Determining the optimal number of Kanban in multi-products supply chain system

NASA Astrophysics Data System (ADS)

Widyadana, G. A.; Wee, H. M.; Chang, Jer-Yuan

2010-02-01

Kanban, a key element of just-in-time system, is a re-order card or signboard giving instruction or triggering the pull system to manufacture or supply a component based on actual usage of material. There are two types of Kanban: production Kanban and withdrawal Kanban. This study uses optimal and meta-heuristic methods to determine the Kanban quantity and withdrawal lot sizes in a supply chain system. Although the mix integer programming method gives an optimal solution, it is not time efficient. For this reason, the meta-heuristic methods are suggested. In this study, a genetic algorithm (GA) and a hybrid of genetic algorithm and simulated annealing (GASA) are used. The study compares the performance of GA and GASA with that of the optimal method using MIP. The given problems show that both GA and GASA result in a near optimal solution, and they outdo the optimal method in term of run time. In addition, the GASA heuristic method gives a better performance than the GA heuristic method.

Optimal design of clinical trials with biologics using dose-time-response models.

PubMed

Lange, Markus R; Schmidli, Heinz

2014-12-30

Biologics, in particular monoclonal antibodies, are important therapies in serious diseases such as cancer, psoriasis, multiple sclerosis, or rheumatoid arthritis. While most conventional drugs are given daily, the effect of monoclonal antibodies often lasts for months, and hence, these biologics require less frequent dosing. A good understanding of the time-changing effect of the biologic for different doses is needed to determine both an adequate dose and an appropriate time-interval between doses. Clinical trials provide data to estimate the dose-time-response relationship with semi-mechanistic nonlinear regression models. We investigate how to best choose the doses and corresponding sample size allocations in such clinical trials, so that the nonlinear dose-time-response model can be precisely estimated. We consider both local and conservative Bayesian D-optimality criteria for the design of clinical trials with biologics. For determining the optimal designs, computer-intensive numerical methods are needed, and we focus here on the particle swarm optimization algorithm. This metaheuristic optimizer has been successfully used in various areas but has only recently been applied in the optimal design context. The equivalence theorem is used to verify the optimality of the designs. The methodology is illustrated based on results from a clinical study in patients with gout, treated by a monoclonal antibody. Copyright © 2014 John Wiley & Sons, Ltd.

Optimization of the capillary zone electrophoresis method for Huperzine A determination using experimental design and artificial neural networks.

PubMed

Hameda, A Ben; Elosta, S; Havel, J

2005-08-19

Huperzine A, natural product from Huperzia serrata, is quite an important compound used to treat the Alzheimer's disease as a food supplement and also proposed as a prospective and prophylactic antidote against organophosphate poisoning. In this work, simple and fast capillary electrophoresis (CE) procedure with UV detection (at 230 nm) for determination of Huperzine A was developed and optimized. Capillary electrophoresis determination of Huperzine A was optimized using a combination of the experimental design (ED) and the artificial neural networks (ANN). In the first stage of optimization, the experiments were done according to the appropriate ED. Data evaluated by ANN allowed finding the optimal values of several analytical parameters (peak area, peak height, and analysis time). Optimal conditions found were 50 mM acetate buffer, pH 4.6, separation voltage 10 kV, hydrodynamic injection time 10 s and temperature 25 degrees C. The developed method shows good repeatability as relative standard division (R.S.D. = 0.9%) and it has been applied for determination of Huperzine A in various pharmaceutical products and in biological liquids. The limit of detection (LOD) in aqueous media was 0.226 ng/ml and 0.233 ng/ml for determination in the serum.

Optimizing Travel Time to Outpatient Interventional Radiology Procedures in a Multi-Site Hospital System Using a Google Maps Application.

PubMed

Mandel, Jacob E; Morel-Ovalle, Louis; Boas, Franz E; Ziv, Etay; Yarmohammadi, Hooman; Deipolyi, Amy; Mohabir, Heeralall R; Erinjeri, Joseph P

2018-02-20

The purpose of this study is to determine whether a custom Google Maps application can optimize site selection when scheduling outpatient interventional radiology (IR) procedures within a multi-site hospital system. The Google Maps for Business Application Programming Interface (API) was used to develop an internal web application that uses real-time traffic data to determine estimated travel time (ETT; minutes) and estimated travel distance (ETD; miles) from a patient's home to each a nearby IR facility in our hospital system. Hypothetical patient home addresses based on the 33 cities comprising our institution's catchment area were used to determine the optimal IR site for hypothetical patients traveling from each city based on real-time traffic conditions. For 10/33 (30%) cities, there was discordance between the optimal IR site based on ETT and the optimal IR site based on ETD at non-rush hour time or rush hour time. By choosing to travel to an IR site based on ETT rather than ETD, patients from discordant cities were predicted to save an average of 7.29 min during non-rush hour (p = 0.03), and 28.80 min during rush hour (p < 0.001). Using a custom Google Maps application to schedule outpatients for IR procedures can effectively reduce patient travel time when more than one location providing IR procedures is available within the same hospital system.

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

Reister, D.B.; Lenhart, S.M.

Recent theoretical results have completely solved the problem of determining the minimum length path for a vehicle with a minimum turning radius moving from an initial configuration to a final configuration. Time optimal paths for a constant speed vehicle are a subset of the minimum length paths. This paper uses the Pontryagin maximum principle to find time optimal paths for a constant speed vehicle. The time optimal paths consist of sequences of axes of circles and straight lines. The maximum principle introduces concepts (dual variables, bang-bang solutions, singular solutions, and transversality conditions) that provide important insight into the nature ofmore » the time optimal paths. We explore the properties of the optimal paths and present some experimental results for a mobile robot following an optimal path.« less

Expected value based fuzzy programming approach to solve integrated supplier selection and inventory control problem with fuzzy demand

NASA Astrophysics Data System (ADS)

Sutrisno; Widowati; Sunarsih; Kartono

2018-01-01

In this paper, a mathematical model in quadratic programming with fuzzy parameter is proposed to determine the optimal strategy for integrated inventory control and supplier selection problem with fuzzy demand. To solve the corresponding optimization problem, we use the expected value based fuzzy programming. Numerical examples are performed to evaluate the model. From the results, the optimal amount of each product that have to be purchased from each supplier for each time period and the optimal amount of each product that have to be stored in the inventory for each time period were determined with minimum total cost and the inventory level was sufficiently closed to the reference level.

Identifying the Best Times for Cognitive Functioning Using New Methods: Matching University Times to Undergraduate Chronotypes

PubMed Central

Evans, M. D. R.; Kelley, Paul; Kelley, Jonathan

2017-01-01

University days generally start at fixed times in the morning, often early morning, without regard to optimal functioning times for students with different chronotypes. Research has shown that later starting times are crucial to high school students' sleep, health, and performance. Shifting the focus to university, this study used two new approaches to determine ranges of start times that optimize cognitive functioning for undergraduates. The first is a survey-based, empirical model (SM), and the second a neuroscience-based, theoretical model (NM). The SM focused on students' self-reported chronotype and times they feel at their best. Using this approach, data from 190 mostly first and second year university students were collected and analyzed to determine optimal times when cognitive performance can be expected to be at its peak. The NM synthesized research in sleep, circadian neuroscience, sleep deprivation's impact on cognition, and practical considerations to create a generalized solution to determine the best learning hours. Strikingly the SM and NM results align with each other and confirm other recent research in indicating later start times. They add several important points: (1) They extend our understanding by showing that much later starting times (after 11 a.m. or 12 noon) are optimal; (2) Every single start time disadvantages one or more chronotypes; and (3) The best practical model may involve three alternative starting times with one afternoon shared session. The implications are briefly considered. PMID:28469566

Optimal pricing and replenishment policies for instantaneous deteriorating items with backlogging and trade credit under inflation

NASA Astrophysics Data System (ADS)

Sundara Rajan, R.; Uthayakumar, R.

2017-12-01

In this paper we develop an economic order quantity model to investigate the optimal replenishment policies for instantaneous deteriorating items under inflation and trade credit. Demand rate is a linear function of selling price and decreases negative exponentially with time over a finite planning horizon. Shortages are allowed and partially backlogged. Under these conditions, we model the retailer's inventory system as a profit maximization problem to determine the optimal selling price, optimal order quantity and optimal replenishment time. An easy-to-use algorithm is developed to determine the optimal replenishment policies for the retailer. We also provide optimal present value of profit when shortages are completely backlogged as a special case. Numerical examples are presented to illustrate the algorithm provided to obtain optimal profit. And we also obtain managerial implications from numerical examples to substantiate our model. The results show that there is an improvement in total profit from complete backlogging rather than the items being partially backlogged.

SCI model structure determination program (OSR) user's guide. [optimal subset regression

NASA Technical Reports Server (NTRS)

1979-01-01

The computer program, OSR (Optimal Subset Regression) which estimates models for rotorcraft body and rotor force and moment coefficients is described. The technique used is based on the subset regression algorithm. Given time histories of aerodynamic coefficients, aerodynamic variables, and control inputs, the program computes correlation between various time histories. The model structure determination is based on these correlations. Inputs and outputs of the program are given.

Optimal design and use of retry in fault tolerant real-time computer systems

NASA Technical Reports Server (NTRS)

Lee, Y. H.; Shin, K. G.

1983-01-01

A new method to determin an optimal retry policy and for use in retry of fault characterization is presented. An optimal retry policy for a given fault characteristic, which determines the maximum allowable retry durations to minimize the total task completion time was derived. The combined fault characterization and retry decision, in which the characteristics of fault are estimated simultaneously with the determination of the optimal retry policy were carried out. Two solution approaches were developed, one based on the point estimation and the other on the Bayes sequential decision. The maximum likelihood estimators are used for the first approach, and the backward induction for testing hypotheses in the second approach. Numerical examples in which all the durations associated with faults have monotone hazard functions, e.g., exponential, Weibull and gamma distributions are presented. These are standard distributions commonly used for modeling analysis and faults.

Two-step optimization of pressure and recovery of reverse osmosis desalination process.

PubMed

Liang, Shuang; Liu, Cui; Song, Lianfa

2009-05-01

Driving pressure and recovery are two primary design variables of a reverse osmosis process that largely determine the total cost of seawater and brackish water desalination. A two-step optimization procedure was developed in this paper to determine the values of driving pressure and recovery that minimize the total cost of RO desalination. It was demonstrated that the optimal net driving pressure is solely determined by the electricity price and the membrane price index, which is a lumped parameter to collectively reflect membrane price, resistance, and service time. On the other hand, the optimal recovery is determined by the electricity price, initial osmotic pressure, and costs for pretreatment of raw water and handling of retentate. Concise equations were derived for the optimal net driving pressure and recovery. The dependences of the optimal net driving pressure and recovery on the electricity price, membrane price, and costs for raw water pretreatment and retentate handling were discussed.

Extraction optimization of mucilage from Basil (Ocimum basilicum L.) seeds using response surface methodology.

PubMed

Nazir, Sadaf; Wani, Idrees Ahmed; Masoodi, Farooq Ahmad

2017-05-01

Aqueous extraction of basil seed mucilage was optimized using response surface methodology. A Central Composite Rotatable Design (CCRD) for modeling of three independent variables: temperature (40-91 °C); extraction time (1.6-3.3 h) and water/seed ratio (18:1-77:1) was used to study the response for yield. Experimental values for extraction yield ranged from 7.86 to 20.5 g/100 g. Extraction yield was significantly ( P  < 0.05) affected by all the variables. Temperature and water/seed ratio were found to have pronounced effect while the extraction time was found to have minor possible effects. Graphical optimization determined the optimal conditions for the extraction of mucilage. The optimal condition predicted an extraction yield of 20.49 g/100 g at 56.7 °C, 1.6 h, and a water/seed ratio of 66.84:1. Optimal conditions were determined to obtain highest extraction yield. Results indicated that water/seed ratio was the most significant parameter, followed by temperature and time.

Optimal critic learning for robot control in time-varying environments.

PubMed

Wang, Chen; Li, Yanan; Ge, Shuzhi Sam; Lee, Tong Heng

2015-10-01

In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q -function-based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. The simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.

Optimal Real-time Dispatch for Integrated Energy Systems

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

Firestone, Ryan Michael

This report describes the development and application of a dispatch optimization algorithm for integrated energy systems (IES) comprised of on-site cogeneration of heat and electricity, energy storage devices, and demand response opportunities. This work is intended to aid commercial and industrial sites in making use of modern computing power and optimization algorithms to make informed, near-optimal decisions under significant uncertainty and complex objective functions. The optimization algorithm uses a finite set of randomly generated future scenarios to approximate the true, stochastic future; constraints are included that prevent solutions to this approximate problem from deviating from solutions to the actual problem.more » The algorithm is then expressed as a mixed integer linear program, to which a powerful commercial solver is applied. A case study of United States Postal Service Processing and Distribution Centers (P&DC) in four cities and under three different electricity tariff structures is conducted to (1) determine the added value of optimal control to a cogeneration system over current, heuristic control strategies; (2) determine the value of limited electric load curtailment opportunities, with and without cogeneration; and (3) determine the trade-off between least-cost and least-carbon operations of a cogeneration system. Key results for the P&DC sites studied include (1) in locations where the average electricity and natural gas prices suggest a marginally profitable cogeneration system, optimal control can add up to 67% to the value of the cogeneration system; optimal control adds less value in locations where cogeneration is more clearly profitable; (2) optimal control under real-time pricing is (a) more complicated than under typical time-of-use tariffs and (b) at times necessary to make cogeneration economic at all; (3) limited electric load curtailment opportunities can be more valuable as a compliment to the cogeneration system than alone; and (4) most of the trade-off between least-cost and least-carbon IES is determined during the system design stage; for the IES system considered, there is little difference between least-cost control and least-carbon control.« less

Control system estimation and design for aerospace vehicles with time delay

NASA Technical Reports Server (NTRS)

Allgaier, G. R.; Williams, T. L.

1972-01-01

The problems of estimation and control of discrete, linear, time-varying systems are considered. Previous solutions to these problems involved either approximate techniques, open-loop control solutions, or results which required excessive computation. The estimation problem is solved by two different methods, both of which yield the identical algorithm for determining the optimal filter. The partitioned results achieve a substantial reduction in computation time and storage requirements over the expanded solution, however. The results reduce to the Kalman filter when no delays are present in the system. The control problem is also solved by two different methods, both of which yield identical algorithms for determining the optimal control gains. The stochastic control is shown to be identical to the deterministic control, thus extending the separation principle to time delay systems. The results obtained reduce to the familiar optimal control solution when no time delays are present in the system.

Improved conventional and microwave-assisted silylation protocols for simultaneous gas chromatographic determination of tocopherols and sterols: Method development and multi-response optimization.

PubMed

Poojary, Mahesha M; Passamonti, Paolo

2016-12-09

This paper reports on improved conventional thermal silylation (CTS) and microwave-assisted silylation (MAS) methods for simultaneous determination of tocopherols and sterols by gas chromatography. Reaction parameters in each of the methods developed were systematically optimized using a full factorial design followed by a central composite design. Initially, experimental conditions for CTS were optimized using a block heater. Further, a rapid MAS was developed and optimized. To understand microwave heating mechanisms, MAS was optimized by two distinct modes of microwave heating: temperature-controlled MAS and power-controlled MAS, using dedicated instruments where reaction temperature and microwave power level were controlled and monitored online. Developed methods: were compared with routine overnight derivatization. On a comprehensive level, while both CTS and MAS were found to be efficient derivatization techniques, MAS significantly reduced the reaction time. The optimal derivatization temperature and time for CTS found to be 55°C and 54min, while it was 87°C and 1.2min for temperature-controlled MAS. Further, a microwave power of 300W and a derivatization time 0.5min found to be optimal for power-controlled MAS. The use of an appropriate derivatization solvent, such as pyridine, was found to be critical for the successful determination. Catalysts, like potassium acetate and 4-dimethylaminopyridine, enhanced the efficiency slightly. The developed methods showed excellent analytical performance in terms of linearity, accuracy and precision. Copyright © 2016 Elsevier B.V. All rights reserved.

Protein Folding Free Energy Landscape along the Committor - the Optimal Folding Coordinate.

PubMed

Krivov, Sergei V

2018-06-06

Recent advances in simulation and experiment have led to dramatic increases in the quantity and complexity of produced data, which makes the development of automated analysis tools very important. A powerful approach to analyze dynamics contained in such data sets is to describe/approximate it by diffusion on a free energy landscape - free energy as a function of reaction coordinates (RC). For the description to be quantitatively accurate, RCs should be chosen in an optimal way. Recent theoretical results show that such an optimal RC exists; however, determining it for practical systems is a very difficult unsolved problem. Here we describe a solution to this problem. We describe an adaptive nonparametric approach to accurately determine the optimal RC (the committor) for an equilibrium trajectory of a realistic system. In contrast to alternative approaches, which require a functional form with many parameters to approximate an RC and thus extensive expertise with the system, the suggested approach is nonparametric and can approximate any RC with high accuracy without system specific information. To avoid overfitting for a realistically sampled system, the approach performs RC optimization in an adaptive manner by focusing optimization on less optimized spatiotemporal regions of the RC. The power of the approach is illustrated on a long equilibrium atomistic folding simulation of HP35 protein. We have determined the optimal folding RC - the committor, which was confirmed by passing a stringent committor validation test. It allowed us to determine a first quantitatively accurate protein folding free energy landscape. We have confirmed the recent theoretical results that diffusion on such a free energy profile can be used to compute exactly the equilibrium flux, the mean first passage times, and the mean transition path times between any two points on the profile. We have shown that the mean squared displacement along the optimal RC grows linear with time as for simple diffusion. The free energy profile allowed us to obtain a direct rigorous estimate of the pre-exponential factor for the folding dynamics.

Constrained Optimization of Average Arrival Time via a Probabilistic Approach to Transport Reliability

PubMed Central

Namazi-Rad, Mohammad-Reza; Dunbar, Michelle; Ghaderi, Hadi; Mokhtarian, Payam

2015-01-01

To achieve greater transit-time reduction and improvement in reliability of transport services, there is an increasing need to assist transport planners in understanding the value of punctuality; i.e. the potential improvements, not only to service quality and the consumer but also to the actual profitability of the service. In order for this to be achieved, it is important to understand the network-specific aspects that affect both the ability to decrease transit-time, and the associated cost-benefit of doing so. In this paper, we outline a framework for evaluating the effectiveness of proposed changes to average transit-time, so as to determine the optimal choice of average arrival time subject to desired punctuality levels whilst simultaneously minimizing operational costs. We model the service transit-time variability using a truncated probability density function, and simultaneously compare the trade-off between potential gains and increased service costs, for several commonly employed cost-benefit functions of general form. We formulate this problem as a constrained optimization problem to determine the optimal choice of average transit time, so as to increase the level of service punctuality, whilst simultaneously ensuring a minimum level of cost-benefit to the service operator. PMID:25992902

Rapid freeze-drying cycle optimization using computer programs developed based on heat and mass transfer models and facilitated by tunable diode laser absorption spectroscopy (TDLAS).

PubMed

Kuu, Wei Y; Nail, Steven L

2009-09-01

Computer programs in FORTRAN were developed to rapidly determine the optimal shelf temperature, T(f), and chamber pressure, P(c), to achieve the shortest primary drying time. The constraint for the optimization is to ensure that the product temperature profile, T(b), is below the target temperature, T(target). Five percent mannitol was chosen as the model formulation. After obtaining the optimal sets of T(f) and P(c), each cycle was assigned with a cycle rank number in terms of the length of drying time. Further optimization was achieved by dividing the drying time into a series of ramping steps for T(f), in a cascading manner (termed the cascading T(f) cycle), to further shorten the cycle time. For the purpose of demonstrating the validity of the optimized T(f) and P(c), four cycles with different predicted lengths of drying time, along with the cascading T(f) cycle, were chosen for experimental cycle runs. Tunable diode laser absorption spectroscopy (TDLAS) was used to continuously measure the sublimation rate. As predicted, maximum product temperatures were controlled slightly below the target temperature of -25 degrees C, and the cascading T(f)-ramping cycle is the most efficient cycle design. In addition, the experimental cycle rank order closely matches with that determined by modeling.

Simulating and Optimizing Preparative Protein Chromatography with ChromX

ERIC Educational Resources Information Center

Hahn, Tobias; Huuk, Thiemo; Heuveline, Vincent; Hubbuch, Ju¨rgen

2015-01-01

Industrial purification of biomolecules is commonly based on a sequence of chromatographic processes, which are adapted slightly to new target components, as the time to market is crucial. To improve time and material efficiency, modeling is increasingly used to determine optimal operating conditions, thus providing new challenges for current and…

Impulsive time-free transfers between halo orbits

NASA Astrophysics Data System (ADS)

Hiday, L. A.; Howell, K. C.

1992-08-01

A methodology is developed to design optimal time-free impulsive transfers between three-dimensional halo orbits in the vicinity of the interior L1 libration point of the sun-earth/moon barycenter system. The transfer trajectories are optimal in the sense that the total characteristics velocity required to implement the transfer exhibits a local minimum. Criteria are established whereby the implementation of a coast in the initial orbit, a coast in the final orbit, or dual coasts accomplishes a reduction in fuel expenditure. The optimality of a reference two-impulse transfer can be determined by examining the slope at the endpoints of a plot of the magnitude of the primer vector on the reference trajectory. If the initial and final slopes of the primer magnitude are zero, the transfer trajectory is optimal; otherwise, the execution of coasts is warranted. The optimal time of flight on the time-free transfer, and consequently, the departure and arrival locations on the halo orbits are determined by the unconstrained minimization of a function of two variables using a multivariable search technique. Results indicate that the cost can be substantially diminished by the allowance for coasts in the initial and final libration-point orbits.

Impulsive Time-Free Transfers Between Halo Orbits

NASA Astrophysics Data System (ADS)

Hiday-Johnston, L. A.; Howell, K. C.

1996-12-01

A methodology is developed to design optimal time-free impulsive transfers between three-dimensional halo orbits in the vicinity of the interior L 1 libration point of the Sun-Earth/Moon barycenter system. The transfer trajectories are optimal in the sense that the total characteristic velocity required to implement the transfer exhibits a local minimum. Criteria are established whereby the implementation of a coast in the initial orbit, a coast in the final orbit, or dual coasts accomplishes a reduction in fuel expenditure. The optimality of a reference two-impulse transfer can be determined by examining the slope at the endpoints of a plot of the magnitude of the primer vector on the reference trajectory. If the initial and final slopes of the primer magnitude are zero, the transfer trajectory is optimal; otherwise, the execution of coasts is warranted. The optimal time of flight on the time-free transfer, and consequently, the departure and arrival locations on the halo orbits are determined by the unconstrained minimization of a function of two variables using a multivariable search technique. Results indicate that the cost can be substantially diminished by the allowance for coasts in the initial and final libration-point orbits.

Optimal design of structures for earthquake loads by a hybrid RBF-BPSO method

NASA Astrophysics Data System (ADS)

Salajegheh, Eysa; Gholizadeh, Saeed; Khatibinia, Mohsen

2008-03-01

The optimal seismic design of structures requires that time history analyses (THA) be carried out repeatedly. This makes the optimal design process inefficient, in particular, if an evolutionary algorithm is used. To reduce the overall time required for structural optimization, two artificial intelligence strategies are employed. In the first strategy, radial basis function (RBF) neural networks are used to predict the time history responses of structures in the optimization flow. In the second strategy, a binary particle swarm optimization (BPSO) is used to find the optimum design. Combining the RBF and BPSO, a hybrid RBF-BPSO optimization method is proposed in this paper, which achieves fast optimization with high computational performance. Two examples are presented and compared to determine the optimal weight of structures under earthquake loadings using both exact and approximate analyses. The numerical results demonstrate the computational advantages and effectiveness of the proposed hybrid RBF-BPSO optimization method for the seismic design of structures.

The fully actuated traffic control problem solved by global optimization and complementarity

NASA Astrophysics Data System (ADS)

Ribeiro, Isabel M.; de Lurdes de Oliveira Simões, Maria

2016-02-01

Global optimization and complementarity are used to determine the signal timing for fully actuated traffic control, regarding effective green and red times on each cycle. The average values of these parameters can be used to estimate the control delay of vehicles. In this article, a two-phase queuing system for a signalized intersection is outlined, based on the principle of minimization of the total waiting time for the vehicles. The underlying model results in a linear program with linear complementarity constraints, solved by a sequential complementarity algorithm. Departure rates of vehicles during green and yellow periods were treated as deterministic, while arrival rates of vehicles were assumed to follow a Poisson distribution. Several traffic scenarios were created and solved. The numerical results reveal that it is possible to use global optimization and complementarity over a reasonable number of cycles and determine with efficiency effective green and red times for a signalized intersection.

Optimizing Real-Time Vaccine Allocation in a Stochastic SIR Model

PubMed Central

Nguyen, Chantal; Carlson, Jean M.

2016-01-01

Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in delayed vaccine deployment, and the interaction between members of different cities facilitates a wide spatial spread of infection. Limited vaccine, time delays, and interaction (or coupling) of cities lead to tradeoffs that impact the overall magnitude of the epidemic. These tradeoffs mandate investigation of optimal strategies that minimize the severity of the epidemic by prioritizing allocation of vaccine to specific subpopulations. We use an SIR model to describe the disease dynamics of an epidemic which breaks out in one city and spreads to another. We solve a master equation to determine the resulting probability distribution of the final epidemic size. We then identify tradeoffs between vaccine, time delay, and coupling, and we determine the optimal vaccination protocols resulting from these tradeoffs. PMID:27043931

Determining Optimal Allocation of Naval Obstetric Resources with Linear Programming

DTIC Science & Technology

2013-12-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA MBA PROFESSIONAL REPORT DETERMINING OPTIMAL ALLOCATION OF NAVAL OBSTETRIC RESOURCES...Davis Approved for public release; distribution is unlimited THIS PAGE INTENTIONALLY LEFT BLANK REPORT DOCUMENTATION PAGE Form Approved...OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for

Adaptive optimal stochastic state feedback control of resistive wall modes in tokamaks

NASA Astrophysics Data System (ADS)

Sun, Z.; Sen, A. K.; Longman, R. W.

2006-01-01

An adaptive optimal stochastic state feedback control is developed to stabilize the resistive wall mode (RWM) instability in tokamaks. The extended least-square method with exponential forgetting factor and covariance resetting is used to identify (experimentally determine) the time-varying stochastic system model. A Kalman filter is used to estimate the system states. The estimated system states are passed on to an optimal state feedback controller to construct control inputs. The Kalman filter and the optimal state feedback controller are periodically redesigned online based on the identified system model. This adaptive controller can stabilize the time-dependent RWM in a slowly evolving tokamak discharge. This is accomplished within a time delay of roughly four times the inverse of the growth rate for the time-invariant model used.

Multi-Objective Trajectory Optimization of a Hypersonic Reconnaissance Vehicle with Temperature Constraints

NASA Astrophysics Data System (ADS)

Masternak, Tadeusz J.

This research determines temperature-constrained optimal trajectories for a scramjet-based hypersonic reconnaissance vehicle by developing an optimal control formulation and solving it using a variable order Gauss-Radau quadrature collocation method with a Non-Linear Programming (NLP) solver. The vehicle is assumed to be an air-breathing reconnaissance aircraft that has specified takeoff/landing locations, airborne refueling constraints, specified no-fly zones, and specified targets for sensor data collections. A three degree of freedom scramjet aircraft model is adapted from previous work and includes flight dynamics, aerodynamics, and thermal constraints. Vehicle control is accomplished by controlling angle of attack, roll angle, and propellant mass flow rate. This model is incorporated into an optimal control formulation that includes constraints on both the vehicle and mission parameters, such as avoidance of no-fly zones and coverage of high-value targets. To solve the optimal control formulation, a MATLAB-based package called General Pseudospectral Optimal Control Software (GPOPS-II) is used, which transcribes continuous time optimal control problems into an NLP problem. In addition, since a mission profile can have varying vehicle dynamics and en-route imposed constraints, the optimal control problem formulation can be broken up into several "phases" with differing dynamics and/or varying initial/final constraints. Optimal trajectories are developed using several different performance costs in the optimal control formulation: minimum time, minimum time with control penalties, and maximum range. The resulting analysis demonstrates that optimal trajectories that meet specified mission parameters and constraints can be quickly determined and used for larger-scale operational and campaign planning and execution.

[Optimization of stir-baking with vinegar technology for Curcumae Radix by orthogonal test].

PubMed

Shi, Dianhua; Su, Benzheng; Sun, Lili; Zhang, Jun; Qu, Yongsheng

2011-05-01

To optimize the stir-baking with vinegar technology for Curcumae Radix. The intrinsic quality (the content of Curcumin) and traditional outward appearance were chosen as indexes. The best technology was determined by orthogonal test L9 (3(4)). The factors of the moistening time, stir-baking temperature and stir-baking time were investigated. The optimal technology was as follows: the quantity of vinegar was 10%, the moistening time was 10 min, the stir-baking temperature was 130 degrees C and the stir-baking time was 10 min. The optimal stir-baking with vinegar technology for Curcumae Radix is reasonable, which can be used to guide the standardized production of Curcumae Radix stir-baked with vinegar.

Determination of optimal environmental policy for reclamation of land unearthed in lignite mines - Strategy and tactics

NASA Astrophysics Data System (ADS)

Batzias, Dimitris F.; Pollalis, Yannis A.

2012-12-01

In this paper, optimal environmental policy for reclamation of land unearthed in lignite mines is defined as a strategic target. The tactics concerning the achievement of this target, includes estimation of optimal time lag between each lignite site (which is a segment of the whole lignite field) complete exploitation and its reclamation. Subsidizing of reclamation has been determined as a function of this time lag and relevant implementation is presented for parameter values valid for the Greek economy. We proved that the methodology we have developed gives reasonable quantitative results within the norms imposed by legislation. Moreover, the interconnection between strategy and tactics becomes evident, since the former causes the latter by deduction and the latter revises the former by induction in the time course of land reclamation.

Optimizing Tsunami Forecast Model Accuracy

NASA Astrophysics Data System (ADS)

Whitmore, P.; Nyland, D. L.; Huang, P. Y.

2015-12-01

Recent tsunamis provide a means to determine the accuracy that can be expected of real-time tsunami forecast models. Forecast accuracy using two different tsunami forecast models are compared for seven events since 2006 based on both real-time application and optimized, after-the-fact "forecasts". Lessons learned by comparing the forecast accuracy determined during an event to modified applications of the models after-the-fact provide improved methods for real-time forecasting for future events. Variables such as source definition, data assimilation, and model scaling factors are examined to optimize forecast accuracy. Forecast accuracy is also compared for direct forward modeling based on earthquake source parameters versus accuracy obtained by assimilating sea level data into the forecast model. Results show that including assimilated sea level data into the models increases accuracy by approximately 15% for the events examined.

Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode

PubMed Central

Zhu, Xiaoning

2014-01-01

Rail mounted gantry crane (RMGC) scheduling is important in reducing makespan of handling operation and improving container handling efficiency. In this paper, we present an RMGC scheduling optimization model, whose objective is to determine an optimization handling sequence in order to minimize RMGC idle load time in handling tasks. An ant colony optimization is proposed to obtain near optimal solutions. Computational experiments on a specific railway container terminal are conducted to illustrate the proposed model and solution algorithm. The results show that the proposed method is effective in reducing the idle load time of RMGC. PMID:25538768

Selecting a proper design period for heliostat field layout optimization using Campo code

NASA Astrophysics Data System (ADS)

Saghafifar, Mohammad; Gadalla, Mohamed

2016-09-01

In this paper, different approaches are considered to calculate the cosine factor which is utilized in Campo code to expand the heliostat field layout and maximize its annual thermal output. Furthermore, three heliostat fields containing different number of mirrors are taken into consideration. Cosine factor is determined by considering instantaneous and time-average approaches. For instantaneous method, different design days and design hours are selected. For the time average method, daily time average, monthly time average, seasonally time average, and yearly time averaged cosine factor determinations are considered. Results indicate that instantaneous methods are more appropriate for small scale heliostat field optimization. Consequently, it is proposed to consider the design period as the second design variable to ensure the best outcome. For medium and large scale heliostat fields, selecting an appropriate design period is more important. Therefore, it is more reliable to select one of the recommended time average methods to optimize the field layout. Optimum annual weighted efficiency for heliostat fields (small, medium, and large) containing 350, 1460, and 3450 mirrors are 66.14%, 60.87%, and 54.04%, respectively.

Optimal control of vaccination rate in an epidemiological model of Clostridium difficile transmission.

PubMed

Stephenson, Brittany; Lanzas, Cristina; Lenhart, Suzanne; Day, Judy

2017-12-01

The spore-forming, gram-negative bacteria Clostridium difficile can cause severe intestinal illness. A striking increase in the number of cases of C. difficile infection (CDI) among hospitals has highlighted the need to better understand how to prevent the spread of CDI. In our paper, we modify and update a compartmental model of nosocomial C. difficile transmission to include vaccination. We then apply optimal control theory to determine the time-varying optimal vaccination rate that minimizes a combination of disease prevalence and spread in the hospital population as well as cost, in terms of time and money, associated with vaccination. Various hospital scenarios are considered, such as times of increased antibiotic prescription rate and times of outbreak, to see how such scenarios modify the optimal vaccination rate. By comparing the values of the objective functional with constant vaccination rates to those with time-varying optimal vaccination rates, we illustrate the benefits of time-varying controls.

Discrete-State Simulated Annealing For Traveling-Wave Tube Slow-Wave Circuit Optimization

NASA Technical Reports Server (NTRS)

Wilson, Jeffrey D.; Bulson, Brian A.; Kory, Carol L.; Williams, W. Dan (Technical Monitor)

2001-01-01

Algorithms based on the global optimization technique of simulated annealing (SA) have proven useful in designing traveling-wave tube (TWT) slow-wave circuits for high RF power efficiency. The characteristic of SA that enables it to determine a globally optimized solution is its ability to accept non-improving moves in a controlled manner. In the initial stages of the optimization, the algorithm moves freely through configuration space, accepting most of the proposed designs. This freedom of movement allows non-intuitive designs to be explored rather than restricting the optimization to local improvement upon the initial configuration. As the optimization proceeds, the rate of acceptance of non-improving moves is gradually reduced until the algorithm converges to the optimized solution. The rate at which the freedom of movement is decreased is known as the annealing or cooling schedule of the SA algorithm. The main disadvantage of SA is that there is not a rigorous theoretical foundation for determining the parameters of the cooling schedule. The choice of these parameters is highly problem dependent and the designer needs to experiment in order to determine values that will provide a good optimization in a reasonable amount of computational time. This experimentation can absorb a large amount of time especially when the algorithm is being applied to a new type of design. In order to eliminate this disadvantage, a variation of SA known as discrete-state simulated annealing (DSSA), was recently developed. DSSA provides the theoretical foundation for a generic cooling schedule which is problem independent, Results of similar quality to SA can be obtained, but without the extra computational time required to tune the cooling parameters. Two algorithm variations based on DSSA were developed and programmed into a Microsoft Excel spreadsheet graphical user interface (GUI) to the two-dimensional nonlinear multisignal helix traveling-wave amplifier analysis program TWA3. The algorithms were used to optimize the computed RF efficiency of a TWT by determining the phase velocity profile of the slow-wave circuit. The mathematical theory and computational details of the DSSA algorithms will be presented and results will be compared to those obtained with a SA algorithm.

Spectrophotometric determination of fluoxetine by molecularly imprinted polypyrrole and optimization by experimental design, artificial neural network and genetic algorithm

NASA Astrophysics Data System (ADS)

Nezhadali, Azizollah; Motlagh, Maryam Omidvar; Sadeghzadeh, Samira

2018-02-01

A selective method based on molecularly imprinted polymer (MIP) solid-phase extraction (SPE) using UV-Vis spectrophotometry as a detection technique was developed for the determination of fluoxetine (FLU) in pharmaceutical and human serum samples. The MIPs were synthesized using pyrrole as a functional monomer in the presence of FLU as a template molecule. The factors that affecting the preparation and extraction ability of MIP such as amount of sorbent, initiator concentration, the amount of monomer to template ratio, uptake shaking rate, uptake time, washing buffer pH, take shaking rate, Taking time and polymerization time were considered for optimization. First a Plackett-Burman design (PBD) consists of 12 randomized runs were applied to determine the influence of each factor. The other optimization processes were performed using central composite design (CCD), artificial neural network (ANN) and genetic algorithm (GA). At optimal condition the calibration curve showed linearity over a concentration range of 10- 7-10- 8 M with a correlation coefficient (R2) of 0.9970. The limit of detection (LOD) for FLU was obtained 6.56 × 10- 9 M. The repeatability of the method was obtained 1.61%. The synthesized MIP sorbent showed a good selectivity and sensitivity toward FLU. The MIP/SPE method was used for the determination of FLU in pharmaceutical, serum and plasma samples, successfully.

Optimization with artificial neural network systems - A mapping principle and a comparison to gradient based methods

NASA Technical Reports Server (NTRS)

Leong, Harrison Monfook

1988-01-01

General formulae for mapping optimization problems into systems of ordinary differential equations associated with artificial neural networks are presented. A comparison is made to optimization using gradient-search methods. The performance measure is the settling time from an initial state to a target state. A simple analytical example illustrates a situation where dynamical systems representing artificial neural network methods would settle faster than those representing gradient-search. Settling time was investigated for a more complicated optimization problem using computer simulations. The problem was a simplified version of a problem in medical imaging: determining loci of cerebral activity from electromagnetic measurements at the scalp. The simulations showed that gradient based systems typically settled 50 to 100 times faster than systems based on current neural network optimization methods.

[Study on the optimal extraction process of chaihushugan powder].

PubMed

Wang, Chun-yan; Zhang, Wan-ming; Zhang, Dan-shen; An, Fang; Tian, Jia-ming

2009-11-01

To study the optimal extraction process of chaihushugan powder by orthogonal design. RP-HPLC method was developed for the determination of saikosaponin a, ferulic acid, hesperidin and paeoniflorin in chaihushugan powder. The contents of the components and the extraction yield were selected as assessment indices. Four factors were study by L9 (3(4)), including the alcohol concentration, amount of alcohol, duration of extraction and times of extraction. The optimal extracting condition was 80% alcohol consumed as 10 times of crude herb amount, and extracting two times for 90 min each time. This study supplies theoretical base for the development of chaihushugan powder formulation.

Simplex optimization of headspace factors for headspace gas chromatography determination of residual solvents in pharmaceutical products.

PubMed

Grodowska, Katarzyna; Parczewski, Andrzej

2013-01-01

The purpose of the present work was to find optimum conditions of headspace gas chromatography (HS-GC) determination of residual solvents which usually appear in pharmaceutical products. Two groups of solvents were taken into account in the present examination. Group I consisted of isopropanol, n-propanol, isobutanol, n-butanol and 1,4-dioxane and group II included cyclohexane, n-hexane and n-heptane. The members of the groups were selected in previous investigations in which experimental design and chemometric methods were applied. Four factors were taken into consideration in optimization which describe HS conditions: sample volume, equilibration time, equilibrium temperature and NaCl concentration in a sample. The relative GC peak area served as an optimization criterion which was considered separately for each analyte. Sequential variable size simplex optimization strategy was used and the progress of optimization was traced and visualized in various ways simultaneously. The optimum HS conditions appeared different for the groups of solvents tested, which proves that influence of experimental conditions (factors) depends on analyte properties. The optimization resulted in significant signal increase (from seven to fifteen times).

Integrating NOE and RDC using sum-of-squares relaxation for protein structure determination.

PubMed

Khoo, Y; Singer, A; Cowburn, D

2017-07-01

We revisit the problem of protein structure determination from geometrical restraints from NMR, using convex optimization. It is well-known that the NP-hard distance geometry problem of determining atomic positions from pairwise distance restraints can be relaxed into a convex semidefinite program (SDP). However, often the NOE distance restraints are too imprecise and sparse for accurate structure determination. Residual dipolar coupling (RDC) measurements provide additional geometric information on the angles between atom-pair directions and axes of the principal-axis-frame. The optimization problem involving RDC is highly non-convex and requires a good initialization even within the simulated annealing framework. In this paper, we model the protein backbone as an articulated structure composed of rigid units. Determining the rotation of each rigid unit gives the full protein structure. We propose solving the non-convex optimization problems using the sum-of-squares (SOS) hierarchy, a hierarchy of convex relaxations with increasing complexity and approximation power. Unlike classical global optimization approaches, SOS optimization returns a certificate of optimality if the global optimum is found. Based on the SOS method, we proposed two algorithms-RDC-SOS and RDC-NOE-SOS, that have polynomial time complexity in the number of amino-acid residues and run efficiently on a standard desktop. In many instances, the proposed methods exactly recover the solution to the original non-convex optimization problem. To the best of our knowledge this is the first time SOS relaxation is introduced to solve non-convex optimization problems in structural biology. We further introduce a statistical tool, the Cramér-Rao bound (CRB), to provide an information theoretic bound on the highest resolution one can hope to achieve when determining protein structure from noisy measurements using any unbiased estimator. Our simulation results show that when the RDC measurements are corrupted by Gaussian noise of realistic variance, both SOS based algorithms attain the CRB. We successfully apply our method in a divide-and-conquer fashion to determine the structure of ubiquitin from experimental NOE and RDC measurements obtained in two alignment media, achieving more accurate and faster reconstructions compared to the current state of the art.

Can Subjects be Guided to Optimal Decisions The Use of a Real-Time Training Intervention Model

DTIC Science & Technology

2016-06-01

execution of the task and may then be analyzed to determine if there is correlation between designated factors (scores, proportion of time in each...state with their decision performance in real time could allow training systems to be designed to tailor training to the individual decision maker...release; distribution is unlimited CAN SUBJECTS BE GUIDED TO OPTIMAL DECISIONS? THE USE OF A REAL- TIME TRAINING INTERVENTION MODEL by Travis D

Optimal Low Energy Earth-Moon Transfers

NASA Technical Reports Server (NTRS)

Griesemer, Paul Ricord; Ocampo, Cesar; Cooley, D. S.

2010-01-01

The optimality of a low-energy Earth-Moon transfer is examined for the first time using primer vector theory. An optimal control problem is formed with the following free variables: the location, time, and magnitude of the transfer insertion burn, and the transfer time. A constraint is placed on the initial state of the spacecraft to bind it to a given initial orbit around a first body, and on the final state of the spacecraft to limit its Keplerian energy with respect to a second body. Optimal transfers in the system are shown to meet certain conditions placed on the primer vector and its time derivative. A two point boundary value problem containing these necessary conditions is created for use in targeting optimal transfers. The two point boundary value problem is then applied to the ballistic lunar capture problem, and an optimal trajectory is shown. Additionally, the ballistic lunar capture trajectory is examined to determine whether one or more additional impulses may improve on the cost of the transfer.

Neighboring Optimal Aircraft Guidance in a General Wind Environment

NASA Technical Reports Server (NTRS)

Jardin, Matthew R. (Inventor)

2003-01-01

Method and system for determining an optimal route for an aircraft moving between first and second waypoints in a general wind environment. A selected first wind environment is analyzed for which a nominal solution can be determined. A second wind environment is then incorporated; and a neighboring optimal control (NOC) analysis is performed to estimate an optimal route for the second wind environment. In particular examples with flight distances of 2500 and 6000 nautical miles in the presence of constant or piecewise linearly varying winds, the difference in flight time between a nominal solution and an optimal solution is 3.4 to 5 percent. Constant or variable winds and aircraft speeds can be used. Updated second wind environment information can be provided and used to obtain an updated optimal route.

Computation of optimal output-feedback compensators for linear time-invariant systems

NASA Technical Reports Server (NTRS)

Platzman, L. K.

1972-01-01

The control of linear time-invariant systems with respect to a quadratic performance criterion was considered, subject to the constraint that the control vector be a constant linear transformation of the output vector. The optimal feedback matrix, f*, was selected to optimize the expected performance, given the covariance of the initial state. It is first shown that the expected performance criterion can be expressed as the ratio of two multinomials in the element of f. This expression provides the basis for a feasible method of determining f* in the case of single-input single-output systems. A number of iterative algorithms are then proposed for the calculation of f* for multiple input-output systems. For two of these, monotone convergence is proved, but they involve the solution of nonlinear matrix equations at each iteration. Another is proposed involving the solution of Lyapunov equations at each iteration, and the gradual increase of the magnitude of a penalty function. Experience with this algorithm will be needed to determine whether or not it does, indeed, possess desirable convergence properties, and whether it can be used to determine the globally optimal f*.

Optimization and validation of Folin-Ciocalteu method for the determination of total polyphenol content of Pu-erh tea.

PubMed

Musci, Marilena; Yao, Shicong

2017-12-01

Pu-erh tea is a post-fermented tea that has recently gained popularity worldwide, due to potential health benefits related to the antioxidant activity resulting from its high polyphenolic content. The Folin-Ciocalteu method is a simple, rapid, and inexpensive assay widely applied for the determination of total polyphenol content. Over the past years, it has been subjected to many modifications, often without any systematic optimization or validation. In our study, we sought to optimize the Folin-Ciocalteu method, evaluate quality parameters including linearity, precision and stability, and then apply the optimized model to determine the total polyphenol content of 57 Chinese teas, including green tea, aged and ripened Pu-erh tea. Our optimized Folin-Ciocalteu method reduced analysis time, allowed for the analysis of a large number of samples, to discriminate among the different teas, and to assess the effect of the post-fermentation process on polyphenol content.

Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons.

PubMed

Yaeli, Steve; Meir, Ron

2010-01-01

Biological systems display impressive capabilities in effectively responding to environmental signals in real time. There is increasing evidence that organisms may indeed be employing near optimal Bayesian calculations in their decision-making. An intriguing question relates to the properties of optimal encoding methods, namely determining the properties of neural populations in sensory layers that optimize performance, subject to physiological constraints. Within an ecological theory of neural encoding/decoding, we show that optimal Bayesian performance requires neural adaptation which reflects environmental changes. Specifically, we predict that neuronal tuning functions possess an optimal width, which increases with prior uncertainty and environmental noise, and decreases with the decoding time window. Furthermore, even for static stimuli, we demonstrate that dynamic sensory tuning functions, acting at relatively short time scales, lead to improved performance. Interestingly, the narrowing of tuning functions as a function of time was recently observed in several biological systems. Such results set the stage for a functional theory which may explain the high reliability of sensory systems, and the utility of neuronal adaptation occurring at multiple time scales.

Is there a trade-off between longevity and quality of life in Grossman's pure investment model?

PubMed

Eisenring, C

2000-12-01

The question is posed whether an individual maximizes lifetime or trades off longevity for quality of life in Grossman's pure investment (PI)-model. It is shown that the answer critically hinges on the assumed production function for healthy time. If the production function for healthy time produces a trade-off between life-span and quality of life, one has to solve a sequence of fixed time problems. The one offering maximal intertemporal utility determines optimal longevity. Comparative static results of optimal longevity for a simplified version of the PI-model are derived. The obtained results predict that higher initial endowments of wealth and health, a rise in the wage rate, or improvements in the technology of producing healthy time, all increase the optimal length of life. On the other hand, optimal longevity is decreasing in the depreciation and interest rate. From a technical point of view, the paper illustrates that a discrete time equivalent to the transversality condition for optimal longevity employed in continuous optimal control models does not exist. Copyright 2000 John Wiley & Sons, Ltd.

Multirate sampled-data yaw-damper and modal suppression system design

NASA Technical Reports Server (NTRS)

Berg, Martin C.; Mason, Gregory S.

1990-01-01

A multirate control law synthesized algorithm based on an infinite-time quadratic cost function, was developed along with a method for analyzing the robustness of multirate systems. A generalized multirate sampled-data control law structure (GMCLS) was introduced. A new infinite-time-based parameter optimization multirate sampled-data control law synthesis method and solution algorithm were developed. A singular-value-based method for determining gain and phase margins for multirate systems was also developed. The finite-time-based parameter optimization multirate sampled-data control law synthesis algorithm originally intended to be applied to the aircraft problem was instead demonstrated by application to a simpler problem involving the control of the tip position of a two-link robot arm. The GMCLS, the infinite-time-based parameter optimization multirate control law synthesis method and solution algorithm, and the singular-value based method for determining gain and phase margins were all demonstrated by application to the aircraft control problem originally proposed for this project.

Optimal control theory determination of feasible return-to-launch-site aborts for the HL-20 Personnel Launch System vehicle

NASA Technical Reports Server (NTRS)

Dutton, Kevin E.

1994-01-01

The personnel launch system (PLS) being studied by NASA is a system to complement the space shuttle and provide alternative access to space. The PLS consists of a manned spacecraft launched by an expendable launch vehicle (ELV). A candidate for the manned spacecraft is the HL-20 lifting body. In the event of an ELV malfunction during the initial portion of the ascent trajectory, the HL-20 will separate from the rocket and perform an unpowered return to launch site (RTLS) abort. This work details an investigation, using optimal control theory, of the RTLS abort scenario. The objective of the optimization was to maximize final altitude. With final altitude as the cost function, the feasibility of an RTLS abort at different times during the ascent was determined. The method of differential inclusions was used to determine the optimal state trajectories, and the optimal controls were then calculated from the optimal states and state rates.

Assessment of hemodynamic load components affecting optimization of cardiac resynchronization therapy by lumped parameter mode.

PubMed

Xu, Ke; Butlin, Mark; Avolio, Alberto P

2012-01-01

Timing of biventricular pacing devices employed in cardiac resynchronization therapy (CRT) is a critical determinant of efficacy of the procedure. Optimization is done by maximizing function in terms of arterial pressure (BP) or cardiac output (CO). However, BP and CO are also determined by the hemodynamic load of the pulmonary and systemic vasculature. This study aims to use a lumped parameter circulatory model to assess the influence of the arterial load on the atrio-ventricular (AV) and inter-ventricular (VV) delay for optimal CRT performance.

On the multiple depots vehicle routing problem with heterogeneous fleet capacity and velocity

NASA Astrophysics Data System (ADS)

Hanum, F.; Hartono, A. P.; Bakhtiar, T.

2018-03-01

This current manuscript concerns with the optimization problem arising in a route determination of products distribution. The problem is formulated in the form of multiple depots and time windowed vehicle routing problem with heterogeneous capacity and velocity of fleet. Model includes a number of constraints such as route continuity, multiple depots availability and serving time in addition to generic constraints. In dealing with the unique feature of heterogeneous velocity, we generate a number of velocity profiles along the road segments, which then converted into traveling-time tables. An illustrative example of rice distribution among villages by bureau of logistics is provided. Exact approach is utilized to determine the optimal solution in term of vehicle routes and starting time of service.

Optimization of ecosystem model parameters with different temporal variabilities using tower flux data and an ensemble Kalman filter

NASA Astrophysics Data System (ADS)

He, L.; Chen, J. M.; Liu, J.; Mo, G.; Zhen, T.; Chen, B.; Wang, R.; Arain, M.

2013-12-01

Terrestrial ecosystem models have been widely used to simulate carbon, water and energy fluxes and climate-ecosystem interactions. In these models, some vegetation and soil parameters are determined based on limited studies from literatures without consideration of their seasonal variations. Data assimilation (DA) provides an effective way to optimize these parameters at different time scales . In this study, an ensemble Kalman filter (EnKF) is developed and applied to optimize two key parameters of an ecosystem model, namely the Boreal Ecosystem Productivity Simulator (BEPS): (1) the maximum photosynthetic carboxylation rate (Vcmax) at 25 °C, and (2) the soil water stress factor (fw) for stomatal conductance formulation. These parameters are optimized through assimilating observations of gross primary productivity (GPP) and latent heat (LE) fluxes measured in a 74 year-old pine forest, which is part of the Turkey Point Flux Station's age-sequence sites. Vcmax is related to leaf nitrogen concentration and varies slowly over the season and from year to year. In contrast, fw varies rapidly in response to soil moisture dynamics in the root-zone. Earlier studies suggested that DA of vegetation parameters at daily time steps leads to Vcmax values that are unrealistic. To overcome the problem, we developed a three-step scheme to optimize Vcmax and fw. First, the EnKF is applied daily to obtain precursor estimates of Vcmax and fw. Then Vcmax is optimized at different time scales assuming fw is unchanged from first step. The best temporal period or window size is then determined by analyzing the magnitude of the minimized cost-function, and the coefficient of determination (R2) and Root-mean-square deviation (RMSE) of GPP and LE between simulation and observation. Finally, the daily fw value is optimized for rain free days corresponding to the Vcmax curve from the best window size. The optimized fw is then used to model its relationship with soil moisture. We found that the optimized fw is best correlated linearly to soil water content at 5 to 10 cm depth. We also found that both the temporal scale or window size and the priori uncertainty of Vcmax (given as its standard deviation) are important in determining the seasonal trajectory of Vcmax. During the leaf expansion stage, an appropriate window size leads to reasonable estimate of Vcmax. In the summer, the fluctuation of optimized Vcmax is mainly caused by the uncertainties in Vcmax but not the window size. Our study suggests that a smooth Vcmax curve optimized from an optimal time window size is close to the reality though the RMSE of GPP at this window is not the minimum. It also suggests that for the accurate optimization of Vcmax, it is necessary to set appropriate levels of uncertainty of Vcmax in the spring and summer because the rate of leaf nitrogen concentration change is different over the season. Parameter optimizations for more sites and multi-years are in progress.

Conception et analyse d'un systeme d'optimisation de plans de vol pour les avions

NASA Astrophysics Data System (ADS)

Maazoun, Wissem

The main objective of this thesis is to develop an optimization method for the preparation of flight plans for aircrafts. The flight plan minimizes all costs associated with the flight. We determine an optimal path for an airplane from a departure airport to a destination airport. The optimal path minimizes the sum of all costs, i.e. the cost of fuel added to the cost of time (wages, rental of the aircraft, arrival delays, etc.). The optimal trajectory is obtained by considering all possible trajectories on a 3D graph (longitude, latitude and altitude) where the altitude levels are separated by 2,000 feet, and by applying a shortest path algorithm. The main task was to accurately compute fuel consumption on each edge of the graph, making sure that each arc has a minimal cost and is covered in a realistic way from the point of view of control, i.e. in accordance with the rules of navigation. To compute the cost of an arc, we take into account weather conditions (temperature, pressure, wind components, etc.). The optimization of each arc is done via the evaluation of an optimum speed that takes all costs into account. Each arc of the graph typically includes several sub-phases of the flight, e.g. altitude change, speed change, and constant speed and altitude. In the initial climb and the final descent phases, the costs are determined by considering altitude changes at constant CAS (Calibrated Air Speed) or constant Mach number. CAS and Mach number are adjusted to minimize cost. The aerodynamic model used is the one proposed by Eurocontrol, which uses the BADA (Base of Aircraft Data) tables. This model is based on the total energy equation that determines the instantaneous fuel consumption. Calculations on each arc are done by solving a system of differential equations that systematically takes all costs into account. To compute the cost of an arc, we must know the time to go through it, which is generally unknown. To have well-posed boundary conditions, we use the horizontal displacement as the independent variable of the system of differential equations. We consider the velocity components of the wind in a 3D system of coordinates to compute the instantaneous ground speed of the aircraft. To consider the cost of time, we use the cost index. The cost of an arc depends on the aircraft mass at the beginning of this arc, and this mass depends on the path. As we consider all possible paths, the cost of an arc must be computed for each trajectory to which it belongs. For a long-distance flight, the number of arcs to be considered in the graph is large and therefore the cost of an arc is typically computed many times. Our algorithm computes the costs of one million arcs in seconds while having a high accuracy. The determination of the optimal trajectory can therefore be done in a short time. To get the optimal path, the mass of the aircraft at the departure point must also be optimal. It is therefore necessary to know the optimal amount of fuel for the journey. The aircraft mass is known only at the arrival point. This mass is the mass of the aircraft including passengers, cargo and reserve fuel mass. The optimal path is determined by calculating backwards, i.e. from the arrival point to the departure point. For the determination of the optimal trajectory, we use an elliptical grid that has focal points at the departure and arrival points. The use of this grid is essential for the construction of a direct and acyclic graph. We use the Bellman-Ford algorithm on a DAG to determine the shortest path. This algorithm is easy to implement and results in short computation times. Our algorithm computes an optimal trajectory with an optimal cost for each arc. Altitude changes are done optimally with respect to the mass of the aircraft and the cost of time. Our algorithm gives the mass, speed, altitude and total cost at any point of the trajectory as well as the optimal profiles of climb and descent. A prototype has been implemented in C. We made simulations of all types of possible arcs and of several complete trajectories to illustrate the behaviour of the algorithm.

[Studies on extraction process optimization of Panax notogingseng saponins].

PubMed

Qu, Lin-hai; Zheng, Ming; Lou, Yi-jia

2006-06-01

To optimize the conditions for the extraction of panax notogingseng saponins (PNS). After selected extraction solvent and suitable particle, we employed orthogonal experimental design to examine the conditions for the extraction by determination of PNS. Significant effect was observed only in extraction times. The optimum condition for extraction of PNS was to extract panax notogingseng (Burk.) F. H. Chen with 10 times 70% ethanol for 1.5 hours for 3 times.

Optimization of a UDP-glucuronosyltransferase assay for trout liver S9 fractions: Activity enhancement by alamethicin, a pore-forming peptide

EPA Science Inventory

An existing assay for hepatic UDP-glucuronosyltransferase (UGT) activity was optimized for use with trout liver S9 fractions. Individual experiments were conducted to determine the time dependence of UGT activity as well as optimal levels of S9 protein, uridine 5’-diphosph...

Optimizing the sequence of diameter distributions and selection harvests for uneven-aged stand management

Treesearch

Robert G. Haight; J. Douglas Brodie; Darius M. Adams

1985-01-01

The determination of an optimal sequence of diameter distributions and selection harvests for uneven-aged stand management is formulated as a discrete-time optimal-control problem with bounded control variables and free-terminal point. An efficient programming technique utilizing gradients provides solutions that are stable and interpretable on the basis of economic...

Optimal impulsive time-fixed orbital rendezvous and interception with path constraints

NASA Technical Reports Server (NTRS)

Taur, D.-R.; Prussing, J. E.; Coverstone-Carroll, V.

1990-01-01

Minimum-fuel, impulsive, time-fixed solutions are obtained for the problem of orbital rendezvous and interception with interior path constraints. Transfers between coplanar circular orbits in an inverse-square gravitational field are considered, subject to a circular path constraint representing a minimum or maximum permissible orbital radius. Primer vector theory is extended to incorporate path constraints. The optimal number of impulses, their times and positions, and the presence of initial or final coasting arcs are determined. The existence of constraint boundary arcs and boundary points is investigated as well as the optimality of a class of singular arc solutions. To illustrate the complexities introduced by path constraints, an analysis is made of optimal rendezvous in field-free space subject to a minimum radius constraint.

Optimization of integrated impeller mixer via radiotracer experiments.

PubMed

Othman, N; Kamarudin, S K; Takriff, M S; Rosli, M I; Engku Chik, E M F; Adnan, M A K

2014-01-01

Radiotracer experiments are carried out in order to determine the mean residence time (MRT) as well as percentage of dead zone, V dead (%), in an integrated mixer consisting of Rushton and pitched blade turbine (PBT). Conventionally, optimization was performed by varying one parameter and others were held constant (OFAT) which lead to enormous number of experiments. Thus, in this study, a 4-factor 3-level Taguchi L9 orthogonal array was introduced to obtain an accurate optimization of mixing efficiency with minimal number of experiments. This paper describes the optimal conditions of four process parameters, namely, impeller speed, impeller clearance, type of impeller, and sampling time, in obtaining MRT and V dead (%) using radiotracer experiments. The optimum conditions for the experiments were 100 rpm impeller speed, 50 mm impeller clearance, Type A mixer, and 900 s sampling time to reach optimization.

Optimizing model: insemination, replacement, seasonal production, and cash flow.

PubMed

DeLorenzo, M A; Spreen, T H; Bryan, G R; Beede, D K; Van Arendonk, J A

1992-03-01

Dynamic programming to solve the Markov decision process problem of optimal insemination and replacement decisions was adapted to address large dairy herd management decision problems in the US. Expected net present values of cow states (151,200) were used to determine the optimal policy. States were specified by class of parity (n = 12), production level (n = 15), month of calving (n = 12), month of lactation (n = 16), and days open (n = 7). Methodology optimized decisions based on net present value of an individual cow and all replacements over a 20-yr decision horizon. Length of decision horizon was chosen to ensure that optimal policies were determined for an infinite planning horizon. Optimization took 286 s of central processing unit time. The final probability transition matrix was determined, in part, by the optimal policy. It was estimated iteratively to determine post-optimization steady state herd structure, milk production, replacement, feed inputs and costs, and resulting cash flow on a calendar month and annual basis if optimal policies were implemented. Implementation of the model included seasonal effects on lactation curve shapes, estrus detection rates, pregnancy rates, milk prices, replacement costs, cull prices, and genetic progress. Other inputs included calf values, values of dietary TDN and CP per kilogram, and discount rate. Stochastic elements included conception (and, thus, subsequent freshening), cow milk production level within herd, and survival. Validation of optimized solutions was by separate simulation model, which implemented policies on a simulated herd and also described herd dynamics during transition to optimized structure.

Microelectrical Impedance Spectroscopy for the Differentiation between Normal and Cancerous Human Urothelial Cell Lines: Real-Time Electrical Impedance Measurement at an Optimal Frequency

PubMed Central

Park, Yangkyu; Kim, Hyeon Woo; Yun, Joho; Seo, Seungwan; Park, Chang-Ju; Lee, Jeong Zoo; Lee, Jong-Hyun

2016-01-01

Purpose. To distinguish between normal (SV-HUC-1) and cancerous (TCCSUP) human urothelial cell lines using microelectrical impedance spectroscopy (μEIS). Materials and Methods. Two types of μEIS devices were designed and used in combination to measure the impedance of SV-HUC-1 and TCCSUP cells flowing through the channels of the devices. The first device (μEIS-OF) was designed to determine the optimal frequency at which the impedance of two cell lines is most distinguishable. The μEIS-OF trapped the flowing cells and measured their impedance at a frequency ranging from 5 kHz to 1 MHz. The second device (μEIS-RT) was designed for real-time impedance measurement of the cells at the optimal frequency. The impedance was measured instantaneously as the cells passed the sensing electrodes of μEIS-RT. Results. The optimal frequency, which maximized the average difference of the amplitude and phase angle between the two cell lines (p < 0.001), was determined to be 119 kHz. The real-time impedance of the cell lines was measured at 119 kHz; the two cell lines differed significantly in terms of amplitude and phase angle (p < 0.001). Conclusion. The μEIS-RT can discriminate SV-HUC-1 and TCCSUP cells by measuring the impedance at the optimal frequency determined by the μEIS-OF. PMID:26998490

Optimal Strategy for Integrated Dynamic Inventory Control and Supplier Selection in Unknown Environment via Stochastic Dynamic Programming

NASA Astrophysics Data System (ADS)

Sutrisno; Widowati; Solikhin

2016-06-01

In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well.

Algorithm and Software for Calculating Optimal Regimes of the Process Water Supply System at the Kalininskaya NPP{sup 1}

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

Murav’ev, V. P., E-mail: murval@mail.ru; Kochetkov, A. V.; Glazova, E. G.

An algorithm and software for calculating the optimal operating regimes of the process water supply system at the Kalininskaya NPP are described. The parameters of the optimal regimes are determined for time varying meteorological conditions and condensation loads of the NPP. The optimal flow of the cooling water in the turbines is determined computationally; a regime map with the data on the optimal water consumption distribution between the coolers and displaying the regimes with an admissible heat load on the natural cooling lakes is composed. Optimizing the cooling system for a 4000-MW NPP will make it possible to conserve atmore » least 155,000 MW · h of electricity per year. The procedure developed can be used to optimize the process water supply systems of nuclear and thermal power plants.« less

Rapid optimization of tension distribution for cable-driven parallel manipulators with redundant cables

NASA Astrophysics Data System (ADS)

Ouyang, Bo; Shang, Weiwei

2016-03-01

The solution of tension distributions is infinite for cable-driven parallel manipulators(CDPMs) with redundant cables. A rapid optimization method for determining the optimal tension distribution is presented. The new optimization method is primarily based on the geometry properties of a polyhedron and convex analysis. The computational efficiency of the optimization method is improved by the designed projection algorithm, and a fast algorithm is proposed to determine which two of the lines are intersected at the optimal point. Moreover, a method for avoiding the operating point on the lower tension limit is developed. Simulation experiments are implemented on a six degree-of-freedom(6-DOF) CDPM with eight cables, and the results indicate that the new method is one order of magnitude faster than the standard simplex method. The optimal distribution of tension distribution is thus rapidly established on real-time by the proposed method.

Development and optimization of an energy-regenerative suspension system under stochastic road excitation

NASA Astrophysics Data System (ADS)

Huang, Bo; Hsieh, Chen-Yu; Golnaraghi, Farid; Moallem, Mehrdad

2015-11-01

In this paper a vehicle suspension system with energy harvesting capability is developed, and an analytical methodology for the optimal design of the system is proposed. The optimization technique provides design guidelines for determining the stiffness and damping coefficients aimed at the optimal performance in terms of ride comfort and energy regeneration. The corresponding performance metrics are selected as root-mean-square (RMS) of sprung mass acceleration and expectation of generated power. The actual road roughness is considered as the stochastic excitation defined by ISO 8608:1995 standard road profiles and used in deriving the optimization method. An electronic circuit is proposed to provide variable damping in the real-time based on the optimization rule. A test-bed is utilized and the experiments under different driving conditions are conducted to verify the effectiveness of the proposed method. The test results suggest that the analytical approach is credible in determining the optimality of system performance.

Optimization and Improvement of Test Processes on a Production Line

NASA Astrophysics Data System (ADS)

Sujová, Erika; Čierna, Helena

2018-06-01

The paper deals with increasing processes efficiency at a production line of cylinder heads of engines in a production company operating in the automotive industry. The goal is to achieve improvement and optimization of test processes on a production line. It analyzes options for improving capacity, availability and productivity of processes of an output test by using modern technology available on the market. We have focused on analysis of operation times before and after optimization of test processes at specific production sections. By analyzing measured results we have determined differences in time before and after improvement of the process. We have determined a coefficient of efficiency OEE and by comparing outputs we have confirmed real improvement of the process of the output test of cylinder heads.

