TRUNCATION POINT IN SIMULATION

2011 ◽  
Keyword(s):  
Truncation Point

Determination of Optimal Reserve between Two Machines in Series with the Repair Time has Change of Distribution after the Truncation Point

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 577-585
Author(s):  
T. Vivekanandan ◽  
S. Sachithanantham
Keyword(s):  
Real Life ◽  
Random Variable ◽  
Repair Time ◽  
Inventory Level ◽  
Optimal Size ◽  
Truncation Point ◽  
In Series ◽  
Optimal Reserve ◽  
Optimal Inventory Level ◽  
Two Machines

In inventory control, suitable models for various real life systems are constructed with the objective of determining the optimal inventory level.  A new type of inventory model using the so-called change of distribution property is analyzed in this paper. There are two machines M1 and M2  in series and the output of M1 is the input of M2. Hence a reserve inventory between M1 and M2 is to be maintained. The method of obtaining the optimal size of reserve inventory, assuming cost of excess inventory, cost of shortage and when the rate of consumption of M2  is a constant, has already been attempted.  In this paper, it is assumed that the repair time of M1  is a random variable and the distribution of the same undergoes a change of distribution  after the truncation point X0 , which is taken to be a random variable.  The optimal size of the reserve inventory is obtained under the above said  assumption . Numerical illustrations are also provided.

Further examination on the truncation point in truncation selection for proportion-defined trait

2004 ◽  
Vol 75 (3) ◽  
pp. 193-199
Author(s):  
Masayuki SHOJO ◽  
Hiroaki IWAISAKI ◽  
Fumio MUKAI
Keyword(s):  
Truncation Point ◽  
Truncation Selection ◽  
Selection For

scholarly journals Robust Methods for Credibility

1992 ◽  
Vol 22 (1) ◽  
pp. 33-49 ◽  
Author(s):  
Hans R. Künsch
Keyword(s):  
Robust Methods ◽  
Truncation Point ◽  
Credibility Estimator ◽  
Standard Linear

AbstractExcess claims lead to an unsatisfactory behavior of standard linear credibility estimators. We suggest in this paper to use robust methods in order to obtain better estimators. Our first proposal is the linear credibility estimator with the claims replaced by a robust M-estimator of scale calculed from the claims. This corresponds to a truncation of the claims with a truncation point depending on the data and different for each contract. We discuss the properties of the robust M-estimator and present several examples. In order to improve the performance for a very small number of years, we propose a second estimator, which incorporates information from other claims into the M-estimator.

Comparison of the favorable gain values of genetic improvement among Indonesian grade cow breeds selected for agrotechnopark intensification

2021 ◽  
Vol 46 (2) ◽  
pp. 106-113
Author(s):  
U. Paputungan ◽  
M. J. Hendrik ◽  
S. E. Siswosubroto
Keyword(s):  
Standard Deviation ◽  
Genetic Improvement ◽  
Live Weight ◽  
Farming System ◽  
Selection Intensity ◽  
Truncation Point ◽  
North Sulawesi ◽  
Breed Group ◽  
Critical Components ◽  
Genetic Development

This research was aimed to compare the small and big truncation point proportions intended to evaluate gain values of genetic improvement for Indonesian Local cow breed groups selected for Agrotechnopark (integrated bio-cycle farming system) intensification. Animal live weights were collected from 674 Indonesian grade breed cows kept by local household farmers in North Sulawesi province. Data of cows were corrected by adjusting to six years old ages. All cows were divided into three breed groups with different genetic compositions of Bali breed cow generation (BG) of 207 cows, Ongole grade cow generation (OG) of 189 cows, and Local grade cow generation (LG) of 178 cows. The genetic improvements of BG, OG and LG were analyzed involving selection intensity (i), accuracy of selection (r), and standard deviation (SD) of breed group traits under selection. Results of this study showed that the critical components was genetic development of local grade breeds by choosing small proportion of 10% truncation point for Agrotechnopark intensification of selected elite cows groups among BG, OG and LG populations with the positive live weight gains of 58.6 kg, 23.15 kg, and 28.62 kg per generation, respectively compared with larger percentages of 20% and 30% proportions of truncation points.

A Image Watermarking Resisting Geometrical Attacks Based on EBCOT Algorithm

2013 ◽  
Vol 321-324 ◽  
pp. 2613-2616
Author(s):  
Wu Ge
Keyword(s):  
Survival Rate ◽  
Image Watermarking ◽  
Rate Distortion ◽  
Plane Boundary ◽  
Random Pattern ◽  
Original Image ◽  
Truncation Point ◽  
Final Output ◽  
Bit Plane ◽  
Geometrical Attacks

This paper, proposes a method that by generating a pseudo random pattern, which will work as the watermark and the watermark is embedded during the quantization procedure. Then WSR (watermarking survival rate) is used to search for the optimized truncation points by running the EBCOT process, the truncation point is adjusted to stay at the bit plane boundary and it is used as the dividing point to split magnitude bits of wavelet coefficients, which is then sent to EBCOT for encoding. The final output is the J2K coded watermarked image. The results show that watermarked EBCOT image is nearly rate-distortion optimized, the decoder can recover the original image, the watermark can be detected effectively, and it is robust against geometric attacking such as rotating attack, cropping and scaling attack.

Optimal Sampling for Identifying a Cluster: An Application in Sorting

1993 ◽  
Vol 7 (3) ◽  
pp. 387-407
Author(s):  
Shmuel Gal ◽  
Dafna Sheinwald
Keyword(s):  
Sample Size ◽  
Sequential Sampling ◽  
A Priori ◽  
Optimal Sampling ◽  
Truncation Point ◽  
Fixed Sample Size ◽  
Fixed Sample ◽  
A Priori Distribution ◽  
Sampling Procedures ◽  
The Cost

We consider the following problem. For a given population of m items, we have to make a decision whether or not the population includes a relatively large cluster of identical items. This decision affects the effectiveness of a subsequent computational process, depending on the actual existence of the cluster and its size. To make a good decision, we use a statistical sample which should indicate the existence of a cluster and find a representative thereof. This paper describes the optimal sampling technique to be used in such a case, given the cost of the sampling and the potential gain in speed of the subsequent process. The optimal fixed sample size is specified, as well as the optimal sequential sampling, along with characterizing the dependence of the cost function on the truncation point.For the case that the a priori distribution of the cluster proportion is known, we present formulae by which the optimal sampling procedures can be easily calculated. For the common situation in which the a priori distribution is not known, we present, in the case of a fixed sample size, a tight upper bound for the sample size, which is independent of the a priori distribution, and for the case of the sequential sampling, we present an approximately optimal truncation point, which is also independent of the a priori distribution.The situation described arose in connection with choosing the best sorting method, an application that will be described in full detail. The most interesting practical result is that for our application truncating the sequential procedure at 35 observations, out of a population of 25,000–30,000 items, guarantees that in our sorting application we are always within 2.1% of the optimal cost independently of the a priori distribution.

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