Abstract: This paper investigates the development of weld zone
in Resistance Spot Welding (RSW) which focuses on weld nugget and Heat Affected Zone (HAZ). The effects of four factors namely
weld current, weld time, electrode force and hold time were studied using a general 24 factorial design augmented by five centre points. The results of the analysis showed that all selected factors except
hold time exhibit significant effect on weld nugget radius and HAZ size. Optimization of the welding parameters (weld current, weld
time and electrode force) to normalize weld nugget and to minimize
HAZ size was then conducted using Central Composite Design (CCD) in Response Surface Methodology (RSM) and the optimum
parameters were determined. A regression model for radius of weld nugget and HAZ size was developed and its adequacy was evaluated.
The experimental results obtained under optimum operating conditions were then compared with the predicted values and were
found to agree satisfactorily with each other
Abstract: This study aims at providing empirical evidence on a
comparison of two equity valuation models: (1) the dividend discount
model (DDM) and (2) the residual income model (RIM), in
estimating equity values of Thai firms during 1995-2004. Results
suggest that DDM and RIM underestimate equity values of Thai
firms and that RIM outperforms DDM in predicting cross-sectional
stock prices. Results on regression of cross-sectional stock prices on
the decomposed DDM and RIM equity values indicate that book
value of equity provides the greatest incremental explanatory power,
relative to other components in DDM and RIM terminal values,
suggesting that book value distortions resulting from accounting
procedures and choices are less severe than forecast and
measurement errors in discount rates and growth rates.
We also document that the incremental explanatory power of book
value of equity during 1998-2004, representing the information
environment under Thai Accounting Standards reformed after the
1997 economic crisis to conform to International Accounting
Standards, is significantly greater than that during 1995-1996,
representing the information environment under the pre-reformed
Thai Accounting Standards. This implies that the book value
distortions are less severe under the 1997 Reformed Thai Accounting
Standards than the pre-reformed Thai Accounting Standards.
Abstract: Response surface methodology (RSM) is a very
efficient tool to provide a good practical insight into developing new
process and optimizing them. This methodology could help
engineers to raise a mathematical model to represent the behavior of
system as a convincing function of process parameters.
Through this paper the sequential nature of the RSM surveyed for process
engineers and its relationship to design of experiments (DOE), regression
analysis and robust design reviewed. The proposed four-step procedure in
two different phases could help system analyst to resolve the parameter
design problem involving responses. In order to check accuracy of the
designed model, residual analysis and prediction error sum of squares
(PRESS) described.
It is believed that the proposed procedure in this study can resolve a
complex parameter design problem with one or more responses. It can be
applied to those areas where there are large data sets and a number of
responses are to be optimized simultaneously. In addition, the proposed
procedure is relatively simple and can be implemented easily by using
ready-made standard statistical packages.
Abstract: In this paper, the concepts of dichotomous logistic
regression (DLR) with leave-one-out (L-O-O) were discussed. To
illustrate this, the L-O-O was run to determine the importance of the
simulation conditions for robust test of spread procedures with good
Type I error rates. The resultant model was then evaluated. The
discussions included 1) assessment of the accuracy of the model, and
2) parameter estimates. These were presented and illustrated by
modeling the relationship between the dichotomous dependent
variable (Type I error rates) with a set of independent variables (the
simulation conditions). The base SAS software containing PROC
LOGISTIC and DATA step functions can be making used to do the
DLR analysis.
Abstract: To extract the important physiological factors related to
diabetes from an oral glucose tolerance test (OGTT) by mathematical
modeling, highly informative but convenient protocols are required.
Current models require a large number of samples and extended
period of testing, which is not practical for daily use. The purpose
of this study is to make model assessments possible even from a
reduced number of samples taken over a relatively short period.
For this purpose, test values were extrapolated using a support
vector machine. A good correlation was found between reference and
extrapolated values in evaluated 741 OGTTs. This result indicates
that a reduction in the number of clinical test is possible through a
computational approach.
Abstract: This paper introduces a technique of distortion
estimation in image watermarking using Genetic Programming (GP).