Algorithm comparison for schedule optimization in MR fingerprinting.

PubMed

Cohen, Ouri; Rosen, Matthew S

2017-09-01

In MR Fingerprinting, the flip angles and repetition times are chosen according to a pseudorandom schedule. In previous work, we have shown that maximizing the discrimination between different tissue types by optimizing the acquisition schedule allows reductions in the number of measurements required. The ideal optimization algorithm for this application remains unknown, however. In this work we examine several different optimization algorithms to determine the one best suited for optimizing MR Fingerprinting acquisition schedules. Copyright © 2017 Elsevier Inc. All rights reserved.

Spectrophotometric determination of fluoxetine by molecularly imprinted polypyrrole and optimization by experimental design, artificial neural network and genetic algorithm.

PubMed

Nezhadali, Azizollah; Motlagh, Maryam Omidvar; Sadeghzadeh, Samira

2018-02-05

A selective method based on molecularly imprinted polymer (MIP) solid-phase extraction (SPE) using UV-Vis spectrophotometry as a detection technique was developed for the determination of fluoxetine (FLU) in pharmaceutical and human serum samples. The MIPs were synthesized using pyrrole as a functional monomer in the presence of FLU as a template molecule. The factors that affecting the preparation and extraction ability of MIP such as amount of sorbent, initiator concentration, the amount of monomer to template ratio, uptake shaking rate, uptake time, washing buffer pH, take shaking rate, Taking time and polymerization time were considered for optimization. First a Plackett-Burman design (PBD) consists of 12 randomized runs were applied to determine the influence of each factor. The other optimization processes were performed using central composite design (CCD), artificial neural network (ANN) and genetic algorithm (GA). At optimal condition the calibration curve showed linearity over a concentration range of 10 -7 -10 -8 M with a correlation coefficient (R 2 ) of 0.9970. The limit of detection (LOD) for FLU was obtained 6.56×10 -9 M. The repeatability of the method was obtained 1.61%. The synthesized MIP sorbent showed a good selectivity and sensitivity toward FLU. The MIP/SPE method was used for the determination of FLU in pharmaceutical, serum and plasma samples, successfully. Copyright © 2017 Elsevier B.V. All rights reserved.

Sandia Internship Fall 2014

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

Kuhn, Joshua

2015-01-01

While working at Sandia National Laboratories as a graduate intern from September 2014 to January 2015, most of my time was spent on two projects. The first project involved designing a test fixture for circuit boards used in a recording device. The test fixture was needed to decrease test set up time. The second project was to use optimization techniques to determine the optimal G-Switch for given acceleration profiles.

Seamline Determination Based on PKGC Segmentation for Remote Sensing Image Mosaicking

PubMed Central

Dong, Qiang; Liu, Jinghong

2017-01-01

This paper presents a novel method of seamline determination for remote sensing image mosaicking. A two-level optimization strategy is applied to determine the seamline. Object-level optimization is executed firstly. Background regions (BRs) and obvious regions (ORs) are extracted based on the results of parametric kernel graph cuts (PKGC) segmentation. The global cost map which consists of color difference, a multi-scale morphological gradient (MSMG) constraint, and texture difference is weighted by BRs. Finally, the seamline is determined in the weighted cost from the start point to the end point. Dijkstra’s shortest path algorithm is adopted for pixel-level optimization to determine the positions of seamline. Meanwhile, a new seamline optimization strategy is proposed for image mosaicking with multi-image overlapping regions. The experimental results show the better performance than the conventional method based on mean-shift segmentation. Seamlines based on the proposed method bypass the obvious objects and take less time in execution. This new method is efficient and superior for seamline determination in remote sensing image mosaicking. PMID:28749446

Safe Onboard Guidance and Control Under Probabilistic Uncertainty

NASA Technical Reports Server (NTRS)

Blackmore, Lars James

2011-01-01

An algorithm was developed that determines the fuel-optimal spacecraft guidance trajectory that takes into account uncertainty, in order to guarantee that mission safety constraints are satisfied with the required probability. The algorithm uses convex optimization to solve for the optimal trajectory. Convex optimization is amenable to onboard solution due to its excellent convergence properties. The algorithm is novel because, unlike prior approaches, it does not require time-consuming evaluation of multivariate probability densities. Instead, it uses a new mathematical bounding approach to ensure that probability constraints are satisfied, and it is shown that the resulting optimization is convex. Empirical results show that the approach is many orders of magnitude less conservative than existing set conversion techniques, for a small penalty in computation time.

Application of the experimental design of experiments (DoE) for the determination of organotin compounds in water samples using HS-SPME and GC-MS/MS.

PubMed

Coscollà, Clara; Navarro-Olivares, Santiago; Martí, Pedro; Yusà, Vicent

2014-02-01

When attempting to discover the important factors and then optimise a response by tuning these factors, experimental design (design of experiments, DoE) gives a powerful suite of statistical methodology. DoE identify significant factors and then optimise a response with respect to them in method development. In this work, a headspace-solid-phase micro-extraction (HS-SPME) combined with gas chromatography tandem mass spectrometry (GC-MS/MS) methodology for the simultaneous determination of six important organotin compounds namely monobutyltin (MBT), dibutyltin (DBT), tributyltin (TBT), monophenyltin (MPhT), diphenyltin (DPhT), triphenyltin (TPhT) has been optimized using a statistical design of experiments (DOE). The analytical method is based on the ethylation with NaBEt4 and simultaneous headspace-solid-phase micro-extraction of the derivative compounds followed by GC-MS/MS analysis. The main experimental parameters influencing the extraction efficiency selected for optimization were pre-incubation time, incubation temperature, agitator speed, extraction time, desorption temperature, buffer (pH, concentration and volume), headspace volume, sample salinity, preparation of standards, ultrasonic time and desorption time in the injector. The main factors (excitation voltage, excitation time, ion source temperature, isolation time and electron energy) affecting the GC-IT-MS/MS response were also optimized using the same statistical design of experiments. The proposed method presented good linearity (coefficient of determination R(2)>0.99) and repeatibilty (1-25%) for all the compounds under study. The accuracy of the method measured as the average percentage recovery of the compounds in spiked surface and marine waters was higher than 70% for all compounds studied. Finally, the optimized methodology was applied to real aqueous samples enabled the simultaneous determination of all compounds under study in surface and marine water samples obtained from Valencia region (Spain). © 2013 Elsevier B.V. All rights reserved.

Optimal replenishment and credit policy in supply chain inventory model under two levels of trade credit with time- and credit-sensitive demand involving default risk

NASA Astrophysics Data System (ADS)

Mahata, Puspita; Mahata, Gour Chandra; Kumar De, Sujit

2018-03-01

Traditional supply chain inventory modes with trade credit usually only assumed that the up-stream suppliers offered the down-stream retailers a fixed credit period. However, in practice the retailers will also provide a credit period to customers to promote the market competition. In this paper, we formulate an optimal supply chain inventory model under two levels of trade credit policy with default risk consideration. Here, the demand is assumed to be credit-sensitive and increasing function of time. The major objective is to determine the retailer's optimal credit period and cycle time such that the total profit per unit time is maximized. The existence and uniqueness of the optimal solution to the presented model are examined, and an easy method is also shown to find the optimal inventory policies of the considered problem. Finally, numerical examples and sensitive analysis are presented to illustrate the developed model and to provide some managerial insights.

Multi-objective trajectory optimization for the space exploration vehicle

NASA Astrophysics Data System (ADS)

Qin, Xiaoli; Xiao, Zhen

2016-07-01

The research determines temperature-constrained optimal trajectory for the space exploration vehicle by developing an optimal control formulation and solving it using a variable order quadrature collocation method with a Non-linear Programming(NLP) solver. The vehicle is assumed to be the space reconnaissance aircraft that has specified takeoff/landing locations, specified no-fly zones, and specified targets for sensor data collections. A three degree of freedom aircraft model is adapted from previous work and includes flight dynamics, and thermal constraints.Vehicle control is accomplished by controlling angle of attack, roll angle, and propellant mass flow rate. This model is incorporated into an optimal control formulation that includes constraints on both the vehicle and mission parameters, such as avoidance of no-fly zones and exploration of space targets. In addition, the vehicle models include the environmental models(gravity and atmosphere). How these models are appropriately employed is key to gaining confidence in the results and conclusions of the research. Optimal trajectories are developed using several performance costs in the optimal control formation,minimum time,minimum time with control penalties,and maximum distance.The resulting analysis demonstrates that optimal trajectories that meet specified mission parameters and constraints can be quickly determined and used for large-scale space exloration.

Single machine total completion time minimization scheduling with a time-dependent learning effect and deteriorating jobs

NASA Astrophysics Data System (ADS)

Wang, Ji-Bo; Wang, Ming-Zheng; Ji, Ping

2012-05-01

In this article, we consider a single machine scheduling problem with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the job processing time is defined by a function of its starting time and total normal processing time of jobs in front of it in the sequence. The objective is to determine an optimal schedule so as to minimize the total completion time. This problem remains open for the case of -1 < a < 0, where a denotes the learning index; we show that an optimal schedule of the problem is V-shaped with respect to job normal processing times. Three heuristic algorithms utilising the V-shaped property are proposed, and computational experiments show that the last heuristic algorithm performs effectively and efficiently in obtaining near-optimal solutions.

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

PubMed Central

Jin, Junchen

2016-01-01

The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality. PMID:27436998

Effect of nucleation time on bending response of ionic polymer–metal composite actuators

DOE PAGES

Kim, Suran; Hong, Seungbum; Choi, Yoon-Young; ...

2013-07-02

We attempted an autocatalytic electro-less plating of nickel in order to replace an electroless impregnation-reduction (IR) method in ionic polymer–metal composite (IPMC) actuators to reduce cost and processing time. Because nucleation time of Pd–Sn colloids is the determining factor of overall processing time, we used the nucleation time as our control parameter. In order to optimize nucleation time and investigate its effect on the performance of IPMC actuators, we analyzed the relationship between the nucleation time, interface morphology and electrical properties. The optimized nucleation time was 10 h. Furthermore, the trends of the performance and electrical properties as a functionmore » of nucleation time were attributed to the fact that the Ni penetration depth was determined by the minimum diffusion length of either Pd–Sn colloids or reducing agent ions. The Ni-IPMC actuators can be fabricated less than 14 h processing time without deteriorating performance of the actuators, which is comparable to Pt-IPMC prepared by IR method.« less

Time-of-flight measurement of ionic species generated during ablation for optimization of focusing condition at free-electron laser beamline

NASA Astrophysics Data System (ADS)

Senba, Y.; Nagasono, M.; Koyama, T.; Yumoto, H.; Ohashi, H.; Tono, K.; Togashi, T.; Inubushi, Y.; Sato, T.; Yabashi, M.; Ishikawa, T.

2013-03-01

Optimization of focusing conditions is important in free-electron laser applications. A time-of-flight mass analyzer has been designed and constructed for this purpose. The time-of-flight spectra of ionic species evolved from laser ablation of gold were measured. The yields of ionic species showed strong correlations with free-electron-laser intensity. This method conveniently allows for direct estimation of laser intensity on sample and determination of focusing position.

Application’s Method of Quadratic Programming for Optimization of Portfolio Selection

NASA Astrophysics Data System (ADS)

Kawamoto, Shigeru; Takamoto, Masanori; Kobayashi, Yasuhiro

Investors or fund-managers face with optimization of portfolio selection, which means that determine the kind and the quantity of investment among several brands. We have developed a method to obtain optimal stock’s portfolio more rapidly from twice to three times than conventional method with efficient universal optimization. The method is characterized by quadratic matrix of utility function and constrained matrices divided into several sub-matrices by focusing on structure of these matrices.

Optimizing preventive maintenance policy: A data-driven application for a light rail braking system.

PubMed

Corman, Francesco; Kraijema, Sander; Godjevac, Milinko; Lodewijks, Gabriel

2017-10-01

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.

Optimizing preventive maintenance policy: A data-driven application for a light rail braking system

PubMed Central

Corman, Francesco; Kraijema, Sander; Godjevac, Milinko; Lodewijks, Gabriel

2017-01-01

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions. PMID:29278245

How to formulate and solve "optimal stand density over time" problems for even-aged stands using dynamic programming.

Treesearch

Chung M. Chen; Dietmar W. Rose; Rolfe A. Leary

1980-01-01

Describes how dynamic programming can be used to solve optimal stand density problems when yields are given by prior simulation or by a new stand growth equation that is a function of the decision variable. Formulations of the latter type allow use of a calculus-based search procedure; they determine exact optimal residual density at each stage.

Determination of proline in honey: comparison between official methods, optimization and validation of the analytical methodology.

PubMed

Truzzi, Cristina; Annibaldi, Anna; Illuminati, Silvia; Finale, Carolina; Scarponi, Giuseppe

2014-05-01

The study compares official spectrophotometric methods for the determination of proline content in honey - those of the International Honey Commission (IHC) and the Association of Official Analytical Chemists (AOAC) - with the original Ough method. Results show that the extra time-consuming treatment stages added by the IHC method with respect to the Ough method are pointless. We demonstrate that the AOACs method proves to be the best in terms of accuracy and time saving. The optimized waiting time for the absorbance recording is set at 35min from the removal of reaction tubes from the boiling bath used in the sample treatment. The optimized method was validated in the matrix: linearity up to 1800mgL(-1), limit of detection 20mgL(-1), limit of quantification 61mgL(-1). The method was applied to 43 unifloral honey samples from the Marche region, Italy. Copyright © 2013 Elsevier Ltd. All rights reserved.

Abort Options for Human Missions to Earth-Moon Halo Orbits

NASA Technical Reports Server (NTRS)

Jesick, Mark C.

2013-01-01

Abort trajectories are optimized for human halo orbit missions about the translunar libration point (L2), with an emphasis on the use of free return trajectories. Optimal transfers from outbound free returns to L2 halo orbits are numerically optimized in the four-body ephemeris model. Circumlunar free returns are used for direct transfers, and cislunar free returns are used in combination with lunar gravity assists to reduce propulsive requirements. Trends in orbit insertion cost and flight time are documented across the southern L2 halo family as a function of halo orbit position and free return flight time. It is determined that the maximum amplitude southern halo incurs the lowest orbit insertion cost for direct transfers but the maximum cost for lunar gravity assist transfers. The minimum amplitude halo is the most expensive destination for direct transfers but the least expensive for lunar gravity assist transfers. The on-orbit abort costs for three halos are computed as a function of abort time and return time. Finally, an architecture analysis is performed to determine launch and on-orbit vehicle requirements for halo orbit missions.

Comparison of Low-Thrust Control Laws for Application in Planetocentric Space

NASA Technical Reports Server (NTRS)

Falck, Robert D.; Sjauw, Waldy K.; Smith, David A.

2014-01-01

Recent interest at NASA for the application of solar electric propulsion for the transfer of significant payloads in cislunar space has led to the development of high-fidelity simulations of such missions. With such transfers involving transfer times on the order of months, simulation time can be significant. In the past, the examination of such missions typically began with the use of lower-fidelity trajectory optimization tools such as SEPSPOT to develop and tune guidance laws which delivered optimal or near- optimal trajectories, where optimal is generally defined as minimizing propellant expenditure or time of flight. The transfer of these solutions to a high-fidelity simulation is typically an iterative process whereby the initial solution may nearly, but not precisely, meet mission objectives. Further tuning of the guidance algorithm is typically necessary when accounting for high-fidelity perturbations such as those due to more detailed gravity models, secondary-body effects, solar radiation pressure, etc. While trajectory optimization is a useful method for determining optimal performance metrics, algorithms which deliver nearly optimal performance with minimal tuning are an attractive alternative.

Scheduling Jobs with Variable Job Processing Times on Unrelated Parallel Machines

PubMed Central

Zhang, Guang-Qian; Wang, Jian-Jun; Liu, Ya-Jing

2014-01-01

m unrelated parallel machines scheduling problems with variable job processing times are considered, where the processing time of a job is a function of its position in a sequence, its starting time, and its resource allocation. The objective is to determine the optimal resource allocation and the optimal schedule to minimize a total cost function that dependents on the total completion (waiting) time, the total machine load, the total absolute differences in completion (waiting) times on all machines, and total resource cost. If the number of machines is a given constant number, we propose a polynomial time algorithm to solve the problem. PMID:24982933

Optimal correction and design parameter search by modern methods of rigorous global optimization

NASA Astrophysics Data System (ADS)

Makino, K.; Berz, M.

2011-07-01

Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle optics for the computation of aberrations allow the determination of particularly sharp underestimators for large regions. As a consequence, the subsequent progressive pruning of the allowed search space as part of the optimization progresses is carried out particularly effectively. The end result is the rigorous determination of the single or multiple optimal solutions of the parameter optimization, regardless of their location, their number, and the starting values of optimization. The methods are particularly powerful if executed in interplay with genetic optimizers generating their new populations within the currently active unpruned space. Their current best guess provides rigorous upper bounds of the minima, which can then beneficially be used for better pruning. Examples of the method and its performance will be presented, including the determination of all operating points of desired tunes or chromaticities, etc. in storage ring lattices.

Self-adaptive multimethod optimization applied to a tailored heating forging process

NASA Astrophysics Data System (ADS)

Baldan, M.; Steinberg, T.; Baake, E.

2018-05-01

The presented paper describes an innovative self-adaptive multi-objective optimization code. Investigation goals concern proving the superiority of this code compared to NGSA-II and applying it to an inductor’s design case study addressed to a “tailored” heating forging application. The choice of the frequency and the heating time are followed by the determination of the turns number and their positions. Finally, a straightforward optimization is performed in order to minimize energy consumption using “optimal control”.

A computerized traffic control algorithm to determine optimal traffic signal settings. Ph.D. Thesis - Toledo Univ.

NASA Technical Reports Server (NTRS)

Seldner, K.

1977-01-01

An algorithm was developed to optimally control the traffic signals at each intersection using a discrete time traffic model applicable to heavy or peak traffic. Off line optimization procedures were applied to compute the cycle splits required to minimize the lengths of the vehicle queues and delay at each intersection. The method was applied to an extensive traffic network in Toledo, Ohio. Results obtained with the derived optimal settings are compared with the control settings presently in use.

Efficient sensitivity analysis and optimization of a helicopter rotor

NASA Technical Reports Server (NTRS)

Lim, Joon W.; Chopra, Inderjit

1989-01-01

Aeroelastic optimization of a system essentially consists of the determination of the optimum values of design variables which minimize the objective function and satisfy certain aeroelastic and geometric constraints. The process of aeroelastic optimization analysis is illustrated. To carry out aeroelastic optimization effectively, one needs a reliable analysis procedure to determine steady response and stability of a rotor system in forward flight. The rotor dynamic analysis used in the present study developed inhouse at the University of Maryland is based on finite elements in space and time. The analysis consists of two major phases: vehicle trim and rotor steady response (coupled trim analysis), and aeroelastic stability of the blade. For a reduction of helicopter vibration, the optimization process requires the sensitivity derivatives of the objective function and aeroelastic stability constraints. For this, the derivatives of steady response, hub loads and blade stability roots are calculated using a direct analytical approach. An automated optimization procedure is developed by coupling the rotor dynamic analysis, design sensitivity analysis and constrained optimization code CONMIN.

Multivariate optimization of a headspace solid-phase microextraction method followed by gas chromatography with mass spectrometry for the determination of terpenes in Nicotiana langsdorffii.

PubMed

Ardini, Francisco; Carro, Marina Di; Abelmoschi, Maria Luisa; Grotti, Marco; Magi, Emanuele

2014-07-01

A simple and sensitive procedure based on headspace solid-phase microextraction and gas chromatography with mass spectrometry was developed for the determination of five terpenes (α-pinene, limonene, linalool, α-terpineol, and geraniol) in the leaves of Nicotiana langsdorffii. The microextraction conditions (extraction temperature, equilibration time, and extraction time) were optimized by means of a Doehlert design. The experimental design showed that, for α-pinene and limonene, a low temperature and a long extraction time were needed for optimal extraction, while linalool, α-terpineol, and geraniol required a high temperature and a long extraction time. The chosen compromise conditions were temperature 60°C, equilibration time 15 min and extraction time 50 min. The main analytical figures of the optimized method were evaluated; LODs ranged from 0.07 ng/g (α-pinene) to 8.0 ng/g (geraniol), while intraday and interday repeatability were in the range 10-17% and 9-13%, respectively. Finally, the procedure was applied to in vitro wild-type and transgenic specimens of N. langsdorffii subjected to abiotic stresses (chemical and heat stress). With the exception of geraniol (75-374 ng/g), low concentration levels of terpenes were measured (ng/g level or lower); some interesting variations in terpene concentration induced by abiotic stress were observed. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Label-Free Toxin Detection by Means of Time-Resolved Electrochemical Impedance Spectroscopy

PubMed Central

Chai, Changhoon; Takhistov, Paul

2010-01-01

The real-time detection of trace concentrations of biological toxins requires significant improvement of the detection methods from those reported in the literature. To develop a highly sensitive and selective detection device it is necessary to determine the optimal measuring conditions for the electrochemical sensor in three domains: time, frequency and polarization potential. In this work we utilized a time-resolved electrochemical impedance spectroscopy for the detection of trace concentrations of Staphylococcus enterotoxin B (SEB). An anti-SEB antibody has been attached to the nano-porous aluminum surface using 3-aminopropyltriethoxysilane/glutaraldehyde coupling system. This immobilization method allows fabrication of a highly reproducible and stable sensing device. Using developed immobilization procedure and optimized detection regime, it is possible to determine the presence of SEB at the levels as low as 10 pg/mL in 15 minutes. PMID:22315560

Cure Cycle Optimization of Rapidly Cured Out-Of-Autoclave Composites.

PubMed

Dong, Anqi; Zhao, Yan; Zhao, Xinqing; Yu, Qiyong

2018-03-13

Out-of-autoclave prepreg typically needs a long cure cycle to guarantee good properties as the result of low processing pressure applied. It is essential to reduce the manufacturing time, achieve real cost reduction, and take full advantage of out-of-autoclave process. The focus of this paper is to reduce the cure cycle time and production cost while maintaining high laminate quality. A rapidly cured out-of-autoclave resin and relative prepreg were independently developed. To determine a suitable rapid cure procedure for the developed prepreg, the effect of heating rate, initial cure temperature, dwelling time, and post-cure time on the final laminate quality were evaluated and the factors were then optimized. As a result, a rapid cure procedure was determined. The results showed that the resin infiltration could be completed at the end of the initial cure stage and no obvious void could be seen in the laminate at this time. The laminate could achieve good internal quality using the optimized cure procedure. The mechanical test results showed that the laminates had a fiber volume fraction of 59-60% with a final glass transition temperature of 205 °C and excellent mechanical strength especially the flexural properties.

Cure Cycle Optimization of Rapidly Cured Out-Of-Autoclave Composites

PubMed Central

Dong, Anqi; Zhao, Yan; Zhao, Xinqing; Yu, Qiyong

2018-01-01

Out-of-autoclave prepreg typically needs a long cure cycle to guarantee good properties as the result of low processing pressure applied. It is essential to reduce the manufacturing time, achieve real cost reduction, and take full advantage of out-of-autoclave process. The focus of this paper is to reduce the cure cycle time and production cost while maintaining high laminate quality. A rapidly cured out-of-autoclave resin and relative prepreg were independently developed. To determine a suitable rapid cure procedure for the developed prepreg, the effect of heating rate, initial cure temperature, dwelling time, and post-cure time on the final laminate quality were evaluated and the factors were then optimized. As a result, a rapid cure procedure was determined. The results showed that the resin infiltration could be completed at the end of the initial cure stage and no obvious void could be seen in the laminate at this time. The laminate could achieve good internal quality using the optimized cure procedure. The mechanical test results showed that the laminates had a fiber volume fraction of 59–60% with a final glass transition temperature of 205 °C and excellent mechanical strength especially the flexural properties. PMID:29534048

Substrate effects on pupation and adult emergence of Hermetia illucens (Diptera: Stratiomyidae).

PubMed

Holmes, L A; Vanlaerhoven, S L; Tomberlin, J K

2013-04-01

Black soldier flies, Hermetia illucens (L.) (Diptera: Stratiomyidae), are of particular interest for their applications in waste management. Feeding on decaying organic waste, black soldier flies successfully reduce manure in confined animal feeding operations of poultry, swine, and cattle. To optimize waste conversion in confined animal feeding operations and landfill facilities, it is imperative to optimize black soldier fly development. Unfortunately, black soldier flies only convert waste during their larval feeding stages and therefore it is of interest to optimize the nonfeeding stages of development, specifically, the postfeeding and pupal stages. The time spent in these stages is thought to be determined by the pupation substrate encountered by the postfeeding larvae. The objective of this study was to determine the effect different pupation substrates have on postfeeding development time, pupation time, and adult emergence success. Five pupation substrates were compared: wood shavings, potting soil, topsoil, sand, and nothing. Postfeeding larvae took longer to reach pupation in the absence of a pupation substrate, although reaching pupation in the shortest time in potting soil and wood shavings. The time spent in the pupal stage was shortest in the absence of a pupation substrate. However, fewer adults emerged when a pupation substrate was not provided.

Optimizing hydraulic retention times in denitrifying woodchip bioreactors treating recirculating aquaculture system wastewater

USDA-ARS?s Scientific Manuscript database

The performance of wood-based denitrifying bioreactors to treat high-nitrate wastewaters from aquaculture systems has not previously been demonstrated. Four pilot-scale woodchip bioreactors (approximately 1:10 scale) were constructed and operated for 268 d to determine the optimal range of design hy...

An innovative time-cost-quality tradeoff modeling of building construction project based on resource allocation.

PubMed

Hu, Wenfa; He, Xinhua

2014-01-01

The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated.

Spatial and temporal optimization in habitat placement for a threatened plant: the case of the western prairie fringed orchid

Treesearch

John Hof; Carolyn Hull Sieg; Michael Bevers

1999-01-01

This paper investigates an optimization approach to determining the placement and timing of habitat protection for the western prairie fringed orchid. This plant’s population dynamics are complex, creating a challenging optimization problem. The sensitivity of the orchid to random climate conditions is handled probabilistically. The plant’s seed, protocorm and above-...

Adjustable control station with movable monitors and cameras for viewing systems in robotics and teleoperations

NASA Technical Reports Server (NTRS)

Diner, Daniel B. (Inventor)

1994-01-01

Real-time video presentations are provided in the field of operator-supervised automation and teleoperation, particularly in control stations having movable cameras for optimal viewing of a region of interest in robotics and teleoperations for performing different types of tasks. Movable monitors to match the corresponding camera orientations (pan, tilt, and roll) are provided in order to match the coordinate systems of all the monitors to the operator internal coordinate system. Automated control of the arrangement of cameras and monitors, and of the configuration of system parameters, is provided for optimal viewing and performance of each type of task for each operator since operators have different individual characteristics. The optimal viewing arrangement and system parameter configuration is determined and stored for each operator in performing each of many types of tasks in order to aid the automation of setting up optimal arrangements and configurations for successive tasks in real time. Factors in determining what is optimal include the operator's ability to use hand-controllers for each type of task. Robot joint locations, forces and torques are used, as well as the operator's identity, to identify the current type of task being performed in order to call up a stored optimal viewing arrangement and system parameter configuration.

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah

PubMed Central

Tian, Le; Latré, Steven

2017-01-01

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks. PMID:28677617

Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.

PubMed

Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen

2017-07-04

IEEE 802.11ah, marketed as Wi-Fi HaLow, extends Wi-Fi to the sub-1 GHz spectrum. Through a number of physical layer (PHY) and media access control (MAC) optimizations, it aims to bring greatly increased range, energy-efficiency, and scalability. This makes 802.11ah the perfect candidate for providing connectivity to Internet of Things (IoT) devices. One of these new features, referred to as the Restricted Access Window (RAW), focuses on improving scalability in highly dense deployments. RAW divides stations into groups and reduces contention and collisions by only allowing channel access to one group at a time. However, the standard does not dictate how to determine the optimal RAW grouping parameters. The optimal parameters depend on the current network conditions, and it has been shown that incorrect configuration severely impacts throughput, latency and energy efficiency. In this paper, we propose a traffic-adaptive RAW optimization algorithm (TAROA) to adapt the RAW parameters in real time based on the current traffic conditions, optimized for sensor networks in which each sensor transmits packets with a certain (predictable) frequency and may change the transmission frequency over time. The TAROA algorithm is executed at each target beacon transmission time (TBTT), and it first estimates the packet transmission interval of each station only based on packet transmission information obtained by access point (AP) during the last beacon interval. Then, TAROA determines the RAW parameters and assigns stations to RAW slots based on this estimated transmission frequency. The simulation results show that, compared to enhanced distributed channel access/distributed coordination function (EDCA/DCF), the TAROA algorithm can highly improve the performance of IEEE 802.11ah dense networks in terms of throughput, especially when hidden nodes exist, although it does not always achieve better latency performance. This paper contributes with a practical approach to optimizing RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks.

Importance of the Time Interval between Bowel Preparation and Colonoscopy in Determining the Quality of Bowel Preparation for Full-Dose Polyethylene Glycol Preparation

PubMed Central

Kim, Tae Kyung; Kim, Hyung Wook; Kim, Su Jin; Ha, Jong Kun; Jang, Hyung Ha; Hong, Young Mi; Park, Su Bum; Choi, Cheol Woong; Kang, Dae Hwan

2014-01-01

Background/Aims The quality of bowel preparation (QBP) is the important factor in performing a successful colonoscopy. Several factors influencing QBP have been reported; however, some factors, such as the optimal preparation-to-colonoscopy time interval, remain controversial. This study aimed to determine the factors influencing QBP and the optimal time interval for full-dose polyethylene glycol (PEG) preparation. Methods A total of 165 patients who underwent colonoscopy from June 2012 to August 2012 were prospectively evaluated. The QBP was assessed using the Ottawa Bowel Preparation Scale (Ottawa) score according to several factors influencing the QBP were analyzed. Results Colonoscopies with a time interval of 5 to 6 hours had the best Ottawa score in all parts of the colon. Patients with time intervals of 6 hours or less had the better QBP than those with time intervals of more than 6 hours (p=0.046). In the multivariate analysis, the time interval (odds ratio, 1.897; 95% confidence interval, 1.006 to 3.577; p=0.048) was the only significant contributor to a satisfactory bowel preparation. Conclusions The optimal time was 5 to 6 hours for the full-dose PEG method, and the time interval was the only significant contributor to a satisfactory bowel preparation. PMID:25368750

Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds

NASA Technical Reports Server (NTRS)

Jardin, Matthew R.

2004-01-01

A computationally efficient algorithm for minimizing the flight time of an aircraft in a variable wind field has been invented. The algorithm, referred to as Neighboring Optimal Wind Routing (NOWR), is based upon neighboring-optimal-control (NOC) concepts and achieves minimum-time paths by adjusting aircraft heading according to wind conditions at an arbitrary number of wind measurement points along the flight route. The NOWR algorithm may either be used in a fast-time mode to compute minimum- time routes prior to flight, or may be used in a feedback mode to adjust aircraft heading in real-time. By traveling minimum-time routes instead of direct great-circle (direct) routes, flights across the United States can save an average of about 7 minutes, and as much as one hour of flight time during periods of strong jet-stream winds. The neighboring optimal routes computed via the NOWR technique have been shown to be within 1.5 percent of the absolute minimum-time routes for flights across the continental United States. On a typical 450-MHz Sun Ultra workstation, the NOWR algorithm produces complete minimum-time routes in less than 40 milliseconds. This corresponds to a rate of 25 optimal routes per second. The closest comparable optimization technique runs approximately 10 times slower. Airlines currently use various trial-and-error search techniques to determine which of a set of commonly traveled routes will minimize flight time. These algorithms are too computationally expensive for use in real-time systems, or in systems where many optimal routes need to be computed in a short amount of time. Instead of operating in real-time, airlines will typically plan a trajectory several hours in advance using wind forecasts. If winds change significantly from forecasts, the resulting flights will no longer be minimum-time. The need for a computationally efficient wind-optimal routing algorithm is even greater in the case of new air-traffic-control automation concepts. For air-traffic-control automation, thousands of wind-optimal routes may need to be computed and checked for conflicts in just a few minutes. These factors motivated the need for a more efficient wind-optimal routing algorithm.

A multimodal logistics service network design with time windows and environmental concerns

PubMed Central

Zhang, Dezhi; He, Runzhong; Wang, Zhongwei

2017-01-01

The design of a multimodal logistics service network with customer service time windows and environmental costs is an important and challenging issue. Accordingly, this work established a model to minimize the total cost of multimodal logistics service network design with time windows and environmental concerns. The proposed model incorporates CO2 emission costs to determine the optimal transportation mode combinations and investment selections for transfer nodes, which consider transport cost, transport time, carbon emission, and logistics service time window constraints. Furthermore, genetic and heuristic algorithms are proposed to set up the abovementioned optimal model. A numerical example is provided to validate the model and the abovementioned two algorithms. Then, comparisons of the performance of the two algorithms are provided. Finally, this work investigates the effects of the logistics service time windows and CO2 emission taxes on the optimal solution. Several important management insights are obtained. PMID:28934272

A multimodal logistics service network design with time windows and environmental concerns.

PubMed

Zhang, Dezhi; He, Runzhong; Li, Shuangyan; Wang, Zhongwei

2017-01-01

The design of a multimodal logistics service network with customer service time windows and environmental costs is an important and challenging issue. Accordingly, this work established a model to minimize the total cost of multimodal logistics service network design with time windows and environmental concerns. The proposed model incorporates CO2 emission costs to determine the optimal transportation mode combinations and investment selections for transfer nodes, which consider transport cost, transport time, carbon emission, and logistics service time window constraints. Furthermore, genetic and heuristic algorithms are proposed to set up the abovementioned optimal model. A numerical example is provided to validate the model and the abovementioned two algorithms. Then, comparisons of the performance of the two algorithms are provided. Finally, this work investigates the effects of the logistics service time windows and CO2 emission taxes on the optimal solution. Several important management insights are obtained.

Mum, why do you keep on growing? Impacts of environmental variability on optimal growth and reproduction allocation strategies of annual plants.

PubMed

De Lara, Michel

2006-05-01

In their 1990 paper Optimal reproductive efforts and the timing of reproduction of annual plants in randomly varying environments, Amir and Cohen considered stochastic environments consisting of i.i.d. sequences in an optimal allocation discrete-time model. We suppose here that the sequence of environmental factors is more generally described by a Markov chain. Moreover, we discuss the connection between the time interval of the discrete-time dynamic model and the ability of the plant to rebuild completely its vegetative body (from reserves). We formulate a stochastic optimization problem covering the so-called linear and logarithmic fitness (corresponding to variation within and between years), which yields optimal strategies. For "linear maximizers'', we analyse how optimal strategies depend upon the environmental variability type: constant, random stationary, random i.i.d., random monotonous. We provide general patterns in terms of targets and thresholds, including both determinate and indeterminate growth. We also provide a partial result on the comparison between ;"linear maximizers'' and "log maximizers''. Numerical simulations are provided, allowing to give a hint at the effect of different mathematical assumptions.

Determination of optimal self-drive tourism route using the orienteering problem method

NASA Astrophysics Data System (ADS)

Hashim, Zakiah; Ismail, Wan Rosmanira; Ahmad, Norfaieqah

2013-04-01

This paper was conducted to determine the optimal travel routes for self-drive tourism based on the allocation of time and expense by maximizing the amount of attraction scores assigned to each city involved. Self-drive tourism represents a type of tourism where tourists hire or travel by their own vehicle. It only involves a tourist destination which can be linked with a network of roads. Normally, the traveling salesman problem (TSP) and multiple traveling salesman problems (MTSP) method were used in the minimization problem such as determination the shortest time or distance traveled. This paper involved an alternative approach for maximization method which is maximize the attraction scores and tested on tourism data for ten cities in Kedah. A set of priority scores are used to set the attraction score at each city. The classical approach of the orienteering problem was used to determine the optimal travel route. This approach is extended to the team orienteering problem and the two methods were compared. These two models have been solved by using LINGO12.0 software. The results indicate that the model involving the team orienteering problem provides a more appropriate solution compared to the orienteering problem model.

Analysis of an inventory model for both linearly decreasing demand and holding cost

NASA Astrophysics Data System (ADS)

Malik, A. K.; Singh, Parth Raj; Tomar, Ajay; Kumar, Satish; Yadav, S. K.

2016-03-01

This study proposes the analysis of an inventory model for linearly decreasing demand and holding cost for non-instantaneous deteriorating items. The inventory model focuses on commodities having linearly decreasing demand without shortages. The holding cost doesn't remain uniform with time due to any form of variation in the time value of money. Here we consider that the holding cost decreases with respect to time. The optimal time interval for the total profit and the optimal order quantity are determined. The developed inventory model is pointed up through a numerical example. It also includes the sensitivity analysis.

Computer-Assisted Optimization of Electrodeposited Hydroxyapatite Coating Parameters on Medical Alloys

NASA Astrophysics Data System (ADS)

Coşkun, M. İbrahim; Karahan, İsmail H.; Yücel, Yasin; Golden, Teresa D.

2016-04-01

CoCrMo bio-metallic alloys were coated with a hydroxyapatite (HA) film by electrodeposition using various electrochemical parameters. Response surface methodology and central composite design were used to optimize deposition parameters such as electrolyte pH, deposition potential, and deposition time. The effects of the coating parameters were evaluated within the limits of solution pH (3.66 to 5.34), deposition potential (-1.13 to -1.97 V), and deposition time (6.36 to 73.64 minutes). A 5-level-3-factor experimental plan was used to determine ideal deposition parameters. Optimum conditions for the deposition parameters of the HA coating with high in vitro corrosion performance were determined as electrolyte pH of 5.00, deposition potential of -1.8 V, and deposition time of 20 minutes.

Ambush frequency should increase over time during optimal predator search for prey

PubMed Central

Alpern, Steve; Fokkink, Robbert; Timmer, Marco; Casas, Jérôme

2011-01-01

We advance and apply the mathematical theory of search games to model the problem faced by a predator searching for prey. Two search modes are available: ambush and cruising search. Some species can adopt either mode, with their choice at a given time traditionally explained in terms of varying habitat and physiological conditions. We present an additional explanation of the observed predator alternation between these search modes, which is based on the dynamical nature of the search game they are playing: the possibility of ambush decreases the propensity of the prey to frequently change locations and thereby renders it more susceptible to the systematic cruising search portion of the strategy. This heuristic explanation is supported by showing that in a new idealized search game where the predator is allowed to ambush or search at any time, and the prey can change locations at intermittent times, optimal predator play requires an alternation (or mixture) over time of ambush and cruise search. Thus, our game is an extension of the well-studied ‘Princess and Monster’ search game. Search games are zero sum games, where the pay-off is the capture time and neither the Searcher nor the Hider knows the location of the other. We are able to determine the optimal mixture of the search modes when the predator uses a mixture which is constant over time, and also to determine how the mode mixture changes over time when dynamic strategies are allowed (the ambush probability increases over time). In particular, we establish the ‘square root law of search predation’: the optimal proportion of active search equals the square root of the fraction of the region that has not yet been explored. PMID:21571944

Ambush frequency should increase over time during optimal predator search for prey.

PubMed

Alpern, Steve; Fokkink, Robbert; Timmer, Marco; Casas, Jérôme

2011-11-07

We advance and apply the mathematical theory of search games to model the problem faced by a predator searching for prey. Two search modes are available: ambush and cruising search. Some species can adopt either mode, with their choice at a given time traditionally explained in terms of varying habitat and physiological conditions. We present an additional explanation of the observed predator alternation between these search modes, which is based on the dynamical nature of the search game they are playing: the possibility of ambush decreases the propensity of the prey to frequently change locations and thereby renders it more susceptible to the systematic cruising search portion of the strategy. This heuristic explanation is supported by showing that in a new idealized search game where the predator is allowed to ambush or search at any time, and the prey can change locations at intermittent times, optimal predator play requires an alternation (or mixture) over time of ambush and cruise search. Thus, our game is an extension of the well-studied 'Princess and Monster' search game. Search games are zero sum games, where the pay-off is the capture time and neither the Searcher nor the Hider knows the location of the other. We are able to determine the optimal mixture of the search modes when the predator uses a mixture which is constant over time, and also to determine how the mode mixture changes over time when dynamic strategies are allowed (the ambush probability increases over time). In particular, we establish the 'square root law of search predation': the optimal proportion of active search equals the square root of the fraction of the region that has not yet been explored.

Response surface methodology for the optimization of sludge solubilization by ultrasonic pre-treatment

NASA Astrophysics Data System (ADS)

Zheng, Mingyue; Zhang, Xiaohui; Lu, Peng; Cao, Qiguang; Yuan, Yuan; Yue, Mingxing; Fu, Yiwei; Wu, Libin

2018-02-01

The present study examines the optimization of the ultrasonic pre-treatment conditions with response surface experimental design in terms of sludge disintegration efficiency (solubilisation of organic components). Ultrasonic pre-treatment for the maximum solubilization with residual sludge enhanced the SCOD release. Optimization of the ultrasonic pre-treatment was conducted through a Box-Behnken design (three variables, a total of 17 experiments) to determine the effects of three independent variables (power, residence time and TS) on COD solubilization of sludge. The optimal COD was obtained at 17349.4mg/L, when the power was 534.67W, the time was 10.77, and TS was 2%, while the SE of this condition was 28792J/kg TS.

Optimal design criteria - prediction vs. parameter estimation

NASA Astrophysics Data System (ADS)

Waldl, Helmut

2014-05-01

G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

Time-saving design of experiment protocol for optimization of LC-MS data processing in metabolomic approaches.

PubMed

Zheng, Hong; Clausen, Morten Rahr; Dalsgaard, Trine Kastrup; Mortensen, Grith; Bertram, Hanne Christine

2013-08-06

We describe a time-saving protocol for the processing of LC-MS-based metabolomics data by optimizing parameter settings in XCMS and threshold settings for removing noisy and low-intensity peaks using design of experiment (DoE) approaches including Plackett-Burman design (PBD) for screening and central composite design (CCD) for optimization. A reliability index, which is based on evaluation of the linear response to a dilution series, was used as a parameter for the assessment of data quality. After identifying the significant parameters in the XCMS software by PBD, CCD was applied to determine their values by maximizing the reliability and group indexes. Optimal settings by DoE resulted in improvements of 19.4% and 54.7% in the reliability index for a standard mixture and human urine, respectively, as compared with the default setting, and a total of 38 h was required to complete the optimization. Moreover, threshold settings were optimized by using CCD for further improvement. The approach combining optimal parameter setting and the threshold method improved the reliability index about 9.5 times for a standards mixture and 14.5 times for human urine data, which required a total of 41 h. Validation results also showed improvements in the reliability index of about 5-7 times even for urine samples from different subjects. It is concluded that the proposed methodology can be used as a time-saving approach for improving the processing of LC-MS-based metabolomics data.

Online Optimization Method for Operation of Generators in a Micro Grid

NASA Astrophysics Data System (ADS)

Hayashi, Yasuhiro; Miyamoto, Hideki; Matsuki, Junya; Iizuka, Toshio; Azuma, Hitoshi

Recently a lot of studies and developments about distributed generator such as photovoltaic generation system, wind turbine generation system and fuel cell have been performed under the background of the global environment issues and deregulation of the electricity market, and the technique of these distributed generators have progressed. Especially, micro grid which consists of several distributed generators, loads and storage battery is expected as one of the new operation system of distributed generator. However, since precipitous load fluctuation occurs in micro grid for the reason of its smaller capacity compared with conventional power system, high-accuracy load forecasting and control scheme to balance of supply and demand are needed. Namely, it is necessary to improve the precision of operation in micro grid by observing load fluctuation and correcting start-stop schedule and output of generators online. But it is not easy to determine the operation schedule of each generator in short time, because the problem to determine start-up, shut-down and output of each generator in micro grid is a mixed integer programming problem. In this paper, the authors propose an online optimization method for the optimal operation schedule of generators in micro grid. The proposed method is based on enumeration method and particle swarm optimization (PSO). In the proposed method, after picking up all unit commitment patterns of each generators satisfied with minimum up time and minimum down time constraint by using enumeration method, optimal schedule and output of generators are determined under the other operational constraints by using PSO. Numerical simulation is carried out for a micro grid model with five generators and photovoltaic generation system in order to examine the validity of the proposed method.

Determination of injection molding process windows for optical lenses using response surface methodology.

PubMed

Tsai, Kuo-Ming; Wang, He-Yi

2014-08-20

This study focuses on injection molding process window determination for obtaining optimal imaging optical properties, astigmatism, coma, and spherical aberration using plastic lenses. The Taguchi experimental method was first used to identify the optimized combination of parameters and significant factors affecting the imaging optical properties of the lens. Full factorial experiments were then implemented based on the significant factors to build the response surface models. The injection molding process windows for lenses with optimized optical properties were determined based on the surface models, and confirmation experiments were performed to verify their validity. The results indicated that the significant factors affecting the optical properties of lenses are mold temperature, melt temperature, and cooling time. According to experimental data for the significant factors, the oblique ovals for different optical properties on the injection molding process windows based on melt temperature and cooling time can be obtained using the curve fitting approach. The confirmation experiments revealed that the average errors for astigmatism, coma, and spherical aberration are 3.44%, 5.62%, and 5.69%, respectively. The results indicated that the process windows proposed are highly reliable.

Microwave-assisted extraction and mild saponification for determination of organochlorine pesticides in oyster samples.

PubMed

Carro, N; García, I; Ignacio, M-C; Llompart, M; Yebra, M-C; Mouteira, A

2002-10-01

A sample-preparation procedure (extraction and saponification) using microwave energy is proposed for determination of organochlorine pesticides in oyster samples. A Plackett-Burman factorial design has been used to optimize the microwave-assisted extraction and mild saponification on a freeze dried sample spiked with a mixture of aldrin, endrin, dieldrin, heptachlor, heptachorepoxide, isodrin, transnonachlor, p, p'-DDE, and p, p'-DDD. Six variables: solvent volume, extraction time, extraction temperature, amount of acetone (%) in the extractant solvent, amount of sample, and volume of NaOH solution were considered in the optimization process. The results show that the amount of sample is statistically significant for dieldrin, aldrin, p, p'-DDE, heptachlor, and transnonachlor and solvent volume for dieldrin, aldrin, and p, p'-DDE. The volume of NaOH solution is statistically significant for aldrin and p, p'-DDE only. Extraction temperature and extraction time seem to be the main factors determining the efficiency of extraction process for isodrin and p, p'-DDE, respectively. The optimized procedure was compared with conventional Soxhlet extraction.

Impact of a Flexible Evaluation System on Effort and Timing of Study

ERIC Educational Resources Information Center

Pacharn, Parunchana; Bay, Darlene; Felton, Sandra

2012-01-01

This paper examines results of a flexible grading system that allows each student to influence the weight allocated to each performance measure. We construct a stylized model to determine students' optimal responses. Our analytical model predicts different optimal strategies for students with varying academic abilities: a frontloading strategy for…

Optimization of wastewater microalgae saccharification using dilute acid hydrolysis for acetone, butanol, and ethanol fermentation

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

Castro, Yessica; Ellis, Joshua T.; Miller, Charles D.

2015-02-01

Exploring and developing sustainable and efficient technologies for biofuel production are crucial for averting global consequences associated with fuel shortages and climate change. Optimization of sugar liberation from wastewater algae through acid hydrolysis was determined for subsequent fermentation to acetone, butanol, and ethanol (ABE) by Clostridium saccharoperbutylacetonicum N1-4. Acid concentration, retention time, and temperature were evaluated to determine optimal hydrolysis conditions by assessing the sugar and ABE yield as well as the associated costs. Sulfuric acid concentrations ranging from 0-1.5 M, retention times of 40-120 min, and temperatures from 23°C- 90°C were combined to form a full factorial experiment. Acidmore » hydrolysis pretreatment of 10% dried wastewater microalgae using 1.0 M sulfuric acid for 120 min at 80-90°C was found to be the optimal parameters, with a sugar yield of 166.1 g for kg of dry algae, concentrations of 5.23 g/L of total ABE, and 3.74 g/L of butanol at a rate of USD $12.83 per kg of butanol.« less

Optimal processor assignment for pipeline computations

NASA Technical Reports Server (NTRS)

Nicol, David M.; Simha, Rahul; Choudhury, Alok N.; Narahari, Bhagirath

1991-01-01

The availability of large scale multitasked parallel architectures introduces the following processor assignment problem for pipelined computations. Given a set of tasks and their precedence constraints, along with their experimentally determined individual responses times for different processor sizes, find an assignment of processor to tasks. Two objectives are of interest: minimal response given a throughput requirement, and maximal throughput given a response time requirement. These assignment problems differ considerably from the classical mapping problem in which several tasks share a processor; instead, it is assumed that a large number of processors are to be assigned to a relatively small number of tasks. Efficient assignment algorithms were developed for different classes of task structures. For a p processor system and a series parallel precedence graph with n constituent tasks, an O(np2) algorithm is provided that finds the optimal assignment for the response time optimization problem; it was found that the assignment optimizing the constrained throughput in O(np2log p) time. Special cases of linear, independent, and tree graphs are also considered.

SU-E-T-247: Determinations of the Optimal Phase for Respiratory Gated Radiotherapy From Statistical Analysis Using a Visible Guidance System

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

Oh, S; Yea, J; Kang, M

Purpose: Respiratory gated radiation therapy (RGRT) is used to minimize the radiation dose to normal tissue in lung cancer patients. Determination of the optimal point in the respiratory phase of a patient is important in RGRT but it is not easy. The goal of the present study was to see if a visible guidance system is helpful in determining the optimal phase in respiratory gated therapy. Methods: The breathing signals of 23 lung cancer patients were recorded with a Real-time Position Management (RPM) respiratory gating system (Varian, USA). The patients underwent breathing training with our visible guidance system, after whichmore » their breathing signals were recorded during 5 min of free breathing and 5 min of guided breathing. The breathing signals recorded between 3 and 5 min before and after training were compared. We performed statistical analysis of the breathing signals to find the optimal duty cycle in guided breathing for RGRT. Results: The breathing signals aided by the visible guidance system had more regular cycles over time and smaller variations in the positions of the marker block than the free breathing signals. Of the 23 lung cancer patients, 19 showed statistically significant differences by time when the values obtained before and after breathing were compared (p < 0.05); 30% and 40% of the duty cycle, respectively, was determined to be the most effective, and the corresponding phases were 30 60% (duty cycle, 30%; p < 0.05) and 30 70% (duty cycle, 40%; p < 0.05). Conclusion: Respiratory regularity was significantly improved with the use of the RPM with our visible guiding system; therefore, it would help improve the accuracy and efficiency of RGRT.« less

Computational methods for optimal linear-quadratic compensators for infinite dimensional discrete-time systems

NASA Technical Reports Server (NTRS)

Gibson, J. S.; Rosen, I. G.

1986-01-01

An abstract approximation theory and computational methods are developed for the determination of optimal linear-quadratic feedback control, observers and compensators for infinite dimensional discrete-time systems. Particular attention is paid to systems whose open-loop dynamics are described by semigroups of operators on Hilbert spaces. The approach taken is based on the finite dimensional approximation of the infinite dimensional operator Riccati equations which characterize the optimal feedback control and observer gains. Theoretical convergence results are presented and discussed. Numerical results for an example involving a heat equation with boundary control are presented and used to demonstrate the feasibility of the method.

Time optimized path-choice in the termite hunting ant Megaponera analis.

PubMed

Frank, Erik T; Hönle, Philipp O; Linsenmair, K Eduard

2018-05-10

Trail network systems among ants have received a lot of scientific attention due to their various applications in problem solving of networks. Recent studies have shown that ants select the fastest available path when facing different velocities on different substrates, rather than the shortest distance. The progress of decision-making by these ants is determined by pheromone-based maintenance of paths, which is a collective decision. However, path optimization through individual decision-making remains mostly unexplored. Here we present the first study of time-optimized path selection via individual decision-making by scout ants. Megaponera analis scouts search for termite foraging sites and lead highly organized raid columns to them. The path of the scout determines the path of the column. Through installation of artificial roads around M. analis nests we were able to influence the pathway choice of the raids. After road installation 59% of all recorded raids took place completely or partly on the road, instead of the direct, i.e. distance-optimized, path through grass from the nest to the termites. The raid velocity on the road was more than double the grass velocity, the detour thus saved 34.77±23.01% of the travel time compared to a hypothetical direct path. The pathway choice of the ants was similar to a mathematical model of least time allowing us to hypothesize the underlying mechanisms regulating the behavior. Our results highlight the importance of individual decision-making in the foraging behavior of ants and show a new procedure of pathway optimization. © 2018. Published by The Company of Biologists Ltd.

Determining optimal parameters in magnetic spacecraft stabilization via attitude feedback

NASA Astrophysics Data System (ADS)

Bruni, Renato; Celani, Fabio

2016-10-01

The attitude control of a spacecraft using magnetorquers can be achieved by a feedback control law which has four design parameters. However, the practical determination of appropriate values for these parameters is a critical open issue. We propose here an innovative systematic approach for finding these values: they should be those that minimize the convergence time to the desired attitude. This a particularly diffcult optimization problem, for several reasons: 1) such time cannot be expressed in analytical form as a function of parameters and initial conditions; 2) design parameters may range over very wide intervals; 3) convergence time depends also on the initial conditions of the spacecraft, which are not known in advance. To overcome these diffculties, we present a solution approach based on derivative-free optimization. These algorithms do not need to write analytically the objective function: they only need to compute it in a number of points. We also propose a fast probing technique to identify which regions of the search space have to be explored densely. Finally, we formulate a min-max model to find robust parameters, namely design parameters that minimize convergence time under the worst initial conditions. Results are very promising.

Locating single-point sources from arrival times containing large picking errors (LPEs): the virtual field optimization method (VFOM)

NASA Astrophysics Data System (ADS)

Li, Xi-Bing; Wang, Ze-Wei; Dong, Long-Jun

2016-01-01

Microseismic monitoring systems using local location techniques tend to be timely, automatic and stable. One basic requirement of these systems is the automatic picking of arrival times. However, arrival times generated by automated techniques always contain large picking errors (LPEs), which may make the location solution unreliable and cause the integrated system to be unstable. To overcome the LPE issue, we propose the virtual field optimization method (VFOM) for locating single-point sources. In contrast to existing approaches, the VFOM optimizes a continuous and virtually established objective function to search the space for the common intersection of the hyperboloids, which is determined by sensor pairs other than the least residual between the model-calculated and measured arrivals. The results of numerical examples and in-site blasts show that the VFOM can obtain more precise and stable solutions than traditional methods when the input data contain LPEs. Furthermore, we discuss the impact of LPEs on objective functions to determine the LPE-tolerant mechanism, velocity sensitivity and stopping criteria of the VFOM. The proposed method is also capable of locating acoustic sources using passive techniques such as passive sonar detection and acoustic emission.

Optimal investment strategies and hedging of derivatives in the presence of transaction costs (Invited Paper)

NASA Astrophysics Data System (ADS)

Muratore-Ginanneschi, Paolo

2005-05-01

Investment strategies in multiplicative Markovian market models with transaction costs are defined using growth optimal criteria. The optimal strategy is shown to consist in holding the amount of capital invested in stocks within an interval around an ideal optimal investment. The size of the holding interval is determined by the intensity of the transaction costs and the time horizon. The inclusion of financial derivatives in the models is also considered. All the results presented in this contributions were previously derived in collaboration with E. Aurell.

Parallel computation of GA search for the artery shape determinants with CFD

NASA Astrophysics Data System (ADS)

Himeno, M.; Noda, S.; Fukasaku, K.; Himeno, R.

2010-06-01

We studied which factors play important role to determine the shape of arteries at the carotid artery bifurcation by performing multi-objective optimization with computation fluid dynamics (CFD) and the genetic algorithm (GA). To perform it, the most difficult problem is how to reduce turn-around time of the GA optimization with 3D unsteady computation of blood flow. We devised two levels of parallel computation method with the following features: level 1: parallel CFD computation with appropriate number of cores; level 2: parallel jobs generated by "master", which finds quickly available job cue and dispatches jobs, to reduce turn-around time. As a result, the turn-around time of one GA trial, which would have taken 462 days with one core, was reduced to less than two days on RIKEN supercomputer system, RICC, with 8192 cores. We performed a multi-objective optimization to minimize the maximum mean WSS and to minimize the sum of circumference for four different shapes and obtained a set of trade-off solutions for each shape. In addition, we found that the carotid bulb has the feature of the minimum local mean WSS and minimum local radius. We confirmed that our method is effective for examining determinants of artery shapes.

Ionic liquid-based microwave-assisted extraction of flavonoids from Bauhinia championii (Benth.) Benth.

PubMed

Xu, Wei; Chu, Kedan; Li, Huang; Zhang, Yuqin; Zheng, Haiyin; Chen, Ruilan; Chen, Lidian

2012-12-03

An ionic liquids (IL)-based microwave-assisted approach for extraction and determination of flavonoids from Bauhinia championii (Benth.) Benth. was proposed for the first time. Several ILs with different cations and anions and the microwave-assisted extraction (MAE) conditions, including sample particle size, extraction time and liquid-solid ratio, were investigated. Two M 1-butyl-3-methylimidazolium bromide ([bmim] Br) solution with 0.80 M HCl was selected as the optimal solvent. Meanwhile the optimized conditions a ratio of liquid to material of 30:1, and the extraction for 10 min at 70 °C. Compared with conventional heat-reflux extraction (CHRE) and the regular MAE, IL-MAE exhibited a higher extraction yield and shorter extraction time (from 1.5 h to 10 min). The optimized extraction samples were analysed by LC-MS/MS. IL extracts of Bauhinia championii (Benth.)Benth consisted mainly of flavonoids, among which myricetin, quercetin and kaempferol, β-sitosterol, triacontane and hexacontane were identified. The study indicated that IL-MAE was an efficient and rapid method with simple sample preparation. LC-MS/MS was also used to determine the chemical composition of the ethyl acetate/MAE extract of Bauhinia championii (Benth.) Benth, and it maybe become a rapid method to determine the composition of new plant extracts.

Interactive optimization approach for optimal impulsive rendezvous using primer vector and evolutionary algorithms

NASA Astrophysics Data System (ADS)

Luo, Ya-Zhong; Zhang, Jin; Li, Hai-yang; Tang, Guo-Jin

2010-08-01

In this paper, a new optimization approach combining primer vector theory and evolutionary algorithms for fuel-optimal non-linear impulsive rendezvous is proposed. The optimization approach is designed to seek the optimal number of impulses as well as the optimal impulse vectors. In this optimization approach, adding a midcourse impulse is determined by an interactive method, i.e. observing the primer-magnitude time history. An improved version of simulated annealing is employed to optimize the rendezvous trajectory with the fixed-number of impulses. This interactive approach is evaluated by three test cases: coplanar circle-to-circle rendezvous, same-circle rendezvous and non-coplanar rendezvous. The results show that the interactive approach is effective and efficient in fuel-optimal non-linear rendezvous design. It can guarantee solutions, which satisfy the Lawden's necessary optimality conditions.

Optimization of culture conditions for penicilazaphilone C production by a marine-derived fungus Penicillium sclerotiorum M-22.

PubMed

Zhao, H-G; Wang, M; Lin, Y-Y; Zhou, S-L

2018-03-01

The aim of this study was to optimize the culture conditions of a marine-derived fungus Penicillium sclerotiorum M-22 for the production of penicilazaphilone C (PAC), a novel azaphilonidal derivative exhibiting broad cytotoxic and antibacterial effects. By single factor experiments, the effects to the production of PAC of aged seawater concentration, initial pH values, fermentation time, carbon sources, nitrogen sources and inorganic salt sources were investigated individually. Response surface methodology (RSM) analysis was adopted to investigate the interactions between variables and determine the optimal values for maximum PAC production. Evaluation of the experimental results signified that the optimum conditions for maximum production of PAC (19·85 mg l -1 ) in 250 ml Erlenmeyer flask were fermentation time 24·83 days, pH of 7·00, corn meal concentration of 10·72 g l -1 , yeast extract concentration of 4·58 g l -1 , crude sea salt concentration of 20·59 g l -1 . Production under optimized conditions increased to 1·344-fold comparing to its production prior to optimization. The higher PAC production and the penicilazaphilone C -producing marine fungus would be provide a promising alterative approach for industrial and commercial applications. Penicilazaphilone C (PAC) was a novel azaphilonidal derivative which had exhibited selective cytotoxicity and antibacterial activity. To further enhance production of PAC by optimizing fermentation conditions of Penicillium sclerotiorum M-22 would provide a promising alterative approach for industrial and commercial applications. We used the single factor test to determine the key factors which influence the PAC production. Then through the Response surface methodology and Box-Behnken design to determine the best fermentation condition for maximum production of PAC. Through these experimental designs and analysis will help us improve experimental efficiency and save time and materials. © 2017 The Society for Applied Microbiology.

The ESSENCE Supernova Survey: Survey Optimization, Observations, and Supernova Photometry

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

Miknaitis, Gajus; Pignata, G.; Rest, A.

We describe the implementation and optimization of the ESSENCE supernova survey, which we have undertaken to measure the equation of state parameter of the dark energy. We present a method for optimizing the survey exposure times and cadence to maximize our sensitivity to the dark energy equation of state parameter w = P/{rho}c{sup 2} for a given fixed amount of telescope time. For our survey on the CTIO 4m telescope, measuring the luminosity distances and redshifts for supernovae at modest redshifts (z {approx} 0.5 {+-} 0.2) is optimal for determining w. We describe the data analysis pipeline based on usingmore » reliable and robust image subtraction to find supernovae automatically and in near real-time. Since making cosmological inferences with supernovae relies crucially on accurate measurement of their brightnesses, we describe our efforts to establish a thorough calibration of the CTIO 4m natural photometric system. In its first four years, ESSENCE has discovered and spectroscopically confirmed 102 type Ia SNe, at redshifts from 0.10 to 0.78, identified through an impartial, effective methodology for spectroscopic classification and redshift determination. We present the resulting light curves for the all type Ia supernovae found by ESSENCE and used in our measurement of w, presented in Wood-Vasey et al. (2007).« less

Reducing variable frequency vibrations in a powertrain system with an adaptive tuned vibration absorber group

NASA Astrophysics Data System (ADS)

Gao, Pu; Xiang, Changle; Liu, Hui; Zhou, Han

2018-07-01

Based on a multiple degrees of freedom dynamic model of a vehicle powertrain system, natural vibration analyses and sensitivity analyses of the eigenvalues are performed to determine the key inertia for each natural vibration of a powertrain system. Then, the results are used to optimize the installation position of each adaptive tuned vibration absorber. According to the relationship between the variable frequency torque excitation and the natural vibration of a powertrain system, the entire vibration frequency band is divided into segments, and the auxiliary vibration absorber and dominant vibration absorber are determined for each sensitive frequency band. The optimum parameters of the auxiliary vibration absorber are calculated based on the optimal frequency ratio and the optimal damping ratio of the passive vibration absorber. The instantaneous change state of the natural vibrations of a powertrain system with adaptive tuned vibration absorbers is studied, and the optimized start and stop tuning frequencies of the adaptive tuned vibration absorber are obtained. These frequencies can be translated into the optimum parameters of the dominant vibration absorber. Finally, the optimal tuning scheme for the adaptive tuned vibration absorber group, which can be used to reduce the variable frequency vibrations of a powertrain system, is proposed, and corresponding numerical simulations are performed. The simulation time history signals are transformed into three-dimensional information related to time, frequency and vibration energy via the Hilbert-Huang transform (HHT). A comprehensive time-frequency analysis is then conducted to verify that the optimal tuning scheme for the adaptive tuned vibration absorber group can significantly reduce the variable frequency vibrations of a powertrain system.

Optimized dispatch in a first-principles concentrating solar power production model

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

Wagner, Michael J.; Newman, Alexandra M.; Hamilton, William T.

Concentrating solar power towers, which include a steam-Rankine cycle with molten salt thermal energy storage, is an emerging technology whose maximum effectiveness relies on an optimal operational and dispatch policy. Given parameters such as start-up and shut-down penalties, expected electricity price profiles, solar availability, and system interoperability requirements, this paper seeks a profit-maximizing solution that determines start-up and shut-down times for the power cycle and solar receiver, and the times at which to dispatch stored and instantaneous quantities of energy over a 48-h horizon at hourly fidelity. The mixed-integer linear program (MIP) is subject to constraints including: (i) minimum andmore » maximum rates of start-up and shut-down, (ii) energy balance, including energetic state of the system as a whole and its components, (iii) logical rules governing the operational modes of the power cycle and solar receiver, and (iv) operational consistency between time periods. The novelty in this work lies in the successful integration of a dispatch optimization model into a detailed techno-economic analysis tool, specifically, the National Renewable Energy Laboratory's System Advisor Model (SAM). The MIP produces an optimized operating strategy, historically determined via a heuristic. Using several market electricity pricing profiles, we present comparative results for a system with and without dispatch optimization, indicating that dispatch optimization can improve plant profitability by 5-20% and thereby alter the economics of concentrating solar power technology. While we examine a molten salt power tower system, this analysis is equally applicable to the more mature concentrating solar parabolic trough system with thermal energy storage.« less

Optimization of supercritical fluid extraction and HPLC identification of wedelolactone from Wedelia calendulacea by orthogonal array design.

PubMed

Patil, Ajit A; Sachin, Bhusari S; Wakte, Pravin S; Shinde, Devanand B

2014-11-01

The purpose of this work is to provide a complete study of the influence of operational parameters of the supercritical carbon dioxide assisted extraction (SC CO2E) on yield of wedelolactone from Wedelia calendulacea Less., and to find an optimal combination of factors that maximize the wedelolactone yield. In order to determine the optimal combination of the four factors viz. operating pressure, temperature, modifier concentration and extraction time, a Taguchi experimental design approach was used: four variables (three levels) in L9 orthogonal array. Wedelolactone content was determined using validated HPLC methodology. Optimum extraction conditions were found to be as follows: extraction pressure, 25 MPa; temperature, 40 °C; modifier concentration, 10% and extraction time, 90 min. Optimum extraction conditions demonstrated wedelolactone yield of 8.01 ± 0.34 mg/100 g W. calendulacea Less. Pressure, temperature and time showed significant (p < 0.05) effect on the wedelolactone yield. The supercritical carbon dioxide extraction showed higher selectivity than the conventional Soxhlet assisted extraction method.

