Journal articles: 'Optimum Sampling Design'

1

Omule, S. A. Y. "Optimum Design in Multivariate Stratified Sampling." Biometrical Journal 27, no. 8 (1985): 907–12. http://dx.doi.org/10.1002/bimj.4710270813.

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Francis, R. I. C. Chris. "Optimum design for catch sampling of eels." Marine and Freshwater Research 50, no. 4 (1999): 343. http://dx.doi.org/10.1071/mf98147.

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Data from the first two seasons of a catch-sampling programme for New Zealand freshwater eels (Anguilla australis and A. diefenbachii) are described. These are used in two simulation experiments to provide information to optimize future sampling. Results are presented in the form of equations that predict the precision of estimates (of species composition, mean size, and mean age at two different sizes) as a function of various survey design variables. Precision typically depends more on the number of landings (catches) that are sampled than the number of eels sampled per landing. Also, the precision obtainable from a given design varies substantially from fishery to fishery. For example, if 50 eels were measured and 10 otoliths collected from each of five landings, estimated standard errors varied by a factor of 9 for species composition, 19 for mean weight, and 5 for mean age at the minimum legal size, depending on which fishery was sampled. Results for mean age estimates are more restricted and less certain (than those for species composition and mean size) because age data were fewer. Three further optimization issues are discussed: sampling costs, the importance of ‘minor’ species, and the pool of fishers from which samples are collected.

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Ansari, Athar Hussain, Rahul Varshney, Najmussehar, and Mohammad Jameel Ahsan. "An optimum multivariate-multiobjective stratified sampling design." METRON 69, no. 3 (December 2011): 227–50. http://dx.doi.org/10.1007/bf03263559.

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Sultan, Torky I. "Optimum design of sampling plans in electronic industry." Microelectronics Reliability 34, no. 8 (August 1994): 1369–73. http://dx.doi.org/10.1016/0026-2714(94)90152-x.

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Asai, Takahiro. "Optimum design of multistage synchronous sampling rate converter." Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 86, no. 4 (December 13, 2002): 26–37. http://dx.doi.org/10.1002/ecjc.10015.

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Ritter, Axel, and Carlos M. Regalado. "Roving revisited, towards an optimum throughfall sampling design." Hydrological Processes 28, no. 1 (October 23, 2012): 123–33. http://dx.doi.org/10.1002/hyp.9561.

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Bakhshi, Ziaul. "STOCHASTIC OPTIMIZATION IN MULTIVARIATE STRATIFIED DOUBLE SAMPLING DESIGN." International Journal of Engineering Technologies and Management Research 5, no. 1 (February 8, 2020): 115–22. http://dx.doi.org/10.29121/ijetmr.v5.i1.2018.54.

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This paper deals with optimum allocation of sample size in stratified double sampling when costs are considered as random in the objective function. When costs function are random, by applying modified E. model, objective function is converted into an equivalent deterministic form. A Numerical example is presented to illustrate the computational procedure and the problem is solved by using LINGO Software.

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Varshney, Rahul, Srikant Gupta, and Irfan Ali. "An Optimum Multivariate-Multiobjective Stratified Sampling Design: Fuzzy Programming Approach." Pakistan Journal of Statistics and Operation Research 13, no. 4 (December 1, 2017): 829. http://dx.doi.org/10.18187/pjsor.v13i4.1834.

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Hao, Peng, Bo Wang, and Gang Li. "Surrogate-Based Optimum Design for Stiffened Shells with Adaptive Sampling." AIAA Journal 50, no. 11 (November 2012): 2389–407. http://dx.doi.org/10.2514/1.j051522.

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El-Shall, Hassan, and Brij M. Moudgil. "Design of Optimum Sampling Plans for Dry Powders and Slurries." KONA Powder and Particle Journal 31 (2014): 82–91. http://dx.doi.org/10.14356/kona.2014014.

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11

Ghufran, Shazia, Saman Khowaja, and M. J. Ahsan. "Optimum multivariate stratified double sampling design: Chebyshev's Goal Programming approach." Journal of Applied Statistics 42, no. 5 (January 8, 2015): 1032–42. http://dx.doi.org/10.1080/02664763.2014.995603.

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Alvarez, A., and B. Mourre. "Optimum Sampling Designs for a Glider–Mooring Observing Network." Journal of Atmospheric and Oceanic Technology 29, no. 4 (April 1, 2012): 601–12. http://dx.doi.org/10.1175/jtech-d-11-00105.1.

