**Commenced**in January 2007

**Frequency:**Monthly

**Edition:**International

**Paper Count:**1541

# Search results for: variable sampling interval

##### 1541 A Markov Chain Approximation for ATS Modeling for the Variable Sampling Interval CCC Control Charts

**Authors:**
Y. K. Chen,
K. C. Chiou,
C. Y. Chen

**Abstract:**

**Keywords:**
Cumulative conformance count,
variable sampling
interval,
Markov Chain,
average time to signal,
control chart.

##### 1540 New Product-Type Estimators for the Population Mean Using Quartiles of the Auxiliary Variable

**Authors:**
Amer Ibrahim Falah Al-Omari

**Abstract:**

In this paper, we suggest new product-type estimators for the population mean of the variable of interest exploiting the first or the third quartile of the auxiliary variable. We obtain mean square error equations and the bias for the estimators. We study the properties of these estimators using simple random sampling (SRS) and ranked set sampling (RSS) methods. It is found that, SRS and RSS produce approximately unbiased estimators of the population mean. However, the RSS estimators are more efficient than those obtained using SRS based on the same number of measured units for all values of the correlation coefficient.

**Keywords:**
Product estimator,
auxiliary variable,
simple random
sampling,
extreme ranked set sampling

##### 1539 Computational Aspects of Regression Analysis of Interval Data

**Authors:**
Michal Cerny

**Abstract:**

We consider linear regression models where both input data (the values of independent variables) and output data (the observations of the dependent variable) are interval-censored. We introduce a possibilistic generalization of the least squares estimator, so called OLS-set for the interval model. This set captures the impact of the loss of information on the OLS estimator caused by interval censoring and provides a tool for quantification of this effect. We study complexity-theoretic properties of the OLS-set. We also deal with restricted versions of the general interval linear regression model, in particular the crisp input – interval output model. We give an argument that natural descriptions of the OLS-set in the crisp input – interval output cannot be computed in polynomial time. Then we derive easily computable approximations for the OLS-set which can be used instead of the exact description. We illustrate the approach by an example.

**Keywords:**
Linear regression,
interval-censored data,
computational complexity.

##### 1538 On Some Properties of Interval Matrices

**Authors:**
K. Ganesan

**Abstract:**

**Keywords:**
Interval arithmetic,
Interval matrix,
linear equations.

##### 1537 Ranking DMUs by Ideal PPS in Data Envelopment Analysis

**Authors:**
V.Rezaie,
M.Khanmohammady

**Abstract:**

**Keywords:**
Data envelopment analysis (DEA),
Decision makingunit (DMU),
Interval DEA,
Ideal points,
Ideal PPS,
Return to scale(RTS).

##### 1536 Comparison of Two Interval Models for Interval-Valued Differential Evolution

**Authors:**
Hidehiko Okada

**Abstract:**

The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks.

**Keywords:**
Evolutionary algorithms,
differential evolution,
neural network,
neuroevolution,
interval arithmetic.

##### 1535 A Voltage Based Maximum Power Point Tracker for Low Power and Low Cost Photovoltaic Applications

**Authors:**
Jawad Ahmad,
Hee-Jun Kim

**Abstract:**

This paper describes the design of a voltage based maximum power point tracker (MPPT) for photovoltaic (PV) applications. Of the various MPPT methods, the voltage based method is considered to be the simplest and cost effective. The major disadvantage of this method is that the PV array is disconnected from the load for the sampling of its open circuit voltage, which inevitably results in power loss. Another disadvantage, in case of rapid irradiance variation, is that if the duration between two successive samplings, called the sampling period, is too long there is a considerable loss. This is because the output voltage of the PV array follows the unchanged reference during one sampling period. Once a maximum power point (MPP) is tracked and a change in irradiation occurs between two successive samplings, then the new MPP is not tracked until the next sampling of the PV array voltage. This paper proposes an MPPT circuit in which the sampling interval of the PV array voltage, and the sampling period have been shortened. The sample and hold circuit has also been simplified. The proposed circuit does not utilize a microcontroller or a digital signal processor and is thus suitable for low cost and low power applications.