Optimization of supercritical fluid extraction and HPLC identification of wedelolactone from Wedelia calendulacea by orthogonal array design

PubMed Central

Patil, Ajit A.; Sachin, Bhusari S.; Wakte, Pravin S.; Shinde, Devanand B.

2013-01-01

The purpose of this work is to provide a complete study of the influence of operational parameters of the supercritical carbon dioxide assisted extraction (SC CO2E) on yield of wedelolactone from Wedelia calendulacea Less., and to find an optimal combination of factors that maximize the wedelolactone yield. In order to determine the optimal combination of the four factors viz. operating pressure, temperature, modifier concentration and extraction time, a Taguchi experimental design approach was used: four variables (three levels) in L9 orthogonal array. Wedelolactone content was determined using validated HPLC methodology. Optimum extraction conditions were found to be as follows: extraction pressure, 25 MPa; temperature, 40 °C; modifier concentration, 10% and extraction time, 90 min. Optimum extraction conditions demonstrated wedelolactone yield of 8.01 ± 0.34 mg/100 g W. calendulacea Less. Pressure, temperature and time showed significant (p < 0.05) effect on the wedelolactone yield. The supercritical carbon dioxide extraction showed higher selectivity than the conventional Soxhlet assisted extraction method. PMID:25687584

Optimization of preparation of antioxidative peptides from pumpkin seeds using response surface method.

PubMed

Fan, Sanhong; Hu, Yanan; Li, Chen; Liu, Yanrong

2014-01-01

Protein isolates of pumpkin (Cucurbita pepo L) seeds were hydrolyzed by acid protease to prepare antioxidative peptides. The hydrolysis conditions were optimized through Box-Behnken experimental design combined with response surface method (RSM). The second-order model, developed for the DPPH radical scavenging activity of pumpkin seed hydrolysates, showed good fit with the experiment data with a high value of coefficient of determination (0.9918). The optimal hydrolysis conditions were determined as follows: hydrolyzing temperature 50°C, pH 2.5, enzyme amount 6000 U/g, substrate concentration 0.05 g/ml and hydrolyzing time 5 h. Under the above conditions, the scavenging activity of DPPH radical was as high as 92.82%.

Optimization of coronary attenuation in coronary computed tomography angiography using diluted contrast material.

PubMed

Kawaguchi, Naoto; Kurata, Akira; Kido, Teruhito; Nishiyama, Yoshiko; Kido, Tomoyuki; Miyagawa, Masao; Ogimoto, Akiyoshi; Mochizuki, Teruhito

2014-01-01

The purpose of this study was to evaluate a personalized protocol with diluted contrast material (CM) for coronary computed tomography angiography (CTA). One hundred patients with suspected coronary artery disease underwent retrospective electrocardiogram-gated coronary CTA on a 256-slice multidetector-row CT scanner. In the diluted CM protocol (n=50), the optimal scan timing and CM dilution rate were determined by the timing bolus scan, with 20% CM dilution (5ml/s during 10s) being considered suitable to achieve the target arterial attenuation of 350 Hounsfield units (HU). In the body weight (BW)-adjusted protocol (n=50, 222mg iodine/kg), only the optimal scan timing was determined by the timing bolus scan. The injection rate and volume in the timing bolus scan and real scan were identical between the 2 protocols. We compared the means and variations in coronary attenuation between the 2 protocols. Coronary attenuation (mean±SD) in the diluted CM and BW-adjusted protocols was 346.1±23.9 HU and 298.8±45.2 HU, respectively. The diluted CM protocol provided significantly higher coronary attenuation and lower variance than did the BW-adjusted protocol (P<0.05, in each). The diluted CM protocol facilitates more uniform attenuation on coronary CTA in comparison with the BW-adjusted protocol.  

Running with horizontal pulling forces: the benefits of towing.

PubMed

Grabowski, Alena M; Kram, Rodger

2008-10-01

Towing, or running with a horizontal pulling force, is a common technique used by adventure racing teams. During an adventure race, the slowest person on a team determines the team's overall performance. To improve overall performance, a faster runner tows a slower runner with an elastic cord attached to their waists. Our purpose was to create and validate a model that predicts the optimal towing force needed by two runners to achieve their best overall performance. We modeled the effects of towing forces between two runners that differ in solo 10-km performance time and/or body mass. We calculated the overall time that could be saved with towing for running distances of 10, 20, and 42.2-km based on equations from previous research. Then, we empirically tested our 10-km model on 15 runners. Towing improved overall running performance considerably and our model accurately predicted this performance improvement. For example, if two runners (a 70 kg runner with a 35 min solo 10-km time and a 70-kg runner with a 50-min solo 10-km time) maintain an optimal towing force throughout a 10-km race, they can improve overall performance by 15%, saving almost 8 min. Ultimately, the race performance time and body mass of each runner determine the optimal towing force.

Direct position determination for digital modulation signals based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yu, Wan-Ting; Yu, Hong-yi; Du, Jian-Ping; Wang, Ding

2018-04-01

The Direct Position Determination (DPD) algorithm has been demonstrated to achieve a better accuracy with known signal waveforms. However, the signal waveform is difficult to be completely known in the actual positioning process. To solve the problem, we proposed a DPD method for digital modulation signals based on improved particle swarm optimization algorithm. First, a DPD model is established for known modulation signals and a cost function is obtained on symbol estimation. Second, as the optimization of the cost function is a nonlinear integer optimization problem, an improved Particle Swarm Optimization (PSO) algorithm is considered for the optimal symbol search. Simulations are carried out to show the higher position accuracy of the proposed DPD method and the convergence of the fitness function under different inertia weight and population size. On the one hand, the proposed algorithm can take full advantage of the signal feature to improve the positioning accuracy. On the other hand, the improved PSO algorithm can improve the efficiency of symbol search by nearly one hundred times to achieve a global optimal solution.

An Innovative Time-Cost-Quality Tradeoff Modeling of Building Construction Project Based on Resource Allocation

PubMed Central

2014-01-01

The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated. PMID:24672351

Optimization of Progressive Freeze Concentration on Apple Juice via Response Surface Methodology

NASA Astrophysics Data System (ADS)

Samsuri, S.; Amran, N. A.; Jusoh, M.

2018-05-01

In this work, a progressive freeze concentration (PFC) system was developed to concentrate apple juice and was optimized by response surface methodology (RSM). The effects of various operating conditions such as coolant temperature, circulation flowrate, circulation time and shaking speed to effective partition constant (K) were investigated. Five different level of central composite design (CCD) was employed to search for optimal concentration of concentrated apple juice. A full quadratic model for K was established by using method of least squares. A coefficient of determination (R2) of this model was found to be 0.7792. The optimum conditions were found to be coolant temperature = -10.59 °C, circulation flowrate = 3030.23 mL/min, circulation time = 67.35 minutes and shaking speed = 30.96 ohm. A validation experiment was performed to evaluate the accuracy of the optimization procedure and the best K value of 0.17 was achieved under the optimized conditions.

A simple approach to optimal control of invasive species.

PubMed

Hastings, Alan; Hall, Richard J; Taylor, Caz M

2006-12-01

The problem of invasive species and their control is one of the most pressing applied issues in ecology today. We developed simple approaches based on linear programming for determining the optimal removal strategies of different stage or age classes for control of invasive species that are still in a density-independent phase of growth. We illustrate the application of this method to the specific example of invasive Spartina alterniflora in Willapa Bay, WA. For all such systems, linear programming shows in general that the optimal strategy in any time step is to prioritize removal of a single age or stage class. The optimal strategy adjusts which class is the focus of control through time and can be much more cost effective than prioritizing removal of the same stage class each year.

Optimal experimental designs for the estimation of thermal properties of composite materials

NASA Technical Reports Server (NTRS)

Scott, Elaine P.; Moncman, Deborah A.

1994-01-01

Reliable estimation of thermal properties is extremely important in the utilization of new advanced materials, such as composite materials. The accuracy of these estimates can be increased if the experiments are designed carefully. The objectives of this study are to design optimal experiments to be used in the prediction of these thermal properties and to then utilize these designs in the development of an estimation procedure to determine the effective thermal properties (thermal conductivity and volumetric heat capacity). The experiments were optimized by choosing experimental parameters that maximize the temperature derivatives with respect to all of the unknown thermal properties. This procedure has the effect of minimizing the confidence intervals of the resulting thermal property estimates. Both one-dimensional and two-dimensional experimental designs were optimized. A heat flux boundary condition is required in both analyses for the simultaneous estimation of the thermal properties. For the one-dimensional experiment, the parameters optimized were the heating time of the applied heat flux, the temperature sensor location, and the experimental time. In addition to these parameters, the optimal location of the heat flux was also determined for the two-dimensional experiments. Utilizing the optimal one-dimensional experiment, the effective thermal conductivity perpendicular to the fibers and the effective volumetric heat capacity were then estimated for an IM7-Bismaleimide composite material. The estimation procedure used is based on the minimization of a least squares function which incorporates both calculated and measured temperatures and allows for the parameters to be estimated simultaneously.

A comparison of dynamic and static economic models of uneven-aged stand management

Treesearch

Robert G. Haight

1985-01-01

Numerical techniques have been used to compute the discrete-time sequence of residual diameter distributions that maximize the present net worth (PNW) of harvestable volume from an uneven-aged stand. Results contradicted optimal steady-state diameter distributions determined with static analysis. In this paper, optimality conditions for solutions to dynamic and static...

Development of optimal models of porous media by combining static and dynamic data: the permeability and porosity distributions.

PubMed

Hamzehpour, Hossein; Rasaei, M Reza; Sahimi, Muhammad

2007-05-01

We describe a method for the development of the optimal spatial distributions of the porosity phi and permeability k of a large-scale porous medium. The optimal distributions are constrained by static and dynamic data. The static data that we utilize are limited data for phi and k, which the method honors in the optimal model and utilizes their correlation functions in the optimization process. The dynamic data include the first-arrival (FA) times, at a number of receivers, of seismic waves that have propagated in the porous medium, and the time-dependent production rates of a fluid that flows in the medium. The method combines the simulated-annealing method with a simulator that solves numerically the three-dimensional (3D) acoustic wave equation and computes the FA times, and a second simulator that solves the 3D governing equation for the fluid's pressure as a function of time. To our knowledge, this is the first time that an optimization method has been developed to determine simultaneously the global minima of two distinct total energy functions. As a stringent test of the method's accuracy, we solve for flow of two immiscible fluids in the same porous medium, without using any data for the two-phase flow problem in the optimization process. We show that the optimal model, in addition to honoring the data, also yields accurate spatial distributions of phi and k, as well as providing accurate quantitative predictions for the single- and two-phase flow problems. The efficiency of the computations is discussed in detail.

[Optimization of prokaryotic expression conditions of Leptospira interrogans trigeminy genus-specific protein antigen based on surface response analysis].

PubMed

Wang, Jiang; Luo, Dongjiao; Sun, Aihua; Yan, Jie

2008-07-01

Lipoproteins LipL32 and LipL21 and transmembrane protein OMPL1 have been confirmed as the superficial genus-specific antigens of Leptospira interrogans, which can be used as antigens for developing a universal genetic engineering vaccine. In order to obtain high expression of an artificial fusion gene lipL32/1-lipL21-ompL1/2, we optimized prokaryotic expression conditions. We used surface response analysis based on the central composite design to optimize culture conditions of a new antigen protein by recombinant Escherichia coli DE3.The culture conditions included initial pH, induction start time, post-induction time, Isopropyl beta-D-thiogalactopyranoside (IPTG) concentration, and temperature. The maximal production of antigen protein was 37.78 mg/l. The optimal culture conditions for high recombinant fusion protein was determined: initial pH 7.9, induction start time 2.5 h, a post-induction time of 5.38 h, 0.20 mM IPTG, and a post-induction temperature of 31 degrees C. Surface response analysis based on CCD increased the target production. This statistical method reduced the number of experiments required for optimization and enabled rapid identification and integration of the key culture condition parameters for optimizing recombinant protein expression.

Optimization of microwave-assisted extraction (MAE) of coriander phenolic antioxidants - response surface methodology approach.

PubMed

Zeković, Zoran; Vladić, Jelena; Vidović, Senka; Adamović, Dušan; Pavlić, Branimir

2016-10-01

Microwave-assisted extraction (MAE) of polyphenols from coriander seeds was optimized by simultaneous maximization of total phenolic (TP) and total flavonoid (TF) yields, as well as maximized antioxidant activity determined by 1,1-diphenyl-2-picrylhydrazyl and reducing power assays. Box-Behnken experimental design with response surface methodology (RSM) was used for optimization of MAE. Extraction time (X1 , 15-35 min), ethanol concentration (X2 , 50-90% w/w) and irradiation power (X3 , 400-800 W) were investigated as independent variables. Experimentally obtained values of investigated responses were fitted to a second-order polynomial model, and multiple regression analysis and analysis of variance were used to determine fitness of the model and optimal conditions. The optimal MAE conditions for simultaneous maximization of polyphenol yield and increased antioxidant activity were an extraction time of 19 min, an ethanol concentration of 63% and an irradiation power of 570 W, while predicted values of TP, TF, IC50 and EC50 at optimal MAE conditions were 311.23 mg gallic acid equivalent per 100 g dry weight (DW), 213.66 mg catechin equivalent per 100 g DW, 0.0315 mg mL(-1) and 0.1311 mg mL(-1) respectively. RSM was successfully used for multi-response optimization of coriander seed polyphenols. Comparison of optimized MAE with conventional extraction techniques confirmed that MAE provides significantly higher polyphenol yields and extracts with increased antioxidant activity. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Numerical approximation for the infinite-dimensional discrete-time optimal linear-quadratic regulator problem

NASA Technical Reports Server (NTRS)

Gibson, J. S.; Rosen, I. G.

1986-01-01

An abstract approximation framework is developed for the finite and infinite time horizon discrete-time linear-quadratic regulator problem for systems whose state dynamics are described by a linear semigroup of operators on an infinite dimensional Hilbert space. The schemes included the framework yield finite dimensional approximations to the linear state feedback gains which determine the optimal control law. Convergence arguments are given. Examples involving hereditary and parabolic systems and the vibration of a flexible beam are considered. Spline-based finite element schemes for these classes of problems, together with numerical results, are presented and discussed.

Optimal cooperative time-fixed impulsive rendezvous

NASA Technical Reports Server (NTRS)

Mirfakhraie, Koorosh; Conway, Bruce A.

1990-01-01

New capabilities have been added to a method that had been developed for determining optimal, i.e., minimum fuel, trajectories for the fixed-time cooperative rendezvous of two spacecraft. The method utilizes the primer vector theory. The new capabilities enable the method to accomodate cases in which there are fuel constraints on the spacecraft and/or enable the addition of a mid-course impulse to one of the vehicle's trajectories. Results are presented for a large number of cases, and the effect of varying parameters, such as vehicle fuel constraints, vehicle initial masses, and time allowed for the rendezvous, is demonstrated.

Effects of Creatine Supplementation on Muscle Strength and Optimal Individual Post-Activation Potentiation Time of the Upper Body in Canoeists.

PubMed

Wang, Chia-Chi; Lin, Shu-Cheng; Hsu, Shu-Ching; Yang, Ming-Ta; Chan, Kuei-Hui

2017-10-27

Creatine supplementation reduces the impact of muscle fatigue on post-activation potentiation (PAP) of the lower body, but its effects on the upper body remain unknown. This study examined the effects of creatine supplementation on muscle strength, explosive power, and optimal individual PAP time of the upper body during a set of complex training bouts in canoeists. Seventeen male high school canoeists performed a bench row for one repetition at maximum strength and conducted complex training bouts to determine the optimal individual timing of PAP and distance of overhead medicine ball throw before and after the supplementation. Subjects were assigned to a creatine or placebo group, and later consumed 20 g of creatine or carboxymethyl cellulose per day for six days. After supplementation, the maximal strength in the creatine group significantly increased ( p < 0.05). The optimal individual PAP time in the creatine group was significantly earlier than the pre-supplementation times ( p < 0.05). There was no significant change in explosive power for either group. Our findings support the notion that creatine supplementation increases maximal strength and shortens the optimal individual PAP time of the upper body in high school athletes, but has no effect on explosive power. Moreover, it was found that the recovery time between a bench row and an overhead medicine ball throw in a complex training bout is an individual phenomenon.

A Decision-making Model for a Two-stage Production-delivery System in SCM Environment

NASA Astrophysics Data System (ADS)

Feng, Ding-Zhong; Yamashiro, Mitsuo

A decision-making model is developed for an optimal production policy in a two-stage production-delivery system that incorporates a fixed quantity supply of finished goods to a buyer at a fixed interval of time. First, a general cost model is formulated considering both supplier (of raw materials) and buyer (of finished products) sides. Then an optimal solution to the problem is derived on basis of the cost model. Using the proposed model and its optimal solution, one can determine optimal production lot size for each stage, optimal number of transportation for semi-finished goods, and optimal quantity of semi-finished goods transported each time to meet the lumpy demand of consumers. Also, we examine the sensitivity of raw materials ordering and production lot size to changes in ordering cost, transportation cost and manufacturing setup cost. A pragmatic computation approach for operational situations is proposed to solve integer approximation solution. Finally, we give some numerical examples.

A pheromone-rate-based analysis on the convergence time of ACO algorithm.

PubMed

Huang, Han; Wu, Chun-Guo; Hao, Zhi-Feng

2009-08-01

Ant colony optimization (ACO) has widely been applied to solve combinatorial optimization problems in recent years. There are few studies, however, on its convergence time, which reflects how many iteration times ACO algorithms spend in converging to the optimal solution. Based on the absorbing Markov chain model, we analyze the ACO convergence time in this paper. First, we present a general result for the estimation of convergence time to reveal the relationship between convergence time and pheromone rate. This general result is then extended to a two-step analysis of the convergence time, which includes the following: 1) the iteration time that the pheromone rate spends on reaching the objective value and 2) the convergence time that is calculated with the objective pheromone rate in expectation. Furthermore, four brief ACO algorithms are investigated by using the proposed theoretical results as case studies. Finally, the conclusions of the case studies that the pheromone rate and its deviation determine the expected convergence time are numerically verified with the experiment results of four one-ant ACO algorithms and four ten-ant ACO algorithms.

The Target Residence Time of Antihistamines Determines Their Antagonism of the G Protein-Coupled Histamine H1 Receptor

PubMed Central

Bosma, Reggie; Witt, Gesa; Vaas, Lea A. I.; Josimovic, Ivana; Gribbon, Philip; Vischer, Henry F.; Gul, Sheraz; Leurs, Rob

2017-01-01

The pharmacodynamics of drug-candidates is often optimized by metrics that describe target binding (Kd or Ki value) or target modulation (IC50). However, these metrics are determined at equilibrium conditions, and consequently information regarding the onset and offset of target engagement and modulation is lost. Drug-target residence time is a measure for the lifetime of the drug-target complex, which has recently been receiving considerable interest, as target residence time is shown to have prognostic value for the in vivo efficacy of several drugs. In this study, we have investigated the relation between the increased residence time of antihistamines at the histamine H1 receptor (H1R) and the duration of effective target-inhibition by these antagonists. Hela cells, endogenously expressing low levels of the H1R, were incubated with a series of antihistamines and dissociation was initiated by washing away the unbound antihistamines. Using a calcium-sensitive fluorescent dye and a label free, dynamic mass redistribution based assay, functional recovery of the H1R responsiveness was measured by stimulating the cells with histamine over time, and the recovery was quantified as the receptor recovery time. Using these assays, we determined that the receptor recovery time for a set of antihistamines differed more than 40-fold and was highly correlated to their H1R residence times, as determined with competitive radioligand binding experiments to the H1R in a cell homogenate. Thus, the receptor recovery time is proposed as a cell-based and physiologically relevant metric for the lead optimization of G protein-coupled receptor antagonists, like the H1R antagonists. Both, label-free or real-time, classical signaling assays allow an efficient and physiologically relevant determination of kinetic properties of drug molecules. PMID:29033838

Optimization of multiwalled carbon nanotubes reinforced hollow-fiber solid-liquid-phase microextraction for the determination of polycyclic aromatic hydrocarbons in environmental water samples using experimental design.

PubMed

Hamedi, Raheleh; Hadjmohammadi, Mohammad Reza

2017-09-01

A novel design of hollow-fiber liquid-phase microextraction containing multiwalled carbon nanotubes as a solid sorbent, which is immobilized in the pore and lumen of hollow fiber by the sol-gel technique, was developed for the pre-concentration and determination of polycyclic aromatic hydrocarbons in environmental water samples. The proposed method utilized both solid- and liquid-phase microextraction media. Parameters that affect the extraction of polycyclic aromatic hydrocarbons were optimized in two successive steps as follows. Firstly, a methodology based on a quarter factorial design was used to choose the significant variables. Then, these significant factors were optimized utilizing central composite design. Under the optimized condition (extraction time = 25 min, amount of multiwalled carbon nanotubes = 78 mg, sample volume = 8 mL, and desorption time = 5 min), the calibration curves showed high linearity (R 2  = 0.99) in the range of 0.01-500 ng/mL and the limits of detection were in the range of 0.007-1.47 ng/mL. The obtained extraction recoveries for 10 ng/mL of polycyclic aromatic hydrocarbons standard solution were in the range of 85-92%. Replicating the experiment under these conditions five times gave relative standard deviations lower than 6%. Finally, the method was successfully applied for pre-concentration and determination of polycyclic aromatic hydrocarbons in environmental water samples. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal timing in biological processes

USGS Publications Warehouse

Williams, B.K.; Nichols, J.D.

1984-01-01

A general approach for obtaining solutions to a class of biological optimization problems is provided. The general problem is one of determining the appropriate time to take some action, when the action can be taken only once during some finite time frame. The approach can also be extended to cover a number of other problems involving animal choice (e.g., mate selection, habitat selection). Returns (assumed to index fitness) are treated as random variables with time-specific distributions, and can be either observable or unobservable at the time action is taken. In the case of unobservable returns, the organism is assumed to base decisions on some ancillary variable that is associated with returns. Optimal policies are derived for both situations and their properties are discussed. Various extensions are also considered, including objective functions based on functions of returns other than the mean, nonmonotonic relationships between the observable variable and returns; possible death of the organism before action is taken; and discounting of future returns. A general feature of the optimal solutions for many of these problems is that an organism should be very selective (i.e., should act only when returns or expected returns are relatively high) at the beginning of the time frame and should become less and less selective as time progresses. An example of the application of optimal timing to a problem involving the timing of bird migration is discussed, and a number of other examples for which the approach is applicable are described.

Optimization of lipids' ultrasonic extraction and production from Chlorella sp. using response-surface methodology.

PubMed

Hadrich, Bilel; Akremi, Ismahen; Dammak, Mouna; Barkallah, Mohamed; Fendri, Imen; Abdelkafi, Slim

2018-04-17

Three steps are very important in order to produce microalgal lipids: (1) controlling microalgae cultivation via experimental and modeling investigations, (2) optimizing culture conditions to maximize lipids production and to determine the fatty acid profile the most appropriate for biodiesel synthesis, and (3) optimizing the extraction of the lipids accumulated in the microalgal cells. Firstly, three kinetics models, namely logistic, logistic-with-lag and modified Gompertz, were tested to fit the experimental kinetics of the Chlorella sp. microalga culture established on standard conditions. Secondly, the response-surface methodology was used for two optimizations in this study. The first optimization was established for lipids production from Chlorella sp. culture under different culture conditions. In fact, different levels of nitrate concentrations, salinities and light intensities were applied to the culture medium in order to study their influences on lipids production and determine their fatty acid profile. The second optimization was concerned with the lipids extraction factors: ultrasonic's time and temperature, and chloroform-methanol solvent ratio. All models (logistic, logistic-with-lag and modified Gompertz) applied for the experimental kinetics of Chlorella sp. show a very interesting fitting quality. The logistic model was chosen to describe the Chlorella sp. kinetics, since it yielded the most important statistical criteria: coefficient of determination of the order of 94.36%; adjusted coefficient of determination equal to 93.79% and root mean square error reaching 3.685 cells · ml - 1 . Nitrate concentration and the two interactions involving the light intensity (Nitrate concentration × light intensity, and salinities × light intensity) showed a very significant influence on lipids production in the first optimization (p < 0.05). Yet, only the quadratic term of chloroform-methanol solvent ratio showed a significant influence on lipids extraction relative to the second step of optimization (p < 0.05). The two most abundant fatty acid methyl esters (≈72%) derived from the Chlorella sp. microalga cultured in the determined optimal conditions are: palmitic acid (C16:0) and oleic acid (C18:1) with the corresponding yields of 51.69% and 20.55% of total fatty acids, respectively. Only the nitrate deficiency and the high intensity of light can influence the microalgal lipids production. The corresponding fatty acid methyl esters composition is very suitable for biodiesel production. Lipids extraction is efficient only over long periods of time when using a solvent with a 2/1 chloroform/methanol ratio.

Solid-phase microextraction of benzimidazole fungicides in environmental liquid samples and HPLC-fluorescence determination.

PubMed

López Monzón, A; Vega Moreno, D; Torres Padrón, M E; Sosa Ferrera, Z; Santana Rodríguez, J J

2007-03-01

Solid-phase microextraction (SPME) coupled with high-performance liquid chromatography (HPLC) with fluorescence detection was optimized for extraction and determination of four benzimidazole fungicides (benomyl, carbendazim, thiabendazole, and fuberidazole) in water. We studied extraction and desorption conditions, for example fiber type, extraction time, ionic strength, extraction temperature, and desorption time to achieve the maximum efficiency in the extraction. Results indicate that SPME using a Carboxen-polydimethylsiloxane 75 microm (CAR-PDMS) fiber is suitable for extraction of these types of compound. Final analysis of benzimidazole fungicides was performed by HPLC with fluorescence detection. Recoveries ranged from 80.6 to 119.6 with RSDs below 9% and limits of detection between 0.03 and 1.30 ng mL-1 for the different analytes. The optimized procedure was applied successfully to the determination of benzimidazole fungicides mixtures in environmental water samples (sea, sewage, and ground water).

Timing of conception and the risk of spontaneous abortion among pregnancies occurring during the use of natural family planning.

PubMed

Gray, R H; Simpson, J L; Kambic, R T; Queenan, J T; Mena, P; Perez, A; Barbato, M

1995-05-01

Our purpose was to ascertain the effects of timing of conception on the risk of spontaneous abortion. To assess these effects, women who conceived while using natural family planning were identified in five centers worldwide between 1987 and 1993. Timing of conception was determined from 868 natural family planning charts that recorded day of intercourse and indices of ovulation (cervical mucus peak obtained according to the ovulation method and/or basal body temperature). Conceptions on days - 1 or 0 with respect to the natural family planning estimated day of ovulation were considered to be "optimally timed," and all other conceptions were considered as "non-optimally timed." The rate of spontaneous abortions per 100 pregnancies was examined in relation to timing of conception, ages, reproductive history, and other covariates with bivariate and multivariate statistical methods. There were 88 spontaneous abortions among 868 pregnancies (10.1%). The spontaneous abortion rate was similar for 361 optimally timed conceptions (9.1%) and 507 non-optimally timed conceptions (10.9%). However, among 171 women who had experienced a spontaneous abortion in a prior pregnancy, the rate of spontaneous abortion in the index pregnancy was significantly higher with non-optimally timed conceptions (22.6%) as compared with optimally timed conceptions (7.3%). This association was not observed among 697 women with no history of pregnancy loss. The adjusted relative risk of spontaneous abortion among women with non-optimally timed conceptions and a history of pregnancy loss was 2.35 (95% confidence intervals 1.42 to 3.89). The excess risk of spontaneous abortion was observed with both preovulatory and postovulatory conceptions. Overall, there is no excess risk of spontaneous abortion among the pregnancies conceived during natural family planning use. However, among women with a history of pregnancy loss, there is an increased risk of spontaneous abortion associated with preovulatory or postovulatory delayed conceptions.

Theory and computation of optimal low- and medium-thrust transfers

NASA Technical Reports Server (NTRS)

Chuang, C.-H.

1994-01-01

This report presents two numerical methods considered for the computation of fuel-optimal, low-thrust orbit transfers in large numbers of burns. The origins of these methods are observations made with the extremal solutions of transfers in small numbers of burns; there seems to exist a trend such that the longer the time allowed to perform an optimal transfer the less fuel that is used. These longer transfers are obviously of interest since they require a motor of low thrust; however, we also find a trend that the longer the time allowed to perform the optimal transfer the more burns are required to satisfy optimality. Unfortunately, this usually increases the difficulty of computation. Both of the methods described use small-numbered burn solutions to determine solutions in large numbers of burns. One method is a homotopy method that corrects for problems that arise when a solution requires a new burn or coast arc for optimality. The other method is to simply patch together long transfers from smaller ones. An orbit correction problem is solved to develop this method. This method may also lead to a good guidance law for transfer orbits with long transfer times.

The Effects of Creatine Supplementation on Explosive Performance and Optimal Individual Postactivation Potentiation Time.

PubMed

Wang, Chia-Chi; Yang, Ming-Ta; Lu, Kang-Hao; Chan, Kuei-Hui

2016-03-04

Creatine plays an important role in muscle energy metabolism. Postactivation potentiation (PAP) is a phenomenon that can acutely increase muscle power, but it is an individualized process that is influenced by muscle fatigue. This study examined the effects of creatine supplementation on explosive performance and the optimal individual PAP time during a set of complex training bouts. Thirty explosive athletes performed tests of back squat for one repetition maximum (1RM) strength and complex training bouts for determining the individual optimal timing of PAP, height and peak power of a counter movement jump before and after the supplementation. Subjects were assigned to a creatine or placebo group and then consumed 20 g of creatine or carboxymethyl cellulose per day for six days. After the supplementation, the 1RM strength in the creatine group significantly increased (p < 0.05). The optimal individual PAP time in the creatine group was also significant earlier than the pre-supplementation and post-supplementation of the placebo group (p < 0.05). There was no significant difference in jump performance between the groups. This study demonstrates that creatine supplementation improves maximal muscle strength and the optimal individual PAP time of complex training but has no effect on explosive performance.

The Effects of Creatine Supplementation on Explosive Performance and Optimal Individual Postactivation Potentiation Time

PubMed Central

Wang, Chia-Chi; Yang, Ming-Ta; Lu, Kang-Hao; Chan, Kuei-Hui

2016-01-01

Creatine plays an important role in muscle energy metabolism. Postactivation potentiation (PAP) is a phenomenon that can acutely increase muscle power, but it is an individualized process that is influenced by muscle fatigue. This study examined the effects of creatine supplementation on explosive performance and the optimal individual PAP time during a set of complex training bouts. Thirty explosive athletes performed tests of back squat for one repetition maximum (1RM) strength and complex training bouts for determining the individual optimal timing of PAP, height and peak power of a counter movement jump before and after the supplementation. Subjects were assigned to a creatine or placebo group and then consumed 20 g of creatine or carboxymethyl cellulose per day for six days. After the supplementation, the 1RM strength in the creatine group significantly increased (p < 0.05). The optimal individual PAP time in the creatine group was also significant earlier than the pre-supplementation and post-supplementation of the placebo group (p < 0.05). There was no significant difference in jump performance between the groups. This study demonstrates that creatine supplementation improves maximal muscle strength and the optimal individual PAP time of complex training but has no effect on explosive performance. PMID:26959056

Brachistochrone of entanglement for spin chains

NASA Astrophysics Data System (ADS)

Carlini, Alberto; Koike, Tatsuhiko

2017-03-01

We analytically investigate the role of entanglement in time-optimal state evolution as an application of the quantum brachistochrone, a general method for obtaining the optimal time-dependent Hamiltonian for reaching a target quantum state. As a model, we treat two qubits indirectly coupled through an intermediate qubit that is directly controllable, which represents a typical situation in quantum information processing. We find the time-optimal unitary evolution law and quantify residual entanglement by the two-tangle between the indirectly coupled qubits, for all possible sets of initial pure quantum states of a tripartite system. The integrals of the motion of the brachistochrone are determined by fixing the minimal time at which the residual entanglement is maximized. Entanglement plays a role for W and Greenberger-Horne-Zeilinger (GHz) initial quantum states, and for the bi-separable initial state in which the indirectly coupled qubits have a nonzero value of the 2-tangle.

The Effects of General Social Support and Social Support for Racial Discrimination on African American Women’s Well-Being

PubMed Central

Seawell, Asani H.; Cutrona, Carolyn E.; Russell, Daniel W.

2012-01-01

The present longitudinal study examined the role of general and tailored social support in mitigating the deleterious impact of racial discrimination on depressive symptoms and optimism in a large sample of African American women. Participants were 590 African American women who completed measures assessing racial discrimination, general social support, tailored social support for racial discrimination, depressive symptoms, and optimism at two time points (2001–2002 and 2003–2004). Our results indicated that higher levels of general and tailored social support predicted optimism one year later; changes in both types of support also predicted changes in optimism over time. Although initial levels of neither measure of social support predicted depressive symptoms over time, changes in tailored support predicted changes in depressive symptoms. We also sought to determine whether general and tailored social support “buffer” or diminish the negative effects of racial discrimination on depressive symptoms and optimism. Our results revealed a classic buffering effect of tailored social support, but not general support on depressive symptoms for women experiencing high levels of discrimination. PMID:24443614

Probability distribution functions for unit hydrographs with optimization using genetic algorithm

NASA Astrophysics Data System (ADS)

Ghorbani, Mohammad Ali; Singh, Vijay P.; Sivakumar, Bellie; H. Kashani, Mahsa; Atre, Atul Arvind; Asadi, Hakimeh

2017-05-01

A unit hydrograph (UH) of a watershed may be viewed as the unit pulse response function of a linear system. In recent years, the use of probability distribution functions (pdfs) for determining a UH has received much attention. In this study, a nonlinear optimization model is developed to transmute a UH into a pdf. The potential of six popular pdfs, namely two-parameter gamma, two-parameter Gumbel, two-parameter log-normal, two-parameter normal, three-parameter Pearson distribution, and two-parameter Weibull is tested on data from the Lighvan catchment in Iran. The probability distribution parameters are determined using the nonlinear least squares optimization method in two ways: (1) optimization by programming in Mathematica; and (2) optimization by applying genetic algorithm. The results are compared with those obtained by the traditional linear least squares method. The results show comparable capability and performance of two nonlinear methods. The gamma and Pearson distributions are the most successful models in preserving the rising and recession limbs of the unit hydographs. The log-normal distribution has a high ability in predicting both the peak flow and time to peak of the unit hydrograph. The nonlinear optimization method does not outperform the linear least squares method in determining the UH (especially for excess rainfall of one pulse), but is comparable.

Optimal impulsive manoeuvres and aerodynamic braking

NASA Technical Reports Server (NTRS)

Jezewski, D. J.

1985-01-01

A method developed for obtaining solutions to the aerodynamic braking problem, using impulses in the exoatmospheric phases is discussed. The solution combines primer vector theory and the results of a suboptimal atmospheric guidance program. For a specified initial and final orbit, the solution determines: (1) the minimum impulsive cost using a maximum of four impulses, (2) the optimal atmospheric entry and exit-state vectors subject to equality and inequality constraints, and (3) the optimal coast times. Numerical solutions which illustrate the characteristics of the solution are presented.

Using Biomechanical Optimization To Interpret Dancers’ Pose Selection For A Partnered Spin

DTIC Science & Technology

2009-05-06

optimized performance of a straight arm backward longswing on the still rings in mens artistic gymnastics . Because gymnasts lose points for excessive swing at...an actual performance and used that as the basis for their search. Yeadon determined that with timing within 15ms, gymnasts can minimize their excess...are moving in an optimal way. 2.5 Body Modeling 2.5.1 Building the Body In his study involving gymnasts on the rings, Yeadon developed a body model com

Study on Operation Optimization of Pumping Station's 24 Hours Operation under Influences of Tides and Peak-Valley Electricity Prices

NASA Astrophysics Data System (ADS)

Yi, Gong; Jilin, Cheng; Lihua, Zhang; Rentian, Zhang

2010-06-01

According to different processes of tides and peak-valley electricity prices, this paper determines the optimal start up time in pumping station's 24 hours operation between the rating state and adjusting blade angle state respectively based on the optimization objective function and optimization model for single-unit pump's 24 hours operation taking JiangDu No.4 Pumping Station for example. In the meantime, this paper proposes the following regularities between optimal start up time of pumping station and the process of tides and peak-valley electricity prices each day within a month: (1) In the rating and adjusting blade angle state, the optimal start up time in pumping station's 24 hours operation which depends on the tide generation at the same day varies with the process of tides. There are mainly two kinds of optimal start up time which include the time at tide generation and 12 hours after it. (2) In the rating state, the optimal start up time on each day in a month exhibits a rule of symmetry from 29 to 28 of next month in the lunar calendar. The time of tide generation usually exists in the period of peak electricity price or the valley one. The higher electricity price corresponds to the higher minimum cost of water pumping at unit, which means that the minimum cost of water pumping at unit depends on the peak-valley electricity price at the time of tide generation on the same day. (3) In the adjusting blade angle state, the minimum cost of water pumping at unit in pumping station's 24 hour operation depends on the process of peak-valley electricity prices. And in the adjusting blade angle state, 4.85%˜5.37% of the minimum cost of water pumping at unit will be saved than that of in the rating state.

[Optimization of Extraction Technology for Sericin from Silkworm Cocoon with Orthogonal Design].

PubMed

Zhao, Chun-ying; Wang, Yan; Li, Yun-feng; Chen, Zhi-hong

2015-05-01

To optimize the appropriate extracting technology for sericin from Silkworm cocoon. Using sericin extraction rates and sericin content as the indices. The single and orthogonal experiments were used to determine the best conditions. The optimal extraction technology for sericin from Silkworm cocoon was as follows: 1: 30 for the ratio of solid to liquid, 3 h reflux for 2 times of extraction and water temperature at 100 degrees C. The extraction rate of sericin from Silkworm cocoon was 27.1%. The optimal extraction technology is stable, feasible, and can provide reference for further pharmacological study on cocoon sericin.

Contributions to optimization of storage and transporting industrial goods

NASA Astrophysics Data System (ADS)

Babanatsas, T.; Babanatis Merce, R. M.; Glăvan, D. O.; Glăvan, A.

2018-01-01

Optimization of storage and transporting industrial goods in a factory either from a constructive, functional, or technological point of view is a determinant parameter in programming the manufacturing process, the performance of the whole process being determined by the correlation realized taking in consideration those two factors (optimization and programming the process). It is imperative to take into consideration each type of production program (range), to restrain as much as possible the area that we are using and to minimize the times of execution, all of these in order to satisfy the client’s needs, to try to classify them in order to be able to define a global software (with general rules) that is expected to fulfil each client’s needs.

Optimization of Preparation of Antioxidative Peptides from Pumpkin Seeds Using Response Surface Method

PubMed Central

Fan, Sanhong; Hu, Yanan; Li, Chen; Liu, Yanrong

2014-01-01

Protein isolates of pumpkin (Cucurbita pepo L) seeds were hydrolyzed by acid protease to prepare antioxidative peptides. The hydrolysis conditions were optimized through Box-Behnken experimental design combined with response surface method (RSM). The second-order model, developed for the DPPH radical scavenging activity of pumpkin seed hydrolysates, showed good fit with the experiment data with a high value of coefficient of determination (0.9918). The optimal hydrolysis conditions were determined as follows: hydrolyzing temperature 50°C, pH 2.5, enzyme amount 6000 U/g, substrate concentration 0.05 g/ml and hydrolyzing time 5 h. Under the above conditions, the scavenging activity of DPPH radical was as high as 92.82%. PMID:24637721

Subspace-based optimization method for inverse scattering problems with an inhomogeneous background medium

NASA Astrophysics Data System (ADS)

Chen, Xudong

2010-07-01

This paper proposes a version of the subspace-based optimization method to solve the inverse scattering problem with an inhomogeneous background medium where the known inhomogeneities are bounded in a finite domain. Although the background Green's function at each discrete point in the computational domain is not directly available in an inhomogeneous background scenario, the paper uses the finite element method to simultaneously obtain the Green's function at all discrete points. The essence of the subspace-based optimization method is that part of the contrast source is determined from the spectrum analysis without using any optimization, whereas the orthogonally complementary part is determined by solving a lower dimension optimization problem. This feature significantly speeds up the convergence of the algorithm and at the same time makes it robust against noise. Numerical simulations illustrate the efficacy of the proposed algorithm. The algorithm presented in this paper finds wide applications in nondestructive evaluation, such as through-wall imaging.

Development of new UV-vis spectroscopic microwave-assisted method for determination of glucose in pharmaceutical samples

NASA Astrophysics Data System (ADS)

Mabood, Fazal; Hussain, Z.; Haq, H.; Arian, M. B.; Boqué, R.; Khan, K. M.; Hussain, K.; Jabeen, F.; Hussain, J.; Ahmed, M.; Alharasi, A.; Naureen, Z.; Hussain, H.; Khan, A.; Perveen, S.

2016-01-01

A new UV-Visible spectroscopic method assisted with microwave for the determination of glucose in pharmaceutical formulations was developed. In this study glucose solutions were oxidized by ammonium molybdate in the presence of microwave energy and reacted with aniline to produce a colored solution. Optimum conditions of the reaction including wavelength, temperature, and pH of the medium and relative concentration ratio of the reactants were investigated. It was found that the optimal wavelength for the reaction is 610 nm, the optimal reaction time is 80 s, the optimal reaction temperature is 160 °C, the optimal reaction pH is 4, and the optimal concentration ratio aniline/ammonium molybdate solution was found to be 1:1. The limits of detection and quantification of the method are 0.82 and 2.75 ppm for glucose solution, respectively. The use of microwaves improved the speed of the method while the use of aniline improved the sensitivity of the method by shifting the wavelength.

Polynomial elimination theory and non-linear stability analysis for the Euler equations

NASA Technical Reports Server (NTRS)

Kennon, S. R.; Dulikravich, G. S.; Jespersen, D. C.

1986-01-01

Numerical methods are presented that exploit the polynomial properties of discretizations of the Euler equations. It is noted that most finite difference or finite volume discretizations of the steady-state Euler equations produce a polynomial system of equations to be solved. These equations are solved using classical polynomial elimination theory, with some innovative modifications. This paper also presents some preliminary results of a new non-linear stability analysis technique. This technique is applicable to determining the stability of polynomial iterative schemes. Results are presented for applying the elimination technique to a one-dimensional test case. For this test case, the exact solution is computed in three iterations. The non-linear stability analysis is applied to determine the optimal time step for solving Burgers' equation using the MacCormack scheme. The estimated optimal time step is very close to the time step that arises from a linear stability analysis.

OPTIMIZED DETERMINATION OF TRACE JET FUEL VOLATILE ORGANIC COMPOUNDS IN HUMAN BLOOD USING IN-FIELD LIQUID-LIQUID EXTRACTION WITH SUBSEQUENT LABORATORY GAS CHROMATOGRAPHIC-MASS SPECTROMETRIC ANALYSIS AND ON-COLUMN LARGE VOLUME INJECTION

EPA Science Inventory

A practical and sensitive method to assess volatile organic compounds (VOCs) from JP-8 jet fuel in human whole blood was developed by modifying previously established liquid-liquid extraction procedures, optimizing extraction times, solvent volume, specific sample processing te...

Efficient global fiber tracking on multi-dimensional diffusion direction maps

NASA Astrophysics Data System (ADS)

Klein, Jan; Köhler, Benjamin; Hahn, Horst K.

2012-02-01

Global fiber tracking algorithms have recently been proposed which were able to compute results of unprecedented quality. They account for avoiding accumulation errors by a global optimization process at the cost of a high computation time of several hours or even days. In this paper, we introduce a novel global fiber tracking algorithm which, for the first time, globally optimizes the underlying diffusion direction map obtained from DTI or HARDI data, instead of single fiber segments. As a consequence, the number of iterations in the optimization process can drastically be reduced by about three orders of magnitude. Furthermore, in contrast to all previous algorithms, the density of the tracked fibers can be adjusted after the optimization within a few seconds. We evaluated our method for diffusion-weighted images obtained from software phantoms, healthy volunteers, and tumor patients. We show that difficult fiber bundles, e.g., the visual pathways or tracts for different motor functions can be determined and separated in an excellent quality. Furthermore, crossing and kissing bundles are correctly resolved. On current standard hardware, a dense fiber tracking result of a whole brain can be determined in less than half an hour which is a strong improvement compared to previous work.

Design of transonic airfoil sections using a similarity theory

NASA Technical Reports Server (NTRS)

Nixon, D.

1978-01-01

A study of the available methods for transonic airfoil and wing design indicates that the most powerful technique is the numerical optimization procedure. However, the computer time for this method is relatively large because of the amount of computation required in the searches during optimization. The optimization method requires that base and calibration solutions be computed to determine a minimum drag direction. The design space is then computationally searched in this direction; it is these searches that dominate the computation time. A recent similarity theory allows certain transonic flows to be calculated rapidly from the base and calibration solutions. In this paper the application of the similarity theory to design problems is examined with the object of at least partially eliminating the costly searches of the design optimization method. An example of an airfoil design is presented.

Optimizing Mars Airplane Trajectory with the Application Navigation System

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Riley, Derek

2004-01-01

Planning complex missions requires a number of programs to be executed in concert. The Application Navigation System (ANS), developed in the NAS Division, can execute many interdependent programs in a distributed environment. We show that the ANS simplifies user effort and reduces time in optimization of the trajectory of a martian airplane. We use a software package, Cart3D, to evaluate trajectories and a shortest path algorithm to determine the optimal trajectory. ANS employs the GridScape to represent the dynamic state of the available computer resources. Then, ANS uses a scheduler to dynamically assign ready task to machine resources and the GridScape for tracking available resources and forecasting completion time of running tasks. We demonstrate system capability to schedule and run the trajectory optimization application with efficiency exceeding 60% on 64 processors.

Empirical Performance Model-Driven Data Layout Optimization and Library Call Selection for Tensor Contraction Expressions

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

Lu, Qingda; Gao, Xiaoyang; Krishnamoorthy, Sriram

Empirical optimizers like ATLAS have been very effective in optimizing computational kernels in libraries. The best choice of parameters such as tile size and degree of loop unrolling is determined by executing different versions of the computation. In contrast, optimizing compilers use a model-driven approach to program transformation. While the model-driven approach of optimizing compilers is generally orders of magnitude faster than ATLAS-like library generators, its effectiveness can be limited by the accuracy of the performance models used. In this paper, we describe an approach where a class of computations is modeled in terms of constituent operations that are empiricallymore » measured, thereby allowing modeling of the overall execution time. The performance model with empirically determined cost components is used to perform data layout optimization together with the selection of library calls and layout transformations in the context of the Tensor Contraction Engine, a compiler for a high-level domain-specific language for expressing computational models in quantum chemistry. The effectiveness of the approach is demonstrated through experimental measurements on representative computations from quantum chemistry.« less

Optimal Transient Growth of Submesoscale Baroclinic Instabilities

NASA Astrophysics Data System (ADS)

White, Brian; Zemskova, Varvara; Passaggia, Pierre-Yves

2016-11-01

Submesoscale instabilities are analyzed using a transient growth approach to determine the optimal perturbation for a rotating Boussinesq fluid subject to baroclinic instabilities. We consider a base flow with uniform shear and stratification and consider the non-normal evolution over finite-time horizons of linear perturbations in an ageostrophic, non-hydrostatic regime. Stone (1966, 1971) showed that the stability of the base flow to normal modes depends on the Rossby and Richardson numbers, with instabilities ranging from geostrophic (Ro -> 0) and ageostrophic (finite Ro) baroclinic modes to symmetric (Ri < 1 , Ro > 1) and Kelvin-Helmholtz (Ri < 1 / 4) modes. Non-normal transient growth, initiated by localized optimal wave packets, represents a faster mechanism for the growth of perturbations and may provide an energetic link between large-scale flows in geostrophic balance and dissipation scales via submesoscale instabilities. Here we consider two- and three-dimensional optimal perturbations by means of direct-adjoint iterations of the linearized Boussinesq Navier-Stokes equations to determine the form of the optimal perturbation, the optimal energy gain, and the characteristics of the most unstable perturbation.

Box-Behnken statistical design to optimize thermal performance of energy storage systems

NASA Astrophysics Data System (ADS)

Jalalian, Iman Joz; Mohammadiun, Mohammad; Moqadam, Hamid Hashemi; Mohammadiun, Hamid

2018-05-01

Latent heat thermal storage (LHTS) is a technology that can help to reduce energy consumption for cooling applications, where the cold is stored in phase change materials (PCMs). In the present study a comprehensive theoretical and experimental investigation is performed on a LHTES system containing RT25 as phase change material (PCM). Process optimization of the experimental conditions (inlet air temperature and velocity and number of slabs) was carried out by means of Box-Behnken design (BBD) of Response surface methodology (RSM). Two parameters (cooling time and COP value) were chosen to be the responses. Both of the responses were significantly influenced by combined effect of inlet air temperature with velocity and number of slabs. Simultaneous optimization was performed on the basis of the desirability function to determine the optimal conditions for the cooling time and COP value. Maximum cooling time (186 min) and COP value (6.04) were found at optimum process conditions i.e. inlet temperature of (32.5), air velocity of (1.98) and slab number of (7).

Optimal cooperative time-fixed impulsive rendezvous

NASA Technical Reports Server (NTRS)

Mirfakhraie, Koorosh; Conway, Bruce A.; Prussing, John E.

1988-01-01

A method has been developed for determining optimal, i.e., minimum fuel, trajectories for the fixed-time cooperative rendezvous of two spacecraft. The method presently assumes that the vehicles perform a total of three impulsive maneuvers with each vehicle being active, that is, making at least one maneuver. The cost of a feasible 'reference' trajectory is improved by an optimizer which uses an analytical gradient developed using primer vector theory and a new solution for the optimal terminal (rendezvous) maneuver. Results are presented for a large number of cases in which the initial orbits of both vehicles are circular but in which the initial positions of the vehicles and the allotted time for rendezvous are varied. In general, the cost of the cooperative rendezvous is less than that of rendezvous with one vehicle passive. Further improvement in cost may be obtained in the future when additional, i.e., midcourse, impulses are allowed and inserted as indicated for some cases by the primer vector histories which are generated by the program.

Algorithms and analyses for stochastic optimization for turbofan noise reduction using parallel reduced-order modeling

NASA Astrophysics Data System (ADS)

Yang, Huanhuan; Gunzburger, Max

2017-06-01

Simulation-based optimization of acoustic liner design in a turbofan engine nacelle for noise reduction purposes can dramatically reduce the cost and time needed for experimental designs. Because uncertainties are inevitable in the design process, a stochastic optimization algorithm is posed based on the conditional value-at-risk measure so that an ideal acoustic liner impedance is determined that is robust in the presence of uncertainties. A parallel reduced-order modeling framework is developed that dramatically improves the computational efficiency of the stochastic optimization solver for a realistic nacelle geometry. The reduced stochastic optimization solver takes less than 500 seconds to execute. In addition, well-posedness and finite element error analyses of the state system and optimization problem are provided.

Influence of the weighing bar size to determine optimal time of biodiesel-glycerol separation by using the buoyancy weighing-bar method

NASA Astrophysics Data System (ADS)

Tambun, R.; Sibagariang, Y.; Manurung, J.

2018-02-01

The buoyancy weighing-bar method is a novel method in the particle size distribution measurement. This method can measure particle size distributions of the settling particles and floating particles. In this study, the buoyancy weighing-bar method is applied to determine optimal time of biodiesel-glycerol separation. The buoyancy weighing-bar method can be applied to determine the separation time because biodiesel and glycerol have the different densities. The influences of diameter of weighing-bar by using the buoyancy weighing-bar method would be experimentally investigated. The diameters of weighing-bar in this experiment are 8 mm, 10 mm, 15 mm and 20 mm, while the graduated cylinder (diameter : 65 mm) is used as vessel. The samples used in this experiment are the mixture of 95 % of biodiesel and 5 % of glycerol. The data obtained by the buoyancy weighing-bar method are analized by using the gas chromatography to determine the purity of biodiesel. Based on the data obtained, the buoyancy weighing-bar method can be used to detect the separation time of biodiesel-glycerol by using the weighing-bar diameter of 8 mm, 10 mm, 15 mm and 20 mm, but the most accuracy in determination the biodiesel-glycerol separation time is obtained by using the weighing-bar diameter of 20 mm. The biodiesel purity of 97.97 % could be detected at 64 minutes by using the buoyancy weighing-bar method when the weighing-bar diameter of 20 mm is used.

Plasma plume expansion dynamics in nanosecond Nd:YAG laserosteotome

NASA Astrophysics Data System (ADS)

Abbasi, Hamed; Rauter, Georg; Guzman, Raphael; Cattin, Philippe C.; Zam, Azhar

2018-02-01

In minimal invasive laser osteotomy precise information about the ablation process can be obtained with LIBS in order to avoid carbonization, or cutting of wrong types of tissue. Therefore, the collecting fiber for LIBS needs to be optimally placed in narrow cavities in the endoscope. To determine this optimal placement, the plasma plume expansion dynamics in ablation of bone tissue by the second harmonic of a nanosecond Nd:YAG laser at 532 nm has been studied. The laserinduced plasma plume was monitored in different time delays, from one nanosecond up to one hundred microseconds. Measurements were performed using high-speed gated illumination imaging. The expansion features were studied using illumination of the overall visible emission by using a gated intensified charged coupled device (ICCD). The camera was capable of having a minimum gate width (Optical FWHM) of 3 ns and the timing resolution (minimum temporal shift of the gate) of 10 ps. The imaging data were used to generate position-time data of the luminous plasma-front. Moreover, the velocity of the plasma plume expansion was studied based on the time-resolved intensity data. By knowing the plasma plume profile over time, the optimum position (axial distance from the laser spot) of the collecting fiber and optimal time delay (to have the best signal to noise ratio) in spatial-resolved and time-resolved laser-induced breakdown spectroscopy (LIBS) can be determined. Additionally, the function of plasma plume expansion could be used to study the shock wave of the plasma plume.

A novel neutron energy spectrum unfolding code using particle swarm optimization

NASA Astrophysics Data System (ADS)

Shahabinejad, H.; Sohrabpour, M.

2017-07-01

A novel neutron Spectrum Deconvolution using Particle Swarm Optimization (SDPSO) code has been developed to unfold the neutron spectrum from a pulse height distribution and a response matrix. The Particle Swarm Optimization (PSO) imitates the bird flocks social behavior to solve complex optimization problems. The results of the SDPSO code have been compared with those of the standard spectra and recently published Two-steps Genetic Algorithm Spectrum Unfolding (TGASU) code. The TGASU code have been previously compared with the other codes such as MAXED, GRAVEL, FERDOR and GAMCD and shown to be more accurate than the previous codes. The results of the SDPSO code have been demonstrated to match well with those of the TGASU code for both under determined and over-determined problems. In addition the SDPSO has been shown to be nearly two times faster than the TGASU code.

The effect of statistical noise on IMRT plan quality and convergence for MC-based and MC-correction-based optimized treatment plans.

PubMed

Siebers, Jeffrey V

2008-04-04

Monte Carlo (MC) is rarely used for IMRT plan optimization outside of research centres due to the extensive computational resources or long computation times required to complete the process. Time can be reduced by degrading the statistical precision of the MC dose calculation used within the optimization loop. However, this eventually introduces optimization convergence errors (OCEs). This study determines the statistical noise levels tolerated during MC-IMRT optimization under the condition that the optimized plan has OCEs <100 cGy (1.5% of the prescription dose) for MC-optimized IMRT treatment plans.Seven-field prostate IMRT treatment plans for 10 prostate patients are used in this study. Pre-optimization is performed for deliverable beams with a pencil-beam (PB) dose algorithm. Further deliverable-based optimization proceeds using: (1) MC-based optimization, where dose is recomputed with MC after each intensity update or (2) a once-corrected (OC) MC-hybrid optimization, where a MC dose computation defines beam-by-beam dose correction matrices that are used during a PB-based optimization. Optimizations are performed with nominal per beam MC statistical precisions of 2, 5, 8, 10, 15, and 20%. Following optimizer convergence, beams are re-computed with MC using 2% per beam nominal statistical precision and the 2 PTV and 10 OAR dose indices used in the optimization objective function are tallied. For both the MC-optimization and OC-optimization methods, statistical equivalence tests found that OCEs are less than 1.5% of the prescription dose for plans optimized with nominal statistical uncertainties of up to 10% per beam. The achieved statistical uncertainty in the patient for the 10% per beam simulations from the combination of the 7 beams is ~3% with respect to maximum dose for voxels with D>0.5D(max). The MC dose computation time for the OC-optimization is only 6.2 minutes on a single 3 Ghz processor with results clinically equivalent to high precision MC computations.

Coordination Between the Sexes Constrains the Optimization of Reproductive Timing in Honey Bee Colonies.

PubMed

Lemanski, Natalie J; Fefferman, Nina H

2017-06-01

Honeybees are an excellent model system for examining how trade-offs shape reproductive timing in organisms with seasonal environments. Honeybee colonies reproduce two ways: producing swarms comprising a queen and thousands of workers or producing males (drones). There is an energetic trade-off between producing workers, which contribute to colony growth, and drones, which contribute only to reproduction. The timing of drone production therefore determines both the drones' likelihood of mating and when colonies reach sufficient size to swarm. Using a linear programming model, we ask when a colony should produce drones and swarms to maximize reproductive success. We find the optimal behavior for each colony is to produce all drones prior to swarming, an impossible solution on a population scale because queens and drones would never co-occur. Reproductive timing is therefore not solely determined by energetic trade-offs but by the game theoretic problem of coordinating the production of reproductives among colonies.

A Sarsa(λ)-based control model for real-time traffic light coordination.

PubMed

Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

Pricing policy for declining demand using item preservation technology.

PubMed

Khedlekar, Uttam Kumar; Shukla, Diwakar; Namdeo, Anubhav

2016-01-01

We have designed an inventory model for seasonal products in which deterioration can be controlled by item preservation technology investment. Demand for the product is considered price sensitive and decreases linearly. This study has shown that the profit is a concave function of optimal selling price, replenishment time and preservation cost parameter. We simultaneously determined the optimal selling price of the product, the replenishment cycle and the cost of item preservation technology. Additionally, this study has shown that there exists an optimal selling price and optimal preservation investment to maximize the profit for every business set-up. Finally, the model is illustrated by numerical examples and sensitive analysis of the optimal solution with respect to major parameters.

Optimal order policy in response to announced price increase for deteriorating items with limited special order quantity

NASA Astrophysics Data System (ADS)

Ouyang, Liang-Yuh; Wu, Kun-Shan; Yang, Chih-Te; Yen, Hsiu-Feng

2016-02-01

When a supplier announces an impending price increase due to take effect at a certain time in the future, it is important for each retailer to decide whether to purchase additional stock to take advantage of the present lower price. This study explores the possible effects of price increases on a retailer's replenishment policy when the special order quantity is limited and the rate of deterioration of the goods is assumed to be constant. The two situations discussed in this study are as follows: (1) when the special order time coincides with the retailer's replenishment time and (2) when the special order time occurs during the retailer's sales period. By analysing the total cost savings between special and regular orders during the depletion time of the special order quantity, the optimal order policy for each situation can be determined. We provide several numerical examples to illustrate the theories in practice. Additionally, we conduct a sensitivity analysis on the optimal solution with respect to the main parameters.

Optimal harvesting of fish stocks under a time-varying discount rate.

PubMed

Duncan, Stephen; Hepburn, Cameron; Papachristodoulou, Antonis

2011-01-21

Optimal control theory has been extensively used to determine the optimal harvesting policy for renewable resources such as fish stocks. In such optimisations, it is common to maximise the discounted utility of harvesting over time, employing a constant time discount rate. However, evidence from human and animal behaviour suggests that we have evolved to employ discount rates which fall over time, often referred to as "hyperbolic discounting". This increases the weight on benefits in the distant future, which may appear to provide greater protection of resources for future generations, but also creates challenges of time-inconsistent plans. This paper examines harvesting plans when the discount rate declines over time. With a declining discount rate, the planner reduces stock levels in the early stages (when the discount rate is high) and intends to compensate by allowing the stock level to recover later (when the discount rate will be lower). Such a plan may be feasible and optimal, provided that the planner remains committed throughout. However, in practice there is a danger that such plans will be re-optimized and adjusted in the future. It is shown that repeatedly restarting the optimization can drive the stock level down to the point where the optimal policy is to harvest the stock to extinction. In short, a key contribution of this paper is to identify the surprising severity of the consequences flowing from incorporating a rather trivial, and widely prevalent, "non-rational" aspect of human behaviour into renewable resource management models. These ideas are related to the collapse of the Peruvian anchovy fishery in the 1970's. Copyright © 2010 Elsevier Ltd. All rights reserved.

Common aero vehicle autonomous reentry trajectory optimization satisfying waypoint and no-fly zone constraints

NASA Astrophysics Data System (ADS)

Jorris, Timothy R.

2007-12-01

To support the Air Force's Global Reach concept, a Common Aero Vehicle is being designed to support the Global Strike mission. "Waypoints" are specified for reconnaissance or multiple payload deployments and "no-fly zones" are specified for geopolitical restrictions or threat avoidance. Due to time critical targets and multiple scenario analysis, an autonomous solution is preferred over a time-intensive, manually iterative one. Thus, a real-time or near real-time autonomous trajectory optimization technique is presented to minimize the flight time, satisfy terminal and intermediate constraints, and remain within the specified vehicle heating and control limitations. This research uses the Hypersonic Cruise Vehicle (HCV) as a simplified two-dimensional platform to compare multiple solution techniques. The solution techniques include a unique geometric approach developed herein, a derived analytical dynamic optimization technique, and a rapidly emerging collocation numerical approach. This up-and-coming numerical technique is a direct solution method involving discretization then dualization, with pseudospectral methods and nonlinear programming used to converge to the optimal solution. This numerical approach is applied to the Common Aero Vehicle (CAV) as the test platform for the full three-dimensional reentry trajectory optimization problem. The culmination of this research is the verification of the optimality of this proposed numerical technique, as shown for both the two-dimensional and three-dimensional models. Additionally, user implementation strategies are presented to improve accuracy and enhance solution convergence. Thus, the contributions of this research are the geometric approach, the user implementation strategies, and the determination and verification of a numerical solution technique for the optimal reentry trajectory problem that minimizes time to target while satisfying vehicle dynamics and control limitation, and heating, waypoint, and no-fly zone constraints.

Decomposition technique and optimal trajectories for the aeroassisted flight experiment

NASA Technical Reports Server (NTRS)

Miele, A.; Wang, T.; Deaton, A. W.

1990-01-01

An actual geosynchronous Earth orbit-to-low Earth orbit (GEO-to-LEO) transfer is considered with reference to the aeroassisted flight experiment (AFE) spacecraft, and optimal trajectories are determined by minimizing the total characteristic velocity. The optimization is performed with respect to the time history of the controls (angle of attack and angle of bank), the entry path inclination and the flight time being free. Two transfer maneuvers are considered: direct ascent (DA) to LEO and indirect ascent (IA) to LEO via parking Earth orbit (PEO). By taking into account certain assumptions, the complete system can be decoupled into two subsystems: one describing the longitudinal motion and one describing the lateral motion. The angle of attack history, the entry path inclination, and the flight time are determined via the longitudinal motion subsystem. In this subsystem, the difference between the instantaneous bank angle and a constant bank angle is minimized in the least square sense subject to the specified orbital inclination requirement. Both the angles of attack and the angle of bank are shown to be constant. This result has considerable importance in the design of nominal trajectories to be used in the guidance of AFE and aeroassisted orbital transfer (AOT) vehicles.

Rapid development of xylanase assay conditions using Taguchi methodology.

PubMed

Prasad Uday, Uma Shankar; Bandyopadhyay, Tarun Kanti; Bhunia, Biswanath

2016-11-01

The present investigation is mainly concerned with the rapid development of extracellular xylanase assay conditions by using Taguchi methodology. The extracellular xylanase was produced from Aspergillus niger (KP874102.1), a new strain isolated from a soil sample of the Baramura forest, Tripura West, India. Four physical parameters including temperature, pH, buffer concentration and incubation time were considered as key factors for xylanase activity and were optimized using Taguchi robust design methodology for enhanced xylanase activity. The main effect, interaction effects and optimal levels of the process factors were determined using signal-to-noise (S/N) ratio. The Taguchi method recommends the use of S/N ratio to measure quality characteristics. Based on analysis of the S/N ratio, optimal levels of the process factors were determined. Analysis of variance (ANOVA) was performed to evaluate statistically significant process factors. ANOVA results showed that temperature contributed the maximum impact (62.58%) on xylanase activity, followed by pH (22.69%), buffer concentration (9.55%) and incubation time (5.16%). Predicted results showed that enhanced xylanase activity (81.47%) can be achieved with pH 2, temperature 50°C, buffer concentration 50 Mm and incubation time 10 min.

Optimizing light delivery for a photoacoustic surgical system

NASA Astrophysics Data System (ADS)

Eddins, Blackberrie; Lediju Bell, Muyinatu A.

2017-03-01

This work explores light delivery optimization for a photoacoustic surgical system previously proposed to provide real-time, intraoperative visualization of the internal carotid arteries hidden by bone during minimally invasive neurosurgeries. Monte Carlo simulations were employed to study 3D light propagation in tissue. For a 2.4 mm diameter drill shaft and 2.9 mm spherical drill tip, the optimal fiber distance from the drill shaft was 2 mm, determined from the maximum normalized fluence seen by the artery. A single fiber was insufficient to deliver light to arteries separated by a minimum of 8 mm. Using similar drill geometry and the optimal 2 mm fiber-to-drill shaft distance, Zemax ray tracing simulations were employed to propagate a 950 nm wavelength Gaussian beam through one or more 600 μm core diameter optical fibers, and the resulting optical beam profile was detected on the representative bone surface. For equally spaced fibers, a single merged optical profile formed with 7 or more fibers, determined by thresholding the resulting light profile images at 1/e times the maximum intensity. The corresponding spot size was larger than that of a single fiber transmitting the same input energy, thus reducing the fluence delivered to the sphenoid bone and enabling higher energies within safety limits. A prototype was designed and built based on these optimization parameters. The methodology we used to optimize our light delivery system to surround surgical tools is generalizable to multiple interventional photoacoustic applications.