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Abstract Ocean observing systems (OOSs) constituted by moorings and gliders are becoming relevant in oceanographic and climate studies. In these observing networks, the temporal variability is captured by mooring observations, while the spatial variability is obtained from gliders sampling in the surrounding area. The advent of this observing capability brings the need to find optimal procedures to sample a given ocean region with a glider in the presence of a neighboring mooring, in order to maximize the information content of the data collected by this observing network. Different criteria (e.g., A, G, or E optimality) commonly used in the geosciences to obtain an optimum design lead to different sampling strategies. The question of which criterion performs better for optimal design in the marine environment remains open. This work investigates optimal procedures to sample a given ocean region with a glider in the presence of a mooring. Specifically, observing systems simulation experiments (OSSEs) are carried out in the Ligurian Sea (western Mediterranean) in August 2010 to study the different sampling strategies. Three criteria, which respectively aim at minimizing the trace (A optimal), maximum diagonal value (G optimal), and maximum eigenvalue of the error covariance matrix (E optimal), are considered. The resulting temperature field estimations are evaluated against a control field at 50-, 100-, and 150-m depth. The results indicate that the most appropriate strategy for environmental characterization using gliders employs the A optimal criterion, minimizing the mean uncertainty over the study area.

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Fatima, Ummatul, Shazia Ghufran, and M. J. Ahsan. "The problem of optimum allocation in multivariate stratified sampling." South Pacific Journal of Natural and Applied Sciences 30, no. 1 (2012): 65. http://dx.doi.org/10.1071/sp12007.

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Generally, sample surveys are multivariate in nature where multiple response are obtained on every unit selected in a sample, that is, more than one characteristics are defined on each and every unit of the population. While dealing with a multivariate stratified population, to workout an allocation that is optimum for all characteristics is almost impossible unless the characteristics are highly correlated. Some compromise must be allowed to obtain an allocation that is optimum, in some sense, for all the characteristics. Since such allocations are based on some compromise criteria they are known as compromise allocations. This paper deals with the problem of obtaining an optimum allocation in multivariate stratified sampling design.

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Mohammad, N., MS Islam, KS Rahman, MM Rahman, and MM Rahman. "Optimum sampling plan of yield contributing characters of pointed gourd." Bangladesh Journal of Agricultural Research 42, no. 2 (June 7, 2017): 301–7. http://dx.doi.org/10.3329/bjar.v42i2.32816.

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To improve efficiency in collecting data from field experiment on fruit attributes of pointed gourd (Patal) the sample size was studied for determining optimum sample size at Olericulture Division, Horticulture Research Centre (HRC) of Bangladesh Agricultural Research Institute (BARI) Gazipur during 2013-14. Fruit length, breadth and weight data were used to design optimum sampling plan for equal number of observations per cell. The observation on fruit length (cm), breadth (cm) and weight (gm) were taken from 7 plots/treatments at random. A randomized complete block design (RCBD) with 2 replications and seven treatments/varieties were used in this experiment. A sampling plan of selecting 3 plants at random and measuring 9 fruits per selected plant (27 fruits per plot and plots were 5m2 i.e. 2.5m long and 2m wide) was found to be optimum and economy for the measurement of fruit attributes of pointed gourd. It saves time required for constant vigilance opening of flower and subsequent observations.Bangladesh J. Agril. Res. 42(2): 301-307, June 2017

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Balan, Ramkumar T., and Expery Massawe. "Optimum Sampling Plan on Quality Indices AOQL and MAPD." Transactions on Machine Learning and Artificial Intelligence 10, no. 5 (October 18, 2022): 57–66. http://dx.doi.org/10.14738/tmlai.105.13168.

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This paper describes a selection procedure for an Optimum Sampling Plan, offering maximum consumer protection in terms of AOQL and MAPD. The greatest lower bound (glb) property of AOQL for a fixed MAPD is used to design the plan offering highest precision on outgoing quality for the lot. Tables for optimum sampling plans corresponding to specified MAPD and g l b of AOQL are listed along with AQL. Empirical relation to determine AOQL for given acceptance number and MAPD is determined. Also an approximated acceptance number function in terms of (MAPD, AOQL) is developed. Lower and Upper bounds of AOQL for some parametric sampling plans are listed.

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Zhou, Wenhui, and Zhaotong Lian. "Optimum design of a new VSS-NP chart with adjusting sampling inspection." International Journal of Production Economics 129, no. 1 (January 2011): 8–13. http://dx.doi.org/10.1016/j.ijpe.2010.07.045.

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Varshney, Rahul, Najmussehar, and M. J. Ahsan. "An optimum multivariate stratified double sampling design in presence of non-response." Optimization Letters 6, no. 5 (April 21, 2011): 993–1008. http://dx.doi.org/10.1007/s11590-011-0329-8.

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Islam, Md Saiful. "Estimation of optimum sample size and number of replications in split-split plot design." Bangladesh Journal of Agricultural Research 32, no. 3 (January 8, 2008): 403–11. http://dx.doi.org/10.3329/bjar.v32i3.542.

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In field experiments, it is necessary to determine the optimum sample size as well as optimum number of replications if researchers have to use sampling techniques for collecting data from such experiments. Estimates of such optimum sample size and number of replications has been determined for split-split plot design minimizing the variance for a given cost of the experiment per treatment.DOI: http://dx.doi.org/10.3329/bjar.v32i3.542Bangladesh J. Agril. Res. 32(3) : 403-411, September 2007

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Quinino, Roberto da Costa, Linda Lee Ho, and Emílio Suyama. "Design of economically optimal zero-defect acceptance sampling with rectification when diagnosis errors are present." Pesquisa Operacional 25, no. 1 (April 2005): 29–44. http://dx.doi.org/10.1590/s0101-74382005000100003.

