile. It is shown in particular that a minimisation of fruit losses is not a good criterion for optimality, and that substantial financial gains may be accomplished when minimising financial losses in stead of fruit losses, which is currently standard practice at most fruit pulping plants.

Loss of idealism or realistic optimism? A cross-sectional analysis of dental hygiene students' and registered dental hygienists' professional identity perceptions.

Science.gov (United States)

Champine, J M; Inglehart, M R; Furgeson, D; Halaris, J F; Fitzgerald, M; Danciu, T E; Kinney, J S

2018-02-01

The dental hygiene profession in the U.S. is in the process of establishing a direct access model of care and contributing to the creation of the profession of a dental therapist. The objectives were to analyse the professional role perceptions of dental hygiene students and registered dental hygienists in these times of change. Specifically, it was explored whether dental hygiene students' current professional identities differ (i) from their expected future identities, and (ii) from dental hygienists' current and (iii) past identities. Survey data were collected from 215 dental hygiene students concerning their present and future role perceptions, and from 352 registered dental hygienists concerning their present and past professional identity perceptions. Students' future professional identity perceptions were even more positive than their very positive current perceptions of their professional role components. Students' current perceptions of professional pride, professional ambition, work ethic and patient relations were more positive than dental hygienists' current perceptions of these professional role components. A comparison of students' current perceptions with dental hygienists' current and retrospective descriptions showed that students were more positive than dental hygienists in each case. The fact that dental hygienists had less positive role perceptions than dental hygiene students might lead to the conclusion that a loss of idealism occurs over the course of a professional lifespan. However, dental hygienists actually improved their role perceptions over time and students' future descriptions were more positive than their current descriptions, supporting the interpretation that realistic optimism dominates professional role perceptions in these times of change. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

MULTI-LEVEL SAMPLING APPROACH FOR CONTINOUS LOSS DETECTION USING ITERATIVE WINDOW AND STATISTICAL MODEL

OpenAIRE

Mohd Fo'ad Rohani; Mohd Aizaini Maarof; Ali Selamat; Houssain Kettani

2010-01-01

This paper proposes a Multi-Level Sampling (MLS) approach for continuous Loss of Self-Similarity (LoSS) detection using iterative window. The method defines LoSS based on Second Order Self-Similarity (SOSS) statistical model. The Optimization Method (OM) is used to estimate self-similarity parameter since it is fast and more accurate in comparison with other estimation methods known in the literature. Probability of LoSS detection is introduced to measure continuous LoSS detection performance...

Reducing Nutrient Losses with Directed Fertilization of Degraded Soils

Science.gov (United States)

Menzies, E.; Walter, M. T.; Schneider, R.

2016-12-01

Degraded soils around the world are stunting agricultural productivity in places where people need it the most. In China, hundreds of years of agriculture and human activity have turned large swaths of productive grasslands into expanses of sandy soils where nothing can grow. Returning soils such as these to healthy productive landscapes is crucial to the livelihoods of rural families and to feeding the expanding population of China and the world at large. Buried wood chips can be used to improve the soils' water holding capacity but additional nutrient inputs are crucial to support plant growth and completely restore degraded soils in China and elsewhere. Improperly applied fertilizer can cause large fluxes of soluble nutrients such as nitrogen (N) and phosphorus (P) to pollute groundwater, and reach surface water bodies causing harmful algal blooms or eutrophication. Similarly, fertilization can create increases in nutrient losses in the form of greenhouse gases (GHGs). It is imperative that nutrient additions to this system be done in a way that fosters restoration and a return to productivity, but minimizes nutrient losses to adjacent surface water bodies and the atmosphere. The primary objective of this study is to characterize soluble and gaseous N and P losses from degraded sandy soils with wood chip and fertilizer amendments in order to identify optimal fertilization methods, frequencies, and quantities for soil restoration. A laboratory soil column study is currently underway to begin examining these questions results of this study will be presented at the Fall Meeting.

Efficiency Optimization by Considering the High Voltage Flyback Transformer Parasitics using an Automatic Winding Layout Technique

DEFF Research Database (Denmark)

Thummala, Prasanth; Schneider, Henrik; Zhang, Zhe

2015-01-01

.The energy efficiency is optimized using a proposed new automatic winding layout (AWL) technique and a comprehensive loss model.The AWL technique generates a large number of transformer winding layouts.The transformer parasitics such as dc resistance, leakage inductance and self-capacitance are calculated...... for each winding layout.An optimization technique is formulated to minimize the sum of energy losses during charge and discharge operations.The efficiency and energy loss distribution results from the optimization routine provide a deep insight into the high voltage transformer designand its impact...

Adaptive Digital Watermarking Scheme Based on Support Vector Machines and Optimized Genetic Algorithm