Fast exploration of an optimal path on the multidimensional free energy surface

PubMed Central

Chen, Changjun

2017-01-01

In a reaction, determination of an optimal path with a high reaction rate (or a low free energy barrier) is important for the study of the reaction mechanism. This is a complicated problem that involves lots of degrees of freedom. For simple models, one can build an initial path in the collective variable space by the interpolation method first and then update the whole path constantly in the optimization. However, such interpolation method could be risky in the high dimensional space for large molecules. On the path, steric clashes between neighboring atoms could cause extremely high energy barriers and thus fail the optimization. Moreover, performing simulations for all the snapshots on the path is also time-consuming. In this paper, we build and optimize the path by a growing method on the free energy surface. The method grows a path from the reactant and extends its length in the collective variable space step by step. The growing direction is determined by both the free energy gradient at the end of the path and the direction vector pointing at the product. With fewer snapshots on the path, this strategy can let the path avoid the high energy states in the growing process and save the precious simulation time at each iteration step. Applications show that the presented method is efficient enough to produce optimal paths on either the two-dimensional or the twelve-dimensional free energy surfaces of different small molecules. PMID:28542475

Use of mathematical decomposition to optimize investments in gas production and distribution

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

Dougherty, E.L.; Lombardino, E.; Hutchinson, P.

1986-01-01

This paper presents an analytical approach based upon the decomposition method of mathematical programming for determining the optimal investment sequence in each year of a planning horizon for a group of reservoirs that produce gas and gas liquids through a trunk-line network and a gas processing plant. The paper describes the development of the simulation and investment planning system (SIPS) to perform the required calculations. Net present value (NPV) is maximized with the requirement that the incremental present value ratio (PWPI) of any investment in any reservoir be greater than a specified minimum value. A unique feature is a gasmore » reservoir simulation model that aids SIPS in evaluating field development investments. The optimal solution supplies specified dry gas offtake requirements through time until the remaining reserves are insufficient to meet requirements economically. The sales value of recovered liquids contributes significantly to NPV, while the required spare gas-producing capacity reduces NPV. Sips was used successfully for 4 years to generate annual investment plans and operating budgets, and to perform many special studies for a producing complex containing over 50 reservoirs. This experience is reviewed. In considering this large problem, SIPS converges to the optimal solution in 10 to 20 iterations. The primary factor that determines this number is how good the starting guess is. Although sips can generate a starting guess, beginning with a previous optimal solution ordinarily results in faster convergence. Computing time increases in proportion to the number of reservoirs because more than 90% of computing time is spent solving the, reservoir, subproblems.« less

Early seizure detection in an animal model of temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Talathi, Sachin S.; Hwang, Dong-Uk; Ditto, William; Carney, Paul R.

2007-11-01

The performance of five seizure detection schemes, i.e., Nonlinear embedding delay, Hurst scaling, Wavelet Scale, autocorrelation and gradient of accumulated energy, in their ability to detect EEG seizures close to the seizure onset time were evaluated to determine the feasibility of their application in the development of a real time closed loop seizure intervention program (RCLSIP). The criteria chosen for the performance evaluation were, high statistical robustness as determined through the predictability index, the sensitivity and the specificity of a given measure to detect an EEG seizure, the lag in seizure detection with respect to the EEG seizure onset time, as determined through visual inspection and the computational efficiency for each detection measure. An optimality function was designed to evaluate the overall performance of each measure dependent on the criteria chosen. While each of the above measures analyzed for seizure detection performed very well in terms of the statistical parameters, the nonlinear embedding delay measure was found to have the highest optimality index due to its ability to detect seizure very close to the EEG seizure onset time, thereby making it the most suitable dynamical measure in the development of RCLSIP in rat model with chronic limbic epilepsy.

[Application of Stir Bar Sorptive Extraction and Gas Chromatograph Mass Spectrometer to the Phthalic Acid Esters Analysis in Seawater].

PubMed

Gao, Chen-chen; Li, Feng-min; Lu, Lun; Sun, Yue

2015-10-01

For the determination of trace amounts of phthalic acid esters (PAEs) in complex seawater matrix, a stir bar sorptive extraction gas chromatography mass spectrometry (SBSE-GC-MS) method was established. Dimethyl phthalate (DMP), diethyl phthalate (DEP), dibutyl phthalate (DBP), butyl benzyl phthalate (BBP), dibutyl phthalate (2-ethylhexyl) phthalate (DEHP) and dioctyl phthalate (DOP) were selected as study objects. The effects of extraction time, amount of methanol, amount of sodium chloride, desorption time and desorption solvent were optimized. The method of SBSE-GC-MS was validated through recoveries and relative standard deviation. The optimal extraction time was 2 h. The optimal methanol content was 10%. The optimal sodium chloride content was 5% . The optimal desorption time was 50 min. The optimal desorption solvent was the mixture of methanol to acetonitrile (4:1, volume: volume). The linear relationship between the peak area and the concentration of PAEs was relevant. The correlation coefficients were greater than 0.997. The detection limits were between 0.25 and 174.42 ng x L(-1). The recoveries of different concentrations were between 56.97% and 124.22% . The relative standard deviations were between 0.41% and 14.39%. On the basis of the method, several estuaries water sample of Jiaozhou Bay were detected. DEP was detected in all samples, and the concentration of BBP, DEHP and DOP were much higher than the rest.

Exposure Time Optimization for Highly Dynamic Star Trackers

PubMed Central

Wei, Xinguo; Tan, Wei; Li, Jian; Zhang, Guangjun

2014-01-01

Under highly dynamic conditions, the star-spots on the image sensor of a star tracker move across many pixels during the exposure time, which will reduce star detection sensitivity and increase star location errors. However, this kind of effect can be compensated well by setting an appropriate exposure time. This paper focuses on how exposure time affects the star tracker under highly dynamic conditions and how to determine the most appropriate exposure time for this case. Firstly, the effect of exposure time on star detection sensitivity is analyzed by establishing the dynamic star-spot imaging model. Then the star location error is deduced based on the error analysis of the sub-pixel centroiding algorithm. Combining these analyses, the effect of exposure time on attitude accuracy is finally determined. Some simulations are carried out to validate these effects, and the results show that there are different optimal exposure times for different angular velocities of a star tracker with a given configuration. In addition, the results of night sky experiments using a real star tracker agree with the simulation results. The summarized regularities in this paper should prove helpful in the system design and dynamic performance evaluation of the highly dynamic star trackers. PMID:24618776

Use of microwaves to improve nutritional value of soybeans for future space inhabitants

NASA Technical Reports Server (NTRS)

Singh, G.

1983-01-01

Whole soybeans from four different varieties at different moisture contents were microwaved for varying times to determine the conditions for maximum destruction of trypsin inhibitor and lipoxygenase activities, and optimal growth of chicks. Microwaving 150 gm samples of soybeans (at 14 to 28% moisture) for 1.5 min was found optimal for reduction of trypsin inhibitor and lipoxygenase activities. Microwaving 1 kgm samples of soybeans for 9 minutes destroyed 82% of the trypsin inhibitor activity and gave optimal chick growth. It should be pointed out that the microwaving time would vary according to the weight of the sample and the power of the microwave oven. The microwave oven used in the above experiments was rated at 650 watts 2450 MHz.

Application of a Box-Behnken design for optimizing the extraction process of agave fructans (Agave tequilana Weber var. Azul).

PubMed

Flores-Girón, Emmanuel; Salazar-Montoya, Juan Alfredo; Ramos-Ramírez, Emma Gloria

2016-08-01

Agave (Agave tequilana Weber var. Azul) is an industrially important crop in México since it is the only raw material appropriate to produce tequila, an alcoholic beverage. Nowadays, however, these plants have also a nutritional interest as a source of functional food ingredients, owing to the prebiotic potential of agave fructans. In this study, a Box-Behnken design was employed to determine the influence of temperature, liquid:solid ratio and time in a maceration process for agave fructan extraction and optimization. The developed regression model indicates that the selected study variables were statistical determinants for the extraction yield, and the optimal conditions for maximum extraction were a temperature of 60 °C, a liquid:solid ratio of 10:1 (v/w) and a time of 26.7 min, corresponding to a predicted extraction yield of 37.84%. Through selective separation via precipitation with ethanol, fructans with a degree of polymerization of 29.1 were obtained. Box-Behnken designs are useful statistical methods for optimizing the extraction process of agave fructans. A mixture of carbohydrates was obtained from agave powder. This optimized method can be used to obtain fructans for use as prebiotics or as raw material for obtaining functional oligosaccharides. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Nutrition and training adaptations in aquatic sports.

PubMed

Mujika, Iñigo; Stellingwerff, Trent; Tipton, Kevin

2014-08-01

The adaptive response to training is determined by the combination of the intensity, volume, and frequency of the training. Various periodized approaches to training are used by aquatic sports athletes to achieve performance peaks. Nutritional support to optimize training adaptations should take periodization into consideration; that is, nutrition should also be periodized to optimally support training and facilitate adaptations. Moreover, other aspects of training (e.g., overload training, tapering and detraining) should be considered when making nutrition recommendations for aquatic athletes. There is evidence, albeit not in aquatic sports, that restricting carbohydrate availability may enhance some training adaptations. More research needs to be performed, particularly in aquatic sports, to determine the optimal strategy for periodizing carbohydrate intake to optimize adaptations. Protein nutrition is an important consideration for optimal training adaptations. Factors other than the total amount of daily protein intake should be considered. For instance, the type of protein, timing and pattern of protein intake and the amount of protein ingested at any one time influence the metabolic response to protein ingestion. Body mass and composition are important for aquatic sport athletes in relation to power-to-mass and for aesthetic reasons. Protein may be particularly important for athletes desiring to maintain muscle while losing body mass. Nutritional supplements, such as b-alanine and sodium bicarbonate, may have particular usefulness for aquatic athletes' training adaptation.

MO-FG-BRA-08: Swarm Intelligence-Based Personalized Respiratory Gating in Lung SAbR

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

Modiri, A; Sabouri, P; Sawant, A

Purpose: Respiratory gating is widely deployed as a clinical motion-management strategy in lung radiotherapy. In conventional gating, the beam is turned on during a pre-determined phase window; typically, around end-exhalation. In this work, we challenge the notion that end-exhalation is always the optimal gating phase. Specifically, we use a swarm-intelligence-based, inverse planning approach to determine the optimal respiratory phase and MU for each beam with respect to (i) the state of the anatomy at each phase and (ii) the time spent in that state, estimated from long-term monitoring of the patient’s breathing motion. Methods: In a retrospective study of fivemore » lung cancer patients, we compared the dosimetric performance of our proposed personalized gating (PG) with that of conventional end-of-exhale gating (CEG) and a previously-developed, fully 4D-optimized plan (combined with MLC tracking delivery). For each patient, respiratory phase probabilities (indicative of the time duration of the phase) were estimated over 2 minutes from lung tumor motion traces recorded previously using the Synchrony system (Accuray Inc.). Based on this information, inverse planning optimization was performed to calculate the optimal respiratory gating phase and MU for each beam. To ensure practical deliverability, each PG beam was constrained to deliver the assigned MU over a time duration comparable to that of CEG delivery. Results: Maximum OAR sparing for the five patients achieved by the PG and the 4D plans compared to CEG plans was: Esophagus Dmax [PG:57%, 4D:37%], Heart Dmax [PG:71%, 4D:87%], Spinal cord Dmax [PG:18%, 4D:68%] and Lung V13 [PG:16%, 4D:31%]. While patients spent the most time in exhalation, the PG-optimization chose end-exhale only for 28% of beams. Conclusion: Our novel gating strategy achieved significant dosimetric improvements over conventional gating, and approached the upper limit represented by fully 4D optimized planning while being significantly simpler and more clinically translatable. This work was partially supported through research funding from National Institutes of Health (R01CA169102) and Varian Medical Systems, Palo Alto, CA, USA.« less

Modeling and optimization of red currants vacuum drying process by response surface methodology (RSM).

PubMed

Šumić, Zdravko; Vakula, Anita; Tepić, Aleksandra; Čakarević, Jelena; Vitas, Jasmina; Pavlić, Branimir

2016-07-15

Fresh red currants were dried by vacuum drying process under different drying conditions. Box-Behnken experimental design with response surface methodology was used for optimization of drying process in terms of physical (moisture content, water activity, total color change, firmness and rehydratation power) and chemical (total phenols, total flavonoids, monomeric anthocyanins and ascorbic acid content and antioxidant activity) properties of dried samples. Temperature (48-78 °C), pressure (30-330 mbar) and drying time (8-16 h) were investigated as independent variables. Experimental results were fitted to a second-order polynomial model where regression analysis and analysis of variance were used to determine model fitness and optimal drying conditions. The optimal conditions of simultaneously optimized responses were temperature of 70.2 °C, pressure of 39 mbar and drying time of 8 h. It could be concluded that vacuum drying provides samples with good physico-chemical properties, similar to lyophilized sample and better than conventionally dried sample. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimal exponential synchronization of general chaotic delayed neural networks: an LMI approach.

PubMed

Liu, Meiqin

2009-09-01

This paper investigates the optimal exponential synchronization problem of general chaotic neural networks with or without time delays by virtue of Lyapunov-Krasovskii stability theory and the linear matrix inequality (LMI) technique. This general model, which is the interconnection of a linear delayed dynamic system and a bounded static nonlinear operator, covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks (CNNs), bidirectional associative memory (BAM) networks, and recurrent multilayer perceptrons (RMLPs) with or without delays. Using the drive-response concept, time-delay feedback controllers are designed to synchronize two identical chaotic neural networks as quickly as possible. The control design equations are shown to be a generalized eigenvalue problem (GEVP) which can be easily solved by various convex optimization algorithms to determine the optimal control law and the optimal exponential synchronization rate. Detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws.

Optimal Time-Resource Allocation for Energy-Efficient Physical Activity Detection

PubMed Central

Thatte, Gautam; Li, Ming; Lee, Sangwon; Emken, B. Adar; Annavaram, Murali; Narayanan, Shrikanth; Spruijt-Metz, Donna; Mitra, Urbashi

2011-01-01

The optimal allocation of samples for physical activity detection in a wireless body area network for health-monitoring is considered. The number of biometric samples collected at the mobile device fusion center, from both device-internal and external Bluetooth heterogeneous sensors, is optimized to minimize the transmission power for a fixed number of samples, and to meet a performance requirement defined using the probability of misclassification between multiple hypotheses. A filter-based feature selection method determines an optimal feature set for classification, and a correlated Gaussian model is considered. Using experimental data from overweight adolescent subjects, it is found that allocating a greater proportion of samples to sensors which better discriminate between certain activity levels can result in either a lower probability of error or energy-savings ranging from 18% to 22%, in comparison to equal allocation of samples. The current activity of the subjects and the performance requirements do not significantly affect the optimal allocation, but employing personalized models results in improved energy-efficiency. As the number of samples is an integer, an exhaustive search to determine the optimal allocation is typical, but computationally expensive. To this end, an alternate, continuous-valued vector optimization is derived which yields approximately optimal allocations and can be implemented on the mobile fusion center due to its significantly lower complexity. PMID:21796237

Precision of Sensitivity in the Design Optimization of Indeterminate Structures

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Hopkins, Dale A.

2006-01-01

Design sensitivity is central to most optimization methods. The analytical sensitivity expression for an indeterminate structural design optimization problem can be factored into a simple determinate term and a complicated indeterminate component. Sensitivity can be approximated by retaining only the determinate term and setting the indeterminate factor to zero. The optimum solution is reached with the approximate sensitivity. The central processing unit (CPU) time to solution is substantially reduced. The benefit that accrues from using the approximate sensitivity is quantified by solving a set of problems in a controlled environment. Each problem is solved twice: first using the closed-form sensitivity expression, then using the approximation. The problem solutions use the CometBoards testbed as the optimization tool with the integrated force method as the analyzer. The modification that may be required, to use the stiffener method as the analysis tool in optimization, is discussed. The design optimization problem of an indeterminate structure contains many dependent constraints because of the implicit relationship between stresses, as well as the relationship between the stresses and displacements. The design optimization process can become problematic because the implicit relationship reduces the rank of the sensitivity matrix. The proposed approximation restores the full rank and enhances the robustness of the design optimization method.

Quantifying noise in optical tweezers by allan variance.

PubMed

Czerwinski, Fabian; Richardson, Andrew C; Oddershede, Lene B

2009-07-20

Much effort is put into minimizing noise in optical tweezers experiments because noise and drift can mask fundamental behaviours of, e.g., single molecule assays. Various initiatives have been taken to reduce or eliminate noise but it has been difficult to quantify their effect. We propose to use Allan variance as a simple and efficient method to quantify noise in optical tweezers setups.We apply the method to determine the optimal measurement time, frequency, and detection scheme, and quantify the effect of acoustic noise in the lab. The method can also be used on-the-fly for determining optimal parameters of running experiments.

Optimal starting conditions for the rendezvous maneuver: Analytical and computational approach

NASA Astrophysics Data System (ADS)

Ciarcia, Marco

The three-dimensional rendezvous between two spacecraft is considered: a target spacecraft on a circular orbit around the Earth and a chaser spacecraft initially on some elliptical orbit yet to be determined. The chaser spacecraft has variable mass, limited thrust, and its trajectory is governed by three controls, one determining the thrust magnitude and two determining the thrust direction. We seek the time history of the controls in such a way that the propellant mass required to execute the rendezvous maneuver is minimized. Two cases are considered: (i) time-to-rendezvous free and (ii) time-to-rendezvous given, respectively equivalent to (i) free angular travel and (ii) fixed angular travel for the target spacecraft. The above problem has been studied by several authors under the assumption that the initial separation coordinates and the initial separation velocities are given, hence known initial conditions for the chaser spacecraft. In this paper, it is assumed that both the initial separation coordinates and initial separation velocities are free except for the requirement that the initial chaser-to-target distance is given so as to prevent the occurrence of trivial solutions. Two approaches are employed: optimal control formulation (Part A) and mathematical programming formulation (Part B). In Part A, analyses are performed with the multiple-subarc sequential gradient-restoration algorithm for optimal control problems. They show that the fuel-optimal trajectory is zero-bang, namely it is characterized by two subarcs: a long coasting zero-thrust subarc followed by a short powered max-thrust braking subarc. While the thrust direction of the powered subarc is continuously variable for the optimal trajectory, its replacement with a constant (yet optimized) thrust direction produces a very efficient guidance trajectory. Indeed, for all values of the initial distance, the fuel required by the guidance trajectory is within less than one percent of the fuel required by the optimal trajectory. For the guidance trajectory, because of the replacement of the variable thrust direction of the powered subarc with a constant thrust direction, the optimal control problem degenerates into a mathematical programming problem with a relatively small number of degrees of freedom, more precisely: three for case (i) time-to-rendezvous free and two for case (ii) time-to-rendezvous given. In particular, we consider the rendezvous between the Space Shuttle (chaser) and the International Space Station (target). Once a given initial distance SS-to-ISS is preselected, the present work supplies not only the best initial conditions for the rendezvous trajectory, but simultaneously the corresponding final conditions for the ascent trajectory. In Part B, an analytical solution of the Clohessy-Wiltshire equations is presented (i) neglecting the change of the spacecraft mass due to the fuel consumption and (ii) and assuming that the thrust is finite, that is, the trajectory includes powered subarcs flown with max thrust and coasting subarc flown with zero thrust. Then, employing the found analytical solution, we study the rendezvous problem under the assumption that the initial separation coordinates and initial separation velocities are free except for the requirement that the initial chaser-to-target distance is given. The main contribution of Part B is the development of analytical solutions for the powered subarcs, an important extension of the analytical solutions already available for the coasting subarcs. One consequence is that the entire optimal trajectory can be described analytically. Another consequence is that the optimal control problems degenerate into mathematical programming problems. A further consequence is that, vis-a-vis the optimal control formulation, the mathematical programming formulation reduces the CPU time by a factor of order 1000. Key words. Space trajectories, rendezvous, optimization, guidance, optimal control, calculus of variations, Mayer problems, Bolza problems, transformation techniques, multiple-subarc sequential gradient-restoration algorithm.

Guidance and Control strategies for aerospace vehicles

NASA Technical Reports Server (NTRS)

Hibey, J. L.; Naidu, D. S.; Charalambous, C. D.

1989-01-01

A neighboring optimal guidance scheme was devised for a nonlinear dynamic system with stochastic inputs and perfect measurements as applicable to fuel optimal control of an aeroassisted orbital transfer vehicle. For the deterministic nonlinear dynamic system describing the atmospheric maneuver, a nominal trajectory was determined. Then, a neighboring, optimal guidance scheme was obtained for open loop and closed loop control configurations. Taking modelling uncertainties into account, a linear, stochastic, neighboring optimal guidance scheme was devised. Finally, the optimal trajectory was approximated as the sum of the deterministic nominal trajectory and the stochastic neighboring optimal solution. Numerical results are presented for a typical vehicle. A fuel-optimal control problem in aeroassisted noncoplanar orbital transfer is also addressed. The equations of motion for the atmospheric maneuver are nonlinear and the optimal (nominal) trajectory and control are obtained. In order to follow the nominal trajectory under actual conditions, a neighboring optimum guidance scheme is designed using linear quadratic regulator theory for onboard real-time implementation. One of the state variables is used as the independent variable in reference to the time. The weighting matrices in the performance index are chosen by a combination of a heuristic method and an optimal modal approach. The necessary feedback control law is obtained in order to minimize the deviations from the nominal conditions.

The initial-value problem for viscous channel flows

NASA Technical Reports Server (NTRS)

Criminale, W. O.; Jackson, T. L.; Lasseigne, D. G.

1995-01-01

Plane viscous channel flows are perturbed and the ensuing initial-value problems are investigated in detail. Unlike traditional methods where traveling wave normal modes are assumed for solution, this works offers a means whereby completely arbitrary initial input can be specified without having to resort to eigenfunction expansions. The full temporal behavior, including both early time transients and the long time asymptotics, can be determined for any initial disturbance. Effects of three-dimensionality can be assessed. The bases for the analysis are: (a) linearization of the governing equations; (b) Fourier decomposition in the spanwise and streamwise directions of the flow; and (c) direct numerical integration of the resulting partial differential equations. All of the stability data that are known for such flows can be reproduced. Also, the optimal initial condition can be determined in a straight forward manner and such optimal conditions clearly reflect transient growth data that is easily determined by a rational choice of a basis for the initial conditions. Although there can be significant transient growth for subcritical values of the Reynolds number using this approach it does not appear possible that arbitrary initial conditions will lead to the exceptionally large transient amplitudes that have been determined by optimization of normal modes. The approach is general and can be applied to other classes of problems where only a finite discrete spectrum exists, such as the boundary layer for example.

Multi objective optimization model for minimizing production cost and environmental impact in CNC turning process

NASA Astrophysics Data System (ADS)

Widhiarso, Wahyu; Rosyidi, Cucuk Nur

2018-02-01

Minimizing production cost in a manufacturing company will increase the profit of the company. The cutting parameters will affect total processing time which then will affect the production cost of machining process. Besides affecting the production cost and processing time, the cutting parameters will also affect the environment. An optimization model is needed to determine the optimum cutting parameters. In this paper, we develop an optimization model to minimize the production cost and the environmental impact in CNC turning process. The model is used a multi objective optimization. Cutting speed and feed rate are served as the decision variables. Constraints considered are cutting speed, feed rate, cutting force, output power, and surface roughness. The environmental impact is converted from the environmental burden by using eco-indicator 99. Numerical example is given to show the implementation of the model and solved using OptQuest of Oracle Crystal Ball software. The results of optimization indicate that the model can be used to optimize the cutting parameters to minimize the production cost and the environmental impact.

Optimization of the Alkaline Pretreatment of Rice Straw for Enhanced Methane Yield

PubMed Central

Song, Zilin; Yang, Gaihe; Han, Xinhui; Feng, Yongzhong; Ren, Guangxin

2013-01-01

The lime pretreatment process for rice straw was optimized to enhance the biodegradation performance and increase biogas yield. The optimization was implemented using response surface methodology (RSM) and Box-Behnken experimental design. The effects of biodegradation, as well as the interactive effects of Ca(OH)2 concentration, pretreatment time, and inoculum amount on biogas improvement, were investigated. Rice straw compounds, such as lignin, cellulose, and hemicellulose, were significantly degraded with increasing Ca(OH)2 concentration. The optimal conditions for the use of pretreated rice straw in anaerobic digestion were 9.81% Ca(OH)2 (w/w TS), 5.89 d treatment time, and 45.12% inoculum content, which resulted in a methane yield of 225.3 mL/g VS. A determination coefficient (R 2) of 96% was obtained, indicating that the model used to predict the anabolic digestion process shows a favorable fit with the experimental parameters. PMID:23509824

Optimal blood glucose level control using dynamic programming based on minimal Bergman model

NASA Astrophysics Data System (ADS)

Rettian Anggita Sari, Maria; Hartono

2018-03-01

The purpose of this article is to simulate the glucose dynamic and the insulin kinetic of diabetic patient. The model used in this research is a non-linear Minimal Bergman model. Optimal control theory is then applied to formulate the problem in order to determine the optimal dose of insulin in the treatment of diabetes mellitus such that the glucose level is in the normal range for some specific time range. The optimization problem is solved using dynamic programming. The result shows that dynamic programming is quite reliable to represent the interaction between glucose and insulin levels in diabetes mellitus patient.

Optimal File-Distribution in Heterogeneous and Asymmetric Storage Networks

NASA Astrophysics Data System (ADS)

Langner, Tobias; Schindelhauer, Christian; Souza, Alexander

We consider an optimisation problem which is motivated from storage virtualisation in the Internet. While storage networks make use of dedicated hardware to provide homogeneous bandwidth between servers and clients, in the Internet, connections between storage servers and clients are heterogeneous and often asymmetric with respect to upload and download. Thus, for a large file, the question arises how it should be fragmented and distributed among the servers to grant "optimal" access to the contents. We concentrate on the transfer time of a file, which is the time needed for one upload and a sequence of n downloads, using a set of m servers with heterogeneous bandwidths. We assume that fragments of the file can be transferred in parallel to and from multiple servers. This model yields a distribution problem that examines the question of how these fragments should be distributed onto those servers in order to minimise the transfer time. We present an algorithm, called FlowScaling, that finds an optimal solution within running time {O}(m log m). We formulate the distribution problem as a maximum flow problem, which involves a function that states whether a solution with a given transfer time bound exists. This function is then used with a scaling argument to determine an optimal solution within the claimed time complexity.

Flight Test of an Adaptive Configuration Optimization System for Transport Aircraft

NASA Technical Reports Server (NTRS)

Gilyard, Glenn B.; Georgie, Jennifer; Barnicki, Joseph S.

1999-01-01

A NASA Dryden Flight Research Center program explores the practical application of real-time adaptive configuration optimization for enhanced transport performance on an L-1011 aircraft. This approach is based on calculation of incremental drag from forced-response, symmetric, outboard aileron maneuvers. In real-time operation, the symmetric outboard aileron deflection is directly optimized, and the horizontal stabilator and angle of attack are indirectly optimized. A flight experiment has been conducted from an onboard research engineering test station, and flight research results are presented herein. The optimization system has demonstrated the capability of determining the minimum drag configuration of the aircraft in real time. The drag-minimization algorithm is capable of identifying drag to approximately a one-drag-count level. Optimizing the symmetric outboard aileron position realizes a drag reduction of 2-3 drag counts (approximately 1 percent). Algorithm analysis of maneuvers indicate that two-sided raised-cosine maneuvers improve definition of the symmetric outboard aileron drag effect, thereby improving analysis results and consistency. Ramp maneuvers provide a more even distribution of data collection as a function of excitation deflection than raised-cosine maneuvers provide. A commercial operational system would require airdata calculations and normal output of current inertial navigation systems; engine pressure ratio measurements would be optional.

Minimal invasive epicardial lead implantation: optimizing cardiac resynchronization with a new mapping device for epicardial lead placement.

PubMed

Maessen, J G; Phelps, B; Dekker, A L A J; Dijkman, B

2004-05-01

To optimize resynchronization in biventricular pacing with epicardial leads, mapping to determine the best pacing site, is a prerequisite. A port access surgical mapping technique was developed that allowed multiple pace site selection and reproducible lead evaluation and implantation. Pressure-volume loops analysis was used for real time guidance in targeting epicardial lead placement. Even the smallest changes in lead position revealed significantly different functional results. Optimizing the pacing site with this technique allowed functional improvement up to 40% versus random pace site selection.

Biological optimization systems for enhancing photosynthetic efficiency and methods of use

DOEpatents

Hunt, Ryan W.; Chinnasamy, Senthil; Das, Keshav C.; de Mattos, Erico Rolim

2012-11-06

Biological optimization systems for enhancing photosynthetic efficiency and methods of use. Specifically, methods for enhancing photosynthetic efficiency including applying pulsed light to a photosynthetic organism, using a chlorophyll fluorescence feedback control system to determine one or more photosynthetic efficiency parameters, and adjusting one or more of the photosynthetic efficiency parameters to drive the photosynthesis by the delivery of an amount of light to optimize light absorption of the photosynthetic organism while providing enough dark time between light pulses to prevent oversaturation of the chlorophyll reaction centers are disclosed.

[Optimization of processing technology for semen cuscuta by uniform and regression analysis].

PubMed

Li, Chun-yu; Luo, Hui-yu; Wang, Shu; Zhai, Ya-nan; Tian, Shu-hui; Zhang, Dan-shen

2011-02-01

To optimize the best preparation technology for the contains of total flavornoids, polysaccharides, the percentage of water and alcohol-soluble components in Semen Cuscuta herb processing. UV-spectrophotometry was applied to determine the contains of total flavornoids and polysaccharides, which were extracted from Semen Cuscuta. And the processing was optimized by the way of uniform design and contour map. The best preparation technology was satisfied with some conditions as follows: baking temperature 150 degrees C, baking time 140 seconds. The regression models are notable and reasonable, which can forecast results precisely.

Optimal feedback strategies for pursuit-evasion and interception in a plane

NASA Technical Reports Server (NTRS)

Rajan, N.; Ardema, M. D.

1983-01-01

Variable-speed pursuit-evasion and interception for two aircraft moving in a horizontal plane are analyzed in terms of a coordinate frame fixed in the plane at termination. Each participant's optimal motion can be represented by extremal trajectory maps. These maps are used to discuss sub-optimal approximations that are independent of the other participant. A method of constructing sections of the barrier, dispersal, and control-level surfaces and thus determining feedback strategies is described. Some examples are shown for pursuit-evasion and the minimum-time interception of a straight-flying target.

Bio-inspired optimization algorithms for optical parameter extraction of dielectric materials: A comparative study

NASA Astrophysics Data System (ADS)

Ghulam Saber, Md; Arif Shahriar, Kh; Ahmed, Ashik; Hasan Sagor, Rakibul

2016-10-01

Particle swarm optimization (PSO) and invasive weed optimization (IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired algorithms are used here for the first time in this particular field to the best of our knowledge. The algorithms are used for modeling graphene oxide and the performances of the two are compared. Two objective functions are used for different boundary values. Root mean square (RMS) deviation is determined and compared.

Network models for solving the problem of multicriterial adaptive optimization of investment projects control with several acceptable technologies

NASA Astrophysics Data System (ADS)

Shorikov, A. F.; Butsenko, E. V.

2017-10-01

This paper discusses the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. On the basis of network modeling proposed a new economic and mathematical model and a method for solving the problem of multicriterial adaptive optimization the control of investment projects in the presence of several technologies. Network economic and mathematical modeling allows you to determine the optimal time and calendar schedule for the implementation of the investment project and serves as an instrument to increase the economic potential and competitiveness of the enterprise. On a meaningful practical example, the processes of forming network models are shown, including the definition of the sequence of actions of a particular investment projecting process, the network-based work schedules are constructed. The calculation of the parameters of network models is carried out. Optimal (critical) paths have been formed and the optimal time for implementing the chosen technologies of the investment project has been calculated. It also shows the selection of the optimal technology from a set of possible technologies for project implementation, taking into account the time and cost of the work. The proposed model and method for solving the problem of managing investment projects can serve as a basis for the development, creation and application of appropriate computer information systems to support the adoption of managerial decisions by business people.

Optimization of alcohol-assisted dispersive liquid-liquid microextraction by experimental design for the rapid determination of fluoxetine in biological samples.

PubMed

Hamedi, Raheleh; Hadjmohammadi, Mohammad Reza

2016-12-01

A sensitive and rapid method based on alcohol-assisted dispersive liquid-liquid microextraction followed by high-performance liquid chromatography for the determination of fluoxetine in human plasma and urine samples was developed. The effects of six parameters on the extraction recovery were investigated and optimized utilizing Plackett-Burman design and Box-Benken design, respectively. According to the Plackett-Burman design results, the volume of disperser solvent, extraction time, and stirring speed had no effect on the recovery of fluoxetine. The optimized conditions included a mixture of 172 μL of 1-octanol as extraction solvent and 400 μL of methanol as disperser solvent, pH of 11.3 and 0% w/v of salt in the sample solution. Replicating the experiment in optimized condition for five times, gave the average extraction recoveries equal to 90.15%. The detection limit of fluoxetine in human plasma was obtained 3 ng/mL, and the linearity was in the range of 10-1200 ng/mL. The corresponding values for human urine were 4.2 ng/mL with the linearity range from 10 to 2000 ng/mL. Relative standard deviations for intra and inter day extraction of fluoxetine were less than 7% in five measurements. The developed method was successfully applied for the determination of fluoxetine in human plasma and urine samples. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The optimized V-V interval determined by interventricular conduction times versus invasive measurement by LVdP/dtMAX.

PubMed

van Gelder, Berry M; Meijer, Albert; Bracke, Frank A

2008-09-01

We compared the calculated optimal V-V interval derived from intracardiac electrograms (IEGM) with the optimized V-V interval determined by invasive measurement of LVdP/dt(MAX). Thirty-two patients with heart failure (six females, ages 68 +/- 7.8 years) had a CRT device implanted. After implantation of the atrial, right and a left ventricular lead, the optimal V-V interval was calculated using the QuickOpt formula (St. Jude Medical, Sylmar, CA, USA) applied to the respective IEGM recordings (V-V(IEGM)), and also determined by invasive measurement of LVdP/dt(MAX) (V-V(dP/dt)). The optimal V-V(IEGM) and V-V(dP/dt) intervals were 52.7 +/- 18 ms and 24.0 +/- 33 ms, respectively (P = 0.017), without correlation between the two. The baseline LVdP/dt(MAX) was 748 +/- 191 mmHg/s. The mean value of LVdP/dt(MAX) at invasive optimization was 947 +/- 198 mmHg/s, and at the calculated optimal V-V(IEGM) interval 920 +/- 191 mmHg/s (P < 0.0001). In spite of this significant difference, there was a good correlation between both methods (R = 0.991, P < 0.0001). However, a similarly good correlation existed between the maximum value of LVdP/dt(MAX) and LVdP/dt(MAX) at a fixed V-V interval of 0 ms (R = 0.993, P < 0.0001), or LVdP/dt(MAX) at a randomly selected V-V interval between 0 and +80 ms (R = 0.991, P < 0.0001). Optimizing the V-V interval with the IEGM method does not yield better hemodynamic results than simultaneous BiV pacing. Although a good correlation between LVdP/dt(MAX) determined with V-V(IEGM) and V-V(dP/dt) can be constructed, there is no correlation with the optimal settings of V-V interval in the individual patient.

Robust optimization for nonlinear time-delay dynamical system of dha regulon with cost sensitivity constraint in batch culture

NASA Astrophysics Data System (ADS)

Yuan, Jinlong; Zhang, Xu; Liu, Chongyang; Chang, Liang; Xie, Jun; Feng, Enmin; Yin, Hongchao; Xiu, Zhilong

2016-09-01

Time-delay dynamical systems, which depend on both the current state of the system and the state at delayed times, have been an active area of research in many real-world applications. In this paper, we consider a nonlinear time-delay dynamical system of dha-regulonwith unknown time-delays in batch culture of glycerol bioconversion to 1,3-propanediol induced by Klebsiella pneumonia. Some important properties and strong positive invariance are discussed. Because of the difficulty in accurately measuring the concentrations of intracellular substances and the absence of equilibrium points for the time-delay system, a quantitative biological robustness for the concentrations of intracellular substances is defined by penalizing a weighted sum of the expectation and variance of the relative deviation between system outputs before and after the time-delays are perturbed. Our goal is to determine optimal values of the time-delays. To this end, we formulate an optimization problem in which the time delays are decision variables and the cost function is to minimize the biological robustness. This optimization problem is subject to the time-delay system, parameter constraints, continuous state inequality constraints for ensuring that the concentrations of extracellular and intracellular substances lie within specified limits, a quality constraint to reflect operational requirements and a cost sensitivity constraint for ensuring that an acceptable level of the system performance is achieved. It is approximated as a sequence of nonlinear programming sub-problems through the application of constraint transcription and local smoothing approximation techniques. Due to the highly complex nature of this optimization problem, the computational cost is high. Thus, a parallel algorithm is proposed to solve these nonlinear programming sub-problems based on the filled function method. Finally, it is observed that the obtained optimal estimates for the time-delays are highly satisfactory via numerical simulations.

Effect of a limited-enforcement intelligent tutoring system in dermatopathology on student errors, goals and solution paths.

PubMed

Payne, Velma L; Medvedeva, Olga; Legowski, Elizabeth; Castine, Melissa; Tseytlin, Eugene; Jukic, Drazen; Crowley, Rebecca S

2009-11-01

Determine effects of a limited-enforcement intelligent tutoring system in dermatopathology on student errors, goals and solution paths. Determine if limited enforcement in a medical tutoring system inhibits students from learning the optimal and most efficient solution path. Describe the type of deviations from the optimal solution path that occur during tutoring, and how these deviations change over time. Determine if the size of the problem-space (domain scope), has an effect on learning gains when using a tutor with limited enforcement. Analyzed data mined from 44 pathology residents using SlideTutor-a Medical Intelligent Tutoring System in Dermatopathology that teaches histopathologic diagnosis and reporting skills based on commonly used diagnostic algorithms. Two subdomains were included in the study representing sub-algorithms of different sizes and complexities. Effects of the tutoring system on student errors, goal states and solution paths were determined. Students gradually increase the frequency of steps that match the tutoring system's expectation of expert performance. Frequency of errors gradually declines in all categories of error significance. Student performance frequently differs from the tutor-defined optimal path. However, as students continue to be tutored, they approach the optimal solution path. Performance in both subdomains was similar for both errors and goal differences. However, the rate at which students progress toward the optimal solution path differs between the two domains. Tutoring in superficial perivascular dermatitis, the larger and more complex domain was associated with a slower rate of approximation towards the optimal solution path. Students benefit from a limited-enforcement tutoring system that leverages diagnostic algorithms but does not prevent alternative strategies. Even with limited enforcement, students converge toward the optimal solution path.

Temperature-dependent biological and demographic parameters of Coleomegilla maculata (Coleoptera: Coccinellidae)

USDA-ARS?s Scientific Manuscript database

The temperature requirements for development and the optimal range of temperatures for growth and reproduction of Coleomegilla maculata De Geer were studied. The development time of individual C. maculata larvae were determined at 18, 21, 24, 27, 30, 33, and 36°C. Development times were converted to...

Optimal control in adaptive optics modeling of nonlinear systems

NASA Astrophysics Data System (ADS)

Herrmann, J.

The problem of using an adaptive optics system to correct for nonlinear effects like thermal blooming is addressed using a model containing nonlinear lenses through which Gaussian beams are propagated. The best correction of this nonlinear system can be formulated as a deterministic open loop optimal control problem. This treatment gives a limit for the best possible correction. Aspects of adaptive control and servo systems are not included at this stage. An attempt is made to determine that control in the transmitter plane which minimizes the time averaged area or maximizes the fluence in the target plane. The standard minimization procedure leads to a two-point-boundary-value problem, which is ill-conditioned in the case. The optimal control problem was solved using an iterative gradient technique. An instantaneous correction is introduced and compared with the optimal correction. The results of the calculations show that for short times or weak nonlinearities the instantaneous correction is close to the optimal correction, but that for long times and strong nonlinearities a large difference develops between the two types of correction. For these cases the steady state correction becomes better than the instantaneous correction and approaches the optimum correction.

A new real-time guidance strategy for aerodynamic ascent flight

NASA Astrophysics Data System (ADS)

Yamamoto, Takayuki; Kawaguchi, Jun'ichiro

2007-12-01

Reusable launch vehicles are conceived to constitute the future space transportation system. If these vehicles use air-breathing propulsion and lift taking-off horizontally, the optimal steering for these vehicles exhibits completely different behavior from that in conventional rockets flight. In this paper, the new guidance strategy is proposed. This method derives from the optimality condition as for steering and an analysis concludes that the steering function takes the form comprised of Linear and Logarithmic terms, which include only four parameters. The parameter optimization of this method shows the acquired terminal horizontal velocity is almost same with that obtained by the direct numerical optimization. This supports the parameterized Liner Logarithmic steering law. And here is shown that there exists a simple linear relation between the terminal states and the parameters to be corrected. The relation easily makes the parameters determined to satisfy the terminal boundary conditions in real-time. The paper presents the guidance results for the practical application cases. The results show the guidance is well performed and satisfies the terminal boundary conditions specified. The strategy built and presented here does guarantee the robust solution in real-time excluding any optimization process, and it is found quite practical.

Computerized optimization of multiple isocentres in stereotactic convergent beam irradiation

NASA Astrophysics Data System (ADS)

Treuer, U.; Treuer, H.; Hoevels, M.; Müller, R. P.; Sturm, V.

1998-01-01

A method for the fully computerized determination and optimization of positions of target points and collimator sizes in convergent beam irradiation is presented. In conventional interactive trial and error methods, which are very time consuming, the treatment parameters are chosen according to the operator's experience and improved successively. This time is reduced significantly by the use of a computerized procedure. After the definition of target volume and organs at risk in the CT or MR scans, an initial configuration is created automatically. In the next step the target point positions and collimator diameters are optimized by the program. The aim of the optimization is to find a configuration for which a prescribed dose at the target surface is approximated as close as possible. At the same time dose peaks inside the target volume are minimized and organs at risk and tissue surrounding the target are spared. To enhance the speed of the optimization a fast method for approximate dose calculation in convergent beam irradiation is used. A possible application of the method for calculating the leaf positions when irradiating with a micromultileaf collimator is briefly discussed. The success of the procedure has been demonstrated for several clinical cases with up to six target points.

Evaluation of Effective Factors on Travel Time in Optimization of Bus Stops Placement Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Bargegol, Iraj; Ghorbanzadeh, Mahyar; Ghasedi, Meisam; Rastbod, Mohammad

2017-10-01

In congested cities, locating and proper designing of bus stops according to the unequal distribution of passengers is crucial issue economically and functionally, since this subject plays an important role in the use of bus system by passengers. Location of bus stops is a complicated subject; by reducing distances between stops, walking time decreases, but the total travel time may increase. In this paper, a specified corridor in the city of Rasht in north of Iran is studied. Firstly, a new formula is presented to calculate the travel time, by which the number of stops and consequently, the travel time can be optimized. An intended corridor with specified number of stops and distances between them is addressed, the related formulas to travel time are created, and its travel time is calculated. Then the corridor is modelled using a meta-heuristic method in order that the placement and the optimal distances of bus stops for that are determined. It was found that alighting and boarding time along with bus capacity are the most effective factors affecting travel time. Consequently, it is better to have more concentration on indicated factors for improving the efficiency of bus system.

CyberArc: a non-coplanar-arc optimization algorithm for CyberKnife

NASA Astrophysics Data System (ADS)

Kearney, Vasant; Cheung, Joey P.; McGuinness, Christopher; Solberg, Timothy D.

2017-07-01

The goal of this study is to demonstrate the feasibility of a novel non-coplanar-arc optimization algorithm (CyberArc). This method aims to reduce the delivery time of conventional CyberKnife treatments by allowing for continuous beam delivery. CyberArc uses a 4 step optimization strategy, in which nodes, beams, and collimator sizes are determined, source trajectories are calculated, intermediate radiation models are generated, and final monitor units are calculated, for the continuous radiation source model. The dosimetric results as well as the time reduction factors for CyberArc are presented for 7 prostate and 2 brain cases. The dosimetric quality of the CyberArc plans are evaluated using conformity index, heterogeneity index, local confined normalized-mutual-information, and various clinically relevant dosimetric parameters. The results indicate that the CyberArc algorithm dramatically reduces the treatment time of CyberKnife plans while simultaneously preserving the dosimetric quality of the original plans.

CyberArc: a non-coplanar-arc optimization algorithm for CyberKnife.

PubMed

Kearney, Vasant; Cheung, Joey P; McGuinness, Christopher; Solberg, Timothy D

2017-06-26

The goal of this study is to demonstrate the feasibility of a novel non-coplanar-arc optimization algorithm (CyberArc). This method aims to reduce the delivery time of conventional CyberKnife treatments by allowing for continuous beam delivery. CyberArc uses a 4 step optimization strategy, in which nodes, beams, and collimator sizes are determined, source trajectories are calculated, intermediate radiation models are generated, and final monitor units are calculated, for the continuous radiation source model. The dosimetric results as well as the time reduction factors for CyberArc are presented for 7 prostate and 2 brain cases. The dosimetric quality of the CyberArc plans are evaluated using conformity index, heterogeneity index, local confined normalized-mutual-information, and various clinically relevant dosimetric parameters. The results indicate that the CyberArc algorithm dramatically reduces the treatment time of CyberKnife plans while simultaneously preserving the dosimetric quality of the original plans.

RAPID COMMUNICATION: A novel time frequency-based 3D Lissajous figure method and its application to the determination of oxygen saturation from the photoplethysmogram

NASA Astrophysics Data System (ADS)

Addison, Paul S.; Watson, James N.

2004-11-01

We present a novel time-frequency method for the measurement of oxygen saturation using the photoplethysmogram (PPG) signals from a standard pulse oximeter machine. The method utilizes the time-frequency transformation of the red and infrared PPGs to derive a 3D Lissajous figure. By selecting the optimal Lissajous, the method provides an inherently robust basis for the determination of oxygen saturation as regions of the time-frequency plane where high- and low-frequency signal artefacts are to be found are automatically avoided.

Simulating changes to emergency care resources to compare system effectiveness.

PubMed

Branas, Charles C; Wolff, Catherine S; Williams, Justin; Margolis, Gregg; Carr, Brendan G

2013-08-01

To apply systems optimization methods to simulate and compare the most effective locations for emergency care resources as measured by access to care. This study was an optimization analysis of the locations of trauma centers (TCs), helicopter depots (HDs), and severely injured patients in need of time-critical care in select US states. Access was defined as the percentage of injured patients who could reach a level I/II TC within 45 or 60 minutes. Optimal locations were determined by a search algorithm that considered all candidate sites within a set of existing hospitals and airports in finding the best solutions that maximized access. Across a dozen states, existing access to TCs within 60 minutes ranged from 31.1% to 95.6%, with a mean of 71.5%. Access increased from 0.8% to 35.0% after optimal addition of one or two TCs. Access increased from 1.0% to 15.3% after optimal addition of one or two HDs. Relocation of TCs and HDs (optimal removal followed by optimal addition) produced similar results. Optimal changes to TCs produced greater increases in access to care than optimal changes to HDs although these results varied across states. Systems optimization methods can be used to compare the impacts of different resource configurations and their possible effects on access to care. These methods to determine optimal resource allocation can be applied to many domains, including comparative effectiveness and patient-centered outcomes research. Copyright © 2013 Elsevier Inc. All rights reserved.

The determination of dark adaptation time using electroretinography in conscious Miniature Schnauzer dogs

PubMed Central

Yu, Hyung-Ah; Jeong, Man-Bok; Park, Shin-Ae; Kim, Won-Tae; Kim, Se-Eun; Chae, Je-Min; Yi, Na-Young

2007-01-01

The optimal dark adaptation time of electroretinograms (ERG's) performed on conscious dogs were determined using a commercially available ERG unit with a contact lens electrode and a built-in light source (LED-electrode). The ERG recordings were performed on nine healthy Miniature Schnauzer dogs. The bilateral ERG's at seven different dark adaptation times at an intensity of 2.5 cd·s/m2 was performed. Signal averaging (4 flashes of light stimuli) was adopted to reduce electrophysiologic noise. As the dark adaptation time increased, a significant increase in the mean a-wave amplitudes was observed in comparison to base-line levels up to 10 min (p < 0.05). Thereafter, no significant differences in amplitude occured over the dark adaptation time. Moreover, at this time the mean amplitude was 60.30 ± 18.47 µV. However, no significant changes were observed for the implicit times of the a-wave. The implicit times and amplitude of the b-wave increased significantly up to 20 min of dark adaptation (p < 0.05). Beyond this time, the mean b-wave amplitudes was 132.92 ± 17.79 µV. The results of the present study demonstrate that, the optimal dark adaptation time when performing ERG's, should be at least 20 min in conscious Miniature Schnauzer dogs. PMID:17993756

The determination of dark adaptation time using electroretinography in conscious miniature Schnauzer dogs.

PubMed

Yu, Hyung-Ah; Jeong, Man-Bok; Park, Shin-Ae; Kim, Won-Tae; Kim, Se-Eun; Chae, Je-Min; Yi, Na-Young; Seo, Kang-Moon

2007-12-01

The optimal dark adaptation time of electroretinograms (ERG's) performed on conscious dogs were determined using a commercially available ERG unit with a contact lens electrode and a built-in light source (LED-electrode). The ERG recordings were performed on nine healthy Miniature Schnauzer dogs. The bilateral ERG's at seven different dark adaptation times at an intensity of 2.5 cd.s/m(2) was performed. Signal averaging (4 flashes of light stimuli) was adopted to reduce electrophysiologic noise. As the dark adaptation time increased, a significant increase in the mean a-wave amplitudes was observed in comparison to base-line levels up to 10 min (p < 0.05). Thereafter, no significant differences in amplitude occurred over the dark adaptation time. Moreover, at this time the mean amplitude was 60.30 +/- 18.47 microV. However, no significant changes were observed for the implicit times of the a-wave. The implicit times and amplitude of the b-wave increased significantly up to 20 min of dark adaptation (p < 0.05). Beyond this time, the mean b-wave amplitudes was 132.92 +/- 17.79 microV. The results of the present study demonstrate that, the optimal dark adaptation time when performing ERG's, should be at least 20 min in conscious Miniature Schnauzer dogs.

OPTIMAL AIRCRAFT TRAJECTORIES FOR SPECIFIED RANGE

NASA Technical Reports Server (NTRS)

Lee, H.

1994-01-01

For an aircraft operating over a fixed range, the operating costs are basically a sum of fuel cost and time cost. While minimum fuel and minimum time trajectories are relatively easy to calculate, the determination of a minimum cost trajectory can be a complex undertaking. This computer program was developed to optimize trajectories with respect to a cost function based on a weighted sum of fuel cost and time cost. As a research tool, the program could be used to study various characteristics of optimum trajectories and their comparison to standard trajectories. It might also be used to generate a model for the development of an airborne trajectory optimization system. The program could be incorporated into an airline flight planning system, with optimum flight plans determined at takeoff time for the prevailing flight conditions. The use of trajectory optimization could significantly reduce the cost for a given aircraft mission. The algorithm incorporated in the program assumes that a trajectory consists of climb, cruise, and descent segments. The optimization of each segment is not done independently, as in classical procedures, but is performed in a manner which accounts for interaction between the segments. This is accomplished by the application of optimal control theory. The climb and descent profiles are generated by integrating a set of kinematic and dynamic equations, where the total energy of the aircraft is the independent variable. At each energy level of the climb and descent profiles, the air speed and power setting necessary for an optimal trajectory are determined. The variational Hamiltonian of the problem consists of the rate of change of cost with respect to total energy and a term dependent on the adjoint variable, which is identical to the optimum cruise cost at a specified altitude. This variable uniquely specifies the optimal cruise energy, cruise altitude, cruise Mach number, and, indirectly, the climb and descent profiles. If the optimum cruise cost is specified, an optimum trajectory can easily be generated; however, the range obtained for a particular optimum cruise cost is not known a priori. For short range flights, the program iteratively varies the optimum cruise cost until the computed range converges to the specified range. For long-range flights, iteration is unnecessary since the specified range can be divided into a cruise segment distance and full climb and descent distances. The user must supply the program with engine fuel flow rate coefficients and an aircraft aerodynamic model. The program currently includes coefficients for the Pratt-Whitney JT8D-7 engine and an aerodynamic model for the Boeing 727. Input to the program consists of the flight range to be covered and the prevailing flight conditions including pressure, temperature, and wind profiles. Information output by the program includes: optimum cruise tables at selected weights, optimal cruise quantities as a function of cruise weight and cruise distance, climb and descent profiles, and a summary of the complete synthesized optimal trajectory. This program is written in FORTRAN IV for batch execution and has been implemented on a CDC 6000 series computer with a central memory requirement of approximately 100K (octal) of 60 bit words. This aircraft trajectory optimization program was developed in 1979.

Simultaneous determination of Cd(II) and Pb(II) by differential pulse anodic stripping voltammetry based on graphite nanofibers-Nafion composite modified bismuth film electrode.

PubMed

Li, Dongyue; Jia, Jianbo; Wang, Jianguo

2010-12-15

A bismuth-film modified graphite nanofibers-Nafion glassy carbon electrode (BiF/GNFs-NA/GCE) was constructed for the simultaneous determination of trace Cd(II) and Pb(II). The electrochemical properties and applications of the modified electrode were studied. Operational parameters such as deposition potential, deposition time, and bismuth ion concentration were optimized for the purpose of determination of trace metal ions in 0.10 M acetate buffer solution (pH 4.5). Under optimal conditions, based on three times the standard deviation of the baseline, the limits of detection were 0.09 μg L(-1) for Cd(II) and 0.02 μg L(-1) for Pb(II) with a 10 min preconcentration. In addition, the BiF/GNFs-NA/GCE displayed good reproducibility and selectivity, making it suitable for the simultaneous determination of Cd(II) and Pb(II) in real sample such as river water and human blood samples. Copyright © 2010 Elsevier B.V. All rights reserved.

Alternatives for jet engine control

NASA Technical Reports Server (NTRS)

Leake, R. J.; Sain, M. K.

1978-01-01

General goals of the research were classified into two categories. The first category involves the use of modern multivariable frequency domain methods for control of engine models in the neighborhood of a quiescent point. The second category involves the use of nonlinear modelling and optimization techniques for control of engine models over a more extensive part of the flight envelope. In the frequency domain category, works were published in the areas of low-interaction design, polynomial design, and multiple setpoint studies. A number of these ideas progressed to the point at which they are starting to attract practical interest. In the nonlinear category, advances were made both in engine modelling and in the details associated with software for determination of time optimal controls. Nonlinear models for a two spool turbofan engine were expanded and refined; and a promising new approach to automatic model generation was placed under study. A two time scale scheme was developed to do two-dimensional dynamic programming, and an outward spiral sweep technique has greatly speeded convergence times in time optimal calculations.

Optimal transfer, ordering and payment policies for joint supplier-buyer inventory model with price-sensitive trapezoidal demand and net credit

NASA Astrophysics Data System (ADS)

Shah, Nita H.; Shah, Digeshkumar B.; Patel, Dushyantkumar G.

2015-07-01

This study aims at formulating an integrated supplier-buyer inventory model when market demand is variable price-sensitive trapezoidal and the supplier offers a choice between discount in unit price and permissible delay period for settling the accounts due against the purchases made. This type of trade credit is termed as 'net credit'. In this policy, if the buyer pays within offered time M1, then the buyer is entitled for a cash discount; otherwise the full account must be settled by the time M2; where M2 > M1 ⩾ 0. The goal is to determine the optimal selling price, procurement quantity, number of transfers from the supplier to the buyer and payment time to maximise the joint profit per unit time. An algorithm is worked out to obtain the optimal solution. A numerical example is given to validate the proposed model. The managerial insights based on sensitivity analysis are deduced.

Optimal subinterval selection approach for power system transient stability simulation

DOE PAGES

Kim, Soobae; Overbye, Thomas J.

2015-10-21

Power system transient stability analysis requires an appropriate integration time step to avoid numerical instability as well as to reduce computational demands. For fast system dynamics, which vary more rapidly than what the time step covers, a fraction of the time step, called a subinterval, is used. However, the optimal value of this subinterval is not easily determined because the analysis of the system dynamics might be required. This selection is usually made from engineering experiences, and perhaps trial and error. This paper proposes an optimal subinterval selection approach for power system transient stability analysis, which is based on modalmore » analysis using a single machine infinite bus (SMIB) system. Fast system dynamics are identified with the modal analysis and the SMIB system is used focusing on fast local modes. An appropriate subinterval time step from the proposed approach can reduce computational burden and achieve accurate simulation responses as well. As a result, the performance of the proposed method is demonstrated with the GSO 37-bus system.« less

Integrating a Genetic Algorithm Into a Knowledge-Based System for Ordering Complex Design Processes

NASA Technical Reports Server (NTRS)

Rogers, James L.; McCulley, Collin M.; Bloebaum, Christina L.

1996-01-01

The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to be able to determine the best ordering of the processes within these subcycles to reduce design cycle time and cost. Many decomposition approaches assume the capability is available to determine what design processes and couplings exist and what order of execution will be imposed during the design cycle. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature, a genetic algorithm, has been added to DeMAID (Design Manager's Aid for Intelligent Decomposition) to allow the design manager to rapidly examine many different combinations of ordering processes in an iterative subcycle and to optimize the ordering based on cost, time, and iteration requirements. Two sample test cases are presented to show the effects of optimizing the ordering with a genetic algorithm.

[DETERMINATION OF THE OPTIMAL SAFE MODE OF PHYSICAL ACTIVITY FOR THE MILITARY SERVANTS UNDER CONDITIONS CLOSE TO FIGHTING].

PubMed

Chernozub, A; Radchenko, Y

2015-01-01

The paper presents the results of research, allowing to establish the need for and feasibility of an integrated method to determine the most effective but at the same time safe modes of load to the body troops. We found that despite the rather promising application of our proposed mode of load of high intensity (Ra = 0.71) to increase the level of physical military training as soon as possible in time of peace (with a minimum set of combat equipment), problematic issue is that in most cases there is a complete-mismatch achieved in the degree of physical development of the body of military requirements and the challenges posed in terms of direct hostilities. Using the integral method developed by us we determine the safest modes of exercise for the military servants to optimize the most appropriate parameters of volume and intensity of the load, and speed up the adaptive changes in their body to enhance maximum performance at this stage of preparation.

Optimal Charging of Nickel-Hydrogen Batteries for Life Extension

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Lorenzo, Carl F.

2002-01-01

We are exploring the possibility of extending the cycle life of battery systems by using a charging profile that minimizes cell damage. Only nickel-hydrogen cells are discussed at this time, but applications to lithium-ion cells are being considered. The process first requires the development of a fractional calculus based nonlinear dynamic model of the specific cells being used. The parameters of this model are determined from the cell transient responses. To extend cell cycle life, an instantaneous damage rate model is developed. The model is based on cycle life data and is highly dependent on cell voltage. Once both the cell dynamic model and the instantaneous damage rate model have been determined, the charging profile for a specific cell is determined by numerical optimization. Results concerning the percentage life extension for different charging strategies are presented. The overall procedure is readily adaptable to real-time implementations where the charging profile can maintain its minimum damage nature as the specific cell ages.

Development of a simple analytical methodology for determination of glucosamine release from modified release matrix tablets.

PubMed

Wu, Yunqi; Hussain, Munir; Fassihi, Reza

2005-06-15

A simple spectrophotometric method for determination of glucosamine release from sustained release (SR) hydrophilic matrix tablet based on reaction with ninhydrin is developed, optimized and validated. The purple color (Ruhemann purple) resulted from the reaction was stabilized and measured at 570 nm. The method optimization was essential as many procedural parameters influenced the accuracy of determination including the ninhydrin concentration, reaction time, pH, reaction temperature, purple color stability period, and glucosamine/ninhydrin ratio. Glucosamine tablets (600 mg) with different hydrophilic polymers were formulated and manufactured on a rotary press. Dissolution studies were conducted (USP 26) using deionized water at 37+/-0.2 degrees C with paddle rotation of 50 rpm, and samples were removed manually at appropriate time intervals. Under given optimized reaction conditions that appeared to be critical, glucosamine was quantitatively analyzed and the calibration curve in the range of 0.202-2.020 mg (r=0.9999) was constructed. The recovery rate of the developed method was 97.8-101.7% (n=6). Reproducible dissolution profiles were achieved from the dissolution studies performed on different glucosamine tablets. The developed method is easy to use, accurate and highly cost-effective for routine studies relative to HPLC and other techniques.

Economics of a nest-box program for the conservation of an endangered species: a reappraisal

Treesearch

Daniel A. Spring; Michael Bevers; John O.S. Kennedy; Dan Harley

2001-01-01

An optimization model is developed to identify timing and placement strategies for the installation of nest boxes and the harvesting of timber to meet joint timber–wildlife objectives. Optimal management regimes are determined on the basis of their impacts on the local abundance of a threatened species and net present value (NPV) and are identified for a range of NPV...

Development and validation of ultrasound-assisted solid-liquid extraction of phenolic compounds from waste spent coffee grounds.

PubMed

Al-Dhabi, Naif Abdullah; Ponmurugan, Karuppiah; Maran Jeganathan, Prakash

2017-01-01

In this current work, Box-Behnken statistical experimental design (BBD) was adopted to evaluate and optimize USLE (ultrasound-assisted solid-liquid extraction) of phytochemicals from spent coffee grounds. Factors employed in this study are ultrasonic power, temperature, time and solid-liquid (SL) ratio. Individual and interactive effect of independent variables over the extraction yield was depicted through mathematical models, which are generated from the experimental data. Determined optimum process conditions are 244W of ultrasonic power, 40°C of temperature, 34min of time and 1:17g/ml of SL ratio. The predicted values were in correlation with experimental values with 95% confidence level, under the determined optimal conditions. This indicates the significance of selected method for USLE of phytochemicals from SCG. Copyright © 2016 Elsevier B.V. All rights reserved.

Bypass valve and coolant flow controls for optimum temperatures in waste heat recovery systems

DOEpatents

Meisner, Gregory P

2013-10-08

Implementing an optimized waste heat recovery system includes calculating a temperature and a rate of change in temperature of a heat exchanger of a waste heat recovery system, and predicting a temperature and a rate of change in temperature of a material flowing through a channel of the waste heat recovery system. Upon determining the rate of change in the temperature of the material is predicted to be higher than the rate of change in the temperature of the heat exchanger, the optimized waste heat recovery system calculates a valve position and timing for the channel that is configurable for achieving a rate of material flow that is determined to produce and maintain a defined threshold temperature of the heat exchanger, and actuates the valve according to the calculated valve position and calculated timing.

Some Operational Aspects of the International Two-Way Satellite Time and Frequency Transfer (TWSTFT) Experiment Using INTELSAT Satellites at 307 Degrees East

NASA Technical Reports Server (NTRS)

DeYoung, J. A.; McKinley, A.; Davis, J. A.; Hetzel, P.; Bauch, A.

1996-01-01

Eight laboratories are participating in an international two-way satellite time and frequency transfer (TWSTFT) experiment. Regular time and frequency transfers have been performed over a period of almost two years, including both European and transatlantic time transfers. The performance of the regular TWSTFT sessions over an extended period has demonstrated conclusively the usefulness of the TWSTFT method for routine international time and frequency comparisons. Regular measurements are performed three times per week resulting in a regular but unevenly spaced data set. A method is presented that allows an estimate of the values of delta (sub y)(gamma) to be formed from these data. In order to maximize efficient use of paid satellite time an investigation to determine the optimal length of a single TWSTFT session is presented. The optimal experiment length is determined by evaluating how long white phase modulation (PM) instabilities are the dominant noise source during the typical 300-second sampling times currently used. A detailed investigation of the frequency transfers realized via the transatlantic TWSTFT links UTC(USNO)-UTC(NPL), UTC(USNO)-UTC(PTB), and UTC(PTB)-UTC(NPL) is presented. The investigation focuses on the frequency instabilities realized, a three cornered hat resolution of the delta (sub y) (gamma) values, and a comparison of the transatlantic and inter-European determination of UTC(PTB)-UTC(NPL). Future directions of this TWSTFT experiment are outlined.

A statistical approach to evaluate the performance of cardiac biomarkers in predicting death due to acute myocardial infarction: time-dependent ROC curve

PubMed

Karaismailoğlu, Eda; Dikmen, Zeliha Günnur; Akbıyık, Filiz; Karaağaoğlu, Ahmet Ergun

2018-04-30

Background/aim: Myoglobin, cardiac troponin T, B-type natriuretic peptide (BNP), and creatine kinase isoenzyme MB (CK-MB) are frequently used biomarkers for evaluating risk of patients admitted to an emergency department with chest pain. Recently, time- dependent receiver operating characteristic (ROC) analysis has been used to evaluate the predictive power of biomarkers where disease status can change over time. We aimed to determine the best set of biomarkers that estimate cardiac death during follow-up time. We also obtained optimal cut-off values of these biomarkers, which differentiates between patients with and without risk of death. A web tool was developed to estimate time intervals in risk. Materials and methods: A total of 410 patients admitted to the emergency department with chest pain and shortness of breath were included. Cox regression analysis was used to determine an optimal set of biomarkers that can be used for estimating cardiac death and to combine the significant biomarkers. Time-dependent ROC analysis was performed for evaluating performances of significant biomarkers and a combined biomarker during 240 h. The bootstrap method was used to compare statistical significance and the Youden index was used to determine optimal cut-off values. Results : Myoglobin and BNP were significant by multivariate Cox regression analysis. Areas under the time-dependent ROC curves of myoglobin and BNP were about 0.80 during 240 h, and that of the combined biomarker (myoglobin + BNP) increased to 0.90 during the first 180 h. Conclusion: Although myoglobin is not clinically specific to a cardiac event, in our study both myoglobin and BNP were found to be statistically significant for estimating cardiac death. Using this combined biomarker may increase the power of prediction. Our web tool can be useful for evaluating the risk status of new patients and helping clinicians in making decisions.