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In this paper we present the optimum sampling size in zero-defect acceptance with rectification sampling scheme in the presence of misclassification errors. Its development is based on an economical model. The procedures are implemented in a program using the software Matlab and illustrated by an example.

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Daimon, Takashi, and Masashi Goto. "OPTIMUM DESIGN OF SAMPLING TIMES FOR INFERENCE OF COMPARTMENT MODELS BASED ON CURVATURE." Journal of the Japanese Society of Computational Statistics 16, no. 1 (2003): 23–38. http://dx.doi.org/10.5183/jjscs1988.16.23.

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Panayirci, E., T. Ozugur, and H. Caglar. "Design of optimum Nyquist signals based on generalized sampling theory for data communications." IEEE Transactions on Signal Processing 47, no. 6 (June 1999): 1753–59. http://dx.doi.org/10.1109/78.765161.

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22

Sager, Sebastian. "Sampling Decisions in Optimum Experimental Design in the Light of Pontryagin's Maximum Principle." SIAM Journal on Control and Optimization 51, no. 4 (January 2013): 3181–207. http://dx.doi.org/10.1137/110835098.

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23

Chen, Chung-Ho, and Chao-Yu Chou. "Fuzzy optimum design of Dodge–Romig sampling rectifying inspection plan under quality investment." Journal of Industrial and Production Engineering 30, no. 5 (July 2013): 296–302. http://dx.doi.org/10.1080/21681015.2013.830650.

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Varshney, Rahul, M. J. Ahsan, and M. G. M. Khan. "An Optimum Multivariate Stratified Sampling Design with Nonresponse: A Lexicographic Goal Programming Approach." Journal of Mathematical Modelling and Algorithms 10, no. 4 (October 25, 2011): 393–405. http://dx.doi.org/10.1007/s10852-011-9164-2.

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Trittler, Stefan, and Fred A. Hamprecht. "Near optimum sampling design and an efficient algorithm for single tone frequency estimation." Digital Signal Processing 19, no. 4 (July 2009): 628–39. http://dx.doi.org/10.1016/j.dsp.2008.10.003.

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26

Fu, Pei, Jiang Huang, Ming Zhong Jin, Min Qing Gong, and Xue Ni Pan. "Grinding Spindle Improvement Based on Structure Optimal Design." Applied Mechanics and Materials 454 (October 2013): 118–22. http://dx.doi.org/10.4028/www.scientific.net/amm.454.118.

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For the structure optimization design of grinder Cui Zhong etc. [1,2] studied problems such like to select sample points which are used to structure the approximate model, to apply optimal Latin hypercube principle in the experimental design, and to take advantage of radical basis function. To minimize error they optimized models by using mathematical programming also. In our paper here using the methods in [1, we construct a model using CAD for grinding components, on the basis of optimum structural design procedure we deal with grinding spindle with structural analysis, sampling point selection, and optimum design, such that we greatly improve the design of high-speed grinding spindle on the wheel frame of CNC8312A[.

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Shu, Leshi, Ping Jiang, Li Wan, Qi Zhou, Xinyu Shao, and Yahui Zhang. "Metamodel-based design optimization employing a novel sequential sampling strategy." Engineering Computations 34, no. 8 (November 6, 2017): 2547–64. http://dx.doi.org/10.1108/ec-01-2016-0034.

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Purpose Metamodels are widely used to replace simulation models in engineering design optimization to reduce the computational cost. The purpose of this paper is to develop a novel sequential sampling strategy (weighted accumulative error sampling, WAES) to obtain accurate metamodels and apply it to improve the quality of global optimization. Design/methodology/approach A sequential single objective formulation is constructed to adaptively select new sample points. In this formulation, the optimization objective is to select a sample point with the maximum weighted accumulative predicted error obtained by analyzing data from previous iterations, and a space-filling criterion is introduced and treated as a constraint to avoid generating clustered sample points. Based on the proposed sequential sampling strategy, a two-step global optimization approach is developed. Findings The proposed WAES approach and the global optimization approach are tested in several cases. A comparison has been made between the proposed approach and other existing approaches. Results illustrate that WAES approach performs the best in improving metamodel accuracy and the two-step global optimization approach has a great ability to avoid local optimum. Originality/value The proposed WAES approach overcomes the shortcomings of some existing approaches. Besides, the two-step global optimization approach can be used for improving the optimization results.

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SRIVASTAVA, PREETI WANTI, and DEEPMALA SHARMA. "BILEVEL PROGRAMMING BASED TIME CENSORED STEP-STRESS PALTSP USING TAMPERED FAILURE RATE MODEL AND WARRANTY." International Journal of Reliability, Quality and Safety Engineering 21, no. 05 (September 18, 2014): 1450022. http://dx.doi.org/10.1142/s0218539314500223.