**Keywords:**
Maximum power point tracker,
Sample and hold amplifier,
Sampling interval,
Sampling period.

##### 1534 Estimating the Population Mean by Using Stratified Double Extreme Ranked Set Sample

**Authors:**
Mahmoud I. Syam,
Kamarulzaman Ibrahim,
Amer I. Al-Omari

**Abstract:**

Stratified double extreme ranked set sampling (SDERSS) method is introduced and considered for estimating the population mean. The SDERSS is compared with the simple random sampling (SRS), stratified ranked set sampling (SRSS) and stratified simple set sampling (SSRS). It is shown that the SDERSS estimator is an unbiased of the population mean and more efficient than the estimators using SRS, SRSS and SSRS when the underlying distribution of the variable of interest is symmetric or asymmetric.

**Keywords:**
Double extreme ranked set sampling,
Extreme
ranked set sampling,
Ranked set sampling,
Stratified double extreme
ranked set sampling.

##### 1533 Design of Bayesian MDS Sampling Plan Based on the Process Capability Index

**Authors:**
Davood Shishebori,
Mohammad Saber Fallah Nezhad,
Sina Seifi

**Abstract:**

In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.

**Keywords:**
MDS sampling plan,
RGS plan,
sampling plan for resubmitted lots,
process capability index,
average sample number,
Bayesian approach.

##### 1532 A New Approach to Design an Efficient CIC Decimator Using Signed Digit Arithmetic

**Authors:**
Vishal Awasthi,
Krishna Raj

**Abstract:**

Any digital processing performed on a signal with larger nyquist interval requires more computation than signal processing performed on smaller nyquist interval. The sampling rate alteration generates the unwanted effects in the system such as spectral aliasing and spectral imaging during signal processing. Multirate-multistage implementation of digital filter can result a significant computational saving than single rate filter designed for sample rate conversion. In this paper, we presented an efficient cascaded integrator comb (CIC) decimation filter that perform fast down sampling using signed digit adder algorithm with compensated frequency droop that arises due to aliasing effect during the decimation process. This proposed compensated CIC decimation filter structure with a hybrid signed digit (HSD) fast adder provide an improved performance in terms of down sampling speed by 65.15% than ripple carry adder (RCA) and reduced area and power by 57.5% and 0.01 % than signed digit (SD) adder algorithms respectively.

**Keywords:**
Sampling rate conversion,
Multirate Filtering,
Compensation Theory,
Decimation filter,
CIC filter,
Redundant signed digit arithmetic,
Fast adders.

##### 1531 The Diameter of an Interval Graph is Twice of its Radius

**Authors:**
Tarasankar Pramanik,
Sukumar Mondal,
Madhumangal Pal

**Abstract:**

In an interval graph G = (V,E) the distance between two vertices u, v is de£ned as the smallest number of edges in a path joining u and v. The eccentricity of a vertex v is the maximum among distances from all other vertices of V . The diameter (δ) and radius (ρ) of the graph G is respectively the maximum and minimum among all the eccentricities of G. The center of the graph G is the set C(G) of vertices with eccentricity ρ. In this context our aim is to establish the relation ρ = δ 2 for an interval graph and to determine the center of it.

**Keywords:**
Interval graph,
interval tree,
radius,
center.

##### 1530 Computing Maximum Uniquely Restricted Matchings in Restricted Interval Graphs

**Authors:**
Swapnil Gupta,
C. Pandu Rangan

**Abstract:**

**Keywords:**
Uniquely restricted matching,
interval graph,
design
and analysis of algorithms,
matching,
induced matching,
witness
counting.

##### 1529 Ratio Type Estimators of the Population Mean Based on Ranked Set Sampling

**Authors:**
Said Ali Al-Hadhrami

**Abstract:**

Ranked set sampling (RSS) was first suggested to increase the efficiency of the population mean. It has been shown that this method is highly beneficial to the estimation based on simple random sampling (SRS). There has been considerable development and many modifications were done on this method. When a concomitant variable is available, ratio estimation based on ranked set sampling was proposed. This ratio estimator is more efficient than that based on SRS. In this paper some ratio type estimators of the population mean based on RSS are suggested. These estimators are found to be more efficient than the estimators of similar form using simple random sample.