Synthesis and acid digestion of biomorphic ceramics: determination of alkaline and alkaline earth ions.

PubMed

Bosch Ojeda, Catalina; Sánchez Rojas, Fuensanta; Cano Pavón, José Manuel

2007-09-01

Ceramic and glass are some of the more recent engineering materials and those that are most resistant to environmental conditions. They belong to advanced materials in that they are being developed for the aerospace and electronics industries. In the last decade, a new class of ceramic materials has been the focus of particular attention. The materials were produced with natural, renewable resources (wood or wood-based products). In this work, we have synthesised a new biomorphic ceramic material from oak wood and Si infiltration. After the material characterization, we have optimized the dissolution of the sample by acid attack in an oven under microwave irradiation. Experimental designs were used as a multivariate strategy for the evaluation of the effects of varying several variables at the same time. The optimization was performed in two steps using factorial design for preliminary evaluation and a Draper-Lin design for determination of the critical experimental conditions. Five variables (time, power, volume of HNO3, volume H2SO4 and volume of HF) were considered as factors and as a response the concentration of different metal ions in the optimization process. Interactions between analytical factors and their optimal levels were investigated using a Draper-Lin design.

Exploring the Pareto frontier using multisexual evolutionary algorithms: an application to a flexible manufacturing problem

NASA Astrophysics Data System (ADS)

Bonissone, Stefano R.; Subbu, Raj

2002-12-01

In multi-objective optimization (MOO) problems we need to optimize many possibly conflicting objectives. For instance, in manufacturing planning we might want to minimize the cost and production time while maximizing the product's quality. We propose the use of evolutionary algorithms (EAs) to solve these problems. Solutions are represented as individuals in a population and are assigned scores according to a fitness function that determines their relative quality. Strong solutions are selected for reproduction, and pass their genetic material to the next generation. Weak solutions are removed from the population. The fitness function evaluates each solution and returns a related score. In MOO problems, this fitness function is vector-valued, i.e. it returns a value for each objective. Therefore, instead of a global optimum, we try to find the Pareto-optimal or non-dominated frontier. We use multi-sexual EAs with as many genders as optimization criteria. We have created new crossover and gender assignment functions, and experimented with various parameters to determine the best setting (yielding the highest number of non-dominated solutions.) These experiments are conducted using a variety of fitness functions, and the algorithms are later evaluated on a flexible manufacturing problem with total cost and time minimization objectives.

Optimization of a hardware implementation for pulse coupled neural networks for image applications

NASA Astrophysics Data System (ADS)

Gimeno Sarciada, Jesús; Lamela Rivera, Horacio; Warde, Cardinal

2010-04-01

Pulse Coupled Neural Networks are a very useful tool for image processing and visual applications, since it has the advantages of being invariant to image changes as rotation, scale, or certain distortion. Among other characteristics, the PCNN changes a given image input into a temporal representation which can be easily later analyzed for pattern recognition. The structure of a PCNN though, makes it necessary to determine all of its parameters very carefully in order to function optimally, so that the responses to the kind of inputs it will be subjected are clearly discriminated allowing for an easy and fast post-processing yielding useful results. This tweaking of the system is a taxing process. In this paper we analyze and compare two methods for modeling PCNNs. A purely mathematical model is programmed and a similar circuital model is also designed. Both are then used to determine the optimal values of the several parameters of a PCNN: gain, threshold, time constants for feed-in and threshold and linking leading to an optimal design for image recognition. The results are compared for usefulness, accuracy and speed, as well as the performance and time requirements for fast and easy design, thus providing a tool for future ease of management of a PCNN for different tasks.

Optimization of removal function in computer controlled optical surfacing

NASA Astrophysics Data System (ADS)

Chen, Xi; Guo, Peiji; Ren, Jianfeng

2010-10-01

The technical principle of computer controlled optical surfacing (CCOS) and the common method of optimizing removal function that is used in CCOS are introduced in this paper. A new optimizing method time-sharing synthesis of removal function is proposed to solve problems of the removal function being far away from Gaussian type and slow approaching of the removal function error that encountered in the mode of planet motion or translation-rotation. Detailed time-sharing synthesis of using six removal functions is discussed. For a given region on the workpiece, six positions are selected as the centers of the removal function; polishing tool controlled by the executive system of CCOS revolves around each centre to complete a cycle in proper order. The overall removal function obtained by the time-sharing process is the ratio of total material removal in six cycles to time duration of the six cycles, which depends on the arrangement and distribution of the six removal functions. Simulations on the synthesized overall removal functions under two different modes of motion, i.e., planet motion and translation-rotation are performed from which the optimized combination of tool parameters and distribution of time-sharing synthesis removal functions are obtained. The evaluation function when optimizing is determined by an approaching factor which is defined as the ratio of the material removal within the area of half of the polishing tool coverage from the polishing center to the total material removal within the full polishing tool coverage area. After optimization, it is found that the optimized removal function obtained by time-sharing synthesis is closer to the ideal Gaussian type removal function than those by the traditional methods. The time-sharing synthesis method of the removal function provides an efficient way to increase the convergence speed of the surface error in CCOS for the fabrication of aspheric optical surfaces, and to reduce the intermediate- and high-frequency error.

A guided search genetic algorithm using mined rules for optimal affective product design

NASA Astrophysics Data System (ADS)

Fung, Chris K. Y.; Kwong, C. K.; Chan, Kit Yan; Jiang, H.

2014-08-01

Affective design is an important aspect of new product development, especially for consumer products, to achieve a competitive edge in the marketplace. It can help companies to develop new products that can better satisfy the emotional needs of customers. However, product designers usually encounter difficulties in determining the optimal settings of the design attributes for affective design. In this article, a novel guided search genetic algorithm (GA) approach is proposed to determine the optimal design attribute settings for affective design. The optimization model formulated based on the proposed approach applied constraints and guided search operators, which were formulated based on mined rules, to guide the GA search and to achieve desirable solutions. A case study on the affective design of mobile phones was conducted to illustrate the proposed approach and validate its effectiveness. Validation tests were conducted, and the results show that the guided search GA approach outperforms the GA approach without the guided search strategy in terms of GA convergence and computational time. In addition, the guided search optimization model is capable of improving GA to generate good solutions for affective design.

Preparation of alpha-emitting nuclides by electrodeposition

NASA Astrophysics Data System (ADS)

Lee, M. H.; Lee, C. W.

2000-06-01

A method is described for electrodepositing the alpha-emitting nuclides. To determine the optimum conditions for plating plutonium, the effects of electrolyte concentration, chelating reagent, current, pH of electrolyte and the time of plating on the electrodeposition were investigated on the base of the ammonium oxalate-ammonium sulfate electrolyte containing diethyl triamino pentaacetic acid. An optimized electrodeposition procedure for the determination of plutonium was validated by application to environmental samples. The chemical yield of the optimized method of electrodeposition step in the environmental sample was a little higher than that of Talvitie's method. The developed electrodeposition procedure in this study was applied to determine the radionuclides such as thorium, uranium and americium that the electrodeposition yields were a little higher than those of the conventional method.

Optimal control of CPR procedure using hemodynamic circulation model

DOEpatents

Lenhart, Suzanne M.; Protopopescu, Vladimir A.; Jung, Eunok

2007-12-25

A method for determining a chest pressure profile for cardiopulmonary resuscitation (CPR) includes the steps of representing a hemodynamic circulation model based on a plurality of difference equations for a patient, applying an optimal control (OC) algorithm to the circulation model, and determining a chest pressure profile. The chest pressure profile defines a timing pattern of externally applied pressure to a chest of the patient to maximize blood flow through the patient. A CPR device includes a chest compressor, a controller communicably connected to the chest compressor, and a computer communicably connected to the controller. The computer determines the chest pressure profile by applying an OC algorithm to a hemodynamic circulation model based on the plurality of difference equations.

Theory of optimal balance predicts and explains the amplitude and decay time of synaptic inhibition

PubMed Central

Kim, Jaekyung K.; Fiorillo, Christopher D.

2017-01-01

Synaptic inhibition counterbalances excitation, but it is not known what constitutes optimal inhibition. We previously proposed that perfect balance is achieved when the peak of an excitatory postsynaptic potential (EPSP) is exactly at spike threshold, so that the slightest variation in excitation determines whether a spike is generated. Using simulations, we show that the optimal inhibitory postsynaptic conductance (IPSG) increases in amplitude and decay rate as synaptic excitation increases from 1 to 800 Hz. As further proposed by theory, we show that optimal IPSG parameters can be learned through anti-Hebbian rules. Finally, we compare our theoretical optima to published experimental data from 21 types of neurons, in which rates of synaptic excitation and IPSG decay times vary by factors of about 100 (5–600 Hz) and 50 (1–50 ms), respectively. From an infinite range of possible decay times, theory predicted experimental decay times within less than a factor of 2. Across a distinct set of 15 types of neuron recorded in vivo, theory predicted the amplitude of synaptic inhibition within a factor of 1.7. Thus, the theory can explain biophysical quantities from first principles. PMID:28281523

Theory of optimal balance predicts and explains the amplitude and decay time of synaptic inhibition

NASA Astrophysics Data System (ADS)

Kim, Jaekyung K.; Fiorillo, Christopher D.

2017-03-01

Synaptic inhibition counterbalances excitation, but it is not known what constitutes optimal inhibition. We previously proposed that perfect balance is achieved when the peak of an excitatory postsynaptic potential (EPSP) is exactly at spike threshold, so that the slightest variation in excitation determines whether a spike is generated. Using simulations, we show that the optimal inhibitory postsynaptic conductance (IPSG) increases in amplitude and decay rate as synaptic excitation increases from 1 to 800 Hz. As further proposed by theory, we show that optimal IPSG parameters can be learned through anti-Hebbian rules. Finally, we compare our theoretical optima to published experimental data from 21 types of neurons, in which rates of synaptic excitation and IPSG decay times vary by factors of about 100 (5-600 Hz) and 50 (1-50 ms), respectively. From an infinite range of possible decay times, theory predicted experimental decay times within less than a factor of 2. Across a distinct set of 15 types of neuron recorded in vivo, theory predicted the amplitude of synaptic inhibition within a factor of 1.7. Thus, the theory can explain biophysical quantities from first principles.

Joint CPT and N resonance in compact atomic time standards

NASA Astrophysics Data System (ADS)

Crescimanno, Michael; Hohensee, Michael; Xiao, Yanhong; Phillips, David; Walsworth, Ron

2008-05-01

Currently development efforts towards small, low power atomic time standards use current-modulated VCSELs to generate phase-coherent optical sidebands that interrogate the hyperfine structure of alkali atoms such as rubidium. We describe and use a modified four-level quantum optics model to study the optimal operating regime of the joint CPT- and N-resonance clock. Resonant and non-resonant light shifts as well as modulation comb detuning effects play a key role in determining the optimal operating point of such clocks. We further show that our model is in good agreement with experimental tests performed using Rb-87 vapor cells.

A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination

PubMed Central

Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control. PMID:24592183

[Preparation procedures of anti-complementary polysaccharides from Houttuynia cordata].

PubMed

Zhang, Juanjuan; Lu, Yan; Chen, Daofeng

2012-07-01

To establish and optimize the preparation procedures of the anti-complementary polysaccharides from Houttuynia cordata. Based on the yield and anti-complementary activity in vitro, the conditions of extraction and alcohol precipitating process were optimized by orthogonal tests. The optimal condition of deproteinization was determined according to the results of protein removed and polysaccharide maintained. The best decoloring method was also optimized by orthogonal experimental design. The optimized preparation procedures were given as follows: extract the coarse powder 3 times with 50 times volume of water at 90 degrees C for 2 hours every time, combine the extracts and concentrate appropriately, equivalent to 0.12 g of H. cordata per milliliter. Add 4 times volume of 90% ethanol to the extract, allow to stand for 24 hours to precipitate totally, filter and the precipitate was successfully washed with anhydrous alcohol, acetone and anhydrous ether. Resolve the residue with water, add trichloroacetic acid (TCA) to a concentration of 20% to remove protein. Decoloration was at a concentration of 3% with activated carbon at pH 3.0, 50 degrees C for 50 min. The above procedures above were tested 3 times, resulting in the average yield of polysaccharides at 4.03% (RSD 0.96%), the average concentrations of polysaccharides and protein at 80.97% (RSD 1.5%) and 2.02% (RSD 2.3%), and average CH50 at 0.079 g x L-(-1) (RSD 3.6%). The established and optimized procedures are repeatable and reliable to prepare the anti-complementary polysaccharides with high quality and activity from H. cordata.

Optimal Quasi-steady Plasma Thruster system characteristics.

NASA Technical Reports Server (NTRS)

Ludwig, D. E.; Kelly, A. J.

1972-01-01

The overall characteristics of a generalized Quasi-steady Plasma Thruster (QPT) system consisting of thruster head, power conditioning network, propellant supply subsystem are studied. Energy balance equations for the system are coupled with component mass relationships in order to determine overall system mass and performance. Power supply power levels varying from 100 to 10,000 watts with thruster power levels ranging from 300 kw to 30 Mw employing argon as the propellant are considered. The manner in which overall system mass, average thrust, and burn time vary as a function power supply power level, quasi-steady power level, and pulse time are studied. Results indicate the existence of optimum pulse times when system mass is employed as an optimization criterion.

Parasitic lasing suppression in large-aperture Ti:sapphire amplifiers by optimizing the seed-pump time delay

NASA Astrophysics Data System (ADS)

Chu, Y. X.; Liang, X. Y.; Yu, L. H.; Xu, L.; Lu, X. M.; Liu, Y. Q.; Leng, Y. X.; Li, R. X.; Xu, Z. Z.

2013-05-01

Theoretical and experimental investigations are carried out to determine the influence of the time delay between the input seed pulse and pump pulses on transverse parasitic lasing in a Ti:sapphire amplifier with a diameter of 80 mm, which is clad by a refractive index-matched liquid doped with an absorber. When the time delay is optimized, a maximum output energy of 50.8 J is achieved at a pump energy of 105 J, which corresponds to a conversion efficiency of 47.5%. Based on the existing compressor, the laser system achieves a peak power of 1.26 PW with a 29.0 fs pulse duration.

Strain Selection and Optimization of Mixed Culture Conditions for Lactobacillus pentosus K1-23 with Antibacterial Activity and Aureobasidium pullulans NRRL 58012 Producing Immune-Enhancing β-Glucan.

PubMed

Sekar, Ashokkumar; Kim, Myoungjin; Jeong, Hyeong Chul; Kim, Keun

2018-05-28

Lactobacillus pentosus K1-23 was selected from among 25 lactic acid bacterial strains owing to its high inhibitory activity against several pathogenic bacteria, including Escherichia coli , Salmonella typhimurium , S. gallinarum , Staphylococcus aureus , Pseudomonas aeruginosa , Clostridium perfringens , and Listeria monocytogenes . Additionally, among 13 strains of Aureobasidium spp., A. pullulans NRRL 58012 was shown to produce the highest amount of β-glucan (15.45 ± 0.07%) and was selected. Next, the optimal conditions for a solid-phase mixed culture with these two different microorganisms (one bacterium and one yeast) were determined. The optimal inoculum sizes for L. pentosus and A. pullulans were 1% and 5%, respectively. The appropriate inoculation time for L. pentosus K1-23 was 3 days after the inoculation of A. pullulans to initiate fermentation. The addition of 0.5% corn steep powder and 0.1% FeSO₄ to the basal medium resulted in the increased production of lactic acid bacterial cells and β-glucan. The following optimal conditions for solid-phase mixed culture were also statistically determined by using the response surface method: 37.84°C, pH 5.25, moisture content of 60.82%, and culture time of 6.08 days for L. pentosus ; and 24.11°C, pH 5.65, moisture content of 60.08%, and culture time of 5.71 days for A. pullulans. Using the predicted optimal conditions, the experimental production values of L. pentosus cells and β-glucan were 3.15 ± 0.10 × 10⁸ CFU/g and 13.41 ± 0.04%, respectively. This mixed culture may function as a highly efficient antibiotic substitute based on the combined action of its anti-pathogenic bacterial and immune-enhancing activities.

Determination of 3-MCPD by GC-MS/MS with PTV-LV injector used for a survey of Spanish foodstuffs.

PubMed

León, Nuria; Yusà, Vicent; Pardo, Olga; Pastor, Agustín

2008-05-15

3-Monochloropropane-1,2-diol (3-MCPD) is the most common chemical contaminant of the group of chloropropanols. It can occur in foods and food ingredients at low levels as a result of processing, migration from packaging materials during storage and domestic cooking. A sensitive method for determination of 3-MCPD in foodstuffs using programmable temperature vaporization (PTV) with large-volume injection (LVI) gas chromatography (GC) with tandem mass spectrometry detection (MS/MS) has been developed and optimized. The optimization of the injection and detection parameters was carried out using statistical experimental design. A Plackett-Burman design was used to estimate the influence of resonance excitation voltage (REV), isolation time (IT), excitation time (ET), ion source temperature (IST), and electron energy (EE) on the analytical response in the ion trap mass spectrometer (ITMS). Only REV was found to have a statically significant effect. On the other hand, a central composite design was used to optimize the settings of injection temperature (T(inlet)), vaporization temperature (T(vap)), vaporization time (t(vap)) and flow (Flow). The optimized method has an instrumental limit of detection (signal-to-noise ratio 3:1) of 0.044 ng mL(-1). From Valencian, Spain, supermarkets 94 samples of foods were surveyed for 3-MCPD. Using the optimized method levels higher than the limit established for soy sauce by the European Union were found in some samples. The estimated daily intake of 3-MCPD throughout the investigated foodstuffs for adults and children was found about 0.005 and 0.01%, respectively, of the established provisional tolerable daily intake.

Hybrid Optimization of Object-Based Classification in High-Resolution Images Using Continous ANT Colony Algorithm with Emphasis on Building Detection

NASA Astrophysics Data System (ADS)

Tamimi, E.; Ebadi, H.; Kiani, A.

2017-09-01

Automatic building detection from High Spatial Resolution (HSR) images is one of the most important issues in Remote Sensing (RS). Due to the limited number of spectral bands in HSR images, using other features will lead to improve accuracy. By adding these features, the presence probability of dependent features will be increased, which leads to accuracy reduction. In addition, some parameters should be determined in Support Vector Machine (SVM) classification. Therefore, it is necessary to simultaneously determine classification parameters and select independent features according to image type. Optimization algorithm is an efficient method to solve this problem. On the other hand, pixel-based classification faces several challenges such as producing salt-paper results and high computational time in high dimensional data. Hence, in this paper, a novel method is proposed to optimize object-based SVM classification by applying continuous Ant Colony Optimization (ACO) algorithm. The advantages of the proposed method are relatively high automation level, independency of image scene and type, post processing reduction for building edge reconstruction and accuracy improvement. The proposed method was evaluated by pixel-based SVM and Random Forest (RF) classification in terms of accuracy. In comparison with optimized pixel-based SVM classification, the results showed that the proposed method improved quality factor and overall accuracy by 17% and 10%, respectively. Also, in the proposed method, Kappa coefficient was improved by 6% rather than RF classification. Time processing of the proposed method was relatively low because of unit of image analysis (image object). These showed the superiority of the proposed method in terms of time and accuracy.

Optimal de novo design of MRM experiments for rapid assay development in targeted proteomics.

PubMed

Bertsch, Andreas; Jung, Stephan; Zerck, Alexandra; Pfeifer, Nico; Nahnsen, Sven; Henneges, Carsten; Nordheim, Alfred; Kohlbacher, Oliver

2010-05-07

Targeted proteomic approaches such as multiple reaction monitoring (MRM) overcome problems associated with classical shotgun mass spectrometry experiments. Developing MRM quantitation assays can be time consuming, because relevant peptide representatives of the proteins must be found and their retention time and the product ions must be determined. Given the transitions, hundreds to thousands of them can be scheduled into one experiment run. However, it is difficult to select which of the transitions should be included into a measurement. We present a novel algorithm that allows the construction of MRM assays from the sequence of the targeted proteins alone. This enables the rapid development of targeted MRM experiments without large libraries of transitions or peptide spectra. The approach relies on combinatorial optimization in combination with machine learning techniques to predict proteotypicity, retention time, and fragmentation of peptides. The resulting potential transitions are scheduled optimally by solving an integer linear program. We demonstrate that fully automated construction of MRM experiments from protein sequences alone is possible and over 80% coverage of the targeted proteins can be achieved without further optimization of the assay.

Optimal Parameter Design of Coarse Alignment for Fiber Optic Gyro Inertial Navigation System.

PubMed

Lu, Baofeng; Wang, Qiuying; Yu, Chunmei; Gao, Wei

2015-06-25

Two different coarse alignment algorithms for Fiber Optic Gyro (FOG) Inertial Navigation System (INS) based on inertial reference frame are discussed in this paper. Both of them are based on gravity vector integration, therefore, the performance of these algorithms is determined by integration time. In previous works, integration time is selected by experience. In order to give a criterion for the selection process, and make the selection of the integration time more accurate, optimal parameter design of these algorithms for FOG INS is performed in this paper. The design process is accomplished based on the analysis of the error characteristics of these two coarse alignment algorithms. Moreover, this analysis and optimal parameter design allow us to make an adequate selection of the most accurate algorithm for FOG INS according to the actual operational conditions. The analysis and simulation results show that the parameter provided by this work is the optimal value, and indicate that in different operational conditions, the coarse alignment algorithms adopted for FOG INS are different in order to achieve better performance. Lastly, the experiment results validate the effectiveness of the proposed algorithm.

Optimal estimation of diffusion coefficients from single-particle trajectories

NASA Astrophysics Data System (ADS)

Vestergaard, Christian L.; Blainey, Paul C.; Flyvbjerg, Henrik

2014-02-01

How does one optimally determine the diffusion coefficient of a diffusing particle from a single-time-lapse recorded trajectory of the particle? We answer this question with an explicit, unbiased, and practically optimal covariance-based estimator (CVE). This estimator is regression-free and is far superior to commonly used methods based on measured mean squared displacements. In experimentally relevant parameter ranges, it also outperforms the analytically intractable and computationally more demanding maximum likelihood estimator (MLE). For the case of diffusion on a flexible and fluctuating substrate, the CVE is biased by substrate motion. However, given some long time series and a substrate under some tension, an extended MLE can separate particle diffusion on the substrate from substrate motion in the laboratory frame. This provides benchmarks that allow removal of bias caused by substrate fluctuations in CVE. The resulting unbiased CVE is optimal also for short time series on a fluctuating substrate. We have applied our estimators to human 8-oxoguanine DNA glycolase proteins diffusing on flow-stretched DNA, a fluctuating substrate, and found that diffusion coefficients are severely overestimated if substrate fluctuations are not accounted for.

Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2010-01-01

This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.

Determination of volatile components of green, black, oolong and white tea by optimized ultrasound-assisted extraction-dispersive liquid-liquid microextraction coupled with gas chromatography.

PubMed

Sereshti, Hassan; Samadi, Soheila; Jalali-Heravi, Mehdi

2013-03-08

Ultrasound assisted extraction (UAE) followed by dispersive liquid-liquid microextraction (DLLME) was used for extraction and preconcentration of volatile constituents of six tea plants. The preconcentrated compounds were analyzed by gas chromatography-mass spectrometry (GC-MS). Totally, 42 compounds were identified and caffeine was quantitatively determined. The main parameters (factors) of the extraction process were optimized by using a central composite design (CCD). Methanol and chloroform were selected as the extraction solvent and preconcentration solvent, respectively .The optimal conditions were obtained as 21 in for sonication time; 32°C for temperature; 27 L for volume of extraction solvent and 7.4% for salt concentration (NaCl/H(2)O). The determination coefficient (R(2)) was 0.9988. The relative standard deviation (RSD %) was 4.8 (n=5), and the enhancement factors (EFs) were 4.0-42.6. Copyright © 2013 Elsevier B.V. All rights reserved.

A lexicographic weighted Tchebycheff approach for multi-constrained multi-objective optimization of the surface grinding process

NASA Astrophysics Data System (ADS)

Khalilpourazari, Soheyl; Khalilpourazary, Saman

2017-05-01

In this article a multi-objective mathematical model is developed to minimize total time and cost while maximizing the production rate and surface finish quality in the grinding process. The model aims to determine optimal values of the decision variables considering process constraints. A lexicographic weighted Tchebycheff approach is developed to obtain efficient Pareto-optimal solutions of the problem in both rough and finished conditions. Utilizing a polyhedral branch-and-cut algorithm, the lexicographic weighted Tchebycheff model of the proposed multi-objective model is solved using GAMS software. The Pareto-optimal solutions provide a proper trade-off between conflicting objective functions which helps the decision maker to select the best values for the decision variables. Sensitivity analyses are performed to determine the effect of change in the grain size, grinding ratio, feed rate, labour cost per hour, length of workpiece, wheel diameter and downfeed of grinding parameters on each value of the objective function.

Optimization of torrefaction conditions of coffee industry residues using desirability function approach.

PubMed

Buratti, C; Barbanera, M; Lascaro, E; Cotana, F

2018-03-01

The aim of the present study is to analyze the influence of independent process variables such as temperature, residence time, and heating rate on the torrefaction process of coffee chaff (CC) and spent coffee grounds (SCGs). Response surface methodology and a three-factor and three-level Box-Behnken design were used in order to evaluate the effects of the process variables on the weight loss (W L ) and the Higher Heating Value (HHV) of the torrefied materials. Results showed that the effects of the three factors on both responses were sequenced as follows: temperature>residence time>heating rate. Data obtained from the experiments were analyzed by analysis of variance (ANOVA) and fitted to second-order polynomial models by using multiple regression analysis. Predictive models were determined, able to obtain satisfactory fittings of the experimental data, with coefficient of determination (R 2 ) values higher than 0.95. An optimization study using Derringer's desired function methodology was also carried out and the optimal torrefaction conditions were found: temperature 271.7°C, residence time 20min, heating rate 5°C/min for CC and 256.0°C, 20min, 25°C/min for SCGs. The experimental values closely agree with the corresponding predicted values. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inactivation disinfection property of Moringa Oleifera seed extract: optimization and kinetic studies

NASA Astrophysics Data System (ADS)

Idris, M. A.; Jami, M. S.; Hammed, A. M.

2017-05-01

This paper presents the statistical optimization study of disinfection inactivation parameters of defatted Moringa oleifera seed extract on Pseudomonas aeruginosa bacterial cells. Three level factorial design was used to estimate the optimum range and the kinetics of the inactivation process was also carried. The inactivation process involved comparing different disinfection models of Chicks-Watson, Collins-Selleck and Homs models. The results from analysis of variance (ANOVA) of the statistical optimization process revealed that only contact time was significant. The optimum disinfection range of the seed extract was 125 mg/L, 30 minutes and 120rpm agitation. At the optimum dose, the inactivation kinetics followed the Collin-Selleck model with coefficient of determination (R2) of 0.6320. This study is the first of its kind in determining the inactivation kinetics of pseudomonas aeruginosa using the defatted seed extract.

A Design Problem of Assembly Line Systems using Genetic Algorithm under the BTO Environment

NASA Astrophysics Data System (ADS)

Abe, Kazuaki; Yamada, Tetsuo; Matsui, Masayuki

Under the BTO environment, stochastic assembly lines require design methods which shorten not only the production lead time but also the ready time for the line design. We propose a design method for Assembly Line Systems (ALS) in Yamada et al. (2001) by using Genetic Algorithm (GA) and Adam-Eve GA, in which all design variables are determined in consideration of constraints such as line length related to the production lead time. First, an ALS model with a line length constraint is introduced, and an optimal design problem is set to maximize the net reward under shorter lead time. Next, a simulation optimization method is developed using Adam-Eve GA and traditional GA. Finally, an optimal design example is shown and discussed by comparing the 2-stage design by Yamada et al. (2001) and both the GA designs. It is shown that the Adam-Eve GA is superior to the traditional GA design in terms of computational time though there is only a slight difference in terms of net reward.

Three-Axis Time-Optimal Attitude Maneuvers of a Rigid-Body

NASA Astrophysics Data System (ADS)

Wang, Xijing; Li, Jisheng

With the development trends for modern satellites towards macro-scale and micro-scale, new demands are requested for its attitude adjustment. Precise pointing control and rapid maneuvering capabilities have long been part of many space missions. While the development of computer technology enables new optimal algorithms being used continuously, a powerful tool for solving problem is provided. Many papers about attitude adjustment have been published, the configurations of the spacecraft are considered rigid body with flexible parts or gyrostate-type systems. The object function always include minimum time or minimum fuel. During earlier satellite missions, the attitude acquisition was achieved by using the momentum ex change devices, performed by a sequential single-axis slewing strategy. Recently, the simultaneous three-axis minimum-time maneuver(reorientation) problems have been studied by many researchers. It is important to research the minimum-time maneuver of a rigid spacecraft within onboard power limits, because of potential space application such as surveying multiple targets in space and academic value. The minimum-time maneuver of a rigid spacecraft is a basic problem because the solutions for maneuvering flexible spacecraft are based on the solution to the rigid body slew problem. A new method for the open-loop solution for a rigid spacecraft maneuver is presented. Having neglected all perturbation torque, the necessary conditions of spacecraft from one state to another state can be determined. There is difference between single-axis with multi-axis. For single- axis analytical solution is possible and the switching line passing through the state-space origin belongs to parabolic. For multi-axis, it is impossible to get analytical solution due to the dynamic coupling between the axes and must be solved numerically. Proved by modern research, Euler axis rotations are quasi-time-optimal in general. On the basis of minimum value principles, a research for reorienting an inertial syrnmetric spacecraft with time cost function from an initial state of rest to a final state of rest is deduced. And the solution to it is stated below: Firstly, the essential condition for solving the problem is deduced with the minimum value principle. The necessary conditions for optimality yield a two point boundary-value problem (TPBVP), which, when solved, produces the control history that minimize time performance index. In the nonsingular control, the solution is the' bang-bang maneuver. The control profile is characterized by Saturated controls for the entire maneuver. The singular control maybe existed. It is only singular in mathematics. According to physical principle, the bigger the mode of the control torque is, the shorter the time is. So saturated controls are used in singular control. Secondly, the control parameters are always in maximum, so the key problem is to determine switch point thus original problem is changed to find the changing time. By the use of adjusting the switch on/off time, the genetic algorithm, which is a new robust method is optimized to determine the switch features without the gyroscopic coupling. There is improvement upon the traditional GA in this research. The homotopy method to find the nonlinear algebra is based on rigorous topology continuum theory. Based on the idea of the homotopy, the relaxation parameters are introduced, and the switch point is figured out with simulated annealing. Computer simulation results using a rigid body show that the new method is feasible and efficient. A practical method of computing approximate solutions to the time-optimal control- switch times for rigid body reorientation has been developed.

Harvesting number and timing effects on shoot yield and flavonoid content in American skullcap (Scutellaria lateriflora)

USDA-ARS?s Scientific Manuscript database

Information on optimal management practices for high dry matter and flavonoid yield in American skullcap is lacking. A field experiment was conducted in central Alabama to determine the effect of timing and frequency of harvest on shoot yield and flavonoid content of American skullcap. In the first ...

Reconstruction of phonon relaxation times from systems featuring interfaces with unknown properties

NASA Astrophysics Data System (ADS)

Forghani, Mojtaba; Hadjiconstantinou, Nicolas G.

2018-05-01

We present a method for reconstructing the phonon relaxation-time function τω=τ (ω ) (including polarization) and associated phonon free-path distribution from thermal spectroscopy data for systems featuring interfaces with unknown properties. Our method does not rely on the effective thermal-conductivity approximation or a particular physical model of the interface behavior. The reconstruction is formulated as an optimization problem in which the relaxation times are determined as functions of frequency by minimizing the discrepancy between the experimentally measured temperature profiles and solutions of the Boltzmann transport equation for the same system. Interface properties such as transmissivities are included as unknowns in the optimization; however, because for the thermal spectroscopy problems considered here the reconstruction is not very sensitive to the interface properties, the transmissivities are only approximately reconstructed and can be considered as byproducts of the calculation whose primary objective is the accurate determination of the relaxation times. The proposed method is validated using synthetic experimental data obtained from Monte Carlo solutions of the Boltzmann transport equation. The method is shown to remain robust in the presence of uncertainty (noise) in the measurement.

Construction of Pancreatic Cancer Classifier Based on SVM Optimized by Improved FOA

PubMed Central

Ma, Xiaoqi

2015-01-01

A novel method is proposed to establish the pancreatic cancer classifier. Firstly, the concept of quantum and fruit fly optimal algorithm (FOA) are introduced, respectively. Then FOA is improved by quantum coding and quantum operation, and a new smell concentration determination function is defined. Finally, the improved FOA is used to optimize the parameters of support vector machine (SVM) and the classifier is established by optimized SVM. In order to verify the effectiveness of the proposed method, SVM and other classification methods have been chosen as the comparing methods. The experimental results show that the proposed method can improve the classifier performance and cost less time. PMID:26543867

Quantitative determination of limonin in citrus juices by HPLC using computerized solvent optimization.

PubMed

Shaw, P E; Wilson, C W

1988-09-01

The commercially available computer program, Drylab, for optimization of separations by high-performance liquid chromatography (HPLC) using binary solvent mixtures is used to improve an HPLC method for separation of the bitter principle, limonin, in grapefruit and navel orange juices. Best conditions for separation of limonin in a reasonable time are 30 to 32% acetonitrile in water at 0.9 mL/min using a 5-micron C18 column 10 cm long. These conditions are used to analyze grapefruit and navel orange juice samples, and these HPLC results are compared with values determined by enzyme immunoassay or thin-layer chromatography (TLC) on the same samples.

Optimizing Site Locations for Determining Shape from Photometric Light Curves

DTIC Science & Technology

2009-09-01

discretize t satellite sh there be a c telescopes Space situa the operati – as well a (Codified d in order to satellites in the degrad photometri ...Departm ller or too far a used to charac llite varies as the solar phase pe. One way ver time or by e following qu l sensor locati the satellite fr...four satellite element sets used in this study and the six time periods in which we determined passes of various orientations to the terminator. Thus

Reinforcement Learning Strategies for Clinical Trials in Non-small Cell Lung Cancer

PubMed Central

Zhao, Yufan; Zeng, Donglin; Socinski, Mark A.; Kosorok, Michael R.

2010-01-01

Summary Typical regimens for advanced metastatic stage IIIB/IV non-small cell lung cancer (NSCLC) consist of multiple lines of treatment. We present an adaptive reinforcement learning approach to discover optimal individualized treatment regimens from a specially designed clinical trial (a “clinical reinforcement trial”) of an experimental treatment for patients with advanced NSCLC who have not been treated previously with systemic therapy. In addition to the complexity of the problem of selecting optimal compounds for first and second-line treatments based on prognostic factors, another primary goal is to determine the optimal time to initiate second-line therapy, either immediately or delayed after induction therapy, yielding the longest overall survival time. A reinforcement learning method called Q-learning is utilized which involves learning an optimal regimen from patient data generated from the clinical reinforcement trial. Approximating the Q-function with time-indexed parameters can be achieved by using a modification of support vector regression which can utilize censored data. Within this framework, a simulation study shows that the procedure can extract optimal regimens for two lines of treatment directly from clinical data without prior knowledge of the treatment effect mechanism. In addition, we demonstrate that the design reliably selects the best initial time for second-line therapy while taking into account the heterogeneity of NSCLC across patients. PMID:21385164

ConvAn: a convergence analyzing tool for optimization of biochemical networks.

PubMed

Kostromins, Andrejs; Mozga, Ivars; Stalidzans, Egils

2012-01-01

Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic properties and the convergence of the objective function to the global optimum is hardly predictable. Determination of suitable optimization method and necessary duration of optimization becomes critical in case of evaluation of high number of combinations of adjustable parameters or in case of large dynamic models. This task is complex due to variety of optimization methods, software tools and nonlinearity features of models in different parameter spaces. A software tool ConvAn is developed to analyze statistical properties of convergence dynamics for optimization runs with particular optimization method, model, software tool, set of optimization method parameters and number of adjustable parameters of the model. The convergence curves can be normalized automatically to enable comparison of different methods and models in the same scale. By the help of the biochemistry adapted graphical user interface of ConvAn it is possible to compare different optimization methods in terms of ability to find the global optima or values close to that as well as the necessary computational time to reach them. It is possible to estimate the optimization performance for different number of adjustable parameters. The functionality of ConvAn enables statistical assessment of necessary optimization time depending on the necessary optimization accuracy. Optimization methods, which are not suitable for a particular optimization task, can be rejected if they have poor repeatability or convergence properties. The software ConvAn is freely available on www.biosystems.lv/convan. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Accuracy and optimal timing of activity measurements in estimating the absorbed dose of radioiodine in the treatment of Graves' disease

NASA Astrophysics Data System (ADS)

Merrill, S.; Horowitz, J.; Traino, A. C.; Chipkin, S. R.; Hollot, C. V.; Chait, Y.

2011-02-01

Calculation of the therapeutic activity of radioiodine 131I for individualized dosimetry in the treatment of Graves' disease requires an accurate estimate of the thyroid absorbed radiation dose based on a tracer activity administration of 131I. Common approaches (Marinelli-Quimby formula, MIRD algorithm) use, respectively, the effective half-life of radioiodine in the thyroid and the time-integrated activity. Many physicians perform one, two, or at most three tracer dose activity measurements at various times and calculate the required therapeutic activity by ad hoc methods. In this paper, we study the accuracy of estimates of four 'target variables': time-integrated activity coefficient, time of maximum activity, maximum activity, and effective half-life in the gland. Clinical data from 41 patients who underwent 131I therapy for Graves' disease at the University Hospital in Pisa, Italy, are used for analysis. The radioiodine kinetics are described using a nonlinear mixed-effects model. The distributions of the target variables in the patient population are characterized. Using minimum root mean squared error as the criterion, optimal 1-, 2-, and 3-point sampling schedules are determined for estimation of the target variables, and probabilistic bounds are given for the errors under the optimal times. An algorithm is developed for computing the optimal 1-, 2-, and 3-point sampling schedules for the target variables. This algorithm is implemented in a freely available software tool. Taking into consideration 131I effective half-life in the thyroid and measurement noise, the optimal 1-point time for time-integrated activity coefficient is a measurement 1 week following the tracer dose. Additional measurements give only a slight improvement in accuracy.

Analysis of Optimal Transport Route Determination of Oil Palm Fresh Fruit Bunches from Plantation to Processing Factory

NASA Astrophysics Data System (ADS)

Tarigan, U.; Sidabutar, R. F.; Tarigan, U. P. P.; Chen, A.

2018-04-01

Manufacturers engaged in the business, producing CPO and kernels whose raw materials are oil palm fresh fruit bunches taken from their own plantation, generally face problems of transporting from plantation to factory where there is often a change of distance traveled by the truck the carrier of FFB is due to non-specific transport instructions. The research was conducted to determine the optimal transportation route in terms of distance, time and route number. The determination of this transportation route is solved using Nearest Neighbours and Clarke & Wright Savings methods. Based on the calculations performed then found in area I with method Nearest Neighbours has a distance of 200.78 Km while Clarke & Wright Savings as with a result of 214.09 Km. As for the harvest area, II obtained results with Nearest Neighbours method of 264.37 Km and Clarke & Wright Savings method with a total distance of 264.33 Km. Based on the calculation of the time to do all the activities of transporting FFB juxtaposed with the work time of the driver got the reduction of conveyance from 8 units to 5 units. There is also improvement of fuel efficiency by 0.8%.

System and method of vehicle operating condition management

DOEpatents

Sujan, Vivek A.; Vajapeyazula, Phani; Follen, Kenneth; Wu, An; Moffett, Barty L.

2015-10-20

A vehicle operating condition profile can be determined over a given route while also considering imposed constraints such as deviation from time targets, deviation from maximum governed speed limits, etc. Given current vehicle speed, engine state and transmission state, the present disclosure optimally manages the engine map and transmission to provide a recommended vehicle operating condition that optimizes fuel consumption in transitioning from one vehicle state to a target state. Exemplary embodiments provide for offline and online optimizations relative to fuel consumption. The benefit is increased freight efficiency in transporting cargo from source to destination by minimizing fuel consumption and maintaining drivability.

Optimal Reservoir Operation using Stochastic Model Predictive Control

NASA Astrophysics Data System (ADS)

Sahu, R.; McLaughlin, D.

2016-12-01

Hydropower operations are typically designed to fulfill contracts negotiated with consumers who need reliable energy supplies, despite uncertainties in reservoir inflows. In addition to providing reliable power the reservoir operator needs to take into account environmental factors such as downstream flooding or compliance with minimum flow requirements. From a dynamical systems perspective, the reservoir operating strategy must cope with conflicting objectives in the presence of random disturbances. In order to achieve optimal performance, the reservoir system needs to continually adapt to disturbances in real time. Model Predictive Control (MPC) is a real-time control technique that adapts by deriving the reservoir release at each decision time from the current state of the system. Here an ensemble-based version of MPC (SMPC) is applied to a generic reservoir to determine both the optimal power contract, considering future inflow uncertainty, and a real-time operating strategy that attempts to satisfy the contract. Contract selection and real-time operation are coupled in an optimization framework that also defines a Pareto trade off between the revenue generated from energy production and the environmental damage resulting from uncontrolled reservoir spills. Further insight is provided by a sensitivity analysis of key parameters specified in the SMPC technique. The results demonstrate that SMPC is suitable for multi-objective planning and associated real-time operation of a wide range of hydropower reservoir systems.

An Improved DINEOF Algorithm for Filling Missing Values in Spatio-Temporal Sea Surface Temperature Data.

PubMed

Ping, Bo; Su, Fenzhen; Meng, Yunshan

2016-01-01

In this study, an improved Data INterpolating Empirical Orthogonal Functions (DINEOF) algorithm for determination of missing values in a spatio-temporal dataset is presented. Compared with the ordinary DINEOF algorithm, the iterative reconstruction procedure until convergence based on every fixed EOF to determine the optimal EOF mode is not necessary and the convergence criterion is only reached once in the improved DINEOF algorithm. Moreover, in the ordinary DINEOF algorithm, after optimal EOF mode determination, the initial matrix with missing data will be iteratively reconstructed based on the optimal EOF mode until the reconstruction is convergent. However, the optimal EOF mode may be not the best EOF for some reconstructed matrices generated in the intermediate steps. Hence, instead of using asingle EOF to fill in the missing data, in the improved algorithm, the optimal EOFs for reconstruction are variable (because the optimal EOFs are variable, the improved algorithm is called VE-DINEOF algorithm in this study). To validate the accuracy of the VE-DINEOF algorithm, a sea surface temperature (SST) data set is reconstructed by using the DINEOF, I-DINEOF (proposed in 2015) and VE-DINEOF algorithms. Four parameters (Pearson correlation coefficient, signal-to-noise ratio, root-mean-square error, and mean absolute difference) are used as a measure of reconstructed accuracy. Compared with the DINEOF and I-DINEOF algorithms, the VE-DINEOF algorithm can significantly enhance the accuracy of reconstruction and shorten the computational time.

A reliable method for spectrophotometric determination of glycine betaine in cell suspension and other systems.

PubMed

Valadez-Bustos, Ma Guadalupe; Aguado-Santacruz, Gerardo Armando; Tiessen-Favier, Axel; Robledo-Paz, Alejandrina; Muñoz-Orozco, Abel; Rascón-Cruz, Quintin; Santacruz-Varela, Amalio

2016-04-01

Glycine betaine is a quaternary ammonium compound that accumulates in a large variety of species in response to different types of stress. Glycine betaine counteracts adverse effects caused by abiotic factors, preventing the denaturation and inactivation of proteins. Thus, its determination is important, particularly for scientists focused on relating structural, biochemical, physiological, and/or molecular responses to plant water status. In the current work, we optimized the periodide technique for the determination of glycine betaine levels. This modification permitted large numbers of samples taken from a chlorophyllic cell line of the grass Bouteloua gracilis to be analyzed. Growth kinetics were assessed using the chlorophyllic suspension to determine glycine betaine levels in control (no stress) cells and cells osmotically stressed with 14 or 21% polyethylene glycol 8000. After glycine extraction, different wavelengths and reading times were evaluated in a spectrophotometer to determine the optimal quantification conditions for this osmolyte. Optimal results were obtained when readings were taken at a wavelength of 290 nm at 48 h after dissolving glycine betaine crystals in dichloroethane. We expect this modification to provide a simple, rapid, reliable, and cheap method for glycine betaine determination in plant samples and cell suspension cultures. Copyright © 2016 Elsevier Inc. All rights reserved.

Effect of C/N Ratio and Media Optimization through Response Surface Methodology on Simultaneous Productions of Intra- and Extracellular Inulinase and Invertase from Aspergillus niger ATCC 20611

PubMed Central

Dinarvand, Mojdeh; Rezaee, Malahat; Masomian, Malihe; Jazayeri, Seyed Davoud; Zareian, Mohsen; Abbasi, Sahar; Ariff, Arbakariya B.

2013-01-01

The study is to identify the extraction of intracellular inulinase (exo- and endoinulinase) and invertase as well as optimization medium composition for maximum productions of intra- and extracellular enzymes from Aspergillus niger ATCC 20611. From two different methods for extraction of intracellular enzymes, ultrasonic method was found more effective. Response surface methodology (RSM) with a five-variable and three-level central composite design (CCD) was employed to optimize the medium composition. The effect of five main reaction parameters including sucrose, yeast extract, NaNO3, Zn+2, and Triton X-100 on the production of enzymes was analyzed. A modified quadratic model was fitted to the data with a coefficient of determination (R 2) more than 0.90 for all responses. The intra-extracellular inulinase and invertase productions increased in the range from 16 to 8.4 times in the optimized medium (10% (w/v) sucrose, 2.5% (w/v) yeast extract, 2% (w/v) NaNO3, 1.5 mM (v/v) Zn+2, and 1% (v/v) Triton X-100) by RSM and from around 1.2 to 1.3 times greater than in the medium optimized by one-factor-at-a-time, respectively. The results of bioprocesses optimization can be useful in the scale-up fermentation and food industry. PMID:24151605

Approximate solution of space and time fractional higher order phase field equation

NASA Astrophysics Data System (ADS)

Shamseldeen, S.

2018-03-01

This paper is concerned with a class of space and time fractional partial differential equation (STFDE) with Riesz derivative in space and Caputo in time. The proposed STFDE is considered as a generalization of a sixth-order partial phase field equation. We describe the application of the optimal homotopy analysis method (OHAM) to obtain an approximate solution for the suggested fractional initial value problem. An averaged-squared residual error function is defined and used to determine the optimal convergence control parameter. Two numerical examples are studied, considering periodic and non-periodic initial conditions, to justify the efficiency and the accuracy of the adopted iterative approach. The dependence of the solution on the order of the fractional derivative in space and time and model parameters is investigated.

Experimental test of an online ion-optics optimizer

NASA Astrophysics Data System (ADS)

Amthor, A. M.; Schillaci, Z. M.; Morrissey, D. J.; Portillo, M.; Schwarz, S.; Steiner, M.; Sumithrarachchi, Ch.

2018-07-01

A technique has been developed and tested to automatically adjust multiple electrostatic or magnetic multipoles on an ion optical beam line - according to a defined optimization algorithm - until an optimal tune is found. This approach simplifies the process of determining high-performance optical tunes, satisfying a given set of optical properties, for an ion optical system. The optimization approach is based on the particle swarm method and is entirely model independent, thus the success of the optimization does not depend on the accuracy of an extant ion optical model of the system to be optimized. Initial test runs of a first order optimization of a low-energy (<60 keV) all-electrostatic beamline at the NSCL show reliable convergence of nine quadrupole degrees of freedom to well-performing tunes within a reasonable number of trial solutions, roughly 500, with full beam optimization run times of roughly two hours. Improved tunes were found both for quasi-local optimizations and for quasi-global optimizations, indicating a good ability of the optimizer to find a solution with or without a well defined set of initial multipole settings.

Volatile decision dynamics: experiments, stochastic description, intermittency control and traffic optimization

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Schönhof, Martin; Kern, Daniel

2002-06-01

The coordinated and efficient distribution of limited resources by individual decisions is a fundamental, unsolved problem. When individuals compete for road capacities, time, space, money, goods, etc, they normally make decisions based on aggregate rather than complete information, such as TV news or stock market indices. In related experiments, we have observed a volatile decision dynamics and far-from-optimal payoff distributions. We have also identified methods of information presentation that can considerably improve the overall performance of the system. In order to determine optimal strategies of decision guidance by means of user-specific recommendations, a stochastic behavioural description is developed. These strategies manage to increase the adaptibility to changing conditions and to reduce the deviation from the time-dependent user equilibrium, thereby enhancing the average and individual payoffs. Hence, our guidance strategies can increase the performance of all users by reducing overreaction and stabilizing the decision dynamics. These results are highly significant for predicting decision behaviour, for reaching optimal behavioural distributions by decision support systems and for information service providers. One of the promising fields of application is traffic optimization.

Box-Behnken design for investigation of microwave-assisted extraction of patchouli oil

NASA Astrophysics Data System (ADS)

Kusuma, Heri Septya; Mahfud, Mahfud

2015-12-01

Microwave-assisted extraction (MAE) technique was employed to extract the essential oil from patchouli (Pogostemon cablin). The optimal conditions for microwave-assisted extraction of patchouli oil were determined by response surface methodology. A Box-Behnken design (BBD) was applied to evaluate the effects of three independent variables (microwave power (A: 400-800 W), plant material to solvent ratio (B: 0.10-0.20 g mL-1) and extraction time (C: 20-60 min)) on the extraction yield of patchouli oil. The correlation analysis of the mathematical-regression model indicated that quadratic polynomial model could be employed to optimize the microwave extraction of patchouli oil. The optimal extraction conditions of patchouli oil was microwave power 634.024 W, plant material to solvent ratio 0.147648 g ml-1 and extraction time 51.6174 min. The maximum patchouli oil yield was 2.80516% under these optimal conditions. Under the extraction condition, the experimental values agreed with the predicted results by analysis of variance. It indicated high fitness of the model used and the success of response surface methodology for optimizing and reflect the expected extraction condition.

Optimization strategies based on sequential quadratic programming applied for a fermentation process for butanol production.

PubMed

Pinto Mariano, Adriano; Bastos Borba Costa, Caliane; de Franceschi de Angelis, Dejanira; Maugeri Filho, Francisco; Pires Atala, Daniel Ibraim; Wolf Maciel, Maria Regina; Maciel Filho, Rubens

2009-11-01

In this work, the mathematical optimization of a continuous flash fermentation process for the production of biobutanol was studied. The process consists of three interconnected units, as follows: fermentor, cell-retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The objective of the optimization was to maximize butanol productivity for a desired substrate conversion. Two strategies were compared for the optimization of the process. In one of them, the process was represented by a deterministic model with kinetic parameters determined experimentally and, in the other, by a statistical model obtained using the factorial design technique combined with simulation. For both strategies, the problem was written as a nonlinear programming problem and was solved with the sequential quadratic programming technique. The results showed that despite the very similar solutions obtained with both strategies, the problems found with the strategy using the deterministic model, such as lack of convergence and high computational time, make the use of the optimization strategy with the statistical model, which showed to be robust and fast, more suitable for the flash fermentation process, being recommended for real-time applications coupling optimization and control.

Enhanced Production of Gamma-Aminobutyric Acid by Optimizing Culture Conditions of Lactobacillus brevis HYE1 Isolated from Kimchi, a Korean Fermented Food.

PubMed

Lim, Hee Seon; Cha, In-Tae; Roh, Seong Woon; Shin, Hae-Hun; Seo, Myung-Ji

2017-03-28

This study evaluated the effects of culture conditions, including carbon and nitrogen sources, L-monosodium glutamate (MSG), and initial pH, on gamma-aminobutyric acid (GABA) production by Lactobacillus brevis HYE1 isolated from kimchi, a Korean traditional fermented food. L. brevis HYE1 was screened by the production analysis of GABA and genetic analysis of the glutamate decarboxylase gene, resulting in 14.64 mM GABA after 48 h of cultivation in MRS medium containing 1% (w/v) MSG. In order to increase GABA production by L. brevis HYE1, the effects of carbon and nitrogen sources on GABA production were preliminarily investigated via one-factor-at-a-time optimization strategy. As the results, 2% maltose and 3% tryptone were determined to produce 17.93 mM GABA in modified MRS medium with 1% (w/v) MSG. In addition, the optimal MSG concentration and initial pH were determined to be 1% and 5.0, respectively, resulting in production of 18.97 mM GABA. Thereafter, response surface methodology (RSM) was applied to determine the optimal conditions of the above four factors. The results indicate that pH was the most significant factor for GABA production. The optimal culture conditions for maximum GABA production were also determined to be 2.14% (w/v) maltose, 4.01% (w/v) tryptone, 2.38% (w/v) MSG, and an initial pH of 4.74. In these conditions, GABA production by L. brevis HYE1 was predicted to be 21.44 mM using the RSM model. The experiment was performed under these optimized conditions, resulting in GABA production of 18.76 mM. These results show that the predicted and experimental values of GABA production are in good agreement.

Estimating soil hydraulic parameters from transient flow experiments in a centrifuge using parameter optimization technique

USGS Publications Warehouse

Šimůnek, Jirka; Nimmo, John R.

2005-01-01

A modified version of the Hydrus software package that can directly or inversely simulate water flow in a transient centrifugal field is presented. The inverse solver for parameter estimation of the soil hydraulic parameters is then applied to multirotation transient flow experiments in a centrifuge. Using time‐variable water contents measured at a sequence of several rotation speeds, soil hydraulic properties were successfully estimated by numerical inversion of transient experiments. The inverse method was then evaluated by comparing estimated soil hydraulic properties with those determined independently using an equilibrium analysis. The optimized soil hydraulic properties compared well with those determined using equilibrium analysis and steady state experiment. Multirotation experiments in a centrifuge not only offer significant time savings by accelerating time but also provide significantly more information for the parameter estimation procedure compared to multistep outflow experiments in a gravitational field.

Determination of semi-volatile additives in wines using SPME and GC-MS.

PubMed

Sagandykova, Gulyaim N; Alimzhanova, Mereke B; Nurzhanova, Yenglik T; Kenessov, Bulat

2017-04-01

Parameters of headspace solid-phase microextraction, such as fiber coating (85μm CAR/PDMS), extraction time (2min for white and 3min for red wines), temperature (85°C), pre-incubation time (15min) were optimized for identification and quantification of semi-volatile additives (propylene glycol, sorbic and benzoic acids) in wines. To overcome problems in their determination, an evaporation of the wine matrix was performed. Using the optimized method, screening of 25 wine samples was performed, and the presence of propylene glycol, sorbic and benzoic acids was found in 22, 20 and 6 samples, respectively. Analysis of different wines using a standard addition approach showed good linearity in concentration ranges 0-250, 0-125, and 0-250mg/L for propylene glycol, sorbic and benzoic acids, respectively. The proposed method can be recommended for quality control of wine and disclosing adulterated samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

Developing a vacuum cooking equipment prototype to produce strawberry jam and optimization of vacuum cooking conditions.

PubMed

Okut, Dilara; Devseren, Esra; Koç, Mehmet; Ocak, Özgül Özdestan; Karataş, Haluk; Kaymak-Ertekin, Figen

2018-01-01

Purpose of this study was to develop prototype cooking equipment that can work at reduced pressure and to evaluate its performance for production of strawberry jam. The effect of vacuum cooking conditions on color soluble solid content, reducing sugars total sugars HMF and sensory properties were investigated. Also, the optimum vacuum cooking conditions for strawberry jam were optimized for Composite Rotatable Design. The optimum cooking temperature and time were determined targeting maximum soluble solid content and sensory attributes (consistency) and minimum Hue value and HMF content. The optimum vacuum cooking conditions determined were 74.4 °C temperature and 19.8 time. The soluble solid content strawberry jam made by vacuum process were similar to those prepared by traditional method. HMF contents of jams produced with vacuum cooking method were well within limit of standards.

Systematic Improvement of Protein Crystals by Determining the Supersolubility Curves of Phase Diagrams

PubMed Central

Saridakis, Emmanuel; Chayen, Naomi E.

2003-01-01

A systematic approach for improving protein crystals by growing them in the metastable zone using the vapor diffusion technique is described. This is a simple technique for optimization of crystallization conditions. Screening around known conditions is performed to establish a working phase diagram for the crystallization of the protein. Dilutions of the crystallization drops across the supersolubility curve into the metastable zone are then carried out as follows: the coverslips holding the hanging drops are transferred, after being incubated for some time at conditions normally giving many small crystals, over reservoirs at concentrations which normally yield clear drops. Fewer, much larger crystals are obtained when the incubation times are optimized, compared with conventional crystallization at similar conditions. This systematic approach has led to the structure determination of the light-harvesting protein C-phycocyanin to the highest-ever resolution of 1.45 Å. PMID:12547801

A risk-based multi-objective model for optimal placement of sensors in water distribution system

NASA Astrophysics Data System (ADS)

Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein

2018-02-01

In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value of losses in WDS.

A random optimization approach for inherent optic properties of nearshore waters

NASA Astrophysics Data System (ADS)

Zhou, Aijun; Hao, Yongshuai; Xu, Kuo; Zhou, Heng

2016-10-01

Traditional method of water quality sampling is time-consuming and highly cost. It can not meet the needs of social development. Hyperspectral remote sensing technology has well time resolution, spatial coverage and more general segment information on spectrum. It has a good potential in water quality supervision. Via the method of semi-analytical, remote sensing information can be related with the water quality. The inherent optical properties are used to quantify the water quality, and an optical model inside the water is established to analysis the features of water. By stochastic optimization algorithm Threshold Acceptance, a global optimization of the unknown model parameters can be determined to obtain the distribution of chlorophyll, organic solution and suspended particles in water. Via the improvement of the optimization algorithm in the search step, the processing time will be obviously reduced, and it will create more opportunity for the increasing the number of parameter. For the innovation definition of the optimization steps and standard, the whole inversion process become more targeted, thus improving the accuracy of inversion. According to the application result for simulated data given by IOCCG and field date provided by NASA, the approach model get continuous improvement and enhancement. Finally, a low-cost, effective retrieval model of water quality from hyper-spectral remote sensing can be achieved.

Ethanol production from banana peels using statistically optimized simultaneous saccharification and fermentation process.

PubMed

Oberoi, Harinder Singh; Vadlani, Praveen V; Saida, Lavudi; Bansal, Sunil; Hughes, Joshua D

2011-07-01

Dried and ground banana peel biomass (BP) after hydrothermal sterilization pretreatment was used for ethanol production using simultaneous saccharification and fermentation (SSF). Central composite design (CCD) was used to optimize concentrations of cellulase and pectinase, temperature and time for ethanol production from BP using SSF. Analysis of variance showed a high coefficient of determination (R(2)) value of 0.92 for ethanol production. On the basis of model graphs and numerical optimization, the validation was done in a laboratory batch fermenter with cellulase, pectinase, temperature and time of nine cellulase filter paper unit/gram cellulose (FPU/g-cellulose), 72 international units/gram pectin (IU/g-pectin), 37 °C and 15 h, respectively. The experiment using optimized parameters in batch fermenter not only resulted in higher ethanol concentration than the one predicted by the model equation, but also saved fermentation time. This study demonstrated that both hydrothermal pretreatment and SSF could be successfully carried out in a single vessel, and use of optimized process parameters helped achieve significant ethanol productivity, indicating commercial potential for the process. To the best of our knowledge, ethanol concentration and ethanol productivity of 28.2 g/l and 2.3 g/l/h, respectively from banana peels have not been reported to date. Copyright © 2011 Elsevier Ltd. All rights reserved.

Central composite rotatable design for investigation of microwave-assisted extraction of okra pod hydrocolloid.

PubMed

Samavati, Vahid

2013-10-01

Microwave-assisted extraction (MAE) technique was employed to extract the hydrocolloid from okra pods (OPH). The optimal conditions for microwave-assisted extraction of OPH were determined by response surface methodology. A central composite rotatable design (CCRD) was applied to evaluate the effects of three independent variables (microwave power (X1: 100-500 W), extraction time (X2: 30-90 min), and extraction temperature (X3: 40-90 °C)) on the extraction yield of OPH. The correlation analysis of the mathematical-regression model indicated that quadratic polynomial model could be employed to optimize the microwave extraction of OPH. The optimal conditions to obtain the highest recovery of OPH (14.911±0.27%) were as follows: microwave power, 395.56 W; extraction time, 67.11 min and extraction temperature, 73.33 °C. Under these optimal conditions, the experimental values agreed with the predicted ones by analysis of variance. It indicated high fitness of the model used and the success of response surface methodology for optimizing OPH extraction. After method development, the DPPH radical scavenging activity of the OPH was evaluated. MAE showed obvious advantages in terms of high extraction efficiency and radical scavenging activity of extract within the shorter extraction time. Copyright © 2013 Elsevier B.V. All rights reserved.

Statistical optimization of medium composition and culture condition for the production of recombinant anti-lipopolysaccharide factor of Eriocheir sinensis in Escherichia coli

NASA Astrophysics Data System (ADS)

Jiang, Shan; Liu, Mei; Wang, Baojie; Jiang, Keyong; Wang, Lei

2011-11-01

Anti-lipopolysaccharide factors (ALFs) are important antimicrobial peptides that are isolated from some aquatic species. In a previous study, we isolated ALF genes from Chinese mitten crab, Eriocheir sinensis. In this study, we optimized the production of a recombinant ALF by expressing E. sinensis ALF genes in Escherichia coli maintained in shake-flasks. In particular, we focused on optimization of both the medium composition and the culture condition. Various medium components were analyzed by the Plackett-Burman design, and two significant screened factors, (NH4)2SO4 and KH2PO4, were further optimized via the central composite design (CCD). Based on the CCD analysis, we investigated the induction start-up time, the isopropylthio-D-galactoside (IPTG) concentration, the post-induction time, and the temperature by response surface methodology. We found that the highest level of ALF fusion protein was achieved in the medium containing 1.89 g/L (NH4)2SO4 and 3.18 g/L KH2PO4, with a cell optical density of 0.8 at 600 nm before induction, an IPTG concentration of 0.5 mmol/L, a post-induction temperature of 32.7°C, and a post-induction time of 4 h. Applying the whole optimization strategy using all optimal factors improved the target protein content from 6.1% (without optimization) to 13.2%. We further applied the optimized medium and conditions in high cell density cultivation, and determined that the soluble target protein constituted 10.5% of the total protein. Our identification of the economic medium composition, optimal culture conditions, and details of the fermentation process should facilitate the potential application of ALF for further research.

Multi-Criteria Optimization of Regulation in Metabolic Networks

PubMed Central

Higuera, Clara; Villaverde, Alejandro F.; Banga, Julio R.; Ross, John; Morán, Federico

2012-01-01

Determining the regulation of metabolic networks at genome scale is a hard task. It has been hypothesized that biochemical pathways and metabolic networks might have undergone an evolutionary process of optimization with respect to several criteria over time. In this contribution, a multi-criteria approach has been used to optimize parameters for the allosteric regulation of enzymes in a model of a metabolic substrate-cycle. This has been carried out by calculating the Pareto set of optimal solutions according to two objectives: the proper direction of flux in a metabolic cycle and the energetic cost of applying the set of parameters. Different Pareto fronts have been calculated for eight different “environments” (specific time courses of end product concentrations). For each resulting front the so-called knee point is identified, which can be considered a preferred trade-off solution. Interestingly, the optimal control parameters corresponding to each of these points also lead to optimal behaviour in all the other environments. By calculating the average of the different parameter sets for the knee solutions more frequently found, a final and optimal consensus set of parameters can be obtained, which is an indication on the existence of a universal regulation mechanism for this system.The implications from such a universal regulatory switch are discussed in the framework of large metabolic networks. PMID:22848435

Focusing light through random photonic layers by four-element division algorithm

NASA Astrophysics Data System (ADS)

Fang, Longjie; Zhang, Xicheng; Zuo, Haoyi; Pang, Lin

2018-02-01

The propagation of waves in turbid media is a fundamental problem of optics with vast applications. Optical phase optimization approaches for focusing light through turbid media using phase control algorithm have been widely studied in recent years due to the rapid development of spatial light modulator. The existing approaches include element-based algorithms - stepwise sequential algorithm, continuous sequential algorithm and whole element optimization approaches - partitioning algorithm, transmission matrix approach and genetic algorithm. The advantage of element-based approaches is that the phase contribution of each element is very clear; however, because the intensity contribution of each element to the focal point is small especially for the case of large number of elements, the determination of the optimal phase for a single element would be difficult. In other words, the signal to noise ratio of the measurement is weak, leading to possibly local maximal during the optimization. As for whole element optimization approaches, all elements are employed for the optimization. Of course, signal to noise ratio during the optimization is improved. However, because more random processings are introduced into the processing, optimizations take more time to converge than the single element based approaches. Based on the advantages of both single element based approaches and whole element optimization approaches, we propose FEDA approach. Comparisons with the existing approaches show that FEDA only takes one third of measurement time to reach the optimization, which means that FEDA is promising in practical application such as for deep tissue imaging.

The Analysis of Fixed Final State Optimal Control in Bilinear System Applied to Bone Marrow by Cell-Cycle Specific (CCS) Chemotherapy

NASA Astrophysics Data System (ADS)

Rainarli, E.; E Dewi, K.

2017-04-01

The research conducted by Fister & Panetta shown an optimal control model of bone marrow cells against Cell Cycle Specific chemotherapy drugs. The model used was a bilinear system model. Fister & Panetta research has proved existence, uniqueness, and characteristics of optimal control (the chemotherapy effect). However, by using this model, the amount of bone marrow at the final time could achieve less than 50 percent from the amount of bone marrow before given treatment. This could harm patients because the lack of bone marrow cells made the number of leukocytes declining and patients will experience leukemia. This research would examine the optimal control of a bilinear system that applied to fixed final state. It will be used to determine the length of optimal time in administering chemotherapy and kept bone marrow cells on the allowed level at the same time. Before simulation conducted, this paper shows that the system could be controlled by using a theory of Lie Algebra. Afterward, it shows the characteristics of optimal control. Based on the simulation, it indicates that strong chemotherapy drug given in a short time frame is the most optimal condition to keep bone marrow cells spine on the allowed level but still could put playing an effective treatment. It gives preference of the weight of treatment for keeping bone marrow cells. The result of chemotherapy’s effect (u) is not able to reach the maximum value. On the other words, it needs to make adjustments of medicine’s dosage to satisfy the final treatment condition e.g. the number of bone marrow cells should be at the allowed level.