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This paper deals with optimal design of time-censored step-stress partially accelerated life test sampling plan (PALTSP) using Burr type-XII life distribution. The Burr type XII distribution has been found appropriate for modeling failures that occur with less frequency and also when there is high occurrence of early failures. This distribution has been found appropriate for accelerated life testing experiments. The optimum sampling plan obtained using bilevel programming approach consists in finding optimum sample size and optimum stress change point by minimizing expected total cost per lot comprising warranty costs with respect to acceptance or rejection of the lot, sampling cost and testing cost such that the producer's and consumer's interested are safeguarded. The methods developed has been illustrated using an example and sensitivity analyses carried out.

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Pennock, D. J., T. T. Yates, and J. T. Braidek. "Towards optimum sampling for regional-scale N2O emission monitoring in Canada." Canadian Journal of Soil Science 86, no. 3 (May 1, 2006): 441–50. http://dx.doi.org/10.4141/s05-104.

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There is an increasing need for field monitoring studies of N2O emissions to assess the reliability of process models. Our goal is to review the issues surrounding the design of monitoring and regional upscaling of fieldmeasured N2O emissions for Canadian conditions. Management history creates a range of controlling conditions and emission responses for each land use present in the study region and multiple fields should be sampled within each land use class. The requirement for multiple sample fields necessitates chamber-based sampling designs (ideally in conjunction with site-specific micrometeorological measurements). Uniformly minimum variance unbiased (UMVU) estimators have been recommended for estimation of the mean and variance of the sample distributions, but use of these estimators is limited where zero or negative values occur. Three basic annual emission patterns are observed across a range of N2O studies: background, seasonal, and event + seasonal. The event + seasonal pattern (where short duration, high emission events are superimposed on an underlying seasonal pattern) is common in Canadian agroecosystems. Background and seasonal annual patterns can be effectively captured with biweekly or even triweekly samplings. For the event + seasonal patterns more frequent samplings at periods when emission are believed to be higher (e.g., snow melt or post-fertilization events) are required. Linear interpolation of emissions between the sporadic measurements is the simplest and most reproducible method of temporal interpolation. Spatial extrapolation of the measured emissions is typically done by a measure and multiply approach, where the measured emissions for a given class are multiplied by the area of the class. The methods used to define the soil wetness, land use, and management classes should be clearly defined and consistently applied. The lack of information on the duration and magnitude of event-based emissions and the diurnal pattern of emissions is a major limitation to temporal interpolation. Key words: Greenhouse gas, upscaling, geographical information systems, landscape

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Hossain, Shakhawat, Nass Toufiq Tayeb, Farzana Islam, Mosab Kaseem, P. D. H. Bui, M. M. K. Bhuiya, Muhammad Aslam, and Kwang-Yong Kim. "Enhancement of Mixing Performance of Two-Layer Crossing Micromixer through Surrogate-Based Optimization." Micromachines 12, no. 2 (February 19, 2021): 211. http://dx.doi.org/10.3390/mi12020211.

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Optimum configuration of a micromixer with two-layer crossing microstructure was performed using mixing analysis, surrogate modeling, along with an optimization algorithm. Mixing performance was used to determine the optimum designs at Reynolds number 40. A surrogate modeling method based on a radial basis neural network (RBNN) was used to approximate the value of the objective function. The optimization study was carried out with three design variables; viz., the ratio of the main channel thickness to the pitch length (H/PI), the ratio of the thickness of the diagonal channel to the pitch length (W/PI), and the ratio of the depth of the channel to the pitch length (d/PI). Through a primary parametric study, the design space was constrained. The design points surrounded by the design constraints were chosen using a well-known technique called Latin hypercube sampling (LHS). The optimal design confirmed a 32.0% enhancement of the mixing index as compared to the reference design.

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Zeng, Fanqi, Jianguo Bu, Yan Yu, Haoran Bian, Lei Yang, and Xinyun Zi. "Optimum design of permanent magnet synchronous generator based on MaxPro sampling and kriging surrogate model." IEEJ Transactions on Electrical and Electronic Engineering 15, no. 2 (November 25, 2019): 278–90. http://dx.doi.org/10.1002/tee.23055.

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Liu, Xiaofeng. "Statistical Power and Optimum Sample Allocation Ratio for Treatment and Control Having Unequal Costs per Unit of Randomization." Journal of Educational and Behavioral Statistics 28, no. 3 (September 2003): 231–48. http://dx.doi.org/10.3102/10769986028003231.

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This article considers optimal sample allocation between the treatment and control condition in multilevel designs when the costs per sampling unit vary due to treatment assignment. Optimal unequal allocation may reduce the cost from that of a balanced design without sacrificing any power. The optimum sample allocation ratio depends only on the cost ratio between the treatment and control regardless of whether the randomization of sampling units occurs at levels 1, 2, or 3. Power functions for the exact tests for the main effect of treatment are derived for prototypical multilevel designs with unequal sample sizes in the treatment and control condition.