The distortion is estimated by considering the problem of obtaining a
distorted watermarked signal from the original watermarked signal as
a function regression problem. This function regression problem is
solved using GP, where the original watermarked signal is
considered as an independent variable. GP-based distortion
estimation scheme is checked for Gaussian attack and Jpeg
compression attack. We have used Gaussian attacks of different
strengths by changing the standard deviation. JPEG compression
attack is also varied by adding various distortions. Experimental
results demonstrate that the proposed technique is able to detect the
watermark even in the case of strong distortions and is more robust
against attacks.
Abstract: It is difficult to judge ripeness by outward
characteristics such as size or external color. In this paper a nondestructive
method was studied to determine watermelon (Crimson
Sweet) quality. Responses of samples to excitation vibrations were
detected using laser Doppler vibrometry (LDV) technology. Phase
shift between input and output vibrations were extracted overall
frequency range. First and second were derived using frequency
response spectrums. After nondestructive tests, watermelons were
sensory evaluated. So the samples were graded in a range of ripeness
based on overall acceptability (total desired traits consumers).
Regression models were developed to predict quality using obtained
results and sample mass. The determination coefficients of the
calibration and cross validation models were 0.89 and 0.71
respectively. This study demonstrated feasibility of information
which is derived vibration response curves for predicting fruit
quality. The vibration response of watermelon using the LDV method
is measured without direct contact; it is accurate and timely, which
could result in significant advantage for classifying watermelons
based on consumer opinions.
Abstract: In the present paper, a set of parametric FE stress
analyses is carried out for two-planar welded tubular DKT-joints
under two different axial load cases. Analysis results are used to
present general remarks on the effect of geometrical parameters on
the stress concentration factors (SCFs) at the inner saddle, outer
saddle, toe, and heel positions on the main (outer) brace. Then a new
set of SCF parametric equations is developed through nonlinear
regression analysis for the fatigue design of two-planar DKT-joints.
An assessment study of these equations is conducted against the
experimental data; and the satisfaction of the criteria regarding the
acceptance of parametric equations is checked. Significant effort has
been devoted by researchers to the study of SCFs in various uniplanar
tubular connections. Nevertheless, for multi-planar joints
covering the majority of practical applications, very few
investigations have been reported due to the complexity and high
cost involved.
Abstract: This study examines the relevance of disclosure
practices in improving the accountability and transparency of
religious nonprofit organizations (RNPOs). The assessment of
disclosure is based on the annual returns of RNPOs for the financial
year 2010. In order to quantify the information disclosed in the
annual returns, partial disclosure indexes of basic information (BI)
disclosure index, financial information (FI) disclosure index and
governance information (GI) disclosure index have been built which
takes into account the content of information items in the annual
returns. The empirical evidence obtained revealed low disclosure
practices among RNPOs in the sample. The multiple regression
results showed that the organizational attribute of the board size
appeared to be the most significant predictor for both partial index on
the extent of BI disclosure index, and FI disclosure index. On the
other hand, the extent of financial information disclosure is related to
the amount of donation received by RNPOs. On GI disclosure index,
the existence of an external audit appeared to be significant variable.
This study has contributed to the academic literature in providing
empirical evidence of the disclosure practices among RNPOs.
Abstract: Soil organic carbon (SOC) plays a key role in soil
fertility, hydrology, contaminants control and acts as a sink or source
of terrestrial carbon content that can affect the concentration of
atmospheric CO2. SOC supports the sustainability and quality of
ecosystems, especially in semi-arid region. This study was
conducted to determine relative importance of 13 different
exploratory climatic, soil and geometric factors on the SOC contents
in one of the semiarid watershed zones in Iran. Two methods
canonical discriminate analysis (CDA) and feed-forward back
propagation neural networks were used to predict SOC. Stepwise
regression and sensitivity analysis were performed to identify
relative importance of exploratory variables. Results from sensitivity
analysis showed that 7-2-1 neural networks and 5 inputs in CDA
models output have highest predictive ability that explains %70 and
%65 of SOC variability. Since neural network models outperformed
CDA model, it should be preferred for estimating SOC.