**Keywords:**
Bias,
Efficiency,
Ranked Set Sampling,
Ratio Type Estimator

##### 1528 Particle Swarm Optimization with Interval-valued Genotypes and Its Application to Neuroevolution

**Authors:**
Hidehiko Okada

**Abstract:**

The author proposes an extension of particle swarm optimization (PSO) for solving interval-valued optimization problems and applies the extended PSO to evolutionary training of neural networks (NNs) with interval weights. In the proposed PSO, values in the genotypes are not real numbers but intervals. Experimental results show that interval-valued NNs trained by the proposed method could well approximate hidden target functions despite the fact that no training data was explicitly provided.

**Keywords:**
Evolutionary algorithms,
swarm intelligence,
particle swarm optimization,
neural network,
interval arithmetic.

##### 1527 Sampling of Variables in Discrete-Event Simulation using the Example of Inventory Evolutions in Job-Shop-Systems Based on Deterministic and Non-Deterministic Data

**Authors:**
Bernd Scholz-Reiter,
Christian Toonen,
Jan Topi Tervo,
Dennis Lappe

**Abstract:**

**Keywords:**
discrete-event simulation,
job-shop-system,
sampling rate.

##### 1526 A Fuzzy Nonlinear Regression Model for Interval Type-2 Fuzzy Sets

**Authors:**
O. Poleshchuk,
E.Komarov

**Abstract:**

This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions.

**Keywords:**
Interval type-2 fuzzy sets,
fuzzy regression,
weighted interval.

##### 1525 Solution of Interval-valued Manufacturing Inventory Models With Shortages

**Authors:**
Susovan Chakrabortty,
Madhumangal Pal,
Prasun Kumar Nayak

**Abstract:**

**Keywords:**
EOQ,
Inventory,
Interval Number,
Demand,
Production,
Simulation

##### 1524 Some Results on Interval-Valued Fuzzy BG-Algebras

**Authors:**
Arsham Borumand Saeid

**Abstract:**

In this note the notion of interval-valued fuzzy BG-algebras (briefly, i-v fuzzy BG-algebras), the level and strong level BG-subalgebra is introduced. Then we state and prove some theorems which determine the relationship between these notions and BG-subalgebras. The images and inverse images of i-v fuzzy BG-subalgebras are defined, and how the homomorphic images and inverse images of i-v fuzzy BG-subalgebra becomes i-v fuzzy BG-algebras are studied.

**Keywords:**
BG-algebra,
fuzzy BG-subalgebra,
interval-valued fuzzy set,
interval-valued fuzzy BG-subalgebra.

##### 1523 On Simple Confidence Intervals for the Normal Mean with Known Coefficient of Variation

**Authors:**
Suparat Niwitpong,
Sa-aat Niwitpong

**Abstract:**

In this paper we proposed the new confidence interval for the normal population mean with known coefficient of variation. In practice, this situation occurs normally in environment and agriculture sciences where we know the standard deviation is proportional to the mean. As a result, the coefficient of variation of is known. We propose the new confidence interval based on the recent work of Khan [3] and this new confidence interval will compare with our previous work, see, e.g. Niwitpong [5]. We derive analytic expressions for the coverage probability and the expected length of each confidence interval. A numerical method will be used to assess the performance of these intervals based on their expected lengths.