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Brahim, MAHIDDINI. "Optimum design of a spur gear using a two level optimization approach." Mechanics 25, no. 4 (August 28, 2019): 304–12. http://dx.doi.org/10.5755/j01.mech.25.4.18994.

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In this paper, we present a two level optimization approach in order to enhance the design process of a one-stage speed reducer. The proposed design methodology is performed using genetic algorithms which are judiciously combined with the use of :i) analytical models (1stlevel) and ii) Finite Element Method (FEM)based models ( 2nd level), to evaluate design candidates. Indeed, the use of CAD-CAE tools to develop higher fidelity FEM models allows to re-evaluate the attained first level designs, while accounting for new design parameters and advanced aspects which have been ignored in the first level. In order to minimize the computational burden, a metamodel based optimization technique is adopted at this second level. To illustrate the efficiency of the proposed approach, a case study of a spur gear based reducer is presented where the design of experiments is built using Hypercube Latin Sampling and surrogate models are constructed using Radial Basic Functions.

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Nie, Yi Zhen. "Design of Quantum Communication Broadband Amplifier Based on Photoelectric Diode." Applied Mechanics and Materials 539 (July 2014): 169–72. http://dx.doi.org/10.4028/www.scientific.net/amm.539.169.

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according to the special requirements of quantum optics experiments, through the optimum design of broadband low noise amplifier circuit, this paper developed a broadband low noise photoelectric detector. We focus on the analysis of the factors affecting the photoelectric detector gain, bandwidth and noise, by a suitable choice of the photodiode, a sampling resistor, feedback resistor and capacitor, the broadband low noise photoelectric detector. Experiments show that, this circuit can be used for broadband low noise quantum communication circuit.

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Albak, Emre İsa, Erol Solmaz, and Ferruh Öztürk. "Optimal design of differential mount using nature-inspired optimization methods." Materials Testing 63, no. 8 (August 1, 2021): 764–69. http://dx.doi.org/10.1515/mt-2021-0006.

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Abstract Structural performance and lightweight design are a significant challenge in the automotive industry. Optimization methods are essential tools to overcome this challenge. Recently, nature-inspired optimization methods have been widely used to find optimum design variables for the weight reduction process. The objective of this study is to investigate the best differential mount design using nature-based optimum design techniques for weight reduction. The performances of the nature-based algorithms are tested using convergence speed, solution quality, and robustness to find the best design outlines. In order to examine the structural performance of the differential mount, static analyses are performed using the finite element method. In the first step of the optimization study, a sampling space is generated by the Latin hypercube sampling method. Then the radial basis function metamodeling technique is used to create the surrogate models. Finally, differential mount optimization is performed by using genetic algorithms (GA), particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), ant lion optimizer (ALO) and dragonfly algorithm (DA), and the results are compared. All methods except PSO gave good and close results. Considering solution quality, robustness and convergence speed data, the best optimization methods were found to be MFO and ALO. As a result of the optimization, the differential mount weight is reduced by 14.6 wt.-% compared to the initial design.

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Nakayama, Shotaro, Gerrit Blacquière, and Tomohide Ishiyama. "Automated survey design for blended acquisition with irregular spatial sampling via the integration of a metaheuristic and deep learning." GEOPHYSICS 84, no. 4 (July 1, 2019): P47—P60. http://dx.doi.org/10.1190/geo2018-0826.1.

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Blended acquisition along with efficient detector and source geometries allows for a cost-effective operation. The outcome of subsequent deblending and data reconstruction is of primary importance in determining the technical success of this manner of data acquisition. Despite its advantages over conventional seismic surveys, finding optimum survey parameters is a difficult task. Although incorporating irregularity into spatial sampling and blending schemes leads to effective deblending and data reconstruction, it inherently provides a significantly large problem space. We have developed a survey-design workflow to provide acquisition parameters that account for the source blending as well as the spatial sampling of detectors and sources in an automated manner. Our method involves an iterative scheme to derive the survey parameters that lead to optimum deblending and data reconstruction quality. The approach deals jointly with deblending and data-reconstruction via a sparse inversion in the frequency-wavenumber domain coupled with constraints based on causality and coherency. The residue from this process is subsequently used to update the survey parameters by integrating a genetic algorithm and a convolutional neural network (CNN). Bioinspired operators enable the simultaneous update of the blending and sampling operators. To relate the choice of survey parameters to the performance of deblending and data reconstruction, we have used a CNN. The applied network architecture successfully rejects suboptimal solutions among newly generated ones from genetic operators. Consequently, only optimal ones are fed into the subsequent step, making our approach computationally affordable. We apply our workflow to design a seismic survey that incorporates the dispersed source array concept. A comparison among different survey-design strategies highlights the ability of the method to effectively derive optimum solutions. The resultant acquisition scenario derived from our approach yields a notable enhancement of deblending and data reconstruction quality attributed solely to the choice of survey parameters.