Abstract: The goal of this research is discovering the
determinants of the success or failure of external cooperation in small
and medium enterprises (SMEs). For this, a survey was given to 190
SMEs that experienced external cooperation within the last 3 years. A
logistic regression model was used to derive organizational or strategic
characteristics that significantly influence whether external
collaboration of domestic SMEs is successful or not. Results suggest
that research and development (R&D) features in general
characteristics (both idea creation and discovering market
opportunities) that focused on and emphasized indirected-market
stakeholders (such as complementary companies and affiliates) and
strategies in innovative strategic characteristics raise the probability of
successful external cooperation. This can be used meaningfully to
build a policy or strategy for inducing successful external cooperation
or to understand the innovation of SMEs.
Abstract: An Artificial Neural Network based modeling
technique has been used to study the influence of different
combinations of meteorological parameters on evaporation from a
reservoir. The data set used is taken from an earlier reported study.
Several input combination were tried so as to find out the importance
of different input parameters in predicting the evaporation. The
prediction accuracy of Artificial Neural Network has also been
compared with the accuracy of linear regression for predicting
evaporation. The comparison demonstrated superior performance of
Artificial Neural Network over linear regression approach. The
findings of the study also revealed the requirement of all input
parameters considered together, instead of individual parameters
taken one at a time as reported in earlier studies, in predicting the
evaporation. The highest correlation coefficient (0.960) along with
lowest root mean square error (0.865) was obtained with the input
combination of air temperature, wind speed, sunshine hours and
mean relative humidity. A graph between the actual and predicted
values of evaporation suggests that most of the values lie within a
scatter of ±15% with all input parameters. The findings of this study
suggest the usefulness of ANN technique in predicting the
evaporation losses from reservoirs.
Abstract: The aim of this paper is to identify the most suitable
model for churn prediction based on three different techniques. The
paper identifies the variables that affect churn in reverence of
customer complaints data and provides a comparative analysis of
neural networks, regression trees and regression in their capabilities
of predicting customer churn.
Abstract: Hydraulic conductivity is one parameter important for predicting the movement of water and contaminants dissolved in the water through the soil. The hydraulic conductivity is measured on soil samples in the lab and sometimes tests carried out in the field. The hydraulic conductivity has been related to soil particle diameter by a number of investigators. In this study, 25 set of soil samples with sand texture. The results show approximately success in predicting hydraulic conductivity from particle diameters data. The following relationship obtained from multiple linear regressions on data (R2 = 0.52): Where d10, d50 and d60, are the soil particle diameter (mm) that 10%, 50% and 60% of all soil particles are finer (smaller) by weight and Ks, saturated hydraulic conductivity is expressed in m/day. The results of regression analysis showed that d10 play a more significant role with respect to Ks, saturated hydraulic conductivity (m/day), and has been named as the effective parameter in Ks calculation.
Abstract: The Malaysian government is promoting
entrepreneurship development skills amongst farmers through informal
courses. These courses will concentrate on teaching managerial skills as
inevitable means for small farms to succeed by making farmers more
creative and innovative. Therefore it is important to assess the effect of
informal agri-entrepreneurial training in developing entrepreneurship
among the farmers in Malaysia. Seven hundred and ninety six farmers
(796) farmers were interviewed via structured questionnaire to define
their opinion on whether the current informal educational and training
establishments are sufficient to teach and develop entrepreneurial
skills. Factor analysis and logic regression analysis were used to
determine the motivating factors and predict their impact on the
development of entrepreneurial skills. The result from the factor analysis
led us to investigate the association between these factors and farmers-
opinions about the development of entrepreneurial skills and traits
through participating in informal entrepreneurship training or education.
The outcome has shown us that the importance of informal training to
promote entrepreneurship among farmers is crucial. The training should
be intensified to encourage farmers to not only focus on the modern
technologies but also on the fundamental changes in their attitude towards
agriculture as a business.