**Keywords:**
confidence interval,
coverage probability,
expected length,
known coefficient of variation.

##### 1522 Classifying and Predicting Efficiencies Using Interval DEA Grid Setting

**Authors:**
Yiannis G. Smirlis

**Abstract:**

**Keywords:**
Data envelopment analysis,
interval DEA,
efficiency classification,
efficiency prediction.

##### 1521 Optimal ECG Sampling Frequency for Multiscale Entropy-Based HRV

**Authors:**
Manjit Singh

**Abstract:**

**Keywords:**
ECG,
heart rate variability,
HRV,
multiscale entropy,
sampling frequency.

##### 1520 Digital Redesign of Interval Systems via Particle Swarm Optimization

**Authors:**
Chen-Chien Hsu,
Chun-Hui Gao

**Abstract:**

**Keywords:**
Digital redesign,
Extremal systems,
Particle swarm optimization,
Uncertain interval systems

##### 1519 Confidence Interval for the Inverse of a Normal Mean with a Known Coefficient of Variation

**Authors:**
Arunee Wongkha,
Suparat Niwitpong,
Sa-aat Niwitpong

**Abstract:**

In this paper, we propose two new confidence intervals for the inverse of a normal mean with a known coefficient of variation. One of new confidence intervals for the inverse of a normal mean with a known coefficient of variation is constructed based on the pivotal statistic Z where Z is a standard normal distribution and another confidence interval is constructed based on the generalized confidence interval, presented by Weerahandi. We examine the performance of these confidence intervals in terms of coverage probabilities and average lengths via Monte Carlo simulation.

**Keywords:**
The inverse of a normal mean,
confidence interval,
generalized confidence intervals,
known coefficient of variation.

##### 1518 Recent Trends in Nonlinear Methods of HRV Analysis: A Review

**Authors:**
Ramesh K. Sunkaria

**Abstract:**

**Keywords:**
chaos,
nonlinear dynamics,
sample entropy,
approximate entropy,
detrended fluctuation analysis.

##### 1517 CNC Wire-Cut Parameter Optimized Determination of the Stair Shape Workpiece

**Authors:**
Chana Raksiri,
Pornchai Chatchaikulsiri

**Abstract:**

**Keywords:**
CNC Wire-Cut,
Variable Thickness Workpiece,
Design of Experiments,
Full Factorial Design

##### 1516 Confidence Intervals for the Difference of Two Normal Population Variances

**Authors:**
Suparat Niwitpong

**Abstract:**

Motivated by the recent work of Herbert, Hayen, Macaskill and Walter [Interval estimation for the difference of two independent variances. Communications in Statistics, Simulation and Computation, 40: 744-758, 2011.], we investigate, in this paper, new confidence intervals for the difference between two normal population variances based on the generalized confidence interval of Weerahandi [Generalized Confidence Intervals. Journal of the American Statistical Association, 88(423): 899-905, 1993.] and the closed form method of variance estimation of Zou, Huo and Taleban [Simple confidence intervals for lognormal means and their differences with environmental applications. Environmetrics 20: 172-180, 2009]. Monte Carlo simulation results indicate that our proposed confidence intervals give a better coverage probability than that of the existing confidence interval. Also two new confidence intervals perform similarly based on their coverage probabilities and their average length widths.

**Keywords:**
Confidence interval,
generalized confidence interval,
the closed form method of variance estimation,
variance.

##### 1515 Fuzzy Logic Approach to Robust Regression Models of Uncertain Medical Categories

**Authors:**
Arkady Bolotin

**Abstract:**

Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.

**Keywords:**
Categorization,
Uncertain medical categories,
Binomial regression model,
Fuzzy dependent variable,
Robustness.

##### 1514 Switching Rule for the Exponential Stability and Stabilization of Switched Linear Systems with Interval Time-varying Delays

**Authors:**
Kreangkri Ratchagit

**Abstract:**

This paper is concerned with exponential stability and stabilization of switched linear systems with interval time-varying delays. The time delay is any continuous function belonging to a given interval, in which the lower bound of delay is not restricted to zero. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton-s formula, a switching rule for the exponential stability and stabilization of switched linear systems with interval time-varying delays and new delay-dependent sufficient conditions for the exponential stability and stabilization of the systems are first established in terms of LMIs. Numerical examples are included to illustrate the effectiveness of the results.

**Keywords:**
Switching design,
exponential stability and stabilization,
switched linear systems,
interval delay,
Lyapunov function,
linear matrix inequalities.

##### 1513 Approximate Confidence Interval for Effect Size Base on Bootstrap Resampling Method

**Authors:**
S. Phanyaem

**Abstract:**

**Keywords:**
Effect size,
confidence interval,
Bootstrap Method.

##### 1512 Multi-Rate Exact Discretization based on Diagonalization of a Linear System - A Multiple-Real-Eigenvalue Case

**Authors:**
T. Sakamoto,
N. Hori

**Abstract:**

**Keywords:**
Multi-rate discretization,
linear systems,
triangularization,
similarity transformation,
diagonalization,
exponential transformation,
multiple eigenvalues