Abstract: In this paper, a linear mixed model which has two
random effects is broken up into two models. This thesis gets
the parameter estimation of the original model and an estimation’s
statistical qualities based on these two models. Then many important
properties are given by comparing this estimation with other general
estimations. At the same time, this paper proves the analysis of
variance estimate (ANOVAE) about σ2 of the original model is equal
to the least-squares estimation (LSE) about σ2 of these two models.
Finally, it also proves that this estimation is better than ANOVAE
under Stein function and special condition in some degree.
Abstract: This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.
Abstract: This paper proposes a GLMM with spatial and
temporal effects for malaria data in Thailand. A Bayesian method is
used for parameter estimation via Gibbs sampling MCMC. A
conditional autoregressive (CAR) model is assumed to present the
spatial effects. The temporal correlation is presented through the
covariance matrix of the random effects. The malaria quarterly data
have been extracted from the Bureau of Epidemiology, Ministry of
Public Health of Thailand. The factors considered are rainfall and
temperature. The result shows that rainfall and temperature are
positively related to the malaria morbidity rate. The posterior means
of the estimated morbidity rates are used to construct the malaria
maps. The top 5 highest morbidity rates (per 100,000 population) are
in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4,
97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82).
According to the DIC criterion, the proposed model has a better
performance than the GLMM with spatial effects but without
temporal terms.
Abstract: Leather industry is the most important traditional
industry to provide the leather products in the world for thousand
years. The fierce global competitive environment and common
awareness of global carbon reduction make livestock supply quantities
falling, salt and wet blue leather material reduces and the price
skyrockets significantly. Exchange rate fluctuation led sales revenue
decreasing which due to the differences of export exchanges and
compresses the overall profitability of leather industry. This paper
applies activity-based benefit assessment approach to build up fitness
fur input mixed model, fur is Wet Blue, which concerned with four key
factors: the output rate of wet blue, unit cost of wet blue, yield rate and
grade level of Wet Blue to achieve the low cost strategy under given
unit price of leather product condition of the company. The research
findings indicate that applying this model may improve the input cost
structure, decrease numbers of leather product inventories and to raise
the competitive advantages of the enterprise in the future.
Abstract: Mixed model assembly lines (MMAL) are a type of
production line where a variety of product models similar in product
characteristics are assembled. The effective design of these lines
requires that schedule for assembling the different products is
determined. In this paper we tried to fit the sequencing problem with
the main characteristics of make to order (MTO) environment. The
problem solved in this paper is a multiple objective sequencing
problem in mixed model assembly lines sequencing using weighted
Sum Method (WSM) using GAMS software for small problem and
an effective GA for large scale problems because of the nature of
NP-hardness of our problem and vast time consume to find the
optimum solution in large problems. In this problem three practically
important objectives are minimizing: total utility work, keeping a
constant production rate variation, and minimizing earliness and
tardiness cost which consider the priority of each customer and
different due date which is a real situation in mixed model assembly
lines and it is the first time we consider different attribute to
prioritize the customers which help the company to reduce the cost of
earliness and tardiness. This mechanism is a way to apply an advance
available to promise (ATP) in mixed model assembly line sequencing
which is the main contribution of this paper.
Abstract: This research investigates risk factors for defective products in autoparts factories. Under a Bayesian framework, a generalized linear mixed model (GLMM) in which the dependent variable, the number of defective products, has a Poisson distribution is adopted. Its performance is compared with the Poisson GLM under a Bayesian framework. The factors considered are production process, machines, and workers. The products coded RT50 are observed. The study found that the Poisson GLMM is more appropriate than the Poisson GLM. For the production Process factor, the highest risk of producing defective products is Process 1, for the Machine factor, the highest risk is Machine 5, and for the Worker factor, the highest risk is Worker 6.
Abstract: Two-dimensional (2D) bar codes were designed to
carry significantly more data with higher information density and
robustness than its 1D counterpart. Thanks to the popular
combination of cameras and mobile phones, it will naturally bring
great commercial value to use the camera phone for 2D bar code
reading. This paper addresses the problem of specific 2D bar code
design for mobile phones and introduces a low-level encoding
method of matrix codes. At the same time, we propose an efficient
scheme for 2D bar codes decoding, of which the effort is put on
solutions of the difficulties introduced by low image quality that is
very common in bar code images taken by a phone camera.
Abstract: Data on 657 lactation from 163 Maltese goat,
collected over a 5-year period were analyzed by a mixed model to
estimate the variance components for heritability. The considered
lactation traits were: milk yield (MY) and lactation length (LL). Year,
parity and type of birth (single or twin) were significant sources of
variation for lactation length; on the other hand milk yield was
significantly influenced only by the year. The average MY was
352.34 kg and the average LL was 230 days. Estimates of heritability
were 0.21 and 0.15 for MY and LL respectively. These values
suggest there is low correlation between genotype and phenotype so
it may be difficult to evaluate animals directly on phenotype. So, the
genetic improvement of this breed may be quite slow without the
support of progeny test aimed to select Maltese breeders.
Abstract: Mixed Model Production is the practice of assembling
several distinct and different models of a product on the same
assembly line without changeovers and then sequencing those models
in a way that smoothes the demand for upstream components. In this
paper, we consider an objective function which minimizes total
stoppage time and total idle time and it is presented sequence
dependent set up time. Many studies have been done on the mixed
model assembly lines. But in this paper we specifically focused on
reducing the idle times. This is possible through various help policies.
For improving the solutions, some cases developed and about 40 tests
problem was considered. We use scatter search for optimization and
for showing the efficiency of our algorithm, experimental results
shows behavior of method. Scatter search and help policies can
produce high quality answers, so it has been used in this paper.
Abstract: Data from 1731 Gentile di Puglia lambs, sired by 65 rams over a 5-year period were analyzed by a mixed model to estimate the variance components for heritability. The considered growth traits were: birth weight (BW), weight at 30 days of age (W30) and average daily gain from birth to 30 days of age (DG). Year of birth, sex of lamb, type of birth (single or twin), dam age at lambing and farm were significant sources of variation for all the considered growth traits. The average lamb weights were 3.85±0.16 kg at birth, 9.57±0.91 kg at 30 days of age and the average daily gain was 191±14 g. Estimates of heritability were 0.33±0.05, 0.41±0.06 and 0.16±0.05 respectively for the same traits. These values suggest there is a good opportunity to improve Gentile di Puglia lambs by selecting animals for growth traits.