DOA:
KMO: Kaiser- Meyer- Olkin Test
MOA: Ministry of Agriculture
NMP: Ninth Malaysia Plan
NAP: Third National Agricultural Policy (2000-2010)
Abstract: One of the vital developmental tasks that an
individual faces during adolescence is choosing a career. Arriving at
a career decision is difficult and anxious for many adolescents in the
tertiary level. The main purpose of this study is to determine the
factors relating to career indecision among freshmen college students
as basis for the formulation of a comprehensive career counseling
program for the psychological well-being of freshmen university
students. The subjects were purposively selected. The Slovin-s
formula was used in determining the sample size, using a 0.05
margin of error in getting the total number of samples per college and
per major. The researcher made use of descriptive correlational study
in determining significant factors relating to career indecision.
Multiple Regression Analysis indicated that career thoughts, career
decisions and vocational identity as factors related to career
indecision.
Abstract: Model-based approaches have been applied successfully
to a wide range of tasks such as specification, simulation, testing, and
diagnosis. But one bottleneck often prevents the introduction of these
ideas: Manual modeling is a non-trivial, time-consuming task.
Automatically deriving models by observing and analyzing running
systems is one possible way to amend this bottleneck. To
derive a model automatically, some a-priori knowledge about the
model structure–i.e. about the system–must exist. Such a model
formalism would be used as follows: (i) By observing the network
traffic, a model of the long-term system behavior could be generated
automatically, (ii) Test vectors can be generated from the model,
(iii) While the system is running, the model could be used to diagnose
non-normal system behavior.
The main contribution of this paper is the introduction of a model
formalism called 'probabilistic regression automaton' suitable for the
tasks mentioned above.
Abstract: Ethanol has been known for a long time, being
perhaps the oldest product obtained through traditional biotechnology
fermentation. Agriculture waste as substrate in fermentation is vastly
discussed as alternative to replace edible food and utilization of
organic material. Pineapple peel, highly potential source as substrate
is a by-product of the pineapple processing industry. Bio-ethanol
from pineapple (Ananas comosus) peel extract was carried out by
controlling fermentation without any treatment. Saccharomyces
ellipsoides was used as inoculum in this fermentation process as it is
naturally found at the pineapple skin. In this study, the capability of
Response Surface Methodology (RSM) for optimization of ethanol
production from pineapple peel extract using Saccharomyces
ellipsoideus in batch fermentation process was investigated. Effect of
five test variables in a defined range of inoculum concentration 6-
14% (v/v), pH (4.0-6.0), sugar concentration (14-22°Brix),
temperature (24-32°C) and time of incubation (30-54 hrs) on the
ethanol production were evaluated. Data obtained from experiment
were analyzed with RSM of MINITAB Software (Version 15)
whereby optimum ethanol concentration of 8.637% (v/v) was
determined. The optimum condition of 14% (v/v) inoculum
concentration, pH 6, 22°Brix, 26°C and 30hours of incubation. The
significant regression equation or model at the 5% level with
correlation value of 99.96% was also obtained.
Abstract: The basis of examines is survey of 500 in the years
2002-2010, which was selected according to homogeneity of land
cover and where 1090 revenues were evaluated. For achieved yields
of winter wheat is obtained multicriterial regression function
depending on the major factors influencing the consumption of
nitrogen. The coefficient of discrimination of the established model is
0.722. The increase in efficiency of fertilization is involved in supply
of organic nutrients, tillage, soil pH, past weather, the humus content
in the subsoil and grain content to 0.001 mm. The decrease in
efficiency was mainly influenced by the total dose of mineral
nitrogen, although it was divided into multiple doses, the proportion
loamy particles up to 0.01 mm, rainy, or conversely dry weather
during the vegetation. The efficiency of nitrogen was found to be the
smallest on undeveloped soils and the highest on chernozem and
alluvial soils.
Abstract: The paper presents an applied study of a multivariate AR(p) process fitted to daily data from U.S. commodity futures markets with the use of Bayesian statistics. In the first part a detailed description of the methods used is given. In the second part two BVAR models are chosen one with assumption of lognormal, the second with normal distribution of prices conditioned on the parameters. For a comparison two simple benchmark models are chosen that are commonly used in todays Financial Mathematics. The article compares the quality of predictions of all the models, tries to find an adequate rate of forgetting of information and questions the validity of Efficient Market Hypothesis in the semi-strong form.