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Agegnehu, Dejen, P. K. Mahajan, and R. K. Gupta. "An alternative approach for construction of strata using quantified sensitivity level." Journal of Applied and Natural Science 13, no. 3 (September 15, 2021): 807–14. http://dx.doi.org/10.31018/jans.v13i3.2679.

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The study is investigated on an alternative method for the construction of strata using sensitivity level when the samples are selected with simple random sampling with replacement (SRSWR) and the data are collected by scrambled optional randomization technique on the sensitive characters. Thus, the optional randomized response model , where k is a random variable having value 1 if the response is scrambled and 0 otherwise, was considered for finding out Approximate Optimum Strata Boundaries by minimizing the variance of the estimator . The cum. was proposed for finding out Approximate Optimum Strata Boundary in Neyman allocation for the optional scrambled response. This is applicable for wider classes of sampling design and estimators in stratification. The proposed rule on optional scrambled randomized response is efficient and can be used effectively for the construction of optimum strata boundary via Rectangular, Right triangular and Exponential distribution.

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Khanday, Manzoor A., and J. R. Singh. "Economic Design of X̅ Control Chart under Double EWMA." Journal of Modern Applied Statistical Methods 18, no. 2 (October 2, 2020): 2–12. http://dx.doi.org/10.22237/jmasm/1604189520.

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Designing of parameters plays an important role in economic design of control charts for lowering the cost and time. Manipulating sample size (n) and sampling interval (h), the effect of double exponentially weighted moving average (DEWMA) model was studied for the Economic Design (ED) of X̅ control chart. Optimum sizes and level were obtained when the characteristics of an item possesses DEWMA model. When shifts are uncertain the optimal design for DEWMA chart should be more conservative and should be implemented for benefiting the consumers as well as producers.

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Feng, Jing, Jian Li Zhang, and Yong Tao Ma. "Analysis on High-Speed Sampling Device with Big Interior Force." Advanced Materials Research 291-294 (July 2011): 1564–67. http://dx.doi.org/10.4028/www.scientific.net/amr.291-294.1564.

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For the biggest top steel ring, the sampling device characteristic seriously influences on precision sampling. The simulation model was built in AMESim and certificated by experiments. Through simulation, the external load and the car interior are important factors in speed stability. It derived the calculation formula on external load and compared with experimental results. Under the load limit, the velocity will stable with load change. Above the load limit, the velocity will fluctuate violently. An overweight car prolongs the starting time and aggravates the braking vibration. Under a reasonable design specification, 300kg is optimum. These conclusions had been applied in this newly designed device effectively.

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Varshney, R., and Mradula. "Optimum allocation in multivariate stratified sampling design in the presence of nonresponse with Gamma cost function." Journal of Statistical Computation and Simulation 89, no. 13 (May 25, 2019): 2454–67. http://dx.doi.org/10.1080/00949655.2019.1620747.

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Zheng, Jun, Zilong Li, Liang Gao, and Guosheng Jiang. "A parameterized lower confidence bounding scheme for adaptive metamodel-based design optimization." Engineering Computations 33, no. 7 (October 3, 2016): 2165–84. http://dx.doi.org/10.1108/ec-04-2015-0088.

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Purpose The purpose of this paper is to efficiently use as few sample points as possible to get a sufficiently explored design space and an accurate optimum for adaptive metamodel-based design optimization (AMBDO). Design/methodology/approach A parameterized lower confidence bounding (PLCB) scheme is proposed in which a cooling strategy is introduced to guarantee the balance between exploitation and exploration by varying weights of the predicting error and optimum of a metamodel. The proposed scheme is investigated by a set of test functions and a structural optimization problem, in which PLCB with four kinds of cooling control functions are studied. Moreover, other infill criteria (such as expected improvement and its extension versions) are taken into comparison. Findings Results show that the proposed PLCB (especially PLCB with the first cooling control function) based AMBDO method can find the optimum with fewer evaluations and maintain good accuracy, which means the proposed PLCB contributes to the excellent efficiency and accuracy in finding global optimal solutions. Originality/value The parameterized version of the lower confidence bound metric is proposed for AMBDO, typically used in the context of adaptive sampling in efficient global optimization.

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Zhang, Si Liang, Ping Zhu, and Wei Chen. "Multi-Point Sequential Sampling Method for Complex Engineering Optimization Problems." Applied Mechanics and Materials 201-202 (October 2012): 78–82. http://dx.doi.org/10.4028/www.scientific.net/amm.201-202.78.

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Metamodeling techniques are commonly used to replace expensive computer simulations in complex engineering optimization problems. Due to the discrepancy between the simulation model and metamodel, the prediction error in predicted responses may lead to a wrong solution. To balance the predicted mean and prediction error, the efficient global optimization (EGO) algorithm using Kriging predictor can be used to explore the design space and find next sample to adaptively improve the fitting accuracy of the predicted responses. However in conventional EGO algorithm, adding one point per iteration may be not efficient for the complex engineering problems. In this paper, a new multi-point sequential sampling method is proposed to include multiple points per iteration. To validate the benefits of the proposed multi-point sequential sampling method, a mathematical example and a highly-nonlinear automotive crashworthiness design example are illustrated. Results show that the proposed method can efficiently mitigate the prediction error and find the global optimum using fewer iterations.