Design, optimization, and analysis of a self-deploying PV tent array

NASA Astrophysics Data System (ADS)

Collozza, Anthony J.

1991-06-01

A tent shaped PV array was designed and the design was optimized for maximum specific power. In order to minimize output power variation a tent angle of 60 deg was chosen. Based on the chosen tent angle an array structure was designed. The design considerations were minimal deployment time, high reliability, and small stowage volume. To meet these considerations the array was chosen to be self-deployable, form a compact storage configuration, using a passive pressurized gas deployment mechanism. Each structural component of the design was analyzed to determine the size necessary to withstand the various forces to which it would be subjected. Through this analysis the component weights were determined. An optimization was performed to determine the array dimensions and blanket geometry which produce the maximum specific power for a given PV blanket. This optimization was performed for both lunar and Martian environmental conditions. Other factors such as PV blanket types, structural material, and wind velocity (for Mars array), were varied to determine what influence they had on the design point. The performance specifications for the array at both locations and with each type of PV blanket were determined. These specifications were calculated using the Arimid fiber composite as the structural material. The four PV blanket types considered were silicon, GaAs/Ge, GaAsCLEFT, and amorphous silicon. The specifications used for each blanket represented either present day or near term technology. For both the Moon and Mars the amorphous silicon arrays produced the highest specific power.

Warpage investigation on side arms using response surface methodology (RSM) and glow-worm swarm optimizations (GSO)

NASA Astrophysics Data System (ADS)

Sow, C. K.; Fathullah, M.; Nasir, S. M.; Shayfull, Z.; Shazzuan, S.

2017-09-01

This paper discusses on an analysis run via injection moulding process in determination of the optimum processing parameters used for manufacturing side arms of catheters in minimizing the warpage issues. The optimization method used was RSM. Moreover, in this research tries to find the most significant factor affecting the warpage. From the previous literature review,4 most significant parameters on warpage defect was selected. Those parameters were melt temperature, packing time, packing pressure, mould temperature and cooling time. At the beginning, side arm was drawn using software of CATIA V5. Then, software Mouldflow and Design Expert were employed to analyses on the popular warpage issues. After that, GSO artificial intelligence was apply using the mathematical model from Design Expert for more optimization on RSM result. Recommended parameter settings from the simulation work were then compared with the optimization work of RSM and GSO. The result show that the warpage on the side arm was improved by 3.27 %

Analysis of power management and system latency in wireless sensor networks

NASA Astrophysics Data System (ADS)

Oswald, Matthew T.; Rohwer, Judd A.; Forman, Michael A.

2004-08-01

Successful power management in a wireless sensor network requires optimization of the protocols which affect energy-consumption on each node and the aggregate effects across the larger network. System optimization for a given deployment scenario requires an analysis and trade off of desired node and network features with their associated costs. The sleep protocol for an energy-efficient wireless sensor network for event detection, target classification, and target tracking developed at Sandia National Laboratories is presented. The dynamic source routing (DSR) algorithm is chosen to reduce network maintenance overhead, while providing a self-configuring and self-healing network architecture. A method for determining the optimal sleep time is developed and presented, providing reference data which spans several orders of magnitude. Message timing diagrams show, that a node in a five-node cluster, employing an optimal cyclic single-radio sleep protocol, consumes 3% more energy and incurs a 16-s increase latency than nodes employing the more complex dual-radio STEM protocol.

Sparse time-frequency decomposition based on dictionary adaptation.

PubMed

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we propose a time-frequency analysis method to obtain instantaneous frequencies and the corresponding decomposition by solving an optimization problem. In this optimization problem, the basis that is used to decompose the signal is not known a priori. Instead, it is adapted to the signal and is determined as part of the optimization problem. In this sense, this optimization problem can be seen as a dictionary adaptation problem, in which the dictionary is adaptive to one signal rather than a training set in dictionary learning. This dictionary adaptation problem is solved by using the augmented Lagrangian multiplier (ALM) method iteratively. We further accelerate the ALM method in each iteration by using the fast wavelet transform. We apply our method to decompose several signals, including signals with poor scale separation, signals with outliers and polluted by noise and a real signal. The results show that this method can give accurate recovery of both the instantaneous frequencies and the intrinsic mode functions. © 2016 The Author(s).

Antioxidant Compound Extraction from Maqui (Aristotelia chilensis [Mol] Stuntz) Berries: Optimization by Response Surface Methodology

PubMed Central

Quispe-Fuentes, Issis; Vega-Gálvez, Antonio; Campos-Requena, Víctor H.

2017-01-01

The optimum conditions for the antioxidant extraction from maqui berry were determined using a response surface methodology. A three level D-optimal design was used to investigate the effects of three independent variables namely, solvent type (methanol, acetone and ethanol), solvent concentration and extraction time over total antioxidant capacity by using the oxygen radical absorbance capacity (ORAC) method. The D-optimal design considered 42 experiments including 10 central point replicates. A second-order polynomial model showed that more than 89% of the variation is explained with a satisfactory prediction (78%). ORAC values are higher when acetone was used as a solvent at lower concentrations, and the extraction time range studied showed no significant influence on ORAC values. The optimal conditions for antioxidant extraction obtained were 29% of acetone for 159 min under agitation. From the results obtained it can be concluded that the given predictive model describes an antioxidant extraction process from maqui berry.

A modelling framework for mitigating customers' waiting time at a vehicle inspection centre

NASA Astrophysics Data System (ADS)

Ahmad, Norazura; Abidin, Norhaslinda Zainal; Ilyas, Khibtiyah; Abduljabbar, Waleed Khalid

2017-11-01

In Malaysia, an agency that is entrusted by the Government to perform mandatory vehicle inspection for public, commercial and private vehicles, receive many customers daily. Often complaints of problems received from the customers are associated with waiting time that leads to lost of business and dissatisfied customers. To address this issue, we propose a framework for modelling a vehicle inspection system using an integration of simulation and optimization approaches. The strengths of simulation and optimization are reviewed briefly that is hoped to reveal the synergy between the established methods in determining an appropriate customer's waiting time for inspection at a vehicle inspection centre. Relevant concepts and preliminary results are also presented and discussed in this paper.

RCQ-GA: RDF Chain Query Optimization Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Hogenboom, Alexander; Milea, Viorel; Frasincar, Flavius; Kaymak, Uzay

The application of Semantic Web technologies in an Electronic Commerce environment implies a need for good support tools. Fast query engines are needed for efficient querying of large amounts of data, usually represented using RDF. We focus on optimizing a special class of SPARQL queries, the so-called RDF chain queries. For this purpose, we devise a genetic algorithm called RCQ-GA that determines the order in which joins need to be performed for an efficient evaluation of RDF chain queries. The approach is benchmarked against a two-phase optimization algorithm, previously proposed in literature. The more complex a query is, the more RCQ-GA outperforms the benchmark in solution quality, execution time needed, and consistency of solution quality. When the algorithms are constrained by a time limit, the overall performance of RCQ-GA compared to the benchmark further improves.

Primer vector theory applied to the linear relative-motion equations. [for N-impulse space trajectory optimization

NASA Technical Reports Server (NTRS)

Jezewski, D.

1980-01-01

Prime vector theory is used in analyzing a set of linear relative-motion equations - the Clohessy-Wiltshire (C/W) equations - to determine the criteria and necessary conditions for an optimal N-impulse trajectory. The analysis develops the analytical criteria for improving a solution by: (1) moving any dependent or independent variable in the initial and/or final orbit, and (2) adding intermediate impulses. If these criteria are violated, the theory establishes a sufficient number of analytical equations. The subsequent satisfaction of these equations will result in the optimal position vectors and times of an N-impulse trajectory. The solution is examined for the specific boundary conditions of: (1) fixed-end conditions, two impulse, and time-open transfer; (2) an orbit-to-orbit transfer; and (3) a generalized renezvous problem.

Determining optimal selling price and lot size with process reliability and partial backlogging considerations

NASA Astrophysics Data System (ADS)

Hsieh, Tsu-Pang; Cheng, Mei-Chuan; Dye, Chung-Yuan; Ouyang, Liang-Yuh

2011-01-01

In this article, we extend the classical economic production quantity (EPQ) model by proposing imperfect production processes and quality-dependent unit production cost. The demand rate is described by any convex decreasing function of the selling price. In addition, we allow for shortages and a time-proportional backlogging rate. For any given selling price, we first prove that the optimal production schedule not only exists but also is unique. Next, we show that the total profit per unit time is a concave function of price when the production schedule is given. We then provide a simple algorithm to find the optimal selling price and production schedule for the proposed model. Finally, we use a couple of numerical examples to illustrate the algorithm and conclude this article with suggestions for possible future research.

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

NASA Technical Reports Server (NTRS)

Momoh, James; Chattopadhyay, Deb; Elfayoumy, Mahmoud

1996-01-01

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

Pharmacokinetic design optimization in children and estimation of maturation parameters: example of cytochrome P450 3A4.

PubMed

Bouillon-Pichault, Marion; Jullien, Vincent; Bazzoli, Caroline; Pons, Gérard; Tod, Michel

2011-02-01

The aim of this work was to determine whether optimizing the study design in terms of ages and sampling times for a drug eliminated solely via cytochrome P450 3A4 (CYP3A4) would allow us to accurately estimate the pharmacokinetic parameters throughout the entire childhood timespan, while taking into account age- and weight-related changes. A linear monocompartmental model with first-order absorption was used successively with three different residual error models and previously published pharmacokinetic parameters ("true values"). The optimal ages were established by D-optimization using the CYP3A4 maturation function to create "optimized demographic databases." The post-dose times for each previously selected age were determined by D-optimization using the pharmacokinetic model to create "optimized sparse sampling databases." We simulated concentrations by applying the population pharmacokinetic model to the optimized sparse sampling databases to create optimized concentration databases. The latter were modeled to estimate population pharmacokinetic parameters. We then compared true and estimated parameter values. The established optimal design comprised four age ranges: 0.008 years old (i.e., around 3 days), 0.192 years old (i.e., around 2 months), 1.325 years old, and adults, with the same number of subjects per group and three or four samples per subject, in accordance with the error model. The population pharmacokinetic parameters that we estimated with this design were precise and unbiased (root mean square error [RMSE] and mean prediction error [MPE] less than 11% for clearance and distribution volume and less than 18% for k(a)), whereas the maturation parameters were unbiased but less precise (MPE < 6% and RMSE < 37%). Based on our results, taking growth and maturation into account a priori in a pediatric pharmacokinetic study is theoretically feasible. However, it requires that very early ages be included in studies, which may present an obstacle to the use of this approach. First-pass effects, alternative elimination routes, and combined elimination pathways should also be investigated.

Frozen embryo transfer: a review on the optimal endometrial preparation and timing.

PubMed

Mackens, S; Santos-Ribeiro, S; van de Vijver, A; Racca, A; Van Landuyt, L; Tournaye, H; Blockeel, C

2017-11-01

What is the optimal endometrial preparation protocol for a frozen embryo transfer (FET)? Although the optimal endometrial preparation protocol for FET needs further research and is yet to be determined, we propose a standardized timing strategy based on the current available evidence which could assist in the harmonization and comparability of clinic practice and future trials. Amid a continuous increase in the number of FET cycles, determining the optimal endometrial preparation protocol has become paramount to maximize ART success. In current daily practice, different FET preparation methods and timing strategies are used. This is a review of the current literature on FET preparation methods, with special attention to the timing of the embryo transfer. Literature on the topic was retrieved in PubMed and references from relevant articles were investigated until June 2017. The number of high quality randomized controlled trials (RCTs) is scarce and, hence, the evidence for the best protocol for FET is poor. Future research should compare both the pregnancy and neonatal outcomes between HRT and true natural cycle (NC) FET. In terms of embryo transfer timing, we propose to start progesterone intake on the theoretical day of oocyte retrieval in HRT and to perform blastocyst transfer at hCG + 7 or LH + 6 in modified or true NC, respectively. As only a few high quality RCTs on the optimal preparation for FET are available in the existing literature, no definitive conclusion for benefit of one protocol over the other can be drawn so far. Caution when using HRT for FET is warranted since the rate of early pregnancy loss is alarmingly high in some reports. S.M. is funded by the Research Fund of Flanders (FWO). H.T. and C.B. report grants from Merck, Goodlife, Besins and Abbott during the conduct of the study. Not applicable. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Optimal Xylocoris flavipes (Reuter) (Hemiptera: Anthocoridae) density and time of introduction for suppression of bruchid progeny in stored legumes

Treesearch

Sharlene E. Sing; Richard T. Arbogast

2008-01-01

The influences of both predator density and elapsed time between initial infestation and introduction of predators were determined for suppression of bruchids infesting stored grain legumes by Xylocoris flavipes (Reuter) (Hemiptera: Anthocoridae). Predator density treatments consisted of zero, one, two, three, or five male:female pairs of adult

Determination of T-2 and HT-2 toxins from maize by direct analysis in real time mass spectrometry

USDA-ARS?s Scientific Manuscript database

Direct analysis in real time (DART) ionization coupled to mass spectrometry (MS) was used for the rapid quantitative analysis of T-2 toxin, and the related HT-2 toxin, extracted from corn. Sample preparation procedures and instrument parameters were optimized to obtain sensitive and accurate determi...

Optimal scan timing and intravenous route for contrast-enhanced computed tomography in patients after Fontan operation.

PubMed

Park, Eun-Ah; Lee, Whal; Chung, Se-Young; Yin, Yong Hu; Chung, Jin Wook; Park, Jae Hyung

2010-01-01

To determine the optimal scan timing and adequate intravenous route for patients having undergone the Fontan operation. A total of 88 computed tomographic images in 49 consecutive patients who underwent the Fontan operation were retrospectively evaluated and divided into 7 groups: group 1, bolus-tracking method with either intravenous route (n = 20); group 2, 1-minute-delay scan with single antecubital route (n = 36); group 3, 1-minute-delay scan with both antecubital routes (n = 2); group 4, 1-minute-delay scan with foot vein route (n = 3); group 5, 1-minute-delay scan with simultaneous infusion via both antecubital and foot vein routes (n = 2); group 6, 3-minute-delay scan with single antecubital route (n = 22); and group 7, 3-minute-delay scan with foot vein route (n = 3). The presence of beam-hardening artifact, uniform enhancement, and optimal enhancement was evaluated at the right pulmonary artery (RPA), left pulmonary artery (LPA), and Fontan tract. Optimal enhancement was determined when evaluation of thrombus was possible. Standard deviation was measured at the RPA, LPA, and Fontan tract. Beam-hardening artifacts of the RPA, LPA, and Fontan tract were frequently present in groups 1, 4, and 5. The success rate of uniform and optimal enhancement was highest (100%) in groups 6 and 7, followed by group 2 (75%). An SD of less than 30 Hounsfield unit for the pulmonary artery and Fontan tract was found in groups 3, 6, and 7. The optimal enhancement of the pulmonary arteries and Fontan tract can be achieved by a 3-minute-delay scan irrespective of the intravenous route location.

Optimization of stent implantation using a high pressure inflation protocol.

PubMed

Vallurupalli, Srikanth; Bahia, Amit; Ruiz-Rodriguez, Ernesto; Ahmed, Zubair; Hakeem, Abdul; Uretsky, Barry F

2016-01-01

High-pressure inflation is the universal standard for stent deployment but a specific protocol for its use is lacking. We developed a standardized "pressure optimization protocol" (POP) using time to inflation pressure stability as an endpoint for determining the required duration of stent inflation. The primary study purpose was to determine the stent inflation time (IT) in a large patient cohort using the standardized inflation protocol, to correlate various patient and lesion characteristics with IT, and ascertain in an in vitro study the time for pressure accommodation within an inflation system. Six hundred fifteen stent implants in 435 patients were studied. Multivariate analysis was performed to determine predictors of longer ITs. In an in vitro study, various stents and balloons were inflated in air to determine the pressure accommodation time of the inflation system. The mean stent IT was 104 ± 41 sec (range 30-380 sec). Stent length was the only predictor of prolonged stent inflation. The "accommodation time" in vitro of the stent inflation system itself was 33 ± 24 sec. The protocol was safe requiring premature inflation termination in <3% of stent implants. No serious adverse events occurred. Achieving stable inflation pressure requires on average over 100 sec and may require several minutes in individual cases. Stent length increases IT. These results suggest that the widespread practice of rapid inflation/deflation may not be sufficient to fully expand the stent and that the use of a pressure stability protocol will allow for safe, predictable, and more complete stent deployment. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Application of Adaptive DP-optimality to Design a Pilot Study for a Clotting Time Test for Enoxaparin.

PubMed

Gulati, Abhishek; Faed, James M; Isbister, Geoffrey K; Duffull, Stephen B

2015-10-01

Dosing of enoxaparin, like other anticoagulants, may result in bleeding following excessive doses and clot formation if the dose is too low. We recently showed that a factor Xa based clotting time test could potentially assess the effect of enoxaparin on the clotting system. However, the test did not perform well in subsequent individuals and effectiveness of an exogenous phospholipid, Actin FS, in reducing the variability in the clotting time was assessed. The aim of this work was to conduct an adaptive pilot study to determine the range of concentrations of Xa and Actin FS to take forward into a proof-of-concept study. A nonlinear parametric function was developed to describe the response surface over the factors of interest. An adaptive method was used to estimate the parameters using a D-optimal design criterion. In order to provide a reasonable probability of observing a success of the clotting time test, a P-optimal design criterion was incorporated using a loss function to describe the hybrid DP-optimality. The use of adaptive DP-optimality method resulted in an efficient estimation of model parameters using data from only 6 healthy volunteers. The use of response surface modelling identified a range of sets of Xa and Actin FS concentrations, any of which could be used for the proof-of-concept study. This study shows that parsimonious adaptive DP-optimal designs may provide both precise parameter estimates for response surface modelling as well as clinical confidence in the potential benefits of the study.

Real option valuation of a decremental regulation service provided by electricity storage.

PubMed

Szabó, Dávid Zoltán; Martyr, Randall

2017-08-13

This paper is a quantitative study of a reserve contract for real-time balancing of a power system. Under this contract, the owner of a storage device, such as a battery, helps smooth fluctuations in electricity demand and supply by using the device to increase electricity consumption. The battery owner must be able to provide immediate physical cover, and should therefore have sufficient storage available in the battery before entering the contract. Accordingly, the following problem can be formulated for the battery owner: determine the optimal time to enter the contract and, if necessary, the optimal time to discharge electricity before entering the contract. This problem is formulated as one of optimal stopping, and is solved explicitly in terms of the model parameters and instantaneous values of the power system imbalance. The optimal operational strategies thus obtained ensure that the battery owner has positive expected economic profit from the contract. Furthermore, they provide explicit conditions under which the optimal discharge time is consistent with the overall objective of power system balancing. This paper also carries out a preliminary investigation of the 'lifetime value' aggregated from an infinite sequence of these balancing reserve contracts. This lifetime value, which can be viewed as a single project valuation of the battery, is shown to be positive and bounded. Therefore, in the long run such reserve contracts can be beneficial to commercial operators of electricity storage, while reducing some of the financial and operational risks in power system balancing.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

Effect of torrefaction conditions on greenhouse crop residue: Optimization of conditions to upgrade solid characteristics.

PubMed

Iáñez-Rodríguez, Irene; Martín-Lara, María Ángeles; Blázquez, Gabriel; Pérez, Antonio; Calero, Mónica

2017-11-01

This work investigated the possibility of using a greenhouse crop waste as a fuel, since it is an abundant residue in the Mediterranean area of Spain. The residue is mainly composed by biomass with a little quantity of plastic. The physical and chemical characteristics of the biomass were determined by elemental analysis, proximate analysis, FT-IR, FE-SEM and thermogravimetry. Additionally, a torrefaction process was carried out as a pre-treatment to improve the energy properties of the biomass material. The optimal conditions (time and temperature) of torrefaction were found to be 263°C and 15min using the gain and loss method. Further studies were carried out with the sample prepared with the nearest conditions to the optimal in order to determine the effect of the plastic fraction in the characteristics and torrefaction process of the waste studied. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimal ordering and production policy for a recoverable item inventory system with learning effect

NASA Astrophysics Data System (ADS)

Tsai, Deng-Maw

2012-02-01

This article presents two models for determining an optimal integrated economic order quantity and economic production quantity policy in a recoverable manufacturing environment. The models assume that the unit production time of the recovery process decreases with the increase in total units produced as a result of learning. A fixed proportion of used products are collected from customers and then recovered for reuse. The recovered products are assumed to be in good condition and acceptable to customers. Constant demand can be satisfied by utilising both newly purchased products and recovered products. The aim of this article is to show how to minimise total inventory-related cost. The total cost functions of the two models are derived and two simple search procedures are proposed to determine optimal policy parameters. Numerical examples are provided to illustrate the proposed models. In addition, sensitivity analyses have also been performed and are discussed.

Determination of the wind power systems load to achieve operation in the maximum energy area

NASA Astrophysics Data System (ADS)

Chioncel, C. P.; Tirian, G. O.; Spunei, E.; Gillich, N.

2018-01-01

This paper analyses the operation of the wind turbine, WT, in the maximum power point, MPP, by linking the load of the Permanent Magnet Synchronous Generator, PMSG, with the wind speed value. The load control methods at wind power systems aiming an optimum performance in terms of energy are based on the fact that the energy captured by the wind turbine significantly depends on the mechanical angular speed of the wind turbine. The presented control method consists in determining the optimal mechanical angular speed, ωOPTIM, using an auxiliary low power wind turbine, WTAUX, operating without load, at maximum angular velocity, ωMAX. The method relies on the fact that the ratio ωOPTIM/ωMAX has a constant value for a given wind turbine and does not depend on the time variation of the wind speed values.

Monitoring Pb in Aqueous Samples by Using Low Density Solvent on Air-Assisted Dispersive Liquid-Liquid Microextraction Coupled with UV-Vis Spectrophotometry.

PubMed

Nejad, Mina Ghasemi; Faraji, Hakim; Moghimi, Ali

2017-04-01

In this study, AA-DLLME combined with UV-Vis spectrophotometry was developed for pre-concentration, microextraction and determination of lead in aqueous samples. Optimization of the independent variables was carried out according to chemometric methods in three steps. According to the screening and optimization study, 86 μL of 1-undecanol (extracting solvent), 12 times syringe pumps, pH 2.0, 0.00% of salt and 0.1% DDTP (chelating agent) were chosen as the optimum independent variables for microextraction and determination of lead. Under the optimized conditions, R = 0.9994, and linearity range was 0.01-100 µg mL -1 . LOD and LOQ were 3.4 and 11.6 ng mL -1 , respectively. The method was applied for analysis of real water samples, such as tap, mineral, river and waste water.

Parallel optimization algorithm for drone inspection in the building industry

NASA Astrophysics Data System (ADS)

Walczyński, Maciej; BoŻejko, Wojciech; Skorupka, Dariusz

2017-07-01

In this paper we present an approach for Vehicle Routing Problem with Drones (VRPD) in case of building inspection from the air. In autonomic inspection process there is a need to determine of the optimal route for inspection drone. This is especially important issue because of the very limited flight time of modern multicopters. The method of determining solutions for Traveling Salesman Problem(TSP), described in this paper bases on Parallel Evolutionary Algorithm (ParEA)with cooperative and independent approach for communication between threads. This method described first by Bożejko and Wodecki [1] bases on the observation that if exists some number of elements on certain positions in a number of permutations which are local minima, then those elements will be in the same position in the optimal solution for TSP problem. Numerical experiments were made on BEM computational cluster with using MPI library.

Stability of cosmetic emulsion containing different amount of hemp oil.

PubMed

Kowalska, M; Ziomek, M; Żbikowska, A

2015-08-01

The aim of the study was to determine the optimal conditions, that is the content of hemp oil and time of homogenization to obtain stable dispersion systems. For this purpose, six emulsions were prepared, their stability was examined empirically and the most correctly formulated emulsion composition was determined using a computer simulation. Variable parameters (oil content and homogenization time) were indicated by the optimization software based on Kleeman's method. Physical properties of the synthesized emulsions were studied by numerous techniques involving particle size analysis, optical microscopy, Turbiscan test and viscosity of emulsions. The emulsion containing 50 g of oil and being homogenized for 6 min had the highest stability. Empirically determined parameters proved to be consistent with the results obtained using the computer software. The computer simulation showed that the most stable emulsion should contain from 30 to 50 g of oil and should be homogenized for 2.5-6 min. The computer software based on Kleeman's method proved to be useful for quick optimization of the composition and production parameters of stable emulsion systems. Moreover, obtaining an emulsion system with proper stability justifies further research extended with sensory analysis, which will allow the application of such systems (containing hemp oil, beneficial for skin) in the cosmetic industry. © 2015 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Hydrolysis of whey lactose by immobilized β-galactosidase in a bioreactor with a spirally wound membrane.

PubMed

Vasileva, Nastya; Ivanov, Yavor; Damyanova, Stanka; Kostova, Iliana; Godjevargova, Tzonka

2016-01-01

The β-galactosidase was covalently immobilized onto a modified polypropylene membrane, using glutaraldehyde. The optimal conditions for hydrolysis of lactose (4.7%) by immobilized β-galactosidase in a batch process were determined 13.6 U enzyme activity, 40°C, pH 6.8 and 10h. The obtained degree of hydrolysis was compared with results received by a free enzyme. It was found, that the lactose hydrolysis by an immobilized enzyme was 1.6 times more effective than the lactose hydrolysis by a free enzyme. It was determined that the stability of the immobilized enzyme was 2 times higher in comparison with the stability of free enzyme. The obtained immobilized system β-galactosidase/polypropylene membrane was applied to produce glucose-galactose syrup from waste whey. The whey characteristics and the different preliminary treatments of the whey were investigated. Then the whey lactose hydrolysis in a bioreactor by an immobilized enzyme on a spirally wound membrane was performed. The optimal membrane surface and the optimal flow rate of the whey through the membrane module were determined, respectively 100 cm(2) and 1.0 mL min(-1). After 10h, the degree of lactose hydrolysis was increased to 91%. The operation stability was studied. After 20th cycle the yield of bioreactor was 69.7%. Copyright © 2015 Elsevier B.V. All rights reserved.

Ultrasound-assisted dispersive magnetic solid phase extraction for preconcentration and determination of trace amount of Hg (II) ions from food samples and aqueous solution by magnetic graphene oxide (Fe3O4@GO/2-PTSC): Central composite design optimization.

PubMed

Keramat, Akram; Zare-Dorabei, Rouholah

2017-09-01

In this work, the synthesis of the magnetic graphene oxide modified by 2-pyridinecarboxaldehyde thiosemicarbazone groups (Fe 3 O 4 @GO/2-PTSC) was utilized for preconcentration and determination of mercuric ions in a trace amount by inductively coupled plasma-optical emission spectrometry (ICP-OES). Characterization of the adsorbent was performed using various techniques, such as FT-IR, VSM, SEM and XRD analysis. Central composite design (CCD) under response surface methodology (RSM) was used for obtaining the most important parameters and probable interactions in variables. The variables such as adsorbent dosage, pH, desorption time, and eluent volume was optimized. These values were 8mg, 5.4min, 0.5mL (HCl, 0.1M), respectively. Sonication had an important role in shortening the adsorption time of Hg (II) ions by enhancing the dispersion of adsorbent in solution. Under the optimal conditions, the proposed method presented high enrichment factor of 193, an extraction percentage of 96.5, a detection limit of 0.0079µgL -1 and a relative standard deviation (RSD %) of 1.63%. Finally, the application of the synthesized material was evaluated for preconcentration and determination of mercuric ions from foods and environmental waters samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Simulation of mechanical behavior and optimization of simulated injection molding process for PLA based antibacterial composite and nanocomposite bone screws using central composite design.

PubMed

Heidari, Behzad Shiroud; Oliaei, Erfan; Shayesteh, Hadi; Davachi, Seyed Mohammad; Hejazi, Iman; Seyfi, Javad; Bahrami, Mozhgan; Rashedi, Hamid

2017-01-01

In this study, injection molding of three poly lactic acid (PLA) based bone screws was simulated and optimized through minimizing the shrinkage and warpage of the bone screws. The optimization was carried out by investigating the process factors such as coolant temperature, mold temperature, melt temperature, packing time, injection time, and packing pressure. A response surface methodology (RSM), based on the central composite design (CCD), was used to determine the effects of the process factors on the PLA based bone screws. Upon applying the method of maximizing the desirability function, optimization of the factors gave the lowest warpage and shrinkage for nanocomposite PLA bone screw (PLA9). Moreover, PLA9 has the greatest desirability among the selected materials for bone screw injection molding. Meanwhile, a finite element analysis (FE analysis) was also performed to determine the force values and concentration points which cause yielding of the screws under certain conditions. The Von-Mises stress distribution showed that PLA9 screw is more resistant against the highest loads as compared to the other ones. Finally, according to the results of injection molding simulations, the design of experiments (DOE) and structural analysis, PLA9 screw is recommended as the best candidate for the production of biomedical materials among all the three types of screws. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling and optimization of trihalomethanes formation potential of surface water (a drinking water source) using Box-Behnken design.

PubMed

Singh, Kunwar P; Rai, Premanjali; Pandey, Priyanka; Sinha, Sarita

2012-01-01

The present research aims to investigate the individual and interactive effects of chlorine dose/dissolved organic carbon ratio, pH, temperature, bromide concentration, and reaction time on trihalomethanes (THMs) formation in surface water (a drinking water source) during disinfection by chlorination in a prototype laboratory-scale simulation and to develop a model for the prediction and optimization of THMs levels in chlorinated water for their effective control. A five-factor Box-Behnken experimental design combined with response surface and optimization modeling was used for predicting the THMs levels in chlorinated water. The adequacy of the selected model and statistical significance of the regression coefficients, independent variables, and their interactions were tested by the analysis of variance and t test statistics. The THMs levels predicted by the model were very close to the experimental values (R(2) = 0.95). Optimization modeling predicted maximum (192 μg/l) TMHs formation (highest risk) level in water during chlorination was very close to the experimental value (186.8 ± 1.72 μg/l) determined in laboratory experiments. The pH of water followed by reaction time and temperature were the most significant factors that affect the THMs formation during chlorination. The developed model can be used to determine the optimum characteristics of raw water and chlorination conditions for maintaining the THMs levels within the safe limit.

Optimal placement of trailing-edge flaps for helicopter vibration reduction using response surface methods

NASA Astrophysics Data System (ADS)

Viswamurthy, S. R.; Ganguli, Ranjan

2007-03-01

This study aims to determine optimal locations of dual trailing-edge flaps to achieve minimum hub vibration levels in a helicopter, while incurring low penalty in terms of required trailing-edge flap control power. An aeroelastic analysis based on finite elements in space and time is used in conjunction with an optimal control algorithm to determine the flap time history for vibration minimization. The reduced hub vibration levels and required flap control power (due to flap motion) are the two objectives considered in this study and the flap locations along the blade are the design variables. It is found that second order polynomial response surfaces based on the central composite design of the theory of design of experiments describe both objectives adequately. Numerical studies for a four-bladed hingeless rotor show that both objectives are more sensitive to outboard flap location compared to the inboard flap location by an order of magnitude. Optimization results show a disjoint Pareto surface between the two objectives. Two interesting design points are obtained. The first design gives 77 percent vibration reduction from baseline conditions (no flap motion) with a 7 percent increase in flap power compared to the initial design. The second design yields 70 percent reduction in hub vibration with a 27 percent reduction in flap power from the initial design.

Inverse Statistics and Asset Allocation Efficiency

NASA Astrophysics Data System (ADS)

Bolgorian, Meysam

In this paper using inverse statistics analysis, the effect of investment horizon on the efficiency of portfolio selection is examined. Inverse statistics analysis is a general tool also known as probability distribution of exit time that is used for detecting the distribution of the time in which a stochastic process exits from a zone. This analysis was used in Refs. 1 and 2 for studying the financial returns time series. This distribution provides an optimal investment horizon which determines the most likely horizon for gaining a specific return. Using samples of stocks from Tehran Stock Exchange (TSE) as an emerging market and S&P 500 as a developed market, effect of optimal investment horizon in asset allocation is assessed. It is found that taking into account the optimal investment horizon in TSE leads to more efficiency for large size portfolios while for stocks selected from S&P 500, regardless of portfolio size, this strategy does not only not produce more efficient portfolios, but also longer investment horizons provides more efficiency.

Polysaccharide extraction from Sphallerocarpus gracilis roots by response surface methodology.

PubMed

Ma, Tingting; Sun, Xiangyu; Tian, Chengrui; Luo, Jiyang; Zheng, Cuiping; Zhan, Jicheng

2016-07-01

The extraction process of Sphallerocarpus gracilis root polysaccharides (SGRP) was optimized using response surface methodology with two methods [hot-water extraction (HWE) and ultrasonic-assisted extraction (UAE)]. The antioxidant activities of SGRP were determined, and the structural features of the untreated materials (HWE residue and UAE residue) and the extracted polysaccharides were compared by scanning electron microscopy. Results showed that the optimal UAE conditions were extraction temperature of 81°C, extraction time of 1.7h, liquid-solid ratio of 17ml/g, ultrasonic power of 300W and three extraction cycles. The optimal HWE conditions were 93°C extraction temperature, 3.6h extraction time, 21ml/g liquid-solid ratio and three extraction cycles. UAE offered a higher extraction yield with a shorter time, lower temperature and a lower solvent consumption compared with HWE, and the extracted polysaccharides possessed a higher antioxidant capacity. Therefore, UAE could be used as an alternative to conventional HWE for SGRP extraction. Copyright © 2016 Elsevier B.V. All rights reserved.

Infinite capacity multi-server queue with second optional service channel

NASA Astrophysics Data System (ADS)

Ke, Jau-Chuan; Wu, Chia-Huang; Pearn, Wen Lea

2013-02-01

This paper deals with an infinite-capacity multi-server queueing system with a second optional service (SOS) channel. The inter-arrival times of arriving customers, the service times of the first essential service (FES) and the SOS channel are all exponentially distributed. A customer may leave the system after the FES channel with probability (1-θ), or at the completion of the FES may immediately require a SOS with probability θ (0 <= θ <= 1). The formulae for computing the rate matrix and stationary probabilities are derived by means of a matrix analytical approach. A cost model is developed to determine the optimal values of the number of servers and the two service rates, simultaneously, at the minimal total expected cost per unit time. Quasi-Newton method are employed to deal with the optimization problem. Under optimal operating conditions, numerical results are provided in which several system performance measures are calculated based on assumed numerical values of the system parameters.

Development, optimization, and single laboratory validation of an event-specific real-time PCR method for the detection and quantification of Golden Rice 2 using a novel taxon-specific assay.

PubMed

Jacchia, Sara; Nardini, Elena; Savini, Christian; Petrillo, Mauro; Angers-Loustau, Alexandre; Shim, Jung-Hyun; Trijatmiko, Kurniawan; Kreysa, Joachim; Mazzara, Marco

2015-02-18

In this study, we developed, optimized, and in-house validated a real-time PCR method for the event-specific detection and quantification of Golden Rice 2, a genetically modified rice with provitamin A in the grain. We optimized and evaluated the performance of the taxon (targeting rice Phospholipase D α2 gene)- and event (targeting the 3' insert-to-plant DNA junction)-specific assays that compose the method as independent modules, using haploid genome equivalents as unit of measurement. We verified the specificity of the two real-time PCR assays and determined their dynamic range, limit of quantification, limit of detection, and robustness. We also confirmed that the taxon-specific DNA sequence is present in single copy in the rice genome and verified its stability of amplification across 132 rice varieties. A relative quantification experiment evidenced the correct performance of the two assays when used in combination.

Optimal sampling strategies for detecting zoonotic disease epidemics.

PubMed

Ferguson, Jake M; Langebrake, Jessica B; Cannataro, Vincent L; Garcia, Andres J; Hamman, Elizabeth A; Martcheva, Maia; Osenberg, Craig W

2014-06-01

The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

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

Powell, Kody M.; Kim, Jong Suk; Cole, Wesley J.

2016-10-01

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens ofmore » thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.« less

Influence of moisture content, particle size and forming temperature on productivity and quality of rice straw pellets

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

Ishii, Kazuei, E-mail: k-ishii@eng.hokudai.ac.jp; Furuichi, Toru

Highlights: • Optimized conditions were determined for the production of rice straw pellets. • The moisture content and forming temperature are key factors. • High quality rice pellets in the lower heating value and durability were produced. - Abstract: A large amount of rice straw is generated and left as much in paddy fields, which causes greenhouse gas emissions as methane. Rice straw can be used as bioenergy. Rice straw pellets are a promising technology because pelletization of rice straw is a form of mass and energy densification, which leads to a product that is easy to handle, transport, storemore » and utilize because of the increase in the bulk density. The operational conditions required to produce high quality rice straw pellets have not been determined. This study determined the optimal moisture content range required to produce rice straw pellets with high yield ratio and high heating value, and also determined the influence of particle size and the forming temperature on the yield ratio and durability of rice straw pellets. The optimal moisture content range was between 13% and 20% under a forming temperature of 60 or 80 °C. The optimal particle size was between 10 and 20 mm, considering the time and energy required for shredding, although the particle size did not significantly affect the yield ratio and durability of the pellets. The optimized conditions provided high quality rice straw pellets with nearly 90% yield ratio, ⩾12 MJ/kg for the lower heating value, and >95% durability.« less

Pulse shape optimization for electron-positron production in rotating fields

NASA Astrophysics Data System (ADS)

Fillion-Gourdeau, François; Hebenstreit, Florian; Gagnon, Denis; MacLean, Steve

2017-07-01

We optimize the pulse shape and polarization of time-dependent electric fields to maximize the production of electron-positron pairs via strong field quantum electrodynamics processes. The pulse is parametrized in Fourier space by a B -spline polynomial basis, which results in a relatively low-dimensional parameter space while still allowing for a large number of electric field modes. The optimization is performed by using a parallel implementation of the differential evolution, one of the most efficient metaheuristic algorithms. The computational performance of the numerical method and the results on pair production are compared with a local multistart optimization algorithm. These techniques allow us to determine the pulse shape and field polarization that maximize the number of produced pairs in computationally accessible regimes.

Safe-trajectory optimization and tracking control in ultra-close proximity to a failed satellite

NASA Astrophysics Data System (ADS)

Zhang, Jingrui; Chu, Xiaoyu; Zhang, Yao; Hu, Quan; Zhai, Guang; Li, Yanyan

2018-03-01

This paper presents a trajectory-optimization method for a chaser spacecraft operating in ultra-close proximity to a failed satellite. Based on the combination of active and passive trajectory protection, the constraints in the optimization framework are formulated for collision avoidance and successful docking in the presence of any thruster failure. The constraints are then handled by an adaptive Gauss pseudospectral method, in which the dynamic residuals are used as the metric to determine the distribution of collocation points. A finite-time feedback control is further employed in tracking the optimized trajectory. In particular, the stability and convergence of the controller are proved. Numerical results are given to demonstrate the effectiveness of the proposed methods.

What is the optimal way to prepare a Bell state using measurement and feedback?

NASA Astrophysics Data System (ADS)

Martin, Leigh; Sayrafi, Mahrud; Whaley, K. Birgitta

2017-12-01

Recent work has shown that the use of quantum feedback can significantly enhance both the speed and success rate of measurement-based remote entanglement generation, but it is generally unknown what feedback protocols are optimal for these tasks. Here we consider two common measurements that are capable of projecting into pairwise entangled states, namely half- and full-parity measurements of two qubits, and determine in each case a globally optimal protocol for generation of entanglement. For the half-parity measurement, we rederive a previously described protocol using more general methods and prove that it is globally optimal for several figures of merit, including maximal concurrence or fidelity and minimal time to reach a specified concurrence or fidelity. For the full-parity measurement, we derive a protocol for rapid entanglement generation related to that of (Hill, Ralph, Phys. Rev. A 77, 014305), and then map the dynamics of the concurrence of the state to the Bloch vector length of an effective qubit. This mapping allows us to prove several optimality results for feedback protocols with full-parity measurements. We further show that our full-parity protocol transfers entanglement optimally from one qubit to the other amongst all measurement-based schemes. The methods developed here will be useful for deriving feedback protocols and determining their optimality properties in many other quantum systems subject to measurement and unitary operations.

Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

NASA Astrophysics Data System (ADS)

Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.

2017-08-01

This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

Impacts of Various Characteristics of Electricity and Heat Demand on the Optimal Configuration of a Microgrid

NASA Astrophysics Data System (ADS)

Bando, Shigeru; Watanabe, Hiroki; Asano, Hiroshi; Tsujita, Shinsuke

A methodology was developed to design the number and capacity for each piece of equipment (e.g. gas engines, batteries, thermal storage tanks) in microgrids with combined heat and power systems. We analyzed three types of microgrids; the first one consists of an office building and an apartment, the second one consists of a hospital and an apartment, the third one consists of a hotel, office and retails. In the methodology, annual cost is minimized by considering the partial load efficiency of a gas engine and its scale economy, and the optimal number and capacity of each piece of equipment and the annual operational schedule are determined by using the optimal planning method. Based on calculations using this design methodology, it is found that the optimal number of gas engines is determined by the ratio of bottom to peak of the electricity demand and the ratio of heat to electricity demand. The optimal capacity of a battery required to supply electricity for a limited time during a peak demand period is auxiliary. The thermal storage tank for space cooling and space heating is selected to minimize the use of auxiliary equipment such as a gas absorption chiller.

Monte Carlo modeling of time-resolved fluorescence for depth-selective interrogation of layered tissue.

PubMed

Pfefer, T Joshua; Wang, Quanzeng; Drezek, Rebekah A

2011-11-01

Computational approaches for simulation of light-tissue interactions have provided extensive insight into biophotonic procedures for diagnosis and therapy. However, few studies have addressed simulation of time-resolved fluorescence (TRF) in tissue and none have combined Monte Carlo simulations with standard TRF processing algorithms to elucidate approaches for cancer detection in layered biological tissue. In this study, we investigate how illumination-collection parameters (e.g., collection angle and source-detector separation) influence the ability to measure fluorophore lifetime and tissue layer thickness. Decay curves are simulated with a Monte Carlo TRF light propagation model. Multi-exponential iterative deconvolution is used to determine lifetimes and fractional signal contributions. The ability to detect changes in mucosal thickness is optimized by probes that selectively interrogate regions superficial to the mucosal-submucosal boundary. Optimal accuracy in simultaneous determination of lifetimes in both layers is achieved when each layer contributes 40-60% of the signal. These results indicate that depth-selective approaches to TRF have the potential to enhance disease detection in layered biological tissue and that modeling can play an important role in probe design optimization. Published by Elsevier Ireland Ltd.

Optimization of a new method for extraction of cyanidin chloride and pelargonidin chloride anthocyanins with magnetic solid phase extraction and determination in fruit samples by HPLC with central composite design.

PubMed

Yari, Abdollah; Rashnoo, Saba

2017-11-01

Here, we are reporting a sensitive, simple and rapid method for the analysis of cyanidin chloride and pelargonidin chloride anthocyanins in cherry, sour cherry, pomegranate and barberry produced in Iran. The analytes were extracted with acetonitrile-hydrochloric acid (1% v/v) mixture under optimized pretreatment conditions. Clean-up of the extract from fruits was conducted by magnetic solid phase extraction using salicylic acid functionalized silica-coated magnetite nanoparticles (SCMNPs) as the adsorbent. The optimized conditions searched with central composite design. Working under optimum conditions specified as: SCMNPs modified with salicylic acid, sorbent contact time and sample 10min, mechanical stirring time 57.3min. HPLC with UV-detection was used for determination of the analytes. The limit of detection, LOD, obtained for the two anthocyanins were 0.02 and 0.03μgg -1 , respectively. The ranges of the spiked recoveries were 80.0-97.6 and 72.9-97.2%, with the relative standard deviations (RSD) of 2.1 and 2.5%, respectively. Copyright © 2017 Elsevier B.V. All rights reserved.

LC-MS determination of steroidal glycosides from Dioscorea deltoidea Wall cell suspension culture: Optimization of pre-LC-MS procedure parameters by Latin Square design.

PubMed

Sarvin, Boris; Fedorova, Elizaveta; Shpigun, Oleg; Titova, Maria; Nikitin, Mikhail; Kochkin, Dmitry; Rodin, Igor; Stavrianidi, Andrey

2018-03-30

In this paper, the ultrasound assisted extraction method for isolation of steroidal glycosides from D. deltoidea plant cell suspension culture with a subsequent HPLC-MS determination was developed. After the organic solvent was selected via a two-factor experiment the optimization via Latin Square 4 × 4 experimental design was carried out for the following parameters: extraction time, organic solvent concentration in extraction solution and the ratio of solvent to sample. It was also shown that the ultrasound assisted extraction method is not suitable for isolation of steroidal glycosides from the D. deltoidea plant material. The results were double-checked using the multiple successive extraction method and refluxing extraction. Optimal conditions for the extraction of steroidal glycosides by the ultrasound assisted extraction method were: extraction time, 60 min; acetonitrile (water) concentration in extraction solution, 50%; the ratio of solvent to sample, 400 mL/g. Also, the developed method was tested on D. deltoidea cell suspension cultures of different terms and conditions of cultivation. The completeness of the extraction was confirmed using the multiple successive extraction method. Copyright © 2018 Elsevier B.V. All rights reserved.

Formulation and pharmacokinetics of diclofenac lipid nanoemulsions for parenteral application.

PubMed

Ramreddy, Srividya; Kandadi, Prabhakar; Veerabrahma, Kishan

2012-01-01

The objective of the present study was to formulate and determine the pharmacokinetics of stable o/w parenteral lipid nanoemulsions (LNEs) of diclofenac acid used to treat arthritic conditions. The LNEs of diclofenac acid with a mean size ranging from 200 to 240 nm and a zeta potential of -29.4 ± 1.04 mV (negatively charged LNEs) and 62.1 ± 3.5 (positively charged LNEs) emulsions were prepared by hot homogenization and ultrasonication process. The influence of formulation variables, such as the change in proportion of cholesterol, was studied, and optimized formulations were developed. The optimized formulations were relatively stable during centrifugal stress, dilution stress, and storage. The drug content and entrapment efficiency were determined using high-performance liquid chromatography. The in vitro drug release was carried out in phosphate-buffered saline pH 7.4 and cumulative amount of drug released was estimated using a UV-visible spectro-photometer. During in vivo pharmacokinetic studies in male Wistar rats, diclofenac serum concentration from LNEs was higher than that of Voveran injection and was detectable up to 12 h. Diclofenac in LNEs showed improved pharmacokinetic profile with increase in area under the curve, elimination half-life and mean residence time in comparison to Voveran. Our aim was to prepare and determine the pharmacokinetics of injectable lipid nanoemulsions of diclofenac acid for treating arthritic conditions by reducing the frequency of dosing and pain at site of injection. The nanoemulsions of diclofenac acid were prepared by homogenization and ultrasonication process. The sizes and charges of oil globules were determined. The effect of cholesterol on stability of emulsion was studied, and an optimized preparation was developed. The optimized formulations were stable during centrifugation, dilution, and storage. The total amount of drug in emulsion and percentage amount of drug present in emulsion globules were determined using high-performance liquid chromatography. The drug release from preparation was carried out in phosphate-buffered saline pH 7.4. The cumulative amount of drug released was estimated using a spectrophotometer. The time course of the released drug in rat serum was determined. Diclofenac concentrations from lipid nanoemulsions were higher than that of Voveran injection (solution form) in serum.

Simplex optimization of the variables influencing the determination of pefloxacin by time-resolved chemiluminescence

NASA Astrophysics Data System (ADS)

Murillo Pulgarín, José A.; Alañón Molina, Aurelia; Jiménez García, Elisa

2018-03-01

A new chemiluminescence (CL) detection system combined with flow injection analysis (FIA) for the determination of Pefloxacin is proposed. The determination is based on an energy transfer from Pefloxacin to terbium (III). The metal ion enhances the weak CL signal produced by the KMnO4/H2SO3/Pefloxacin system. A modified simplex method was used to optimize chemical and instrumental variables. The influence of the interaction of the permanganate, Tb (III), sodium sulphite and sulphuric acid concentrations, flow rate and injected sample volume was thoroughly investigated by using a modified simplex optimization procedure. The results revealed a strong direct relationship between flow rate and CL intensity throughout the studied range that was confirmed by a gamma test. The response factor for the CL emission intensity was used to assess performance in order to identify the optimum conditions for maximization of the response. Under such conditions, the CL response was proportional to the Pefloxacin concentration over a wide range. The detection limit as calculated according to Clayton's criterion 13.7 μg L- 1. The analyte was successfully determined in milk samples with an average recovery of 100.6 ± 9.8%.

Optimization of ethylene glycol concentrations, freezing rates and holding times in liquid nitrogen vapor for cryopreservation of rhesus macaque (Macaca mulatta) sperm.

PubMed

Yang, Shihua; Ping, Shuhuang; Si, Wei; He, Xiechao; Wang, Xinyi; Lu, Yongqing; Ji, Shaohui; Niu, Yuyu; Ji, Weizhi

2011-06-01

Ethylene glycol (EG) has been speculated to be the most appropriate penetrating cryoprotectant for cryopreservation of rhesus macaque sperm due to its higher permeability coefficient. The present study aimed to determine the optimal EG concentration, freezing rate and holding time in liquid nitrogen (LN(2)) vapor for rhesus sperm cryopreservation. Among six tested EG concentrations (0, 0.18, 0.35, 0.7, 1.4 and 2.1 M), 0.7 M EG showed the most effective cryoprotection (P<0.05). Sperm frozen with 0.7 M EG at -183°C/min showed higher post-thaw motility than sperm frozen at -10, -67 or -435°C/min (P<0.05). Sperm frozen in LN(2) vapor at -183°C/min with 0.7 M EG and a holding time of 10 min showed higher post-thaw motility compared with a holding time of 5 or 15 min (P<0.05). The function of sperm cryopreserved at the optimized EG concentration, freezing rate and holding time was further evaluated by in vitro fertilization. Of the 36 oocytes collected from gonadotropin-stimulated rhesus macaques, 61.1% were fertilized, and 61.1, 44.4 and 36.1% of the oocytes developed to 2 cells, morulae and blastocysts, respectively. Our findings provide an alternative penetrating cryoprotectant and optimal protocol for genetic preservation purposes in this important species.

Use of an administrative data set to determine optimal scheduling of an alcohol intervention worker.

PubMed

Peterson, Timothy A; Desmond, Jeffrey S; Cunningham, Rebecca

2012-06-01

Brief alcohol interventions are efficacious in reducing alcohol-related consequences among emergency department (ED) patients. Use of non-clinical staff may increase alcohol screening and intervention; however, optimal scheduling of an alcohol intervention worker (AIW) is unknown. Determine optimal scheduling of an AIW based on peak discharge time of alcohol-related ED visits. Discharge times for consecutive patients with an alcohol-related diagnosis were abstracted from an urban ED's administrative data set from September 2005 through August 2007. Queuing theory was used to identify optimal scheduling. Data for weekends and weekdays were analyzed separately. Stationary independent period-by-period analysis was performed for hourly periods. An M/M/s queuing model, for Markovian inter-arrival time/Markovian service time/and potentially more than one server, was developed for each hour assuming: 1) a single unlimited queue; 2) 75% of patients waited no longer than 30 min for intervention; 3) AIW spent an average 20 min/patient. Estimated average utilization/hour was calculated; if utilization/hour exceeded 25%, AIW staff was considered necessary. There were 2282 patient visits (mean age 38 years, range 11-84 years). Weekdays accounted for 45% of visits; weekends 55%. On weekdays, one AIW from 6:00 a.m.-9:00 a.m. (max utilization 42%/hour) would accommodate 28% of weekday alcohol-related patients. On weekends, 5:00 a.m.-11:00 a.m. (max utilization 50%), one AIW would cover 54% of all weekend alcohol-related visits. During other hours the utilization rate falls below 25%/hour. Evaluating 2 years of discharge data revealed that 30 h of dedicated AIW time--18 weekend hours (5:00 a.m.-11:00 a.m.), 12 weekday hours (6:00 a.m.-9:00 a.m.)--would allow maximal patient alcohol screening and intervention with minimal additional burden to clinical staff. Copyright © 2012 Elsevier Inc. All rights reserved.

Non-parametric early seizure detection in an animal model of temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Talathi, Sachin S.; Hwang, Dong-Uk; Spano, Mark L.; Simonotto, Jennifer; Furman, Michael D.; Myers, Stephen M.; Winters, Jason T.; Ditto, William L.; Carney, Paul R.

2008-03-01

The performance of five non-parametric, univariate seizure detection schemes (embedding delay, Hurst scale, wavelet scale, nonlinear autocorrelation and variance energy) were evaluated as a function of the sampling rate of EEG recordings, the electrode types used for EEG acquisition, and the spatial location of the EEG electrodes in order to determine the applicability of the measures in real-time closed-loop seizure intervention. The criteria chosen for evaluating the performance were high statistical robustness (as determined through the sensitivity and the specificity of a given measure in detecting a seizure) and the lag in seizure detection with respect to the seizure onset time (as determined by visual inspection of the EEG signal by a trained epileptologist). An optimality index was designed to evaluate the overall performance of each measure. For the EEG data recorded with microwire electrode array at a sampling rate of 12 kHz, the wavelet scale measure exhibited better overall performance in terms of its ability to detect a seizure with high optimality index value and high statistics in terms of sensitivity and specificity.

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. These approaches are implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Turbomachinery Airfoil Design Optimization Using Differential Evolution

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

An aerodynamic design optimization procedure that is based on a evolutionary algorithm known at Differential Evolution is described. Differential Evolution is a simple, fast, and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems, including highly nonlinear systems with discontinuities and multiple local optima. The method is combined with a Navier-Stokes solver that evaluates the various intermediate designs and provides inputs to the optimization procedure. An efficient constraint handling mechanism is also incorporated. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated. Substantial reductions in the overall computing time requirements are achieved by using the algorithm in conjunction with neural networks.

Optimal policy for profit maximising in an EOQ model under non-linear holding cost and stock-dependent demand rate

NASA Astrophysics Data System (ADS)

Pando, V.; García-Laguna, J.; San-José, L. A.

2012-11-01

In this article, we integrate a non-linear holding cost with a stock-dependent demand rate in a maximising profit per unit time model, extending several inventory models studied by other authors. After giving the mathematical formulation of the inventory system, we prove the existence and uniqueness of the optimal policy. Relying on this result, we can obtain the optimal solution using different numerical algorithms. Moreover, we provide a necessary and sufficient condition to determine whether a system is profitable, and we establish a rule to check when a given order quantity is the optimal lot size of the inventory model. The results are illustrated through numerical examples and the sensitivity of the optimal solution with respect to changes in some values of the parameters is assessed.

Optimization protocol for the extraction of 6-gingerol and 6-shogaol from Zingiber officinale var. rubrum Theilade and improving antioxidant and anticancer activity using response surface methodology.

PubMed

Ghasemzadeh, Ali; Jaafar, Hawa Z E; Rahmat, Asmah

2015-07-30

Analysis and extraction of plant matrices are important processes for the development, modernization, and quality control of herbal formulations. Response surface methodology is a collection of statistical and mathematical techniques that are used to optimize the range of variables in various experimental processes to reduce the number of experimental runs, cost , and time, compared to other methods. Response surface methodology was applied for optimizing reflux extraction conditions for achieving high 6-gingerol and 6-shogaol contents, and high antioxidant activity in Zingiber officinale var. rubrum Theilade . The two-factor central composite design was employed to determine the effects of two independent variables, namely extraction temperature (X1: 50-80 °C) and time (X2: 2-4 h), on the properties of the extracts. The 6-gingerol and 6-shogaol contents were measured using ultra-performance liquid chromatography. The antioxidant activity of the rhizome extracts was determined by means of the 1,1-diphenyl-2-picrylhydrazyl assay. Anticancer activity of optimized extracts against HeLa cancer cell lines was measured using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Increasing the extraction temperature and time induced significant response of the variables. The optimum extraction condition for all responses was at 76.9 °C for 3.4 h. Under the optimum condition, the corresponding predicted response values for 6-gingerol, 6-shogaol, and the antioxidant activity were 2.89 mg/g DW, 1.85 mg/g DW, and 84.3%, respectively. 6-gingerol and 6-shogaol were extracted under optimized condition to check the viability of the models. The values were 2.92 and 1.88 mg/g DW, and 84.0% for 6-gingerol, 6-shogaol, and the antioxidant activity respectively. The experimental values agreed with those predicted, thus indicating suitability of the models employed and the success of RSM in optimizing the extraction condition. With optimizing of reflux extraction anticancer activity of extracts against HeLa cancer cells enhanced about 16.8%. The half inhibition concentration (IC50) value of optimized and unoptimized extract was found at concentration of 20.9 and 38.4 μg/mL respectively. Optimized extract showed more distinct anticancer activities against HeLa cancer cells in a concentration of 40 μg/mL (P < 0.01) without toxicity to normal cells. The results indicated that the pharmaceutical quality of ginger could be improved significantly by optimizing of extraction process using response surface methodology.

Co-state initialization for the minimum-time low-thrust trajectory optimization

NASA Astrophysics Data System (ADS)

Taheri, Ehsan; Li, Nan I.; Kolmanovsky, Ilya

2017-05-01

This paper presents an approach for co-state initialization which is a critical step in solving minimum-time low-thrust trajectory optimization problems using indirect optimal control numerical methods. Indirect methods used in determining the optimal space trajectories typically result in two-point boundary-value problems and are solved by single- or multiple-shooting numerical methods. Accurate initialization of the co-state variables facilitates the numerical convergence of iterative boundary value problem solvers. In this paper, we propose a method which exploits the trajectory generated by the so-called pseudo-equinoctial and three-dimensional finite Fourier series shape-based methods to estimate the initial values of the co-states. The performance of the approach for two interplanetary rendezvous missions from Earth to Mars and from Earth to asteroid Dionysus is compared against three other approaches which, respectively, exploit random initialization of co-states, adjoint-control transformation and a standard genetic algorithm. The results indicate that by using our proposed approach the percent of the converged cases is higher for trajectories with higher number of revolutions while the computation time is lower. These features are advantageous for broad trajectory search in the preliminary phase of mission designs.

Fuel Optimal, Finite Thrust Guidance Methods to Circumnavigate with Lighting Constraints

NASA Astrophysics Data System (ADS)

Prince, E. R.; Carr, R. W.; Cobb, R. G.

This paper details improvements made to the authors' most recent work to find fuel optimal, finite-thrust guidance to inject an inspector satellite into a prescribed natural motion circumnavigation (NMC) orbit about a resident space object (RSO) in geosynchronous orbit (GEO). Better initial guess methodologies are developed for the low-fidelity model nonlinear programming problem (NLP) solver to include using Clohessy- Wiltshire (CW) targeting, a modified particle swarm optimization (PSO), and MATLAB's genetic algorithm (GA). These initial guess solutions may then be fed into the NLP solver as an initial guess, where a different NLP solver, IPOPT, is used. Celestial lighting constraints are taken into account in addition to the sunlight constraint, ensuring that the resulting NMC also adheres to Moon and Earth lighting constraints. The guidance is initially calculated given a fixed final time, and then solutions are also calculated for fixed final times before and after the original fixed final time, allowing mission planners to choose the lowest-cost solution in the resulting range which satisfies all constraints. The developed algorithms provide computationally fast and highly reliable methods for determining fuel optimal guidance for NMC injections while also adhering to multiple lighting constraints.

Time Scale Optimization and the Hunt for Astronomical Cycles in Deep Time Strata

NASA Astrophysics Data System (ADS)

Meyers, Stephen R.

2016-04-01

A valuable attribute of astrochronology is the direct link between chronometer and climate change, providing a remarkable opportunity to constrain the evolution of the surficial Earth System. Consequently, the hunt for astronomical cycles in strata has spurred the development of a rich conceptual framework for climatic/oceanographic change, and has allowed exploration of the geologic record with unprecedented temporal resolution. Accompanying these successes, however, has been a persistent skepticism about appropriate astrochronologic testing and circular reasoning: how does one reliably test for astronomical cycles in stratigraphic data, especially when time is poorly constrained? From this perspective, it would seem that the merits and promise of astrochronology (e.g., a geologic time scale measured in ≤400 kyr increments) also serves as its Achilles heel, if the confirmation of such short rhythms defies rigorous statistical testing. To address these statistical challenges in astrochronologic testing, a new approach has been developed that (1) explicitly evaluates time scale uncertainty, (2) is resilient to common problems associated with spectrum confidence level assessment and 'multiple testing', and (3) achieves high statistical power under a wide range of conditions (it can identify astronomical cycles when present in data). Designated TimeOpt (for "time scale optimization"; Meyers 2015), the method employs a probabilistic linear regression model framework to investigate amplitude modulation and frequency ratios (bundling) in stratigraphic data, while simultaneously determining the optimal time scale. This presentation will review the TimeOpt method, and demonstrate how the flexible statistical framework can be further extended to evaluate (and optimize upon) complex sedimentation rate models, enhancing the statistical power of the approach, and addressing the challenge of unsteady sedimentation. Meyers, S. R. (2015), The evaluation of eccentricity-related amplitude modulation and bundling in paleoclimate data: An inverse approach for astrochronologic testing and time scale optimization, Paleoceanography, 30, doi:10.1002/ 2015PA002850.

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

Christy, Brian; Anella, Ryan; Lommen, Andrea

Pulsar timing arrays (PTAs) are a collection of precisely timed millisecond pulsars (MSPs) that can search for gravitational waves (GWs) in the nanohertz frequency range by observing characteristic signatures in the timing residuals. The sensitivity of a PTA depends on the direction of the propagating GW source, the timing accuracy of the pulsars, and the allocation of the available observing time. The goal of this paper is to determine the optimal time allocation strategy among the MSPs in the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) for a single source of GW under a particular set of assumptions. Wemore » consider both an isotropic distribution of sources across the sky and a specific source in the Virgo cluster. This work improves on previous efforts by modeling the effect of intrinsic spin noise for each pulsar. We find that, in general, the array is optimized by maximizing time spent on the best-timed pulsars, with sensitivity improvements typically ranging from a factor of 1.5 to 4.« less

Optimal trajectories of aircraft and spacecraft

NASA Technical Reports Server (NTRS)

Miele, A.

1990-01-01

Work done on algorithms for the numerical solutions of optimal control problems and their application to the computation of optimal flight trajectories of aircraft and spacecraft is summarized. General considerations on calculus of variations, optimal control, numerical algorithms, and applications of these algorithms to real-world problems are presented. The sequential gradient-restoration algorithm (SGRA) is examined for the numerical solution of optimal control problems of the Bolza type. Both the primal formulation and the dual formulation are discussed. Aircraft trajectories, in particular, the application of the dual sequential gradient-restoration algorithm (DSGRA) to the determination of optimal flight trajectories in the presence of windshear are described. Both take-off trajectories and abort landing trajectories are discussed. Take-off trajectories are optimized by minimizing the peak deviation of the absolute path inclination from a reference value. Abort landing trajectories are optimized by minimizing the peak drop of altitude from a reference value. Abort landing trajectories are optimized by minimizing the peak drop of altitude from a reference value. The survival capability of an aircraft in a severe windshear is discussed, and the optimal trajectories are found to be superior to both constant pitch trajectories and maximum angle of attack trajectories. Spacecraft trajectories, in particular, the application of the primal sequential gradient-restoration algorithm (PSGRA) to the determination of optimal flight trajectories for aeroassisted orbital transfer are examined. Both the coplanar case and the noncoplanar case are discussed within the frame of three problems: minimization of the total characteristic velocity; minimization of the time integral of the square of the path inclination; and minimization of the peak heating rate. The solution of the second problem is called nearly-grazing solution, and its merits are pointed out as a useful engineering compromise between energy requirements and aerodynamics heating requirements.

Optimizing Sustainable Geothermal Heat Extraction

NASA Astrophysics Data System (ADS)

Patel, Iti; Bielicki, Jeffrey; Buscheck, Thomas

2016-04-01

Geothermal heat, though renewable, can be depleted over time if the rate of heat extraction exceeds the natural rate of renewal. As such, the sustainability of a geothermal resource is typically viewed as preserving the energy of the reservoir by weighing heat extraction against renewability. But heat that is extracted from a geothermal reservoir is used to provide a service to society and an economic gain to the provider of that service. For heat extraction used for market commodities, sustainability entails balancing the rate at which the reservoir temperature renews with the rate at which heat is extracted and converted into economic profit. We present a model for managing geothermal resources that combines simulations of geothermal reservoir performance with natural resource economics in order to develop optimal heat mining strategies. Similar optimal control approaches have been developed for managing other renewable resources, like fisheries and forests. We used the Non-isothermal Unsaturated-saturated Flow and Transport (NUFT) model to simulate the performance of a sedimentary geothermal reservoir under a variety of geologic and operational situations. The results of NUFT are integrated into the optimization model to determine the extraction path over time that maximizes the net present profit given the performance of the geothermal resource. Results suggest that the discount rate that is used to calculate the net present value of economic gain is a major determinant of the optimal extraction path, particularly for shallower and cooler reservoirs, where the regeneration of energy due to the natural geothermal heat flux is a smaller percentage of the amount of energy that is extracted from the reservoir.

Adjoint Sensitivity Method to Determine Optimal Set of Stations for Tsunami Source Inversion

NASA Astrophysics Data System (ADS)

Gusman, A. R.; Hossen, M. J.; Cummins, P. R.; Satake, K.