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Zhang, Lizhang, Dong Mi, Cheng Yan, and Fangming Tang. "Multidisciplinary Design Optimization for a Centrifugal Compressor Based on Proper Orthogonal Decomposition and an Adaptive Sampling Method." Applied Sciences 8, no. 12 (December 13, 2018): 2608. http://dx.doi.org/10.3390/app8122608.

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A centrifugal compressor is required to increase aerodynamic efficiency, ensure structural integrity, and reduce processing costs. This paper presents a dimension reduction technique based on proper orthogonal decomposition (POD) in combination with an adaptive sampling method to reduce computational costs. Design of experiment (DOE) is first used to choose initial sampling points. Then, parts of the sampling points are selected to format the snapshot matrix. Subsequently, the number of principal components to be retained is determined after POD analysis. An adaptive sampling point adding approach is used to increase new sampling points. The approach places more points around the regions of initial optimum designs by learning the information from previous data through POD analysis. Finally, the POD coefficients are selected to act as new design variables in the following multidisciplinary design optimization process. The method is first tested by three mathematical benchmark functions. The proposed method is then used to optimize a centrifugal compressor, of which the results are verified by tests. A normalized isentropic efficiency improvement of 3.7% and 3.0% in the maximum speed state and cruise state has been obtained after optimization. Additionally, the processing costs are reduced by about 30% owing to the number of blades reduced.

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Vasudeva, G., and B. V. Uma. "Design and Implementation of High Speed and Low Power 12-bit SAR ADC using 22nm FinFET." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 17 (January 3, 2022): 1–15. http://dx.doi.org/10.37394/23203.2022.17.1.

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Successive Approximation Register (SAR) Analog to Digital Converter (ADC) architecture comprises of sub modules such as comparator, Digital to Analog Converter and SAR logic. Each of these modules imposes challenges as the signal makes transition from analog to digital and vice-versa. Design strategies for optimum design of circuits considering 22nm FinFET technology meeting area, timing, power requirements and ADC metrics is presented in this work. Operational Transconductance Amplifier (OTA) based comparator, 12-bit two stage segmented resistive string DAC architecture and low power SAR logic is designed and integrated to form the ADC architecture with maximum sampling rate of 1 GS/s. Circuit schematic is captured in Cadence environment with optimum geometrical parameters and performance metrics of the proposed ADC is evaluated in MATLAB environment. Differential Non Linearity and Integral Non Linearity metrics for the 12-bit ADC is limited to +1.15/-1 LSB and +1.22/-0.69 LSB respectively. ENOB of 10.1663 with SNR of 62.9613 dB is achieved for the designed ADC measured for conversion of input signal of 100 MHz with 20dB noise. ADC with sampling frequency upto 1 GSps is designed in this work with low power dissipation less than 10 mW.

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Deng, Zhenzhou, Yushan Deng, and Guandong Chen. "Design and Evaluation of LYSO/SiPM LIGHTENING PET Detector with DTI Sampling Method." Sensors 20, no. 20 (October 15, 2020): 5820. http://dx.doi.org/10.3390/s20205820.

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Positron emission tomography (PET) has a wide range of applications in the treatment and prevention of major diseases owing to its high sensitivity and excellent resolution. However, there is still much room for optimization in the readout circuit and fast pulse sampling to further improve the performance of the PET scanner. In this work, a LIGHTENING® PET detector using a 13 × 13 lutetium-yttrium oxyorthosilicate (LYSO) crystal array read out by a 6 × 6 silicon photomultiplier (SiPM) array was developed. A novel sampling method, referred to as the dual time interval (DTI) method, is therefore proposed to realize digital acquisition of fast scintillation pulse. A semi-cut light guide was designed, which greatly improves the resolution of the edge region of the crystal array. The obtained flood histogram shown that all the 13 × 13 crystal pixels can be clearly discriminated. The optimum operating conditions for the detector were obtained by comparing the flood histogram quality under different experimental conditions. An average energy resolution (FWHM) of 14.3% and coincidence timing resolution (FWHM) of 972 ps were measured. The experimental results demonstrated that the LIGHTENING® PET detector achieves extremely high resolution which is suitable for the development of a high performance time-of-flight PET scanner.

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Mohammad, N., MS Islam, KS Rahman, MM Rahman, and S. Nasrin. "Determination of optimum sample size for measuring the contributing characters of bottle gourd." Bangladesh Journal of Agricultural Research 40, no. 4 (March 2, 2016): 703–9. http://dx.doi.org/10.3329/bjar.v40i4.26944.