2017-12-01

We applied the adjoint sensitivity technique in tsunami science for the first time to determine an optimal set of stations for a tsunami source inversion. The adjoint sensitivity (AS) method has been used in numerical weather prediction to find optimal locations for adaptive observations. We implemented this technique to Green's Function based Time Reverse Imaging (GFTRI), which is recently used in tsunami source inversion in order to reconstruct the initial sea surface displacement, known as tsunami source model. This method has the same source representation as the traditional least square (LSQ) source inversion method where a tsunami source is represented by dividing the source region into a regular grid of "point" sources. For each of these, Green's function (GF) is computed using a basis function for initial sea surface displacement whose amplitude is concentrated near the grid point. We applied the AS method to the 2009 Samoa earthquake tsunami that occurred on 29 September 2009 in the southwest Pacific, near the Tonga trench. Many studies show that this earthquake is a doublet associated with both normal faulting in the outer-rise region and thrust faulting in the subduction interface. To estimate the tsunami source model for this complex event, we initially considered 11 observations consisting of 5 tide gauges and 6 DART bouys. After implementing AS method, we found the optimal set of observations consisting with 8 stations. Inversion with this optimal set provides better result in terms of waveform fitting and source model that shows both sub-events associated with normal and thrust faulting.

Optimal cycling time trial position models: aerodynamics versus power output and metabolic energy.

PubMed

Fintelman, D M; Sterling, M; Hemida, H; Li, F-X

2014-06-03

The aerodynamic drag of a cyclist in time trial (TT) position is strongly influenced by the torso angle. While decreasing the torso angle reduces the drag, it limits the physiological functioning of the cyclist. Therefore the aims of this study were to predict the optimal TT cycling position as function of the cycling speed and to determine at which speed the aerodynamic power losses start to dominate. Two models were developed to determine the optimal torso angle: a 'Metabolic Energy Model' and a 'Power Output Model'. The Metabolic Energy Model minimised the required cycling energy expenditure, while the Power Output Model maximised the cyclists׳ power output. The input parameters were experimentally collected from 19 TT cyclists at different torso angle positions (0-24°). The results showed that for both models, the optimal torso angle depends strongly on the cycling speed, with decreasing torso angles at increasing speeds. The aerodynamic losses outweigh the power losses at cycling speeds above 46km/h. However, a fully horizontal torso is not optimal. For speeds below 30km/h, it is beneficial to ride in a more upright TT position. The two model outputs were not completely similar, due to the different model approaches. The Metabolic Energy Model could be applied for endurance events, while the Power Output Model is more suitable in sprinting or in variable conditions (wind, undulating course, etc.). It is suggested that despite some limitations, the models give valuable information about improving the cycling performance by optimising the TT cycling position. Copyright © 2014 Elsevier Ltd. All rights reserved.

Quality of red blood cells washed using the ACP 215 cell processor: assessment of optimal pre- and postwash storage times and conditions.

PubMed

Hansen, Adele; Yi, Qi-Long; Acker, Jason P

2013-08-01

Washing of red blood cell concentrates (RCCs) is required for potassium-sensitive transfusion recipients, including neonates in need of large-volume transfusions. When open, nonsterile washing systems are used, postwash outdate time is limited to 24 hours, often leading to problems providing the component to the patient before expiry. A closed, automated cell processor, the ACP 215 from Haemonetics Corporation, was used to wash RCCs and determine optimal pre- and postwash storage times. Two postwash storage solutions, additive solution (AS)-3 and saline-adenine-glucose-mannitol (SAGM), were compared. The in vitro quality of leukoreduced RCCs, prepared from citrate-phosphate-dextrose-anticoagulated whole blood, was determined postwash and compared to existing guidelines for RCC quality (hemoglobin content, hematocrit, and hemolysis) and predetermined criteria for ATP and supernatant potassium levels. A criterion for visual hemolysis was also applied. The prewash storage time, postwash storage time, and the postwash resuspension solution all contributed to RCC quality postwash. Levels of hemolysis were greater when washed RCCs were resuspended in SAGM (p = 0.01), while AS-3 proved worse at maintaining ATP levels postwash (p < 0.01). Immediately postwash, all units had supernatant K+ levels below the detection limit of the instrument (<1 mmol/L), but these increased to above acceptable levels within 14 days. Based on all acceptance criteria, a maximum 14-day prewash storage period and 7-day postwash storage period in SAGM preservative was found to be optimal. The longer outdate time postwashing should help lessen challenges in providing components to patients before expiry. © 2013 American Association of Blood Banks.

A cost–benefit analysis of acclimation to low irradiance in tropical rainforest tree seedlings: leaf life span and payback time for leaf deployment

PubMed Central

Coste, Sabrina; Roggy, Jean-Christophe; Schimann, Heidy; Epron, Daniel; Dreyer, Erwin

2011-01-01

The maintenance in the long run of a positive carbon balance under very low irradiance is a prerequisite for survival of tree seedlings below the canopy or in small gaps in a tropical rainforest. To provide a quantitative basis for this assumption, experiments were carried out to determine whether construction cost (CC) and payback time for leaves and support structures, as well as leaf life span (i) differ among species and (ii) display an irradiance-elicited plasticity. Experiments were also conducted to determine whether leaf life span correlates to CC and payback time and is close to the optimal longevity derived from an optimization model. Saplings from 13 tropical tree species were grown under three levels of irradiance. Specific-CC was computed, as well as CC scaled to leaf area at the metamer level. Photosynthesis was recorded over the leaf life span. Payback time was derived from CC and a simple photosynthesis model. Specific-CC displayed only little interspecific variability and irradiance-elicited plasticity, in contrast to CC scaled to leaf area. Leaf life span ranged from 4 months to >26 months among species, and was longest in seedlings grown under lowest irradiance. It was always much longer than payback time, even under the lowest irradiance. Leaves were shed when their photosynthesis had reached very low values, in contrast to what was predicted by an optimality model. The species ranking for the different traits was stable across irradiance treatments. The two pioneer species always displayed the smallest CC, leaf life span, and payback time. All species displayed a similar large irradiance-elicited plasticity. PMID:21511904

Determination of hyporheic travel time distributions and other parameters from concurrent conservative and reactive tracer tests by local-in-global optimization

NASA Astrophysics Data System (ADS)

Knapp, Julia L. A.; Cirpka, Olaf A.

2017-06-01

The complexity of hyporheic flow paths requires reach-scale models of solute transport in streams that are flexible in their representation of the hyporheic passage. We use a model that couples advective-dispersive in-stream transport to hyporheic exchange with a shape-free distribution of hyporheic travel times. The model also accounts for two-site sorption and transformation of reactive solutes. The coefficients of the model are determined by fitting concurrent stream-tracer tests of conservative (fluorescein) and reactive (resazurin/resorufin) compounds. The flexibility of the shape-free models give rise to multiple local minima of the objective function in parameter estimation, thus requiring global-search algorithms, which is hindered by the large number of parameter values to be estimated. We present a local-in-global optimization approach, in which we use a Markov-Chain Monte Carlo method as global-search method to estimate a set of in-stream and hyporheic parameters. Nested therein, we infer the shape-free distribution of hyporheic travel times by a local Gauss-Newton method. The overall approach is independent of the initial guess and provides the joint posterior distribution of all parameters. We apply the described local-in-global optimization method to recorded tracer breakthrough curves of three consecutive stream sections, and infer section-wise hydraulic parameter distributions to analyze how hyporheic exchange processes differ between the stream sections.

Physicochemical properties and starch digestibility of Chinese noodles in relation to optimal cooking time.

PubMed

Ye, Xiaoting; Sui, Zhongquan

2016-03-01

Changes in the physicochemical properties and starch digestibility of white salted noodles (WSN) at different cooking stage were investigated. The noodles were dried in fresh air and then cooked for 2-12 min by boiling in distilled water to determine the properties of cooking quality, textural properties and optical characteristic. For starch digestibility, dry noodles were milled and sieved into various particle size classes ranging from 0.5 mm to 5.0 mm, and hydrolyzed by porcine pancreatic α-amylase. The optimal cooking time of WSN determined by squeezing between glasses was 6 min. The results showed that the kinetics of solvation of starch and protein molecules were responsible for changes of the physicochemical properties of WSN during cooking. The susceptibility of starch to α-amylase was influenced by the cooking time, particle size and enzyme treatment. The greater value of rapidly digestible starch (RDS) and lower value of slowly digestible starch (SDS) and resistant starch (RS) were reached at the optimal cooking stage ranging between 63.14-71.97%, 2.47-10.74% and 23.94-26.88%, respectively, indicating the susceptibility on hydrolysis by enzyme was important in defining the cooked stage. The study suggested that cooking quality and digestibility were not correlated but the texture greatly controls the digestibility of the noodles. Copyright © 2015 Elsevier B.V. All rights reserved.

Time-oriented experimental design method to optimize hydrophilic matrix formulations with gelation kinetics and drug release profiles.

PubMed

Shin, Sangmun; Choi, Du Hyung; Truong, Nguyen Khoa Viet; Kim, Nam Ah; Chu, Kyung Rok; Jeong, Seong Hoon

2011-04-04

A new experimental design methodology was developed by integrating the response surface methodology and the time series modeling. The major purposes were to identify significant factors in determining swelling and release rate from matrix tablets and their relative factor levels for optimizing the experimental responses. Properties of tablet swelling and drug release were assessed with ten factors and two default factors, a hydrophilic model drug (terazosin) and magnesium stearate, and compared with target values. The selected input control factors were arranged in a mixture simplex lattice design with 21 experimental runs. The obtained optimal settings for gelation were PEO, LH-11, Syloid, and Pharmacoat with weight ratios of 215.33 (88.50%), 5.68 (2.33%), 19.27 (7.92%), and 3.04 (1.25%), respectively. The optimal settings for drug release were PEO and citric acid with weight ratios of 191.99 (78.91%) and 51.32 (21.09%), respectively. Based on the results of matrix swelling and drug release, the optimal solutions, target values, and validation experiment results over time were similar and showed consistent patterns with very small biases. The experimental design methodology could be a very promising experimental design method to obtain maximum information with limited time and resources. It could also be very useful in formulation studies by providing a systematic and reliable screening method to characterize significant factors in the sustained release matrix tablet. Copyright © 2011 Elsevier B.V. All rights reserved.

Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.

PubMed

Miao, Minmin; Zeng, Hong; Wang, Aimin; Zhao, Changsen; Liu, Feixiang

2017-02-15

Common spatial pattern (CSP) is most widely used in motor imagery based brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the eigenvectors corresponding to both extreme eigenvalues are selected to construct the optimal spatial filter. In addition, an appropriate selection of subject-specific time segments and frequency bands plays an important role in its successful application. This study proposes to optimize spatial-frequency-temporal patterns for discriminative feature extraction. Spatial optimization is implemented by channel selection and finding discriminative spatial filters adaptively on each time-frequency segment. A novel Discernibility of Feature Sets (DFS) criteria is designed for spatial filter optimization. Besides, discriminative features located in multiple time-frequency segments are selected automatically by the proposed sparse time-frequency segment common spatial pattern (STFSCSP) method which exploits sparse regression for significant features selection. Finally, a weight determined by the sparse coefficient is assigned for each selected CSP feature and we propose a Weighted Naïve Bayesian Classifier (WNBC) for classification. Experimental results on two public EEG datasets demonstrate that optimizing spatial-frequency-temporal patterns in a data-driven manner for discriminative feature extraction greatly improves the classification performance. The proposed method gives significantly better classification accuracies in comparison with several competing methods in the literature. The proposed approach is a promising candidate for future BCI systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Application of the optimal homotopy asymptotic method to nonlinear Bingham fluid dampers

NASA Astrophysics Data System (ADS)

Marinca, Vasile; Ene, Remus-Daniel; Bereteu, Liviu

2017-10-01

Dynamic response time is an important feature for determining the performance of magnetorheological (MR) dampers in practical civil engineering applications. The objective of this paper is to show how to use the Optimal Homotopy Asymptotic Method (OHAM) to give approximate analytical solutions of the nonlinear differential equation of a modified Bingham model with non-viscous exponential damping. Our procedure does not depend upon small parameters and provides us with a convenient way to optimally control the convergence of the approximate solutions. OHAM is very efficient in practice for ensuring very rapid convergence of the solution after only one iteration and with a small number of steps.

The "Best Worst" Field Optimization and Focusing

NASA Technical Reports Server (NTRS)

Vaughnn, David; Moore, Ken; Bock, Noah; Zhou, Wei; Ming, Liang; Wilson, Mark

2008-01-01

A simple algorithm for optimizing and focusing lens designs is presented. The goal of the algorithm is to simultaneously create the best and most uniform image quality over the field of view. Rather than relatively weighting multiple field points, only the image quality from the worst field point is considered. When optimizing a lens design, iterations are made to make this worst field point better until such a time as a different field point becomes worse. The same technique is used to determine focus position. The algorithm works with all the various image quality metrics. It works with both symmetrical and asymmetrical systems. It works with theoretical models and real hardware.

Genetic Algorithm for Optimization: Preprocessing with n Dimensional Bisection and Error Estimation

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam Ali

2006-01-01

A knowledge of the appropriate values of the parameters of a genetic algorithm (GA) such as the population size, the shrunk search space containing the solution, crossover and mutation probabilities is not available a priori for a general optimization problem. Recommended here is a polynomial-time preprocessing scheme that includes an n-dimensional bisection and that determines the foregoing parameters before deciding upon an appropriate GA for all problems of similar nature and type. Such a preprocessing is not only fast but also enables us to get the global optimal solution and its reasonably narrow error bounds with a high degree of confidence.

Adaptive critics for dynamic optimization.

PubMed

Kulkarni, Raghavendra V; Venayagamoorthy, Ganesh Kumar

2010-06-01

A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The proposed combination of a particle swarm optimization-based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. The objective of the sleep scheduler is to dynamically adapt the sleep duration to node's battery capacity and movement pattern of animals in its environment in order to obtain snapshots of the animal on its trajectory uniformly. Simulation results show that the sleep time of the node determined by the actor critic yields superior quality of sensory data acquisition and enhanced node longevity. Copyright 2010 Elsevier Ltd. All rights reserved.

An optimal control model approach to the design of compensators for simulator delay

NASA Technical Reports Server (NTRS)

Baron, S.; Lancraft, R.; Caglayan, A.

1982-01-01

The effects of display delay on pilot performance and workload and of the design of the filters to ameliorate these effects were investigated. The optimal control model for pilot/vehicle analysis was used both to determine the potential delay effects and to design the compensators. The model was applied to a simple roll tracking task and to a complex hover task. The results confirm that even small delays can degrade performance and impose a workload penalty. A time-domain compensator designed by using the optimal control model directly appears capable of providing extensive compensation for these effects even in multi-input, multi-output problems.

Fast machine-learning online optimization of ultra-cold-atom experiments.

PubMed

Wigley, P B; Everitt, P J; van den Hengel, A; Bastian, J W; Sooriyabandara, M A; McDonald, G D; Hardman, K S; Quinlivan, C D; Manju, P; Kuhn, C C N; Petersen, I R; Luiten, A N; Hope, J J; Robins, N P; Hush, M R

2016-05-16

We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates (BEC). BEC is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled scientific experimentation and observations our 'learner' discovers an optimal evaporation ramp for BEC production. In contrast to previous work, our learner uses a Gaussian process to develop a statistical model of the relationship between the parameters it controls and the quality of the BEC produced. We demonstrate that the Gaussian process machine learner is able to discover a ramp that produces high quality BECs in 10 times fewer iterations than a previously used online optimization technique. Furthermore, we show the internal model developed can be used to determine which parameters are essential in BEC creation and which are unimportant, providing insight into the optimization process of the system.

Fast machine-learning online optimization of ultra-cold-atom experiments

PubMed Central

Wigley, P. B.; Everitt, P. J.; van den Hengel, A.; Bastian, J. W.; Sooriyabandara, M. A.; McDonald, G. D.; Hardman, K. S.; Quinlivan, C. D.; Manju, P.; Kuhn, C. C. N.; Petersen, I. R.; Luiten, A. N.; Hope, J. J.; Robins, N. P.; Hush, M. R.

2016-01-01

We apply an online optimization process based on machine learning to the production of Bose-Einstein condensates (BEC). BEC is typically created with an exponential evaporation ramp that is optimal for ergodic dynamics with two-body s-wave interactions and no other loss rates, but likely sub-optimal for real experiments. Through repeated machine-controlled scientific experimentation and observations our ‘learner’ discovers an optimal evaporation ramp for BEC production. In contrast to previous work, our learner uses a Gaussian process to develop a statistical model of the relationship between the parameters it controls and the quality of the BEC produced. We demonstrate that the Gaussian process machine learner is able to discover a ramp that produces high quality BECs in 10 times fewer iterations than a previously used online optimization technique. Furthermore, we show the internal model developed can be used to determine which parameters are essential in BEC creation and which are unimportant, providing insight into the optimization process of the system. PMID:27180805

Optimal strategy analysis based on robust predictive control for inventory system with random demand

NASA Astrophysics Data System (ADS)

Saputra, Aditya; Widowati, Sutrisno

2017-12-01

In this paper, the optimal strategy for a single product single supplier inventory system with random demand is analyzed by using robust predictive control with additive random parameter. We formulate the dynamical system of this system as a linear state space with additive random parameter. To determine and analyze the optimal strategy for the given inventory system, we use robust predictive control approach which gives the optimal strategy i.e. the optimal product volume that should be purchased from the supplier for each time period so that the expected cost is minimal. A numerical simulation is performed with some generated random inventory data. We simulate in MATLAB software where the inventory level must be controlled as close as possible to a set point decided by us. From the results, robust predictive control model provides the optimal strategy i.e. the optimal product volume that should be purchased and the inventory level was followed the given set point.

Decision-Aiding and Optimization for Vertical Navigation of Long-Haul Aircraft

NASA Technical Reports Server (NTRS)

Patrick, Nicholas J. M.; Sheridan, Thomas B.

1996-01-01

Most decisions made in the cockpit are related to safety, and have therefore been proceduralized in order to reduce risk. There are very few which are made on the basis of a value metric such as economic cost. One which can be shown to be value based, however, is the selection of a flight profile. Fuel consumption and flight time both have a substantial effect on aircraft operating cost, but they cannot be minimized simultaneously. In addition, winds, turbulence, and performance vary widely with altitude and time. These factors make it important and difficult for pilots to (a) evaluate the outcomes associated with a particular trajectory before it is flown and (b) decide among possible trajectories. The two elements of this problem considered here are: (1) determining what constitutes optimality, and (2) finding optimal trajectories. Pilots and dispatchers from major u.s. airlines were surveyed to determine which attributes of the outcome of a flight they considered the most important. Avoiding turbulence-for passenger comfort-topped the list of items which were not safety related. Pilots' decision making about the selection of flight profile on the basis of flight time, fuel burn, and exposure to turbulence was then observed. Of the several behavioral and prescriptive decision models invoked to explain the pilots' choices, utility maximization is shown to best reproduce the pilots' decisions. After considering more traditional methods for optimizing trajectories, a novel method is developed using a genetic algorithm (GA) operating on a discrete representation of the trajectory search space. The representation is a sequence of command altitudes, and was chosen to be compatible with the constraints imposed by Air Traffic Control, and with the training given to pilots. Since trajectory evaluation for the GA is performed holistically, a wide class of objective functions can be optimized easily. Also, using the GA it is possible to compare the costs associated with different airspace design and air traffic management policies. A decision aid is proposed which would combine the pilot's notion of optimality with the GA-based optimization, provide the pilot with a number of alternative pareto-optimal trajectories, and allow him to consider unmodelled attributes and constraints in choosing among them. A solution to the problem of displaying alternatives in a multi-attribute decision space is also presented.

Development of a chromatographic method with multi-criteria decision making design for simultaneous determination of nifedipine and atenolol in content uniformity testing.

PubMed

Ahmed, Sameh; Alqurshi, Abdulmalik; Mohamed, Abdel-Maaboud Ismail

2018-07-01

A new robust and reliable high-performance liquid chromatography (HPLC) method with multi-criteria decision making (MCDM) approach was developed to allow simultaneous quantification of atenolol (ATN) and nifedipine (NFD) in content uniformity testing. Felodipine (FLD) was used as an internal standard (I.S.) in this study. A novel marriage between a new interactive response optimizer and a HPLC method was suggested for multiple response optimizations of target responses. An interactive response optimizer was used as a decision and prediction tool for the optimal settings of target responses, according to specified criteria, based on Derringer's desirability. Four independent variables were considered in this study: Acetonitrile%, buffer pH and concentration along with column temperature. Eight responses were optimized: retention times of ATN, NFD, and FLD, resolutions between ATN/NFD and NFD/FLD, and plate numbers for ATN, NFD, and FLD. Multiple regression analysis was applied in order to scan the influences of the most significant variables for the regression models. The experimental design was set to give minimum retention times, maximum resolution and plate numbers. The interactive response optimizer allowed prediction of optimum conditions according to these criteria with a good composite desirability value of 0.98156. The developed method was validated according to the International Conference on Harmonization (ICH) guidelines with the aid of the experimental design. The developed MCDM-HPLC method showed superior robustness and resolution in short analysis time allowing successful simultaneous content uniformity testing of ATN and NFD in marketed capsules. The current work presents an interactive response optimizer as an efficient platform to optimize, predict responses, and validate HPLC methodology with tolerable design space for assay in quality control laboratories. Copyright © 2018 Elsevier B.V. All rights reserved.

Optimization of a Lunar Pallet Lander Reinforcement Structure Using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Burt, Adam

2014-01-01

In this paper, a unique system level spacecraft design optimization will be presented. A Genetic Algorithm is used to design the global pattern of the reinforcing structure, while a gradient routine is used to adequately stiffen the sub-structure. The system level structural design includes determining the optimal physical location (and number) of reinforcing beams of a lunar pallet lander deck structure. Design of the substructure includes determining placement of secondary stiffeners and the number of rivets required for assembly.. In this optimization, several considerations are taken into account. The primary objective was to raise the primary natural frequencies of the structure such that the Pallet Lander primary structure does not significantly couple with the launch vehicle. A secondary objective is to determine how to properly stiffen the reinforcing beams so that the beam web resists the shear buckling load imparted by the spacecraft components mounted to the pallet lander deck during launch and landing. A third objective is that the calculated stress does not exceed the allowable strength of the material. These design requirements must be met while, minimizing the overall mass of the spacecraft. The final paper will discuss how the optimization was implemented as well as the results. While driven by optimization algorithms, the primary purpose of this effort was to demonstrate the capability of genetic algorithms to enable design automation in the preliminary design cycle. By developing a routine that can automatically generate designs through the use of Finite Element Analysis, considerable design efficiencies, both in time and overall product, can be obtained over more traditional brute force design methods.

[Callose accumulation during treatment of tomato (Lycopersicon esculentum L.) cells with biotic elicitors].

PubMed

Emel'ianov, V I; Kravchuk, Zh N; Poliakovskiĭ, S A; Dmitriev, A P

2008-01-01

Time-course of induced accumulation of callose in tomato cells has been studied. Localization of callose in L. esculenthum cells was investigated by fluorescent microscopy technique, and the optimal time for its determination was found. Callose accumulation in tomato cells treated with different biotic elicitors was determined. Nonlinear dependence between callose accumulation and concentration of chitin oligomers (with 3-5 N-acetylglucosamine fragments) was established. Increasing of callose accumulation in tomato cells was proportional to the increase of concentration ofchitin dimer and chitosan in the culture medium.

Comparison of the Immulite and RIA assay methods for measuring peripheral blood progesterone levels in Greyhound bitches.

PubMed

Chapwanya, A; Clegg, T; Stanley, P; Vaughan, L

2008-09-15

Determination of optimal breeding time in bitches earmarked for single insemination only is based on measurement of peripheral blood serum or plasma progesterone concentration. In this paper a comparison is made between radioimmune assay (RIA) and chemoluminescent assay (Immulite) for determination of P4 concentrations in the bitch. The Immulite assay is shown to be an accurate and reliable method for serum or plasma P4 measurement. It compares favourably with other methods in terms of turn-around time, cost and accessibility for veterinarians in practice.

Optimization of Bioactive Ingredient Extraction from Chinese Herbal Medicine Glycyrrhiza glabra: A Comparative Study of Three Optimization Models

PubMed Central

Li, Xiaohong; Zhang, Yuyan

2018-01-01

The ultraviolet spectrophotometric method is often used for determining the content of glycyrrhizic acid from Chinese herbal medicine Glycyrrhiza glabra. Based on the traditional single variable approach, four extraction parameters of ammonia concentration, ethanol concentration, circumfluence time, and liquid-solid ratio are adopted as the independent extraction variables. In the present work, central composite design of four factors and five levels is applied to design the extraction experiments. Subsequently, the prediction models of response surface methodology, artificial neural networks, and genetic algorithm-artificial neural networks are developed to analyze the obtained experimental data, while the genetic algorithm is utilized to find the optimal extraction parameters for the above well-established models. It is found that the optimization of extraction technology is presented as ammonia concentration 0.595%, ethanol concentration 58.45%, return time 2.5 h, and liquid-solid ratio 11.065 : 1. Under these conditions, the model predictive value is 381.24 mg, the experimental average value is 376.46 mg, and the expectation discrepancy is 4.78 mg. For the first time, a comparative study of these three approaches is conducted for the evaluation and optimization of the effects of the extraction independent variables. Furthermore, it is demonstrated that the combinational method of genetic algorithm and artificial neural networks provides a more reliable and more accurate strategy for design and optimization of glycyrrhizic acid extraction from Glycyrrhiza glabra. PMID:29887907

Optimization of Bioactive Ingredient Extraction from Chinese Herbal Medicine Glycyrrhiza glabra: A Comparative Study of Three Optimization Models.

PubMed

Yu, Li; Jin, Weifeng; Li, Xiaohong; Zhang, Yuyan

2018-01-01

The ultraviolet spectrophotometric method is often used for determining the content of glycyrrhizic acid from Chinese herbal medicine Glycyrrhiza glabra . Based on the traditional single variable approach, four extraction parameters of ammonia concentration, ethanol concentration, circumfluence time, and liquid-solid ratio are adopted as the independent extraction variables. In the present work, central composite design of four factors and five levels is applied to design the extraction experiments. Subsequently, the prediction models of response surface methodology, artificial neural networks, and genetic algorithm-artificial neural networks are developed to analyze the obtained experimental data, while the genetic algorithm is utilized to find the optimal extraction parameters for the above well-established models. It is found that the optimization of extraction technology is presented as ammonia concentration 0.595%, ethanol concentration 58.45%, return time 2.5 h, and liquid-solid ratio 11.065 : 1. Under these conditions, the model predictive value is 381.24 mg, the experimental average value is 376.46 mg, and the expectation discrepancy is 4.78 mg. For the first time, a comparative study of these three approaches is conducted for the evaluation and optimization of the effects of the extraction independent variables. Furthermore, it is demonstrated that the combinational method of genetic algorithm and artificial neural networks provides a more reliable and more accurate strategy for design and optimization of glycyrrhizic acid extraction from Glycyrrhiza glabra .

A novel adaptive needle insertion sequencing for robotic, single needle MR-guided high-dose-rate prostate brachytherapy

NASA Astrophysics Data System (ADS)

Borot de Battisti, M.; de Senneville, B. Denis; Hautvast, G.; Binnekamp, D.; Lagendijk, J. J. W.; Maenhout, M.; Moerland, M. A.

2017-05-01

MR-guided high-dose-rate (HDR) brachytherapy has gained increasing interest as a treatment for patients with localized prostate cancer because of the superior value of MRI for tumor and surrounding tissues localization. To enable needle insertion into the prostate with the patient in the MR bore, a single needle MR-compatible robotic system involving needle-by-needle dose delivery has been developed at our institution. Throughout the intervention, dose delivery may be impaired by: (1) sub-optimal needle positioning caused by e.g. needle bending, (2) intra-operative internal organ motion such as prostate rotations or swelling, or intra-procedural rectum or bladder filling. This may result in failure to reach clinical constraints. To assess the first aforementioned challenge, a recent study from our research group demonstrated that the deposited dose may be greatly improved by real-time adaptive planning with feedback on the actual needle positioning. However, the needle insertion sequence is left to the doctor and therefore, this may result in sub-optimal dose delivery. In this manuscript, a new method is proposed to determine and update automatically the needle insertion sequence. This strategy is based on the determination of the most sensitive needle track. The sensitivity of a needle track is defined as its impact on the dose distribution in case of sub-optimal positioning. A stochastic criterion is thus presented to determine each needle track sensitivity based on needle insertion simulations. To assess the proposed sequencing strategy, HDR prostate brachytherapy was simulated on 11 patients with varying number of needle insertions. Sub-optimal needle positioning was simulated at each insertion (modeled by typical random angulation errors). In 91% of the scenarios, the dose distribution improved when the needle was inserted into the most compared to the least sensitive needle track. The computation time for sequencing was less than 6 s per needle track. The proposed needle insertion sequencing can therefore assist in delivering an optimal dose in HDR prostate brachytherapy.

Demand side management in recycling and electricity retail pricing

NASA Astrophysics Data System (ADS)

Kazan, Osman

This dissertation addresses several problems from the recycling industry and electricity retail market. The first paper addresses a real-life scheduling problem faced by a national industrial recycling company. Based on their practices, a scheduling problem is defined, modeled, analyzed, and a solution is approximated efficiently. The recommended application is tested on the real-life data and randomly generated data. The scheduling improvements and the financial benefits are presented. The second problem is from electricity retail market. There are well-known patterns in daily usage in hours. These patterns change in shape and magnitude by seasons and days of the week. Generation costs are multiple times higher during the peak hours of the day. Yet most consumers purchase electricity at flat rates. This work explores analytic pricing tools to reduce peak load electricity demand for retailers. For that purpose, a nonlinear model that determines optimal hourly prices is established based on two major components: unit generation costs and consumers' utility. Both are analyzed and estimated empirically in the third paper. A pricing model is introduced to maximize the electric retailer's profit. As a result, a closed-form expression for the optimal price vector is obtained. Possible scenarios are evaluated for consumers' utility distribution. For the general case, we provide a numerical solution methodology to obtain the optimal pricing scheme. The models recommended are tested under various scenarios that consider consumer segmentation and multiple pricing policies. The recommended model reduces the peak load significantly in most cases. Several utility companies offer hourly pricing to their customers. They determine prices using historical data of unit electricity cost over time. In this dissertation we develop a nonlinear model that determines optimal hourly prices with parameter estimation. The last paper includes a regression analysis of the unit generation cost function obtained from Independent Service Operators. A consumer experiment is established to replicate the peak load behavior. As a result, consumers' utility function is estimated and optimal retail electricity prices are computed.

Optimization strategy for and structural properties of traffic efficiency under bounded information accessibility

NASA Astrophysics Data System (ADS)

Sanghyun, Ahn; Seungwoong, Ha; Kim, Soo Yong

2016-06-01

A vital challenge for many socioeconomic systems is determining the optimum use of limited information. Traffic systems, wherein the range of resources is limited, are a particularly good example of this challenge. Based on bounded information accessibility in terms of, for example, high costs or technical limitations, we develop a new optimization strategy to improve the efficiency of a traffic system with signals and intersections. Numerous studies, including the study by Chowdery and Schadschneider (whose method we denote by ChSch), have attempted to achieve the maximum vehicle speed or the minimum wait time for a given traffic condition. In this paper, we introduce a modified version of ChSch with an independently functioning, decentralized control system. With the new model, we determine the optimization strategy under bounded information accessibility, which proves the existence of an optimal point for phase transitions in the system. The paper also provides insight that can be applied by traffic engineers to create more efficient traffic systems by analyzing the area and symmetry of local sites. We support our results with a statistical analysis using empirical traffic data from Seoul, Korea.

Optimized ultrasound-assisted emulsification microextraction for simultaneous trace multielement determination of heavy metals in real water samples by ICP-OES.

PubMed

Sereshti, Hassan; Heravi, Yeganeh Entezari; Samadi, Soheila

2012-08-15

Ultrasonic-assisted emulsification microextraction (USAEME) combined with inductively coupled plasma-optical emission spectrometry (ICP-OES) was used for preconcentration and determination of aluminum, bismuth, cadmium, cobalt, copper, iron, gallium, indium, nickel, lead, thallium and zinc in real water samples. Ammonium pyrrolidine dithiocarbamate (APDC) and carbon tetrachloride (CCl(4)) were used as the chelating agent and extraction solvent, respectively. The effective parameters (factors) of the extraction process such as volume of extraction solvent, pH, sonication time, and concentration of chelating agent were optimized by a small central composite design (CCD). The optimum conditions were found to be 98 μL for extraction solvent, 1476 mg L(-1) for chelating agent, 3.8 for pH and 9 min for sonication time. Under the optimal conditions, the limits of detection (LODs) for Al, Bi, Cd, Co, Cu, Fe, Ga, In, Ni, Pb, Tl and Zn were 0.13, 0.48, 0.19, 0.28, 0.29, 0.27, 0.27, 0.38, 0.44, 0.47, 0.52 and 0.17 μg L(-1), respectively. The linear dynamic range (LDR) was 1-1000 μ gL(-1) with determination coefficients of 0.991-0.998. Relative standard deviations (RSDs, C=200 μg L(-1), n=6) were between 1.87%-5.65%. The proposed method was successfully applied to the extraction and determination of heavy metals in real water samples and the satisfactory relative recoveries (90.3%-105.5%) were obtained. Copyright © 2012 Elsevier B.V. All rights reserved.

Dynamic Histogram Analysis To Determine Free Energies and Rates from Biased Simulations.

PubMed

Stelzl, Lukas S; Kells, Adam; Rosta, Edina; Hummer, Gerhard

2017-12-12

We present an algorithm to calculate free energies and rates from molecular simulations on biased potential energy surfaces. As input, it uses the accumulated times spent in each state or bin of a histogram and counts of transitions between them. Optimal unbiased equilibrium free energies for each of the states/bins are then obtained by maximizing the likelihood of a master equation (i.e., first-order kinetic rate model). The resulting free energies also determine the optimal rate coefficients for transitions between the states or bins on the biased potentials. Unbiased rates can be estimated, e.g., by imposing a linear free energy condition in the likelihood maximization. The resulting "dynamic histogram analysis method extended to detailed balance" (DHAMed) builds on the DHAM method. It is also closely related to the transition-based reweighting analysis method (TRAM) and the discrete TRAM (dTRAM). However, in the continuous-time formulation of DHAMed, the detailed balance constraints are more easily accounted for, resulting in compact expressions amenable to efficient numerical treatment. DHAMed produces accurate free energies in cases where the common weighted-histogram analysis method (WHAM) for umbrella sampling fails because of slow dynamics within the windows. Even in the limit of completely uncorrelated data, where WHAM is optimal in the maximum-likelihood sense, DHAMed results are nearly indistinguishable. We illustrate DHAMed with applications to ion channel conduction, RNA duplex formation, α-helix folding, and rate calculations from accelerated molecular dynamics. DHAMed can also be used to construct Markov state models from biased or replica-exchange molecular dynamics simulations. By using binless WHAM formulated as a numerical minimization problem, the bias factors for the individual states can be determined efficiently in a preprocessing step and, if needed, optimized globally afterward.

Comparison between four dissimilar solar panel configurations

NASA Astrophysics Data System (ADS)

Suleiman, K.; Ali, U. A.; Yusuf, Ibrahim; Koko, A. D.; Bala, S. I.

2017-12-01

Several studies on photovoltaic systems focused on how it operates and energy required in operating it. Little attention is paid on its configurations, modeling of mean time to system failure, availability, cost benefit and comparisons of parallel and series-parallel designs. In this research work, four system configurations were studied. Configuration I consists of two sub-components arranged in parallel with 24 V each, configuration II consists of four sub-components arranged logically in parallel with 12 V each, configuration III consists of four sub-components arranged in series-parallel with 8 V each, and configuration IV has six sub-components with 6 V each arranged in series-parallel. Comparative analysis was made using Chapman Kolmogorov's method. The derivation for explicit expression of mean time to system failure, steady state availability and cost benefit analysis were performed, based on the comparison. Ranking method was used to determine the optimal configuration of the systems. The results of analytical and numerical solutions of system availability and mean time to system failure were determined and it was found that configuration I is the optimal configuration.

Efficacy tests and determination of optimal spray timing values to control nantucket pine tip moth - (Lepidoptera: Tortricidae) infestation

Treesearch

John T. Nowak; Christopher J. Fettig; Kenneth W. McCravy; C. Wayne Berisford

2000-01-01

The Nantucket pine tip moth, Rhyaciona frustrana (Comstock), a common regeneration pest of loblolly pine, Pinus taeda L., has been shown to reduce tree volume yields through larval feeding. Chemical applications can be effective in protecting trees from the growth losses associated with this feeding and optimum spray timing values...

Determining Optimal Machine Replacement Events with Periodic Inspection Intervals

DTIC Science & Technology

2013-03-01

10 2.3 Remaining Useful Life Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.4...has some idea of the characteristic reliability inherent to that system. From assembly lines, to computers, to aircraft, quantities such as mean time...to failure, mean time to critical failure, and others have been quantified to a great extent. Further, any entity concerned with cost will also have an

Real-Time Enzyme Kinetics by Quantitative NMR Spectroscopy and Determination of the Michaelis-Menten Constant Using the Lambert-W Function

ERIC Educational Resources Information Center

Her, Cheenou; Alonzo, Aaron P.; Vang, Justin Y.; Torres, Ernesto; Krishnan, V. V.

2015-01-01

Enzyme kinetics is an essential part of a chemistry curriculum, especially for students interested in biomedical research or in health care fields. Though the concept is routinely performed in undergraduate chemistry/biochemistry classrooms using other spectroscopic methods, we provide an optimized approach that uses a real-time monitoring of the…

Firefly

DTIC Science & Technology

2012-05-29

Hunter College has completed work on baseline measurements of relaxation times for pentacene at various temperatures in order to determine optimal...temperatures for measuring relaxation rate as a function of doping. We have also repeated these measurements on pentacene samples at 2 different...P3HT using a time-lag method. 2 Technical Accomplishments This Period Relaxation Measurements on Pentacene . As described initially in the 1Q

Utilizing high-throughput experimentation to enhance specific productivity of an E.coli T7 expression system by phosphate limitation.

PubMed

Huber, Robert; Roth, Simon; Rahmen, Natalie; Büchs, Jochen

2011-03-17

The specific productivity of cultivation processes can be optimized, amongst others, by using genetic engineering of strains, choice of suitable host/vector systems or process optimization (e.g. choosing the right induction time). A further possibility is to reduce biomass buildup in favor of an enhanced product formation, e.g. by limiting secondary substrates in the medium, such as phosphate. However, with conventional techniques (e.g. small scale cultivations in shake flasks), it is very tedious to establish optimal conditions for cell growth and protein expression, as the start of protein expression (induction time) and the degree of phosphate limitation have to be determined in numerous concerted, manually conducted experiments. We investigated the effect of different induction times and a concurrent phosphate limitation on the specific productivity of the T7 expression system E.coli BL21(DE3) pRhotHi-2-EcFbFP, which produces the model fluorescence protein EcFbFP upon induction. Therefore, specific online-monitoring tools for small scale cultivations (RAMOS, BioLector) as well as a novel cultivation platform (Robo-Lector) were used for rapid process optimization. The RAMOS system monitored the oxygen transfer rate in shake flasks, whereas the BioLector device allowed to monitor microbial growth and the production of EcFbFP in microtiter plates. The Robo-Lector is a combination of a BioLector and a pipetting robot and can conduct high-throughput experiments fully automated. By using these tools, it was possible to determine the optimal induction time and to increase the specific productivity for EcFbFP from 22% (for unlimited conditions) to 31% of total protein content of the E.coli cells via a phosphate limitation. The results revealed that a phosphate limitation at the right induction time was suitable to redirect the available cellular resources during cultivation to protein expression rather than in biomass production. To our knowledge, such an effect was shown for the first time for an IPTG-inducible expression system. Finally, this finding and the utilization of the introduced high-throughput experimentation approach could help to find new targets to further enhance the production capacity of recombinant E.coli-strains.

Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques

DOEpatents

Wroblewski, David [Mentor, OH; Katrompas, Alexander M [Concord, OH; Parikh, Neel J [Richmond Heights, OH

2009-09-01

A method and apparatus for optimizing the operation of a power generating plant using artificial intelligence techniques. One or more decisions D are determined for at least one consecutive time increment, where at least one of the decisions D is associated with a discrete variable for the operation of a power plant device in the power generating plant. In an illustrated embodiment, the power plant device is a soot cleaning device associated with a boiler.

Proposed algorithm to improve job shop production scheduling using ant colony optimization method

NASA Astrophysics Data System (ADS)

Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

2017-12-01

This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

Optimal short-range trajectories for helicopters

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

Slater, G.L.; Erzberger, H.

1982-12-01

An optimal flight path algorithm using a simplified altitude state model and a priori climb cruise descent flight profile was developed and applied to determine minimum fuel and minimum cost trajectories for a helicopter flying a fixed range trajectory. In addition, a method was developed for obtaining a performance model in simplified form which is based on standard flight manual data and which is applicable to the computation of optimal trajectories. The entire performance optimization algorithm is simple enough that on line trajectory optimization is feasible with a relatively small computer. The helicopter model used is the Silorsky S-61N. Themore » results show that for this vehicle the optimal flight path and optimal cruise altitude can represent a 10% fuel saving on a minimum fuel trajectory. The optimal trajectories show considerable variability because of helicopter weight, ambient winds, and the relative cost trade off between time and fuel. In general, reasonable variations from the optimal velocities and cruise altitudes do not significantly degrade the optimal cost. For fuel optimal trajectories, the optimum cruise altitude varies from the maximum (12,000 ft) to the minimum (0 ft) depending on helicopter weight.« less

Study of a mixed dispersal population dynamics model

DOE PAGES

Chugunova, Marina; Jadamba, Baasansuren; Kao, Chiu -Yen; ...

2016-08-27

In this study, we consider a mixed dispersal model with periodic and Dirichlet boundary conditions and its corresponding linear eigenvalue problem. This model describes the time evolution of a population which disperses both locally and non-locally. We investigate how long time dynamics depend on the parameter values. Furthermore, we study the minimization of the principal eigenvalue under the constraints that the resource function is bounded from above and below, and with a fixed total integral. Biologically, this minimization problem is motivated by the question of determining the optimal spatial arrangement of favorable and unfavorable regions for the species to diemore » out more slowly or survive more easily. Our numerical simulations indicate that the optimal favorable region tends to be a simply-connected domain. Numerous results are shown to demonstrate various scenarios of optimal favorable regions for periodic and Dirichlet boundary conditions.« less

Analysis of Bioactive Amino Acids from Fish Hydrolysates with a New Bioinformatic Intelligent System Approach.

PubMed

Elaziz, Mohamed Abd; Hemdan, Ahmed Monem; Hassanien, AboulElla; Oliva, Diego; Xiong, Shengwu

2017-09-07

The current economics of the fish protein industry demand rapid, accurate and expressive prediction algorithms at every step of protein production especially with the challenge of global climate change. This help to predict and analyze functional and nutritional quality then consequently control food allergies in hyper allergic patients. As, it is quite expensive and time-consuming to know these concentrations by the lab experimental tests, especially to conduct large-scale projects. Therefore, this paper introduced a new intelligent algorithm using adaptive neuro-fuzzy inference system based on whale optimization algorithm. This algorithm is used to predict the concentration levels of bioactive amino acids in fish protein hydrolysates at different times during the year. The whale optimization algorithm is used to determine the optimal parameters in adaptive neuro-fuzzy inference system. The results of proposed algorithm are compared with others and it is indicated the higher performance of the proposed algorithm.

The Optimal Dose of Nicardipine for Enhancement of Indirect Portography

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

Inoue, Yutaka; Nakamura, Hironobu; Akaji, Hideyo

1998-01-15

Purpose: To determine the optimal dose of nicardipine (NCR) for enhancement of indirect portography. Methods: Forty-eight patients underwent conventional film indirect portography via the superior mesenteric artery (SMA) first without and then with preinjection of 1/64-2 mg of NCR into the SMA. Results: NCR (1/8-2 mg) shortened the arterial phase to 50% and the portal appearance time to 60% of control without reflux of contrast medium into the aorta. Portal enhancement was excellent at doses of 1/32 mg or more. Blood pressures and pulse rate showed no significant change at 1/4 mg or less. Conclusion: NCR (1/8-1/4 mg) into themore » SMA is the optimal dose for achieving sufficient contrast enhancement on indirect portography while reducing the transit time of contrast medium and minimizing effects on the systemic circulation.« less

Ultrasound-assisted temperature-controlled ionic liquid emulsification microextraction coupled with capillary electrophoresis for the determination of parabens in personal care products.

PubMed

Ma, Teng; Li, Zheng; Jia, Qiong; Zhou, Weihong

2016-07-01

We developed a CE and ultrasound-assisted temperature-controlled ionic liquid emulsification microextraction method for the determination of four parabens (methyl paraben, ethyl paraben, propyl paraben, and butyl paraben) in personal care products including mouthwash and toning lotion. In the proposed extraction procedure, ionic liquid (IL, 1-octyl-3-methylimidazolium hexafluorophosphate) was used as extraction solvent, moreover, no disperser solvent was needed. Parameters affecting the extraction efficiency including volume of IL, heating temperature, ultrasonic time, extraction time, sample pH, ionic strength, and centrifugation time were optimized. Under the optimized conditions, the method was found to be linear over the range of 3-500 ng/mL with coefficient of determination (R(2) ) in the range of 0.9990-0.9998. The LODs and LOQs for the four parabens were 0.45-0.72 ng/mL and 1.50-2.40 ng/mL, respectively. Intraday and interday precisions (RSDs, n = 5) were in the range of 5.4-6.8% and 7.0-8.7%, respectively. The recoveries of parabens at different spiked levels ranged from 71.9 to 119.2% with RSDs less than 9.5%. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimal current waveforms for brushless permanent magnet motors

NASA Astrophysics Data System (ADS)

Moehle, Nicholas; Boyd, Stephen

2015-07-01

In this paper, we give energy-optimal current waveforms for a permanent magnet synchronous motor that result in a desired average torque. Our formulation generalises previous work by including a general back-electromotive force (EMF) wave shape, voltage and current limits, an arbitrary phase winding connection, a simple eddy current loss model, and a trade-off between power loss and torque ripple. Determining the optimal current waveforms requires solving a small convex optimisation problem. We show how to use the alternating direction method of multipliers to find the optimal current in milliseconds or hundreds of microseconds, depending on the processor used, which allows the possibility of generating optimal waveforms in real time. This allows us to adapt in real time to changes in the operating requirements or in the model, such as a change in resistance with winding temperature, or even gross changes like the failure of one winding. Suboptimal waveforms are available in tens or hundreds of microseconds, allowing for quick response after abrupt changes in the desired torque. We demonstrate our approach on a simple numerical example, in which we give the optimal waveforms for a motor with a sinusoidal back-EMF, and for a motor with a more complicated, nonsinusoidal waveform, in both the constant-torque region and constant-power region.

Evaluation of the volatile profile of Tuber liyuanum by HS-SPME with GC-MS.

PubMed

Liu, Changjiao; Li, Yu

2017-04-01

The volatile components of Tuber liyuanum were determined by HS-SPME with GC-MS for the first time. The effects of different fibre coating, extraction time, extraction temperature and sample amount were studied to get optimal extraction conditions. The optimal conditions were SPME fibre of Carboxen/PDMS, extraction time of 40 min, extraction temperature of 80 °C, sample amount of 2 g. Under these conditions 57 compounds in volatile of T. liyuanum were detected with a resemblance percentage above 80%. Aldehydes and aromatics were the main chemical families identified. The contribution of 3-Octanone(11.67%), phenylethyl alcohol (10.60%), isopentana (9.29%) and methylbutana (8.06%) for the total volatile profile were more significant in T. liyuanum than other compounds.

Concrete thawing studied by single-point ramped imaging.

PubMed

Prado, P J; Balcom, B J; Beyea, S D; Armstrong, R L; Bremner, T W

1997-12-01

A series of two-dimensional images of proton distribution in a hardened concrete sample has been obtained during the thawing process (from -50 degrees C up to 11 degrees C). The SPRITE sequence is optimal for this study given the characteristic short relaxation times of water in this porous media (T2* < 200 micros and T1 < 3.6 ms). The relaxation parameters of the sample were determined in order to optimize the time efficiency of the sequence, permitting a 4-scan 64 x 64 acquisition in under 3 min. The image acquisition is fast on the time scale of the temperature evolution of the specimen. The frozen water distribution is quantified through a position based study of the image contrast. A multiple point acquisition method is presented and the signal sensitivity improvement is discussed.

Classical Optimal Control for Energy Minimization Based On Diffeomorphic Modulation under Observable-Response-Preserving Homotopy.

PubMed

Soley, Micheline B; Markmann, Andreas; Batista, Victor S

2018-06-12

We introduce the so-called "Classical Optimal Control Optimization" (COCO) method for global energy minimization based on the implementation of the diffeomorphic modulation under observable-response-preserving homotopy (DMORPH) gradient algorithm. A probe particle with time-dependent mass m( t;β) and dipole μ( r, t;β) is evolved classically on the potential energy surface V( r) coupled to an electric field E( t;β), as described by the time-dependent density of states represented on a grid, or otherwise as a linear combination of Gaussians generated by the k-means clustering algorithm. Control parameters β defining m( t;β), μ( r, t;β), and E( t;β) are optimized by following the gradients of the energy with respect to β, adapting them to steer the particle toward the global minimum energy configuration. We find that the resulting COCO algorithm is capable of resolving near-degenerate states separated by large energy barriers and successfully locates the global minima of golf potentials on flat and rugged surfaces, previously explored for testing quantum annealing methodologies and the quantum optimal control optimization (QuOCO) method. Preliminary results show successful energy minimization of multidimensional Lennard-Jones clusters. Beyond the analysis of energy minimization in the specific model systems investigated, we anticipate COCO should be valuable for solving minimization problems in general, including optimization of parameters in applications to machine learning and molecular structure determination.

A method to incorporate leakage and head scatter corrections into a tomotherapy inverse treatment planning algorithm

NASA Astrophysics Data System (ADS)

Holmes, Timothy W.

2001-01-01

A detailed tomotherapy inverse treatment planning method is described which incorporates leakage and head scatter corrections during each iteration of the optimization process, allowing these effects to be directly accounted for in the optimized dose distribution. It is shown that the conventional inverse planning method for optimizing incident intensity can be extended to include a `concurrent' leaf sequencing operation from which the leakage and head scatter corrections are determined. The method is demonstrated using the steepest-descent optimization technique with constant step size and a least-squared error objective. The method was implemented using the MATLAB scientific programming environment and its feasibility demonstrated for 2D test cases simulating treatment delivery using a single coplanar rotation. The results indicate that this modification does not significantly affect convergence of the intensity optimization method when exposure times of individual leaves are stratified to a large number of levels (>100) during leaf sequencing. In general, the addition of aperture dependent corrections, especially `head scatter', reduces incident fluence in local regions of the modulated fan beam, resulting in increased exposure times for individual collimator leaves. These local variations can result in 5% or greater local variation in the optimized dose distribution compared to the uncorrected case. The overall efficiency of the modified intensity optimization algorithm is comparable to that of the original unmodified case.

Optimizing separate phase light hydrocarbon recovery from contaminated unconfined aquifers

NASA Astrophysics Data System (ADS)

Cooper, Grant S.; Peralta, Richard C.; Kaluarachchi, Jagath J.

A modeling approach is presented that optimizes separate phase recovery of light non-aqueous phase liquids (LNAPL) for a single dual-extraction well in a homogeneous, isotropic unconfined aquifer. A simulation/regression/optimization (S/R/O) model is developed to predict, analyze, and optimize the oil recovery process. The approach combines detailed simulation, nonlinear regression, and optimization. The S/R/O model utilizes nonlinear regression equations describing system response to time-varying water pumping and oil skimming. Regression equations are developed for residual oil volume and free oil volume. The S/R/O model determines optimized time-varying (stepwise) pumping rates which minimize residual oil volume and maximize free oil recovery while causing free oil volume to decrease a specified amount. This S/R/O modeling approach implicitly immobilizes the free product plume by reversing the water table gradient while achieving containment. Application to a simple representative problem illustrates the S/R/O model utility for problem analysis and remediation design. When compared with the best steady pumping strategies, the optimal stepwise pumping strategy improves free oil recovery by 11.5% and reduces the amount of residual oil left in the system due to pumping by 15%. The S/R/O model approach offers promise for enhancing the design of free phase LNAPL recovery systems and to help in making cost-effective operation and management decisions for hydrogeologists, engineers, and regulators.

Comparison of Genetic Algorithm and Hill Climbing for Shortest Path Optimization Mapping

NASA Astrophysics Data System (ADS)

Fronita, Mona; Gernowo, Rahmat; Gunawan, Vincencius

2018-02-01

Traveling Salesman Problem (TSP) is an optimization to find the shortest path to reach several destinations in one trip without passing through the same city and back again to the early departure city, the process is applied to the delivery systems. This comparison is done using two methods, namely optimization genetic algorithm and hill climbing. Hill Climbing works by directly selecting a new path that is exchanged with the neighbour's to get the track distance smaller than the previous track, without testing. Genetic algorithms depend on the input parameters, they are the number of population, the probability of crossover, mutation probability and the number of generations. To simplify the process of determining the shortest path supported by the development of software that uses the google map API. Tests carried out as much as 20 times with the number of city 8, 16, 24 and 32 to see which method is optimal in terms of distance and time computation. Based on experiments conducted with a number of cities 3, 4, 5 and 6 producing the same value and optimal distance for the genetic algorithm and hill climbing, the value of this distance begins to differ with the number of city 7. The overall results shows that these tests, hill climbing are more optimal to number of small cities and the number of cities over 30 optimized using genetic algorithms.

Optimal Observations for Variational Data Assimilation

NASA Technical Reports Server (NTRS)

Koehl, Armin; Stammer, Detlef

2003-01-01

An important aspect of Ocean state estimation is the design of an observing system that allows the efficient study of climate aspects in the ocean. A solution of the design problem is presented here in terms of optimal observations that emerge as nondimensionalized singular vectors of the modified data resolution matrix. The actual computation is feasible only for scalar quantities in the limit of large observational errors. In the framework of a lo resolution North Atlantic primitive equation model it is demonstrated that such optimal observations when applied to determining the strength of the volume and heat transport across the Greenland-Scotland ridge, perform significantly better than traditional section data. On seasonal to inter-annual time-scales optimal observations are located primarily along the continental shelf and information about heat-transport, wind stress and stratification is being communicated via boundary waves and advective processes. On time-scales of about a month, sea surface height observations appear to be more efficient in reconstructing the cross-ridge heat transport than hydrographic observations. Optimal observations also provide a tool for understanding how the ocean state is effected by anomalies of integral quantities such as meridional heat transport.

Optimization strategies for radiation induced grafting of 4-vinylpyridine onto poly(ethylene-co-tetraflouroethene) film using Box-Behnken design

NASA Astrophysics Data System (ADS)

Mahmoud Nasef, Mohamed; Shamsaei, Ezzatollah; Ghassemi, Payman; Ahmed Aly, Amgad; Hamid Yahaya, Abdul

2012-04-01

The radiation induced grafting of 4-vinylpyridine (4-VP) onto poly(ethylene-co-tetrafluoroethene) (ETFE) was optimized using the Box-Behnken factorial design available in the response surface method (RSM). The optimized grafting parameters; absorbed dose, monomer concentration, grafting time and reaction temperature were varied in four levels to quantify their effect on the grafting yield (GY). The validity of the statistical model was supported by the small deviation between the predicted (GY=61%) and experimental (GY=57%) values. The optimum conditions for enhancing GY were determined at the following values: monomer concentration of 48 vol%, absorbed dose of 64 kGy, reaction time of 4 h and temperature of 68 °C. A comparison was made between the optimization model developed for the present grafting system and that for grafting of 1-vinylimidazole (1-VIm) onto ETFE to confirm the validly and reliability of the Box-Behnken for the optimization of various radiation induced grafting reactions. Fourier transform infrared (FTIR), thermogravimetric analysis (TGA) and X-ray diffraction (XRD) were used to investigate the properties of the obtained films and provide evidence for grafting.

Numerical optimization of actuator trajectories for ITER hybrid scenario profile evolution

NASA Astrophysics Data System (ADS)

van Dongen, J.; Felici, F.; Hogeweij, G. M. D.; Geelen, P.; Maljaars, E.

2014-12-01

Optimal actuator trajectories for an ITER hybrid scenario ramp-up are computed using a numerical optimization method. For both L-mode and H-mode scenarios, the time trajectory of plasma current, EC heating and current drive distribution is determined that minimizes a chosen cost function, while satisfying constraints. The cost function is formulated to reflect two desired properties of the plasma q profile at the end of the ramp-up. The first objective is to maximize the ITG turbulence threshold by maximizing the volume-averaged s/q ratio. The second objective is to achieve a stationary q profile by having a flat loop voltage profile. Actuator and physics-derived constraints are included, imposing limits on plasma current, ramp rates, internal inductance and q profile. This numerical method uses the fast control-oriented plasma profile evolution code RAPTOR, which is successfully benchmarked against more complete CRONOS simulations for L-mode and H-mode mode ITER hybrid scenarios. It is shown that the optimized trajectories computed using RAPTOR also result in an improved ramp-up scenario for CRONOS simulations using the same input trajectories. Furthermore, the optimal trajectories are shown to vary depending on the precise timing of the L-H transition.

Simulation-based planning for theater air warfare

NASA Astrophysics Data System (ADS)

Popken, Douglas A.; Cox, Louis A., Jr.

2004-08-01

Planning for Theatre Air Warfare can be represented as a hierarchy of decisions. At the top level, surviving airframes must be assigned to roles (e.g., Air Defense, Counter Air, Close Air Support, and AAF Suppression) in each time period in response to changing enemy air defense capabilities, remaining targets, and roles of opposing aircraft. At the middle level, aircraft are allocated to specific targets to support their assigned roles. At the lowest level, routing and engagement decisions are made for individual missions. The decisions at each level form a set of time-sequenced Courses of Action taken by opposing forces. This paper introduces a set of simulation-based optimization heuristics operating within this planning hierarchy to optimize allocations of aircraft. The algorithms estimate distributions for stochastic outcomes of the pairs of Red/Blue decisions. Rather than using traditional stochastic dynamic programming to determine optimal strategies, we use an innovative combination of heuristics, simulation-optimization, and mathematical programming. Blue decisions are guided by a stochastic hill-climbing search algorithm while Red decisions are found by optimizing over a continuous representation of the decision space. Stochastic outcomes are then provided by fast, Lanchester-type attrition simulations. This paper summarizes preliminary results from top and middle level models.

Enzymatic hydrolysis of pretreated Alfa fibers (Stipa tenacissima) using β-d-glucosidase and xylanase of Talaromyces thermophilus from solid-state fermentation.

PubMed

Mallek-Fakhfakh, Hanen; Fakhfakh, Jawhar; Walha, Kamel; Hassairi, Hajer; Gargouri, Ali; Belghith, Hafedh

2017-10-01

This work aims at realizing an optimal hydrolysis of pretreated Alfa fibers (Stipa tenacissima) through the use of enzymes produced from Talaromyces thermophilus AX4, namely β-d-glucosidase and xylanase, by a solid state fermentation process of an agro-industrial waste (wheat bran supplemented with lactose). The carbon source was firstly selected and the optimal values of three other parameters were determined: substrate loading (10g), moisture content (85%) and production time (10days); which led to an optimized enzymatic juice. The outcome was then supplemented with cellulases of T. reesei and used to optimize the enzymatic saccharification of alkali-pretreated Alfa fibers (PAF). The maximum saccharification yield of 83.23% was achieved under optimized conditions (substrate concentration 3.7% (w/v), time 144h and enzyme loading of 0.8 FPU, 15U CMCase, 60U β-d-glucosidase and 125U xylanase).The structural modification of PAF due to enzymatic saccharification was supported by the changes of morphologic and chemical composition observed through macroscopic representation, FTIR and X-Ray analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimal investment in a portfolio of HIV prevention programs.

PubMed

Zaric, G S; Brandeau, M L

2001-01-01

In this article, the authors determine the optimal allocation of HIV prevention funds and investigate the impact of different allocation methods on health outcomes. The authors present a resource allocation model that can be used to determine the allocation of HIV prevention funds that maximizes quality-adjusted life years (or life years) gained or HIV infections averted in a population over a specified time horizon. They apply the model to determine the allocation of a limited budget among 3 types of HIV prevention programs in a population of injection drug users and nonusers: needle exchange programs, methadone maintenance treatment, and condom availability programs. For each prevention program, the authors estimate a production function that relates the amount invested to the associated change in risky behavior. The authors determine the optimal allocation of funds for both objective functions for a high-prevalence population and a low-prevalence population. They also consider the allocation of funds under several common rules of thumb that are used to allocate HIV prevention resources. It is shown that simpler allocation methods (e.g., allocation based on HIV incidence or notions of equity among population groups) may lead to alloctions that do not yield the maximum health benefit. The optimal allocation of HIV prevention funds in a population depends on HIV prevalence and incidence, the objective function, the production functions for the prevention programs, and other factors. Consideration of cost, equity, and social and political norms may be important when allocating HIV prevention funds. The model presented in this article can help decision makers determine the health consequences of different allocations of funds.

Optimization of differentiation time of mesenchymal-stem-cell to tenocyte under a cyclic stretching with a microgrooved culture membrane and selected measurement cells.

PubMed

Morita, Yasuyuki; Yamashita, Takahiro; Toku, Toku; Ju, Yang

2018-01-01

There is a need for efficient stem cell-to-tenocyte differentiation techniques for tendon tissue engineering. More than 1 week is required for tenogenic differentiation with chemical stimuli, including co-culturing. Research has begun to examine the utility of mechanical stimuli, which reduces the differentiation time to several days. However, the precise length of time required to differentiate human bone marrow-derived mesenchymal stem cells (hBMSCs) into tenocytes has not been clarified. Understanding the precise time required is important for future tissue engineering projects. Therefore, in this study, a method was developed to more precisely determine the length of time required to differentiate hBMSCs into tenocytes with cyclic stretching stimulus. First, it had to be determined how stretching stimulation affected the cells. Microgrooved culture membranes were used to suppress cell orientation behavior. Then, only cells oriented parallel to the microgrooves were selected and evaluated for protein synthesis levels for differentiation. The results revealed that growing cells on the microgrooved membrane and selecting optimally-oriented cells for measurement improved the accuracy of the differentiation evaluation, and that hBMSCs differentiated into tenocytes in approximately 10 h. The differentiation time corresponded to the time required for cellular cytoskeleton reorganization and cellular morphology alterations. This suggests that cells, when subjected to mechanical stimulus, secrete mRNAs and proteins for both cytoskeleton reorganization and differentiation.

Design of experiments to optimize an in vitro cast to predict human nasal drug deposition.

PubMed

Shah, Samir A; Dickens, Colin J; Ward, David J; Banaszek, Anna A; George, Chris; Horodnik, Walter

2014-02-01

Previous studies showed nasal spray in vitro tests cannot predict in vivo deposition, pharmacokinetics, or pharmacodynamics. This challenge makes it difficult to assess deposition achieved with new technologies delivering to the therapeutically beneficial posterior nasal cavity. In this study, we determined best parameters for using a regionally divided nasal cast to predict deposition. Our study used a model suspension and a design of experiments to produce repeatable deposition results that mimic nasal deposition patterns of nasal suspensions from the literature. The seven-section (the nozzle locator, nasal vestibule, front turbinate, rear turbinate, olfactory region, nasopharynx, and throat filter) nylon nasal cast was based on computed tomography images of healthy humans. It was coated with a glycerol/Brij-35 solution to mimic mucus. After assembling and orienting, airflow was applied and nasal spray containing a model suspension was sprayed. After disassembling the cast, drug depositing in each section was assayed by HPLC. The success criteria for optimal settings were based on nine in vivo studies in the literature. The design of experiments included exploratory and half factorial screening experiments to identify variables affecting deposition (angles, airflow, and airflow time), optimization experiments, and then repeatability and reproducibility experiments. We found tilt angle and airflow time after actuation affected deposition the most. The optimized settings were flow rate of 16 L/min, postactuation flow time of 12 sec, a tilt angle of 23°, nozzle angles of 0°, and actuation speed of 5 cm/sec. Neither cast nor operator caused significant variation of results. We determined cast parameters to produce results resembling suspension nasal sprays in the literature. The results were repeatable and unaffected by operator or cast. These nasal spray parameters could be used to assess deposition from new devices or formulations. For human deposition studies using radiolabeled formulations, this cast could show that radiolabel deposition represents drug deposition. Our methods could also be used to optimize settings for other casts.

Study of genetic direct search algorithms for function optimization

NASA Technical Reports Server (NTRS)

Zeigler, B. P.

1974-01-01

The results are presented of a study to determine the performance of genetic direct search algorithms in solving function optimization problems arising in the optimal and adaptive control areas. The findings indicate that: (1) genetic algorithms can outperform standard algorithms in multimodal and/or noisy optimization situations, but suffer from lack of gradient exploitation facilities when gradient information can be utilized to guide the search. (2) For large populations, or low dimensional function spaces, mutation is a sufficient operator. However for small populations or high dimensional functions, crossover applied in about equal frequency with mutation is an optimum combination. (3) Complexity, in terms of storage space and running time, is significantly increased when population size is increased or the inversion operator, or the second level adaptation routine is added to the basic structure.

Optimal control of multiplicative control systems arising from cancer therapy

NASA Technical Reports Server (NTRS)

Bahrami, K.; Kim, M.

1975-01-01

This study deals with ways of curtailing the rapid growth of cancer cell populations. The performance functional that measures the size of the population at the terminal time as well as the control effort is devised. With use of the discrete maximum principle, the Hamiltonian for this problem is determined and the condition for optimal solutions are developed. The optimal strategy is shown to be a bang-bang control. It is shown that the optimal control for this problem must be on the vertices of an N-dimensional cube contained in the N-dimensional Euclidean space. An algorithm for obtaining a local minimum of the performance function in an orderly fashion is developed. Application of the algorithm to the design of antitumor drug and X-irradiation schedule is discussed.

Efficiency of operation of wind turbine rotors optimized by the Glauert and Betz methods

NASA Astrophysics Data System (ADS)

Okulov, V. L.; Mikkelsen, R.; Litvinov, I. V.; Naumov, I. V.

2015-11-01

The models of two types of rotors with blades constructed using different optimization methods are compared experimentally. In the first case, the Glauert optimization by the pulsed method is used, which is applied independently for each individual blade cross section. This method remains the main approach in designing rotors of various duties. The construction of the other rotor is based on the Betz idea about optimization of rotors by determining a special distribution of circulation over the blade, which ensures the helical structure of the wake behind the rotor. It is established for the first time as a result of direct experimental comparison that the rotor constructed using the Betz method makes it possible to extract more kinetic energy from the homogeneous incoming flow.

Optimization of groundwater artificial recharge systems using a genetic algorithm: a case study in Beijing, China

NASA Astrophysics Data System (ADS)

Hao, Qichen; Shao, Jingli; Cui, Yali; Zhang, Qiulan; Huang, Linxian

2018-05-01

An optimization approach is used for the operation of groundwater artificial recharge systems in an alluvial fan in Beijing, China. The optimization model incorporates a transient groundwater flow model, which allows for simulation of the groundwater response to artificial recharge. The facilities' operation with regard to recharge rates is formulated as a nonlinear programming problem to maximize the volume of surface water recharged into the aquifers under specific constraints. This optimization problem is solved by the parallel genetic algorithm (PGA) based on OpenMP, which could substantially reduce the computation time. To solve the PGA with constraints, the multiplicative penalty method is applied. In addition, the facilities' locations are implicitly determined on the basis of the results of the recharge-rate optimizations. Two scenarios are optimized and the optimal results indicate that the amount of water recharged into the aquifers will increase without exceeding the upper limits of the groundwater levels. Optimal operation of this artificial recharge system can also contribute to the more effective recovery of the groundwater storage capacity.

A study of the influence of the sun on optimal two-impulse Earth-to-Moon trajectories with moderate time of flight in the three-body and four-body models

NASA Astrophysics Data System (ADS)

Filho, Luiz Arthur Gagg; da Silva Fernandes, Sandro

2017-05-01

In this work, a study about the influence of the Sun on optimal two-impulse Earth-to-Moon trajectories for interior transfers with moderate time of flight is presented considering the three-body and the four-body models. The optimization criterion is the total characteristic velocity which represents the fuel consumption of an infinite thrust propulsion system. The optimization problem has been formulated using the classic planar circular restricted three-body problem (PCR3BP) and the planar bi-circular restricted four-body problem (PBR4BP), and, it consists of transferring a spacecraft from a circular low Earth orbit (LEO) to a circular low Moon orbit (LMO) with minimum fuel consumption. The Sequential Gradient Restoration Algorithm (SGRA) is applied to determine the optimal solutions. Numerical results are presented for several final altitudes of a clockwise or a counterclockwise circular low Moon orbit considering a specified altitude of a counterclockwise circular low Earth orbit. Two types of analysis are performed: in the first one, the initial position of the Sun is taken as a parameter and the major parameters describing the optimal trajectories are obtained by solving an optimization problem of one degree of freedom. In the second analysis, an optimization problem with two degrees of freedom is considered and the initial position of the Sun is taken as an additional unknown.

Design and Analysis of Optimal Ascent Trajectories for Stratospheric Airships

NASA Astrophysics Data System (ADS)

Mueller, Joseph Bernard

Stratospheric airships are lighter-than-air vehicles that have the potential to provide a long-duration airborne presence at altitudes of 18-22 km. Designed to operate on solar power in the calm portion of the lower stratosphere and above all regulated air traffic and cloud cover, these vehicles represent an emerging platform that resides between conventional aircraft and satellites. A particular challenge for airship operation is the planning of ascent trajectories, as the slow moving vehicle must traverse the high wind region of the jet stream. Due to large changes in wind speed and direction across altitude and the susceptibility of airship motion to wind, the trajectory must be carefully planned, preferably optimized, in order to ensure that the desired station be reached within acceptable performance bounds of flight time and energy consumption. This thesis develops optimal ascent trajectories for stratospheric airships, examines the structure and sensitivity of these solutions, and presents a strategy for onboard guidance. Optimal ascent trajectories are developed that utilize wind energy to achieve minimum-time and minimum-energy flights. The airship is represented by a three-dimensional point mass model, and the equations of motion include aerodynamic lift and drag, vectored thrust, added mass effects, and accelerations due to mass flow rate, wind rates, and Earth rotation. A representative wind profile is developed based on historical meteorological data and measurements. Trajectory optimization is performed by first defining an optimal control problem with both terminal and path constraints, then using direct transcription to develop an approximate nonlinear parameter optimization problem of finite dimension. Optimal ascent trajectories are determined using SNOPT for a variety of upwind, downwind, and crosswind launch locations. Results of extensive optimization solutions illustrate definitive patterns in the ascent path for minimum time flights across varying launch locations, and show that significant energy savings can be realized with minimum-energy flights, compared to minimum-time time flights, given small increases in flight time. The performance of the optimal trajectories are then studied with respect to solar energy production during ascent, as well as sensitivity of the solutions to small changes in drag coefficient and wind model parameters. Results of solar power model simulations indicate that solar energy is sufficient to power ascent flights, but that significant energy loss can occur for certain types of trajectories. Sensitivity to the drag and wind model is approximated through numerical simulations, showing that optimal solutions change gradually with respect to changing wind and drag parameters and providing deeper insight into the characteristics of optimal airship flights. Finally, alternative methods are developed to generate near-optimal ascent trajectories in a manner suitable for onboard implementation. The structures and characteristics of previously developed minimum-time and minimum-energy ascent trajectories are used to construct simplified trajectory models, which are efficiently solved in a smaller numerical optimization problem. Comparison of these alternative solutions to the original SNOPT solutions show excellent agreement, suggesting the alternate formulations are an effective means to develop near-optimal solutions in an onboard setting.

Aerodynamic Shape Optimization Using Hybridized Differential Evolution

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2003-01-01

An aerodynamic shape optimization method that uses an evolutionary algorithm known at Differential Evolution (DE) in conjunction with various hybridization strategies is described. DE is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Various hybridization strategies for DE are explored, including the use of neural networks as well as traditional local search methods. A Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the hybrid DE optimizer. The method is implemented on distributed parallel computers so that new designs can be obtained within reasonable turnaround times. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. (The final paper will include at least one other aerodynamic design application). The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated.

Implementation and on-sky results of an optimal wavefront controller for the MMT NGS adaptive optics system

NASA Astrophysics Data System (ADS)

Powell, Keith B.; Vaitheeswaran, Vidhya

2010-07-01

The MMT observatory has recently implemented and tested an optimal wavefront controller for the NGS adaptive optics system. Open loop atmospheric data collected at the telescope is used as the input to a MATLAB based analytical model. The model uses nonlinear constrained minimization to determine controller gains and optimize the system performance. The real-time controller performing the adaptive optics close loop operation is implemented on a dedicated high performance PC based quad core server. The controller algorithm is written in C and uses the GNU scientific library for linear algebra. Tests at the MMT confirmed the optimal controller significantly reduced the residual RMS wavefront compared with the previous controller. Significant reductions in image FWHM and increased peak intensities were obtained in J, H and K-bands. The optimal PID controller is now operating as the baseline wavefront controller for the MMT NGS-AO system.

Optimal groundwater remediation design of pump and treat systems via a simulation-optimization approach and firefly algorithm

NASA Astrophysics Data System (ADS)

Javad Kazemzadeh-Parsi, Mohammad; Daneshmand, Farhang; Ahmadfard, Mohammad Amin; Adamowski, Jan; Martel, Richard

2015-01-01

In the present study, an optimization approach based on the firefly algorithm (FA) is combined with a finite element simulation method (FEM) to determine the optimum design of pump and treat remediation systems. Three multi-objective functions in which pumping rate and clean-up time are design variables are considered and the proposed FA-FEM model is used to minimize operating costs, total pumping volumes and total pumping rates in three scenarios while meeting water quality requirements. The groundwater lift and contaminant concentration are also minimized through the optimization process. The obtained results show the applicability of the FA in conjunction with the FEM for the optimal design of groundwater remediation systems. The performance of the FA is also compared with the genetic algorithm (GA) and the FA is found to have a better convergence rate than the GA.

Determination of nitrate esters in water samples Comparison of efficiency of solid-phase extraction and solid-phase microextraction.

PubMed

Jezová, Vera; Skládal, Jan; Eisner, Ales; Bajerová, Petra; Ventura, Karel

2007-12-07

This paper deals with comparison of efficiency of extraction techniques (solid-phase extraction, SPE and solid-phase microextraction, SPME) used for extraction of nitrate esters (ethyleneglycoldinitrate, EGDN and nitroglycerin, NG), representing the first step of the method of quantitative determination of trace concentrations of nitrate esters in water samples. EGDN and NG are subsequently determined by means of high-performance liquid chromatography with ultraviolet detection (HPLC-UV). Optimization of SPE and SPME conditions was carried out using model water samples. Seven SPE cartridges were tested and the conditions were optimized (type of sorbent, type and volume of solvent to be used as eluent). For both nitrate esters the limit of detection (LOD) and the limit of quantification (LOQ) obtained using SPE/HPLC-UV were 0.23 microg mL(-1) and 0.70 microg mL(-1), respectively. Optimization of SPME conditions: type of SPME fibre (four fibres were tested), type and time of sorption/desorption, temperature of sorption. PDMS/DVB (polydimethylsiloxane/divinylbenzene) fibre coating proved to be suitable for extraction of EGDN and NG. For this fibre the LOD and the LOQ for both nitrate esters were 0.16 microg mL(-1) and 0.50 microg mL(-1), respectively. Optimized methods SPE/HPLC-UV and SPME/HPLC-UV were then used for quantitative determination of nitrate esters content in real water samples from the production of EGDN and NG.

Noninvasive, automatic optimization strategy in cardiac resynchronization therapy.

PubMed

Reumann, Matthias; Osswald, Brigitte; Doessel, Olaf

2007-07-01

Optimization of cardiac resynchronization therapy (CRT) is still unsolved. It has been shown that optimal electrode position,atrioventricular (AV) and interventricular (VV) delays improve the success of CRT and reduce the number of non-responders. However, no automatic, noninvasive optimization strategy exists to date. Cardiac resynchronization therapy was simulated on the Visible Man and a patient data-set including fiber orientation and ventricular heterogeneity. A cellular automaton was used for fast computation of ventricular excitation. An AV block and a left bundle branch block were simulated with 100%, 80% and 60% interventricular conduction velocity. A right apical and 12 left ventricular lead positions were set. Sequential optimization and optimization with the downhill simplex algorithm (DSA) were carried out. The minimal error between isochrones of the physiologic excitation and the therapy was computed automatically and leads to an optimal lead position and timing. Up to 1512 simulations were carried out per pathology per patient. One simulation took 4 minutes on an Apple Macintosh 2 GHz PowerPC G5. For each electrode pair an optimal pacemaker delay was found. The DSA reduced the number of simulations by an order of magnitude and the AV-delay and VV - delay were determined with a much higher resolution. The findings are well comparable with clinical studies. The presented computer model of CRT automatically evaluates an optimal lead position and AV-delay and VV-delay, which can be used to noninvasively plan an optimal therapy for an individual patient. The application of the DSA reduces the simulation time so that the strategy is suitable for pre-operative planning in clinical routine. Future work will focus on clinical evaluation of the computer models and integration of patient data for individualized therapy planning and optimization.

BP-ANN for Fitting the Temperature-Germination Model and Its Application in Predicting Sowing Time and Region for Bermudagrass

PubMed Central

Pi, Erxu; Mantri, Nitin; Ngai, Sai Ming; Lu, Hongfei; Du, Liqun

2013-01-01

Temperature is one of the most significant environmental factors that affects germination of grass seeds. Reliable prediction of the optimal temperature for seed germination is crucial for determining the suitable regions and favorable sowing timing for turf grass cultivation. In this study, a back-propagation-artificial-neural-network-aided dual quintic equation (BP-ANN-QE) model was developed to improve the prediction of the optimal temperature for seed germination. This BP-ANN-QE model was used to determine optimal sowing times and suitable regions for three Cynodon dactylon cultivars (C. dactylon, ‘Savannah’ and ‘Princess VII’). Prediction of the optimal temperature for these seeds was based on comprehensive germination tests using 36 day/night (high/low) temperature regimes (both ranging from 5/5 to 40/40°C with 5°C increments). Seed germination data from these temperature regimes were used to construct temperature-germination correlation models for estimating germination percentage with confidence intervals. Our tests revealed that the optimal high/low temperature regimes required for all the three bermudagrass cultivars are 30/5, 30/10, 35/5, 35/10, 35/15, 35/20, 40/15 and 40/20°C; constant temperatures ranging from 5 to 40°C inhibited the germination of all three cultivars. While comparing different simulating methods, including DQEM, Bisquare ANN-QE, and BP-ANN-QE in establishing temperature based germination percentage rules, we found that the R2 values of germination prediction function could be significantly improved from about 0.6940–0.8177 (DQEM approach) to 0.9439–0.9813 (BP-ANN-QE). These results indicated that our BP-ANN-QE model has better performance than the rests of the compared models. Furthermore, data of the national temperature grids generated from monthly-average temperature for 25 years were fit into these functions and we were able to map the germination percentage of these C. dactylon cultivars in the national scale of China, and suggested the optimum sowing regions and times for them. PMID:24349278

A decision support system for real-time hydropower scheduling in a competitive power market environment

NASA Astrophysics Data System (ADS)

Shawwash, Ziad Khaled Elias

2000-10-01

The electricity supply market is rapidly changing from a monopolistic to a competitive environment. Being able to operate their system of reservoirs and generating facilities to get maximum benefits out of existing assets and resources is important to the British Columbia Hydro Authority (B.C. Hydro). A decision support system has been developed to help B.C. Hydro operate their system in an optimal way. The system is operational and is one of the tools that are currently used by the B.C. Hydro system operations engineers to determine optimal schedules that meet the hourly domestic load and also maximize the value B.C. Hydro obtains from spot transactions in the Western U.S. and Alberta electricity markets. This dissertation describes the development and implementation of the decision support system in production mode. The decision support system consists of six components: the input data preparation routines, the graphical user interface (GUI), the communication protocols, the hydraulic simulation model, the optimization model, and the results display software. A major part of this work involved the development and implementation of a practical and detailed large-scale optimization model that determines the optimal tradeoff between the long-term value of water and the returns from spot trading transactions in real-time operations. The postmortem-testing phase showed that the gains in value from using the model accounted for 0.25% to 1.0% of the revenues obtained. The financial returns from using the decision support system greatly outweigh the costs of building it. Other benefits are the savings in the time needed to prepare the generation and trading schedules. The system operations engineers now can use the time saved to focus on other important aspects of their job. The operators are currently experimenting with the system in production mode, and are gradually gaining confidence that the advice it provides is accurate, reliable and sensible. The main lesson learned from developing and implementing the system was that there is no alternative to working very closely with the intended end-users of the system, and with the people who have deep knowledge, experience and understanding of how the system is and should be operated.

Time-Dependent Computed Tomographic Perfusion Thresholds for Patients With Acute Ischemic Stroke.

PubMed

d'Esterre, Christopher D; Boesen, Mari E; Ahn, Seong Hwan; Pordeli, Pooneh; Najm, Mohamed; Minhas, Priyanka; Davari, Paniz; Fainardi, Enrico; Rubiera, Marta; Khaw, Alexander V; Zini, Andrea; Frayne, Richard; Hill, Michael D; Demchuk, Andrew M; Sajobi, Tolulope T; Forkert, Nils D; Goyal, Mayank; Lee, Ting Y; Menon, Bijoy K

2015-12-01

Among patients with acute ischemic stroke, we determine computed tomographic perfusion (CTP) thresholds associated with follow-up infarction at different stroke onset-to-CTP and CTP-to-reperfusion times. Acute ischemic stroke patients with occlusion on computed tomographic angiography were acutely imaged with CTP. Noncontrast computed tomography and magnectic resonance diffusion-weighted imaging between 24 and 48 hours were used to delineate follow-up infarction. Reperfusion was assessed on conventional angiogram or 4-hour repeat computed tomographic angiography. Tmax, cerebral blood flow, and cerebral blood volume derived from delay-insensitive CTP postprocessing were analyzed using receiver-operator characteristic curves to derive optimal thresholds for combined patient data (pooled analysis) and individual patients (patient-level analysis) based on time from stroke onset-to-CTP and CTP-to-reperfusion. One-way ANOVA and locally weighted scatterplot smoothing regression was used to test whether the derived optimal CTP thresholds were different by time. One hundred and thirty-two patients were included. Tmax thresholds of >16.2 and >15.8 s and absolute cerebral blood flow thresholds of <8.9 and <7.4 mL·min(-1)·100 g(-1) were associated with infarct if reperfused <90 min from CTP with onset <180 min. The discriminative ability of cerebral blood volume was modest. No statistically significant relationship was noted between stroke onset-to-CTP time and the optimal CTP thresholds for all parameters based on discrete or continuous time analysis (P>0.05). A statistically significant relationship existed between CTP-to-reperfusion time and the optimal thresholds for cerebral blood flow (P<0.001; r=0.59 and 0.77 for gray and white matter, respectively) and Tmax (P<0.001; r=-0.68 and -0.60 for gray and white matter, respectively) parameters. Optimal CTP thresholds associated with follow-up infarction depend on time from imaging to reperfusion. © 2015 American Heart Association, Inc.

Optimization of fixed-range trajectories for supersonic transport aircraft

NASA Astrophysics Data System (ADS)

Windhorst, Robert Dennis

1999-11-01

This thesis develops near-optimal guidance laws that generate minimum fuel, time, or direct operating cost fixed-range trajectories for supersonic transport aircraft. The approach uses singular perturbation techniques to time-scale de-couple the equations of motion into three sets of dynamics, two of which are analyzed in the main body of this thesis and one of which is analyzed in the Appendix. The two-point-boundary-value-problems obtained by application of the maximum principle to the dynamic systems are solved using the method of matched asymptotic expansions. Finally, the two solutions are combined using the matching principle and an additive composition rule to form a uniformly valid approximation of the full fixed-range trajectory. The approach is used on two different time-scale formulations. The first holds weight constant, and the second allows weight and range dynamics to propagate on the same time-scale. Solutions for the first formulation are only carried out to zero order in the small parameter, while solutions for the second formulation are carried out to first order. Calculations for a HSCT design were made to illustrate the method. Results show that the minimum fuel trajectory consists of three segments: a minimum fuel energy-climb, a cruise-climb, and a minimum drag glide. The minimum time trajectory also has three segments: a maximum dynamic pressure ascent, a constant altitude cruise, and a maximum dynamic pressure glide. The minimum direct operating cost trajectory is an optimal combination of the two. For realistic costs of fuel and flight time, the minimum direct operating cost trajectory is very similar to the minimum fuel trajectory. Moreover, the HSCT has three local optimum cruise speeds, with the globally optimum cruise point at the highest allowable speed, if range is sufficiently long. The final range of the trajectory determines which locally optimal speed is best. Ranges of 500 to 6,000 nautical miles, subsonic and supersonic mixed flight, and varying fuel efficiency cases are analyzed. Finally, the payload-range curve of the HSCT design is determined.

Optimal design of active EMC filters

NASA Astrophysics Data System (ADS)

Chand, B.; Kut, T.; Dickmann, S.

2013-07-01

A recent trend in automotive industry is adding electrical drive systems to conventional drives. The electrification allows an expansion of energy sources and provides great opportunities for environmental friendly mobility. The electrical powertrain and its components can also cause disturbances which couple into nearby electronic control units and communication cables. Therefore the communication can be degraded or even permanently disrupted. To minimize these interferences, different approaches are possible. One possibility is to use EMC filters. However, the diversity of filters is very large and the determination of an appropriate filter for each application is time-consuming. Therefore, the filter design is determined by using a simulation tool including an effective optimization algorithm. This method leads to improvements in terms of weight, volume and cost.

Determination of the propellant combustion law under ballistic experiment conditions

NASA Astrophysics Data System (ADS)

Ishchenko, A. N.; Diachkovskii, A. S.; Zykova, A. I.; Kasimov, VZ; Samorokova, N. M.

2017-11-01

The main characteristics of ballistic experiment are the maximum pressure in the combustion chamber P max and the projectile velocity at the time of barrel leaving U M. During the work the burning law of the new high-energy fuel was determined in a ballistic experiment. This burning law was used for a parametric study of depending P max and U M from a powder charge mass and a traveling charge at initial temperature of + 20 °C was carried out. The optimal conditions for loading were obtained for improving the muzzle velocity by 14.9 %. Under optimal loading, there is defined the conditions, which is possible to get the greatest value muzzle velocity projectile at pressures up to 600 MPa.

Optimal plane search method in blood flow measurements by magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Bargiel, Pawel; Orkisz, Maciej; Przelaskowski, Artur; Piatkowska-Janko, Ewa; Bogorodzki, Piotr; Wolak, Tomasz

2004-07-01

This paper offers an algorithm for determining the blood flow parameters in the neck vessel segments using a single (optimal) measurement plane instead of the usual approach involving four planes orthogonal to the artery axis. This new approach aims at significantly shortening the time required to complete measurements using Nuclear Magnetic Resonance techniques. Based on a defined error function, the algorithm scans the solution space to find the minimum of the error function, and thus to determine a single plane characterized by a minimum measurement error, which allows for an accurate measurement of blood flow in the four carotid arteries. The paper also comprises a practical implementation of this method (as a module of a larger imaging-measuring system), including preliminary research results.

Space-time interpolation of satellite winds in the tropics

NASA Astrophysics Data System (ADS)

Patoux, Jérôme; Levy, Gad

2013-09-01

A space-time interpolator for creating average geophysical fields from satellite measurements is presented and tested. It is designed for optimal spatiotemporal averaging of heterogeneous data. While it is illustrated with satellite surface wind measurements in the tropics, the methodology can be useful for interpolating, analyzing, and merging a wide variety of heterogeneous and satellite data in the atmosphere and ocean over the entire globe. The spatial and temporal ranges of the interpolator are determined by averaging satellite and in situ measurements over increasingly larger space and time windows and matching the corresponding variability at each scale. This matching provides a relationship between temporal and spatial ranges, but does not provide a unique pair of ranges as a solution to all averaging problems. The pair of ranges most appropriate for a given application can be determined by performing a spectral analysis of the interpolated fields and choosing the smallest values that remove any or most of the aliasing due to the uneven sampling by the satellite. The methodology is illustrated with the computation of average divergence fields over the equatorial Pacific Ocean from SeaWinds-on-QuikSCAT surface wind measurements, for which 72 h and 510 km are suggested as optimal interpolation windows. It is found that the wind variability is reduced over the cold tongue and enhanced over the Pacific warm pool, consistent with the notion that the unstably stratified boundary layer has generally more variable winds and more gustiness than the stably stratified boundary layer. It is suggested that the spectral analysis optimization can be used for any process where time-space correspondence can be assumed.

Bifunctional ultrasound assisted extraction and determination of Elettaria cardamomum Maton essential oil.

PubMed

Sereshti, Hassan; Rohanifar, Ahmad; Bakhtiari, Sadjad; Samadi, Soheila

2012-05-18

A new hyphenated extraction method composed of ultrasound assisted extraction (UAE)-optimized ultrasound assisted emulsification microextraction (USAEME) was developed for the extraction and preconcentration of the essential oil of Elettaria cardamomum Maton. The essential oil was analyzed by gas chromatography-mass spectrometry (GC-MS) and optimization was performed using gas chromatography-flame ionization detection (GC-FID). Ultrasound played two different roles in the extraction of the essential oil. First, as a source of sufficient energy to break the oil-containing glands in order to release the oil, and second as an emulsifier to disperse the organic phase within water. The effective parameters (factors) of USAEME including volume of extraction solvent (C(2)H(4)Cl(2)), extraction temperature and ultrasonic time were optimized by using a central composite design (CCD). The optimal conditions were 120 μL for extraction solvent volume, 32.5 °C for temperature and 10.5 min for ultrasonic time. The linear dynamic ranges (LDRs) were 0.01-50 mg L(-1) with the determination coefficients in the range of 0.9990-0.9999. The limits of detection (LODs) and the relative standard deviations (RSDs) were 0.001-0.007 mg L(-1) and 3.6-6.3%, respectively. The enrichment factors were 93-98. The main components of the extracted essential oil were α-terpenyl acetate (46.0%), 1,8-cineole (27.7%), linalool (5.3%), α-terpineol (4.0%), linalyl acetate (3.5%). Copyright © 2012 Elsevier B.V. All rights reserved.

Optimizing Extraction Conditions of Free and Bound Phenolic Compounds from Rice By-Products and Their Antioxidant Effects.

PubMed

Irakli, Maria; Kleisiaris, Fotis; Kadoglidou, Kalliopi; Katsantonis, Dimitrios

2018-06-13

Rice by-products are extensively abundant agricultural wastes from the rice industry. This study was designed to optimize experimental conditions for maximum recovery of free and bound phenolic compounds from rice by-products. Optimized conditions were determined using response surface methodology based on total phenolic content (TPC), ABTS radical scavenging activity and ferric reducing power (FRAP). A Box-Behnken design was used to investigate the effects of ethanol concentration, extraction time and temperature, and NaOH concentration, hydrolysis time and temperature for free and bound fractions, respectively. The optimal conditions for the free phenolics were 41⁻56%, 40 °C, 10 min, whereas for bound phenolics were 2.5⁻3.6 M, 80 °C, 120 min. Under these conditions free TPC, ABTS and FRAP values in the bran were approximately 2-times higher than in the husk. However, bound TPC and FRAP values in the husk were 1.9- and 1.2-times higher than those in the bran, respectively, while bran fraction observed the highest ABTS value. Ferulic acid was most evident in the bran, whereas p -coumaric acid was mostly found in the husk. Findings from this study demonstrates that rice by-products could be exploited as valuable sources of bioactive components that could be used as ingredients of functional food and nutraceuticals.

The primer vector in linear, relative-motion equations. [spacecraft trajectory optimization

NASA Technical Reports Server (NTRS)

1980-01-01

Primer vector theory is used in analyzing a set of linear, relative-motion equations - the Clohessy-Wiltshire equations - to determine the criteria and necessary conditions for an optimal, N-impulse trajectory. Since the state vector for these equations is defined in terms of a linear system of ordinary differential equations, all fundamental relations defining the solution of the state and costate equations, and the necessary conditions for optimality, can be expressed in terms of elementary functions. The analysis develops the analytical criteria for improving a solution by (1) moving any dependent or independent variable in the initial and/or final orbit, and (2) adding intermediate impulses. If these criteria are violated, the theory establishes a sufficient number of analytical equations. The subsequent satisfaction of these equations will result in the optimal position vectors and times of an N-impulse trajectory. The solution is examined for the specific boundary conditions of (1) fixed-end conditions, two-impulse, and time-open transfer; (2) an orbit-to-orbit transfer; and (3) a generalized rendezvous problem. A sequence of rendezvous problems is solved to illustrate the analysis and the computational procedure.

Optimization of focused ultrasonic extraction of propellant components determined by gas chromatography/mass spectrometry.

PubMed

Fryš, Ondřej; Česla, Petr; Bajerová, Petra; Adam, Martin; Ventura, Karel

2012-09-15

A method for focused ultrasonic extraction of nitroglycerin, triphenyl amine and acetyl tributyl citrate presented in double-base propellant samples following by the gas chromatography/mass spectrometry analysis was developed. A face-centered central composite design of the experiments and response surface modeling was used for optimization of the time, amplitude and sample amount. The dichloromethane was used as the extractant solvent. The optimal extraction conditions with respect to the maximum yield of the lowest abundant compound triphenyl amine were found at the 20 min extraction time, 35% amplitude of ultrasonic waves and 2.5 g of the propellant sample. The results obtained under optimal conditions were compared with the results achieved with validated Soxhlet extraction method, which is typically used for isolation and pre-concentration of compounds from the samples of explosives. The extraction yields for acetyl tributyl citrate using both extraction methods were comparable; however, the yield of ultrasonic extraction of nitroglycerin and triphenyl amine was lower than using Soxhlet extraction. The possible sources of different extraction yields are estimated and discussed. Copyright © 2012 Elsevier B.V. All rights reserved.

Screening and optimization of pectin lyase and polygalacturonase activity from ginseng pathogen Cylindrocarpon Destructans

PubMed Central

Sathiyaraj, Gayathri; Srinivasan, Sathiyaraj; Kim, Ho-Bin; Subramaniyam, Sathiyamoorthy; Lee, Ok Ran; Kim, Yeon-Ju; Yang, Deok Chun

2011-01-01

Cylindrocarpon destructans isolated from ginseng field was found to produce pectinolytic enzymes. A Taguchi’s orthogonal array experimental design was applied to optimize the preliminary production of polygalacturonase (PG) and pectin lyase (PL) using submerged culture condition. This method was applied to evaluate the significant parameters for the production of enzymes. The process variables were pH, pectin concentration, incubation time and temperature. Optimization of process parameters resulted in high levels of enzyme (PG and PL) production after ten days of incubation at a pH of 5.0 at 25°C in the presence of 1.5% pectin. Among different nitrogen sources, urea and peptone showed high production of PG and PL, respectively. The enzyme production and mycelial growth seems to have direct influence on the culture conditions; therefore, at stationary state high enzyme production and mycelial growth were obtained than agitation state. Along with this, optimization of enzyme activity was also determined using various physiological parameters like, temperature, incubation time and pH. Taguchi’s data was also analyzed using one step ANOVA statistical method. PMID:24031695

Solar electricity supply isolines of generation capacity and storage.

PubMed

Grossmann, Wolf; Grossmann, Iris; Steininger, Karl W

2015-03-24

The recent sharp drop in the cost of photovoltaic (PV) electricity generation accompanied by globally rapidly increasing investment in PV plants calls for new planning and management tools for large-scale distributed solar networks. Of major importance are methods to overcome intermittency of solar electricity, i.e., to provide dispatchable electricity at minimal costs. We find that pairs of electricity generation capacity G and storage S that give dispatchable electricity and are minimal with respect to S for a given G exhibit a smooth relationship of mutual substitutability between G and S. These isolines between G and S support the solving of several tasks, including the optimal sizing of generation capacity and storage, optimal siting of solar parks, optimal connections of solar parks across time zones for minimizing intermittency, and management of storage in situations of far below average insolation to provide dispatchable electricity. G-S isolines allow determining the cost-optimal pair (G,S) as a function of the cost ratio of G and S. G-S isolines provide a method for evaluating the effect of geographic spread and time zone coverage on costs of solar electricity.

Evaluation of polyvinyl alcohols as mucoadhesive polymers for mucoadhesive buccal tablets prepared by direct compression.

PubMed

Ikeuchi-Takahashi, Yuri; Ishihara, Chizuko; Onishi, Hiraku

2017-09-01

The purpose of the present work was to evaluate polyvinyl alcohols (PVAs) as a mucoadhesive polymer for mucoadhesive buccal tablets prepared by direct compression. Various polymerization degree and particle diameter PVAs were investigated for their usability. The tensile strength, in vitro adhesive force, and water absorption properties of the tablets were determined to compare the various PVAs. The highest values of the tensile strength and the in vitro adhesive force were observed for PVAs with a medium viscosity and small particle size. The optimal PVA was identified by a factorial design analysis. Mucoadhesive tablets containing the optimal PVA were compared with carboxyvinyl polymer and hydroxypropyl cellulose formulations. The optimal PVA gives a high adhesive force, has a low viscosity, and resulted in relatively rapid drug release. Formulations containing carboxyvinyl polymer had high tensile strengths but short disintegration times. Higher hydroxypropyl cellulose concentration formulations had good adhesion forces and very long disintegration times. We identified the optimal characteristics of PVA, and the usefulness of mucoadhesive buccal tablets containing this PVA was suggested from their formulation properties.

Solar electricity supply isolines of generation capacity and storage

PubMed Central

Grossmann, Wolf; Grossmann, Iris; Steininger, Karl W.

2015-01-01

The recent sharp drop in the cost of photovoltaic (PV) electricity generation accompanied by globally rapidly increasing investment in PV plants calls for new planning and management tools for large-scale distributed solar networks. Of major importance are methods to overcome intermittency of solar electricity, i.e., to provide dispatchable electricity at minimal costs. We find that pairs of electricity generation capacity G and storage S that give dispatchable electricity and are minimal with respect to S for a given G exhibit a smooth relationship of mutual substitutability between G and S. These isolines between G and S support the solving of several tasks, including the optimal sizing of generation capacity and storage, optimal siting of solar parks, optimal connections of solar parks across time zones for minimizing intermittency, and management of storage in situations of far below average insolation to provide dispatchable electricity. G−S isolines allow determining the cost-optimal pair (G,S) as a function of the cost ratio of G and S. G−S isolines provide a method for evaluating the effect of geographic spread and time zone coverage on costs of solar electricity. PMID:25755261

Box-Behnken design based statistical modeling for ultrasound-assisted extraction of corn silk polysaccharide.

PubMed

Prakash Maran, J; Manikandan, S; Thirugnanasambandham, K; Vigna Nivetha, C; Dinesh, R

2013-01-30

In this study, ultrasound assisted extraction (UAE) conditions on the yield of polysaccharide from corn silk were studied using three factors, three level Box-Behnken response surface design. Process parameters, which affect the efficiency of UAE such as extraction temperature (40-60 °C), time (10-30 min) and solid-liquid ratio (1:10-1:30 g/ml) were investigated. The results showed that, the extraction conditions have significant effects on extraction yield of polysaccharide. The obtained experimental data were fitted to a second-order polynomial equation using multiple regression analysis with high coefficient of determination value (R(2)) of 0.994. An optimization study using Derringer's desired function methodology was performed and the optimal conditions based on both individual and combinations of all independent variables (extraction temperature of 56 °C, time of 17 min and solid-liquid ratio of 1:20 g/ml) were determined with maximum polysaccharide yield of 6.06%, which was confirmed through validation experiments. Copyright © 2012 Elsevier Ltd. All rights reserved.

An inverse problem of determining the implied volatility in option pricing

NASA Astrophysics Data System (ADS)

Deng, Zui-Cha; Yu, Jian-Ning; Yang, Liu

2008-04-01

In the Black-Scholes world there is the important quantity of volatility which cannot be observed directly but has a major impact on the option value. In practice, traders usually work with what is known as implied volatility which is implied by option prices observed in the market. In this paper, we use an optimal control framework to discuss an inverse problem of determining the implied volatility when the average option premium, namely the average value of option premium corresponding with a fixed strike price and all possible maturities from the current time to a chosen future time, is known. The issue is converted into a terminal control problem by Green function method. The existence and uniqueness of the minimum of the control functional are addressed by the optimal control method, and the necessary condition which must be satisfied by the minimum is also given. The results obtained in the paper may be useful for those who engage in risk management or volatility trading.

Optimized method for the quantification of pyruvic acid in onions by microplate reader and confirmation by high resolution mass spectra.

PubMed

Metrani, Rita; Jayaprakasha, G K; Patil, Bhimanagouda S

2018-03-01

The present study describes the rapid microplate method to determine pyruvic acid content in different varieties of onions. Onion juice was treated with 2,4-dinitrophenylhydrazine to obtain hydrazone, which was further treated with potassium hydroxide to get stable colored complex. The stability of potassium complex was enhanced up to two hours and the structures of hydrazones were confirmed by LC-MS for the first time. The developed method was optimized by testing different bases, acids with varying concentrations of dinitrophenyl hydrazine to get stable color and results were comparable to developed method. Repeatability and precision showed <9% relative standard deviation. Moreover, sweet onion juice was stored for four weeks at different temperatures for the stability; the pyruvate remained stable at all temperatures except at 25°C. Thus, the developed method has good potential to determine of pungency in large number of onions in a short time using minimal amount of reagents. Copyright © 2017 Elsevier Ltd. All rights reserved.

Brown algae hydrolysis in 1-n-butyl-3-methylimidazolium chloride with mineral acid catalyst system.

PubMed

Malihan, Lenny B; Nisola, Grace M; Chung, Wook-Jin

2012-08-01

The amenability of three brown algal species, Sargassum fulvellum, Laminaria japonica and Undaria pinnatifida, to hydrolysis were investigated using the ionic liquid (IL), 1-n-butyl-3-methylimidazolium chloride ([BMIM]Cl). Compositional analyses of the brown algae reveal that sufficient amounts of sugars (15.5-29.4 wt.%) can be recovered. Results from hydrolysis experiments show that careful selection of the type of mineral acid as catalyst and control of acid loading could maximize the recovery of sugars. Optimal reaction time and temperature were determined from the kinetic studies on the sequential reducing sugar (TRS) formation and degradation. Optimal reaction times were determined based on the extent of furfurals formation as TRS degradation products. X-ray diffraction and environmental scanning electron microscopy confirmed the suitability of [BMIM]Cl as solvent for the hydrolysis of the three brown algae. Overall results show the potential of brown algae as renewable energy resources for the production of valuable chemicals and biofuels. Copyright © 2012 Elsevier Ltd. All rights reserved.

Agarose-chitosan-C18 film micro-solid phase extraction combined with high performance liquid chromatography for the determination of phenanthrene and pyrene in chrysanthemum tea samples.

PubMed

Ng, Nyuk Ting; Sanagi, Mohd Marsin; Wan Ibrahim, Wan Nazihah; Wan Ibrahim, Wan Aini

2017-05-01

Agarose-chitosan-immobilized octadecylsilyl-silica (C 18 ) film micro-solid phase extraction (μSPE) was developed and applied for the determination of phenanthrene (PHE) and pyrene (PYR) in chrysanthemum tea samples using high performance liquid chromatography-ultraviolet detection (HPLC-UV). The film of blended agarose and chitosan allows good dispersion of C 18 , prevents the leaching of C 18 during application and enhances the film mechanical stability. Important μSPE parameters were optimized including amount of sorbent loading, extraction time, desorption solvent and desorption time. The matrix match calibration curves showed good linearity (r⩾0.994) over a concentration range of 1-500ppb. Under the optimized conditions, the proposed method showed good limits of detection (0.549-0.673ppb), good analyte recoveries (100.8-105.99%) and good reproducibilities (RSDs⩽13.53%, n=3) with preconcentration factors of 4 and 72 for PHE and PYR, respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Water soluble polysaccharides from Spirulina platensis: extraction and in vitro anti-cancer activity.

PubMed

Kurd, Forouzan; Samavati, Vahid

2015-03-01

Polysaccharides from Spirulina platensis algae (SP) were extracted by ultrasound-assisted extraction procedure. The optimal conditions for ultrasonic extraction of SP were determined by response surface methodology. The four parameters were, extraction time (X1), extraction temperature (X2), ultrasonic power (X3) and the ratio of water to raw material (X4), respectively. The experimental data obtained were fitted to a second-order polynomial equation. The optimum conditions were extraction time of 25 min, extraction temperature 85°C, ultrasonic power 90 W and ratio of water to raw material 20 mL/g. Under these optimal conditions, the experimental yield was 13.583±0.51%, well matched with the predicted models with the coefficients of determination (R2) of 0.9971. Then, we demonstrated that SP polysaccharides had strong scavenging activities in vitro on DPPH and hydroxyl radicals. Overall, SP may have potential applications in the medical and food industries. Copyright © 2015 Elsevier B.V. All rights reserved.

An Optimization Model for the Selection of Bus-Only Lanes in a City.

PubMed

Chen, Qun

2015-01-01

The planning of urban bus-only lane networks is an important measure to improve bus service and bus priority. To determine the effective arrangement of bus-only lanes, a bi-level programming model for urban bus lane layout is developed in this study that considers accessibility and budget constraints. The goal of the upper-level model is to minimize the total travel time, and the lower-level model is a capacity-constrained traffic assignment model that describes the passenger flow assignment on bus lines, in which the priority sequence of the transfer times is reflected in the passengers' route-choice behaviors. Using the proposed bi-level programming model, optimal bus lines are selected from a set of candidate bus lines; thus, the corresponding bus lane network on which the selected bus lines run is determined. The solution method using a genetic algorithm in the bi-level programming model is developed, and two numerical examples are investigated to demonstrate the efficacy of the proposed model.

ATTDES: An Expert System for Satellite Attitude Determination and Control. 2

NASA Technical Reports Server (NTRS)

Mackison, Donald L.; Gifford, Kevin

1996-01-01

The design, analysis, and flight operations of satellite attitude determintion and attitude control systems require extensive mathematical formulations, optimization studies, and computer simulation. This is best done by an analyst with extensive education and experience. The development of programs such as ATTDES permit the use of advanced techniques by those with less experience. Typical tasks include the mission analysis to select stabilization and damping schemes, attitude determination sensors and algorithms, and control system designs to meet program requirements. ATTDES is a system that includes all of these activities, including high fidelity orbit environment models that can be used for preliminary analysis, parameter selection, stabilization schemes, the development of estimators covariance analyses, and optimization, and can support ongoing orbit activities. The modification of existing simulations to model new configurations for these purposes can be an expensive, time consuming activity that becomes a pacing item in the development and operation of such new systems. The use of an integrated tool such as ATTDES significantly reduces the effort and time required for these tasks.

NMR Parameters Determination through ACE Committee Machine with Genetic Implanted Fuzzy Logic and Genetic Implanted Neural Network

NASA Astrophysics Data System (ADS)

Asoodeh, Mojtaba; Bagheripour, Parisa; Gholami, Amin

2015-06-01

Free fluid porosity and rock permeability, undoubtedly the most critical parameters of hydrocarbon reservoir, could be obtained by processing of nuclear magnetic resonance (NMR) log. Despite conventional well logs (CWLs), NMR logging is very expensive and time-consuming. Therefore, idea of synthesizing NMR log from CWLs would be of a great appeal among reservoir engineers. For this purpose, three optimization strategies are followed. Firstly, artificial neural network (ANN) is optimized by virtue of hybrid genetic algorithm-pattern search (GA-PS) technique, then fuzzy logic (FL) is optimized by means of GA-PS, and eventually an alternative condition expectation (ACE) model is constructed using the concept of committee machine to combine outputs of optimized and non-optimized FL and ANN models. Results indicated that optimization of traditional ANN and FL model using GA-PS technique significantly enhances their performances. Furthermore, the ACE committee of aforementioned models produces more accurate and reliable results compared with a singular model performing alone.

Determination of the optimal mesh parameters for Iguassu centrifuge flow and separation calculations

NASA Astrophysics Data System (ADS)

Romanihin, S. M.; Tronin, I. V.

2016-09-01

We present the method and the results of the determination for optimal computational mesh parameters for axisymmetric modeling of flow and separation in the Iguasu gas centrifuge. The aim of this work was to determine the mesh parameters which provide relatively low computational cost whithout loss of accuracy. We use direct search optimization algorithm to calculate optimal mesh parameters. Obtained parameters were tested by the calculation of the optimal working regime of the Iguasu GC. Separative power calculated using the optimal mesh parameters differs less than 0.5% from the result obtained on the detailed mesh. Presented method can be used to determine optimal mesh parameters of the Iguasu GC with different rotor speeds.

An Optimized Analytical Method for the Simultaneous Detection of Iodoform, Iodoacetic Acid, and Other Trihalomethanes and Haloacetic Acids in Drinking Water

PubMed Central

Jiang, Songhui; Templeton, Michael R.; He, Gengsheng; Qu, Weidong

2013-01-01

An optimized method is presented using liquid-liquid extraction and derivatization for the extraction of iodoacetic acid (IAA) and other haloacetic acids (HAA9) and direct extraction of iodoform (IF) and other trihalomethanes (THM4) from drinking water, followed by detection by gas chromatography with electron capture detection (GC-ECD). A Doehlert experimental design was performed to determine the optimum conditions for the five most significant factors in the derivatization step: namely, the volume and concentration of acidic methanol (optimized values  = 15%, 1 mL), the volume and concentration of Na2SO4 solution (129 g/L, 8.5 mL), and the volume of saturated NaHCO3 solution (1 mL). Also, derivatization time and temperature were optimized by a two-variable Doehlert design, resulting in the following optimized parameters: an extraction time of 11 minutes for IF and THM4 and 14 minutes for IAA and HAA9; mass of anhydrous Na2SO4 of 4 g for IF and THM4 and 16 g for IAA and HAA9; derivatization time of 160 min and temperature at 40°C. Under optimal conditions, the optimized procedure achieves excellent linearity (R2 ranges 0.9990–0.9998), low detection limits (0.0008–0.2 µg/L), low quantification limits (0.008–0.4 µg/L), and good recovery (86.6%–106.3%). Intra- and inter-day precision were less than 8.9% and 8.8%, respectively. The method was validated by applying it to the analysis of raw, flocculated, settled, and finished waters collected from a water treatment plant in China. PMID:23613747

Improving the seismic torsional behavior of plan-asymmetric, single-storey, concrete moment resisting buildings with fluid viscous dampers

NASA Astrophysics Data System (ADS)

Rofooei, Fayaz Rahimzadeh; Mohammadzadeh, Sahar

2016-03-01

The optimal distribution of fluid viscous dampers (FVD) in controlling the seismic response of eccentric, single-storey, moment resisting concrete structures is investigated using the previously defined center of damping constant (CDC). For this purpose, a number of structural models with different one-way stiffness and strength eccentricities are considered. Extensive nonlinear time history analyses are carried out for various arrangements of FVDs. It is shown that the arrangement of FVDs for controlling the torsional behavior due to asymmetry in the concrete structures is very dependent on the intensity of the peak ground acceleration (PGA) and the extent of the structural stiffness and strength eccentricities. The results indicate that, in the linear range of structural behavior the stiffness eccentricity es which is the main parameter in determining the location of optimal CDC, is found to be less or smaller than the optimal damping constant eccentricity e*d, i.e., |e*d| > |es|. But, in the nonlinear range of structural behavior where the strength eccentricity er is the dominant factor in determining the location of optimal CDC, |e*d| > |er|. It is also concluded that for the majority of the plan-asymmetric, concrete structures considered in this study with er ≠ 0, the optimal CDC approaches the center of mass as er decreases.

[Rapid determination of trace iodate using monolithic column ion-pair chromatography coupled with direct conductivity detection].

PubMed

Liu, Yuzhen; Yu, Hong; Li, Siwen

2011-10-01

A method was developed on a monolithic column for the fast determination of trace iodate (IO(3)- ) by ion-pair chromatography with direct conductivity detection. The analytes were separated using a mobile phase of tetrabutylammonium hydroxide (TBA)-phthalic acid-acetonitrile on a reversed-phase silica-based monolithic column. The effects of eluent, flow rate and column temperature on the retention of iodate were investigated. The optimized chromatographic conditions for the determination of the anion were as follows: 0. 25 mmol/L TBA-0. 18 mmol/L phthalic acid-3% acetonitrile (pH 5.5) as mobile phase, a flow rate of 4.0 mL/min and a column temperature of 30 degrees C. Under the optimal conditions, retention time of iodate was less than 0. 5 min and the baseline separation of iodate was achieved without any interference by other anions (Cl-, NO , SO4(2)-, I- ). The detection limit (S/N= 3) was 0.36 mg/L for IO(3)- . Relative standard deviation (RSD, n = 5) of chromatographic peak area and retention time were 0. 35% and 0. 28%, respectively. The proposed method was applied to the determination of trace iodate in iodized medicine. The spiked recovery of iodate was 96. 4%. The method is rapid, simple, accurate, reliable, and practical.

LTI system order reduction approach based on asymptotical equivalence and the Co-operation of biology-related algorithms

NASA Astrophysics Data System (ADS)

Ryzhikov, I. S.; Semenkin, E. S.; Akhmedova, Sh A.

2017-02-01

A novel order reduction method for linear time invariant systems is described. The method is based on reducing the initial problem to an optimization one, using the proposed model representation, and solving the problem with an efficient optimization algorithm. The proposed method of determining the model allows all the parameters of the model with lower order to be identified and by definition, provides the model with the required steady-state. As a powerful optimization tool, the meta-heuristic Co-Operation of Biology-Related Algorithms was used. Experimental results proved that the proposed approach outperforms other approaches and that the reduced order model achieves a high level of accuracy.

Effective learning strategies for real-time image-guided adaptive control of multiple-source hyperthermia applicators.

PubMed

Cheng, Kung-Shan; Dewhirst, Mark W; Stauffer, Paul R; Das, Shiva

2010-03-01

This paper investigates overall theoretical requirements for reducing the times required for the iterative learning of a real-time image-guided adaptive control routine for multiple-source heat applicators, as used in hyperthermia and thermal ablative therapy for cancer. Methods for partial reconstruction of the physical system with and without model reduction to find solutions within a clinically practical timeframe were analyzed. A mathematical analysis based on the Fredholm alternative theorem (FAT) was used to compactly analyze the existence and uniqueness of the optimal heating vector under two fundamental situations: (1) noiseless partial reconstruction and (2) noisy partial reconstruction. These results were coupled with a method for further acceleration of the solution using virtual source (VS) model reduction. The matrix approximation theorem (MAT) was used to choose the optimal vectors spanning the reduced-order subspace to reduce the time for system reconstruction and to determine the associated approximation error. Numerical simulations of the adaptive control of hyperthermia using VS were also performed to test the predictions derived from the theoretical analysis. A thigh sarcoma patient model surrounded by a ten-antenna phased-array applicator was retained for this purpose. The impacts of the convective cooling from blood flow and the presence of sudden increase of perfusion in muscle and tumor were also simulated. By FAT, partial system reconstruction directly conducted in the full space of the physical variables such as phases and magnitudes of the heat sources cannot guarantee reconstructing the optimal system to determine the global optimal setting of the heat sources. A remedy for this limitation is to conduct the partial reconstruction within a reduced-order subspace spanned by the first few maximum eigenvectors of the true system matrix. By MAT, this VS subspace is the optimal one when the goal is to maximize the average tumor temperature. When more than 6 sources present, the steps required for a nonlinear learning scheme is theoretically fewer than that of a linear one, however, finite number of iterative corrections is necessary for a single learning step of a nonlinear algorithm. Thus, the actual computational workload for a nonlinear algorithm is not necessarily less than that required by a linear algorithm. Based on the analysis presented herein, obtaining a unique global optimal heating vector for a multiple-source applicator within the constraints of real-time clinical hyperthermia treatments and thermal ablative therapies appears attainable using partial reconstruction with minimum norm least-squares method with supplemental equations. One way to supplement equations is the inclusion of a method of model reduction.

Real-time inverse planning for Gamma Knife radiosurgery.

PubMed

Wu, Q Jackie; Chankong, Vira; Jitprapaikulsarn, Suradet; Wessels, Barry W; Einstein, Douglas B; Mathayomchan, Boonyanit; Kinsella, Timothy J

2003-11-01

The challenges of real-time Gamma Knife inverse planning are the large number of variables involved and the unknown search space a priori. With limited collimator sizes, shots have to be heavily overlapped to form a smooth prescription isodose line that conforms to the irregular target shape. Such overlaps greatly influence the total number of shots per plan, making pre-determination of the total number of shots impractical. However, this total number of shots usually defines the search space, a pre-requisite for most of the optimization methods. Since each shot only covers part of the target, a collection of shots in different locations and various collimator sizes selected makes up the global dose distribution that conforms to the target. Hence, planning or placing these shots is a combinatorial optimization process that is computationally expensive by nature. We have previously developed a theory of shot placement and optimization based on skeletonization. The real-time inverse planning process, reported in this paper, is an expansion and the clinical implementation of this theory. The complete planning process consists of two steps. The first step is to determine an optimal number of shots including locations and sizes and to assign initial collimator size to each of the shots. The second step is to fine-tune the weights using a linear-programming technique. The objective function is to minimize the total dose to the target boundary (i.e., maximize the dose conformity). Results of an ellipsoid test target and ten clinical cases are presented. The clinical cases are also compared with physician's manual plans. The target coverage is more than 99% for manual plans and 97% for all the inverse plans. The RTOG PITV conformity indices for the manual plans are between 1.16 and 3.46, compared to 1.36 to 2.4 for the inverse plans. All the inverse plans are generated in less than 2 min, making real-time inverse planning a reality.

Optimal Timing of Heart Transplant After HeartMate II Left Ventricular Assist Device Implantation.

PubMed

Steffen, Robert J; Blackstone, Eugene H; Smedira, Nicholas G; Soltesz, Edward G; Hoercher, Katherine J; Thuita, Lucy; Starling, Randall C; Mountis, Maria; Moazami, Nader

2017-11-01

Optimal timing of heart transplantation in patients supported with second-generation left ventricular assist devices (LVADs) is unknown. Despite this, patients with LVADs continue to receive priority on the heart transplant waiting list. Our objective was to determine the optimal timing of transplantation for patients bridged with continuous-flow LVADs. A total of 301 HeartMate II LVADs (Thoratec Corp, Pleasanton, CA) were implanted in 285 patients from October 2004 to June 2013, and 86 patients underwent transplantation through the end of follow-up. Optimal transplantation timing was the product of surviving on LVAD support and surviving transplant. Three-year survival after both HeartMate II implantation and heart transplantation was unchanged when transplantation occurred within 9 months of implantation. Survival decreased as the duration of support exceeded this. Preoperative risk factors for death on HeartMate II support were prior valve operation, prior coronary artery bypass grafting, low albumin, low glomerular filtration rate, higher mean arterial pressure, hypertension, and earlier date of implant. Survival for patients without these risk factors was lowest when transplant was performed within 3 months but was relatively constant with increased duration of support. Longer duration of support was associated with poorer survival for patients with many of these risk factors. Device reimplantation, intracranial hemorrhage, and postimplant dialysis during HeartMate II support were associated with decreased survival. Survival of patients supported by the HeartMate II is affected by preoperative comorbidities and postoperative complications. Transplantation before complications is imperative in optimizing survival. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Optimizing read-out of the NECTAr front-end electronics

NASA Astrophysics Data System (ADS)

Vorobiov, S.; Feinstein, F.; Bolmont, J.; Corona, P.; Delagnes, E.; Falvard, A.; Gascón, D.; Glicenstein, J.-F.; Naumann, C. L.; Nayman, P.; Ribo, M.; Sanuy, A.; Tavernet, J.-P.; Toussenel, F.; Vincent, P.

2012-12-01

We describe the optimization of the read-out specifications of the NECTAr front-end electronics for the Cherenkov Telescope Array (CTA). The NECTAr project aims at building and testing a demonstrator module of a new front-end electronics design, which takes an advantage of the know-how acquired while building the cameras of the CAT, H.E.S.S.-I and H.E.S.S.-II experiments. The goal of the optimization work is to define the specifications of the digitizing electronics of a CTA camera, in particular integration time window, sampling rate, analog bandwidth using physics simulations. We employed for this work real photomultiplier pulses, sampled at 100 ps with a 600 MHz bandwidth oscilloscope. The individual pulses are drawn randomly at the times at which the photo-electrons, originating from atmospheric showers, arrive at the focal planes of imaging atmospheric Cherenkov telescopes. The timing information is extracted from the existing CTA simulations on the GRID and organized in a local database, together with all the relevant physical parameters (energy, primary particle type, zenith angle, distance from the shower axis, pixel offset from the optical axis, night-sky background level, etc.), and detector configurations (telescope types, camera/mirror configurations, etc.). While investigating the parameter space, an optimal pixel charge integration time window, which minimizes relative error in the measured charge, has been determined. This will allow to gain in sensitivity and to lower the energy threshold of CTA telescopes. We present results of our optimizations and first measurements obtained using the NECTAr demonstrator module.

Validation of a dye stain assay for vaginally inserted HEC-filled microbicide applicators

PubMed Central

Katzen, Lauren L.; Fernández-Romero, José A.; Sarna, Avina; Murugavel, Kailapuri G.; Gawarecki, Daniel; Zydowsky, Thomas M.; Mensch, Barbara S.

2011-01-01

Background The reliability and validity of self-reports of vaginal microbicide use are questionable given the explicit understanding that participants are expected to comply with study protocols. Our objective was to optimize the Population Council's previously validated dye stain assay (DSA) and related procedures, and establish predictive values for the DSA's ability to identify vaginally inserted single-use, low-density polyethylene microbicide applicators filled with hydroxyethylcellulose gel. Methods Applicators, inserted by 252 female sex workers enrolled in a microbicide feasibility study in Southern India, served as positive controls for optimization and validation experiments. Prior to validation, optimal dye concentration and staining time were ascertained. Three validation experiments were conducted to determine sensitivity, specificity, negative predictive values and positive predictive values. Results The dye concentration of 0.05% (w/v) FD&C Blue No. 1 Granular Food Dye and staining time of five seconds were determined to be optimal and were used for the three validation experiments. There were a total of 1,848 possible applicator readings across validation experiments; 1,703 (92.2%) applicator readings were correct. On average, the DSA performed with 90.6% sensitivity, 93.9% specificity, and had a negative predictive value of 93.8% and a positive predictive value of 91.0%. No statistically significant differences between experiments were noted. Conclusions The DSA was optimized and successfully validated for use with single-use, low-density polyethylene applicators filled with hydroxyethylcellulose (HEC) gel. We recommend including the DSA in future microbicide trials involving vaginal gels in order to identify participants who have low adherence to dosing regimens. In doing so, we can develop strategies to improve adherence as well as investigate the association between product use and efficacy. PMID:21992983

Evaluation, prediction and optimization the ultrasound-assisted extraction method using response surface methodology: antioxidant and biological properties of Stachys parviflora L.

PubMed

Bashi, Davoud Salar; Dowom, Samaneh Attaran; Bazzaz, Bibi Sedigheh Fazly; Khanzadeh, Farhad; Soheili, Vahid; Mohammadpour, Ali

2016-05-01

To optimize the extraction method using response surface methodology, extract the phenolic compounds, and identify the antioxidant and biological properties of Stachys parviflora L. extracts. Maceration and ultrasound-assisted extraction (UAE) (4, 7, 10 min treatment time, 40, 70, 100 % high-intensity and 60, 80, 100 % (v v-1) methanol purity) were applied to obtain the extracts. SEM was conducted to provide the microstructure of the extracted plant. MICs (colorimetric assay), MFCs (colony diameter), total phenolic content, total flavonoid content, radical scavenging capacity and extraction efficiency were determined. HPLC analysis was applied to measure the existent phenolic compounds. A quadratic model (4 min treatment time, 74.5 % high-intensity and 74.2 % solvent purity) was suggested as the best (TPC: 20.89 mg GAE g-1 d.m., TFC: 6.22 mg QEs g-1 d.m., DPPH IC50: 21.86 µg ml-1 and EE: 113.65 mg g-1 d.m.) UAE extraction model. The optimized UAE extract was generally more effective against Gram-positive microorganisms (MIC: 10-20; MBC: 10-40 (mg ml-1)) than Gram-negative ones (MIC: 40; MBC: >40 (mg ml-1)). Moreover, it (MGI: 2.32-100 %) revealed more anti-mold activity than maceration (MGI: <28.77 %). Explosive disruption of the cell walls, therefore, enhanced extraction yield by acoustic cavitation, was elucidated using SEM. Caffeic acid, tannic acid, quercetin, trans ferulic acid and rosmarinic acid were determined as the phenolic compounds in the optimized extract. RSM optimization was successfully applied for UAE from S. parviflora. The considerable antioxidant and biological properties were attributed to the phenolic compounds.

Evaluation, prediction and optimization the ultrasound-assisted extraction method using response surface methodology: antioxidant and biological properties of Stachys parviflora L.

PubMed Central

Bashi, Davoud Salar; Dowom, Samaneh Attaran; Bazzaz, Bibi Sedigheh Fazly; Khanzadeh, Farhad; Soheili, Vahid; Mohammadpour, Ali

2016-01-01

Objective(s): To optimize the extraction method using response surface methodology, extract the phenolic compounds, and identify the antioxidant and biological properties of Stachys parviflora L. extracts. Materials and Methods: Maceration and ultrasound-assisted extraction (UAE) (4, 7, 10 min treatment time, 40, 70, 100 % high-intensity and 60, 80, 100 % (v v-1) methanol purity) were applied to obtain the extracts. SEM was conducted to provide the microstructure of the extracted plant. MICs (colorimetric assay), MFCs (colony diameter), total phenolic content, total flavonoid content, radical scavenging capacity and extraction efficiency were determined. HPLC analysis was applied to measure the existent phenolic compounds. Results: A quadratic model (4 min treatment time, 74.5 % high-intensity and 74.2 % solvent purity) was suggested as the best (TPC: 20.89 mg GAE g-1 d.m., TFC: 6.22 mg QEs g-1 d.m., DPPH IC50: 21.86 µg ml-1 and EE: 113.65 mg g-1 d.m.) UAE extraction model. The optimized UAE extract was generally more effective against Gram-positive microorganisms (MIC: 10-20; MBC: 10-40 (mg ml-1)) than Gram-negative ones (MIC: 40; MBC: >40 (mg ml-1)). Moreover, it (MGI: 2.32-100 %) revealed more anti-mold activity than maceration (MGI: <28.77 %). Explosive disruption of the cell walls, therefore, enhanced extraction yield by acoustic cavitation, was elucidated using SEM. Caffeic acid, tannic acid, quercetin, trans ferulic acid and rosmarinic acid were determined as the phenolic compounds in the optimized extract. Conclusion: RSM optimization was successfully applied for UAE from S. parviflora. The considerable antioxidant and biological properties were attributed to the phenolic compounds. PMID:27403260

Low Density Solvent-Based Dispersive Liquid-Liquid Microextraction for the Determination of Synthetic Antioxidants in Beverages by High-Performance Liquid Chromatography

PubMed Central

Çabuk, Hasan; Köktürk, Mustafa

2013-01-01

A simple and efficient method was established for the determination of synthetic antioxidants in beverages by using dispersive liquid-liquid microextraction combined with high-performance liquid chromatography with ultraviolet detection. Butylated hydroxy toluene, butylated hydroxy anisole, and tert-butylhydroquinone were the antioxidants evaluated. Experimental parameters including extraction solvent, dispersive solvent, pH of sample solution, salt concentration, and extraction time were optimized. Under optimal conditions, the extraction recoveries ranged from 53 to 96%. Good linearity was observed by the square of correlation coefficients ranging from 0.9975 to 0.9997. The relative standard deviations ranged from 1.0 to 5.2% for all of the analytes. Limits of detection ranged from 0.85 to 2.73 ng mL−1. The method was successfully applied for determination of synthetic antioxidants in undiluted beverage samples with satisfactory recoveries. PMID:23853535

Concurrently adjusting interrelated control parameters to achieve optimal engine performance

DOEpatents

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2015-12-01

Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.

Due-Window Assignment Scheduling with Variable Job Processing Times

PubMed Central

Wu, Yu-Bin

2015-01-01

We consider a common due-window assignment scheduling problem jobs with variable job processing times on a single machine, where the processing time of a job is a function of its position in a sequence (i.e., learning effect) or its starting time (i.e., deteriorating effect). The problem is to determine the optimal due-windows, and the processing sequence simultaneously to minimize a cost function includes earliness, tardiness, the window location, window size, and weighted number of tardy jobs. We prove that the problem can be solved in polynomial time. PMID:25918745

Solving fuzzy shortest path problem by genetic algorithm

NASA Astrophysics Data System (ADS)

Syarif, A.; Muludi, K.; Adrian, R.; Gen, M.

2018-03-01

Shortest Path Problem (SPP) is known as one of well-studied fields in the area Operations Research and Mathematical Optimization. It has been applied for many engineering and management designs. The objective is usually to determine path(s) in the network with minimum total cost or traveling time. In the past, the cost value for each arc was usually assigned or estimated as a deteministic value. For some specific real world applications, however, it is often difficult to determine the cost value properly. One way of handling such uncertainty in decision making is by introducing fuzzy approach. With this situation, it will become difficult to solve the problem optimally. This paper presents the investigations on the application of Genetic Algorithm (GA) to a new SPP model in which the cost values are represented as Triangular Fuzzy Number (TFN). We adopts the concept of ranking fuzzy numbers to determine how good the solutions. Here, by giving his/her degree value, the decision maker can determine the range of objective value. This would be very valuable for decision support system in the real world applications.Simulation experiments were carried out by modifying several test problems with 10-25 nodes. It is noted that the proposed approach is capable attaining a good solution with different degree of optimism for the tested problems.

Implementation of Particle Swarm Optimization Method for Voltage Stability Analysis in 150 kV Sub System Grati – Paiton East Java

NASA Astrophysics Data System (ADS)

Kusumaningtyas, A. B.; Hidayat, M. N.; Ronilaya, F.

2018-04-01

Based on the data from State Electric Company on 15 January 2013, the undistributed power in the 150 kV sub system Grati-Paiton Region IV, that consist of 26 bus 150 kV and 2 bus generation 500 kV system, was recorded 3.286,00 MW. At the same time, the frequency of the system was down to 49 Hz. This lead to a deficit generation and unstable voltage condition in the system. Fast Voltage Stability Index (FVSI) method is used in this research to analyze the voltage stability of the buses. For buses with unstable voltage condition, reactive power will be injected through capacitor installation. The site where the capacitor will be installed is determined using the Fast Voltage Stability Index (FVSI) method while the size of the capacitor is determined using the Particle Swarm Optimization (PSO) method. The PSO method has been applied in some researches, such as to determine optimal placement and sizing in radial distribution network as well as in transmission network.. In this research, the PSO method is used to find the Qloss of an interconnection transmission system, which in turn, the value of the Qloss is used to determine the capacitance of the capacitor needed by the system.

Enhancing Nursing Staffing Forecasting With Safety Stock Over Lead Time Modeling.

PubMed

McNair, Douglas S

2015-01-01

In balancing competing priorities, it is essential that nursing staffing provide enough nurses to safely and effectively care for the patients. Mathematical models to predict optimal "safety stocks" have been routine in supply chain management for many years but have up to now not been applied in nursing workforce management. There are various aspects that exhibit similarities between the 2 disciplines, such as an evolving demand forecast according to acuity and the fact that provisioning "stock" to meet demand in a future period has nonzero variable lead time. Under assumptions about the forecasts (eg, the demand process is well fit as an autoregressive process) and about the labor supply process (≥1 shifts' lead time), we show that safety stock over lead time for such systems is effectively equivalent to the corresponding well-studied problem for systems with stationary demand bounds and base stock policies. Hence, we can apply existing models from supply chain analytics to find the optimal safety levels of nurse staffing. We use a case study with real data to demonstrate that there are significant benefits from the inclusion of the forecast process when determining the optimal safety stocks.