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To improve efficiency in collecting data from field experiment on fruit attributes of bottle gourd (Lau), the sample size was studied for sample size at Olericulture Division, Horticulture Research Centre (HRC) of Bangladesh Agricultural Research Institute (BARI) Gazipur during 2012-13. The treatments/varieties were LS 0026-5-3, LS 0012-5-3, LS 117-F-1, LS 117-A-2 and BARI Lau-3. Fruit length, breadth and weight of bottle gourd (Lau) data were collected from the experimental plot. The data were used to design optimum sampling plan from equal number of observations per cell. The observation on fruit length (cm), breadth (cm) and weight (kg) were taken from 5 plots/treatments at random. A randomized complete block design (RCBD) with 3 replications and five treatments/varieties was used in this experiment. Five (5) plants per plot and 2 fruits per plants (10 fruits per plot) were the original sampling plan for this experiment. A sampling plan of selecting 4 plants at random and measuring 2 fruits per selected plant (8 fruits per plot and plots were 25m2 i.e. 10m long and 2.5m wide) was found to be optimum and economical for taking measurements of fruit attributes in field experiments on bottle gourd.Bangladesh J. Agril. Res. 40(4): 703-709, December 2015

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Priya, P. Kavi, and A. R. Sudamani Ramaswamy. "A DESIGN OF SPECIAL PURPOSE DOUBLE SAMPLING PLAN OF TYPE DSP(0, 1) USING FUZZY PARAMETER." South East Asian J. of Mathematics and Mathematical Sciences 18, no. 02 (September 26, 2022): 319–30. http://dx.doi.org/10.56827/seajmms.2022.1802.27.

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In traditional sampling plan, the proportion defective is generally assumed to be crisp value. But, in real life parameters are vague and assumptions are too rigid. So traditional methods are inaccurate. In this paper Fuzzy set theory is applied to acceptance sampling. A procedure for designing Special Purpose Double Sampling Plan of Type DSP(0, 1) using trapezoidal fuzzy number is developed and it is based on fuzzy binomial distribution. The OC curve values are determined using fuzzy parameter while fixing the sample size. Fuzzy probability of acceptance values are calculated for different AQL ] and LQL ] values and are presented in Tables for the selection of DSP(0, 1) Plan. Optimum value of the sample size is obtained such that it satisfies both the condition of producer’s risk and consumer’s risk for given AQL ] and LQL ] values. The sample size is obtained such that it minimizes the sum of risks. Numerical examples are provided for the illustrations.

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McGee, E. J., M. J. Keatinge, H. J. Synnott, and P. A. Colgan. "The Variability in Fallout Content of Soils and Plants and the Design of Optimum Field Sampling Strategies." Health Physics 68, no. 3 (March 1995): 320–27. http://dx.doi.org/10.1097/00004032-199503000-00003.

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Zhang, Siliang, Zhengchao Song, Guohong Shi, and Rongying Qiu. "Adaptive multi-point sequential sampling methodology for high-dimensional and highly nonlinear crashworthiness optimization problems." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 231, no. 10 (December 23, 2015): 1816–25. http://dx.doi.org/10.1177/0954406215624722.

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Metamodel-based crashworthiness optimization is an expensive and highly nonlinear design problem. Due to the lack of finite element simulations, the responses fitted by different metamodeling methods are not fully equivalent to the real responses. The metamodel error may induce to find a local or an infeasible design solution. Compared to the traditional one-step sampling DOE method, the objective-oriented sequential sampling strategies have been demonstrated as a higher efficient way to find the true optimum design. However, existing infilling criteria of the sequential sampling methods are restricted to specify the number of the sequential samples obtained in each iteration. It is not practical for the real engineering optimization applications. In this paper, a new adaptive multi-point sequential sampling method is developed. The sequential samples obtained in each iteration are determined by the prediction states of the fitting metamodels. To demonstrate the benefits, the new proposed method is applied to a high-dimensional and highly nonlinear frontal crashworthiness optimization problem. Results show that the proposed method can mitigate the effect of the metamodel prediction error and more efficiently find the global design solution compared to the conventional approach.

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Shahzad, Faisal, Zhensheng Huang, and Ambreen Shafqat. "The Design of GLR Control Chart for Monitoring the Geometric Observations Using Sequential Sampling Scheme." Symmetry 12, no. 12 (November 27, 2020): 1964. http://dx.doi.org/10.3390/sym12121964.

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The control charts’ design is focused on system forecasting which is important in mathematics and statistics; these techniques are commonly employed in manufacturing industries. The need for a control chart that can conceptualize and identify the symmetric or asymmetric structure of the monitoring phase with more than one aspect of the standard attribute is a necessity of industries. The generalized likelihood ratio (GLR) chart is a well-known method to track both the decrease and increase in the mechanism effectively. A control chart, termed as a GLR control chart, is established in this article, focusing on a sequential sampling scheme (the SS GLR chart) to evaluate the geometrically distributed process parameter. The SS GLR chart statistic is examined on a window of past samples. In contexts of the steady-state average time to signal, the output of the SS GLR control chart is analyzed and compared with the non-sequential geometric GLR chart and the cumulative sum (CUSUM) charts. In this article, the optimum parameter options are presented, and regression equations are established to calculate the SS GLR chart limits.

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Journal articles on the topic 'Optimum Sampling Design'

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