Abstract: Dried tomato peel (DTP) was tested in vivo (n=10) in 42 week-old laying hens at rates of 0, 40, 70, 100 and 130g/kg DM feed. Laying hens were fed in group 120 g DM/day/animal for 26 days. After 21 days, feed intake was not affected after DTP incorporation (97% of the offered feed in the five groups). Laying rate was not significantly different after DTP incorporation at 4 and 10% from the control group. Egg yolk resulting from DTP-enriched diets, contained lower amounts of cholesterol (14 to 17mg/g) and triglyceride (188mg/g) compared to the control group (22 and 241 mg/g, respectively) (P
Abstract: Lean production (or lean management respectively)
gained popularity in several waves. The last three decades have been
filled with numerous attempts to apply these concepts in companies.
However, this has only been partially successful. The roots of lean
production can be traced back to Toyota-s just-in-time production.
This concept, which according to Womack-s, Jones- and Roos-
research at MIT was employed by Japanese car manufacturers,
became popular under its international names “lean production",
“lean-manufacturing" and was termed “Schlanke Produktion" in
Germany. This contribution shows a review about lean production in
Germany over the last thirty years: development, trial & error and
implementation as well.
Abstract: One of the biggest drawbacks of the wireless
environment is the limited bandwidth. However, the users sharing
this limited bandwidth have been increasing considerably. SDMA
technique which entails using directional antennas allows to increase
the capacity of a wireless network by separating users in the medium.
In this paper, it has been presented how the capacity can be enhanced
while the mean delay is reduced by using directional antennas in
wireless networks employing TDMA/FDD MAC. Computer
modeling and simulation of the wireless system studied are realized
using OPNET Modeler. Preliminary simulation results are presented
and the performance of the model using directional antennas is
evaluated and compared consistently with the one using
omnidirectional antennas.
Abstract: Intercropping is one of the sustainable agricultural
factors. The SPAD meter can be used to predict nitrogen index
reliably, it may also be a useful tool for assessing the relative impact
of weeds on crops. In order to study the effect of weeds on SPAD in
corn (Zea mays L.), sweet basil (Ocimum basilicum L.) and borage
(Borago officinalis L.) in intercropping system, a factorial experiment
was conducted in three replications in 2011. Experimental factors
were included intercropping of corn with sweet basil and borage in
different ratios (100:0, 75:25, 50:50, 25:75 and 0:100 corn: borage or
sweet basil) and weed infestation (weed control and weed
interference). The results showed that intercropping of corn with
sweet basil and borage increased the SPAD value of corn compare to
monoculture in weed interference condition. Sweet basil SPAD value
in weed control treatments (43.66) was more than weed interference
treatments (40.17). Corn could increase the borage SPAD value
compare to monoculture in weed interference treatments.
Abstract: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form If P Then D. The PRs, however, are unable to handle
exceptions and do not exhibit variable precision. The Censored
Production Rules (CPRs), an extension of PRs, were proposed by
Michalski & Winston that exhibit variable precision and supports an
efficient mechanism for handling exceptions. A CPR is an
augmented production rule of the form:
If P Then D Unless C, where C (Censor) is an exception to the rule.
Such rules are employed in situations, in which the conditional
statement 'If P Then D' holds frequently and the assertion C holds
rarely. By using a rule of this type we are free to ignore the exception
conditions, when the resources needed to establish its presence are
tight or there is simply no information available as to whether it
holds or not. Thus, the 'If P Then D' part of the CPR expresses
important information, while the Unless C part acts only as a switch
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.
Abstract: This paper discusses a new model of Islamic code of
ethics for directors. Several corporate scandals and local (example
Transmile and Megan Media) and overseas corporate (example
Parmalat and Enron) collapses show that the current corporate
governance and regulatory reform are unable to prevent these events
from recurring. Arguably, the code of ethics for directors is under
research and the current code of ethics only concentrates on binding
the work of the employee of the organization as a whole, without
specifically putting direct attention to the directors, the group of
people responsible for the performance of the company. This study
used a semi-structured interview survey of well-known Islamic
scholars such as the Mufti to develop the model. It is expected that
the outcome of the research is a comprehensive model of code of
ethics based on the Islamic principles that can be applied and used by
the company to construct a code of ethics for their directors.
Abstract: The software industry has been considered a critical
infrastructure for any nation. Several studies have indicated that
national competitiveness increasingly depends upon Information and
Communication Technology (ICT), and software is one of the major
components of ICT, important for both large and small enterprises.
Even though there has been strong growth in the software industry in
Thailand, the industry has faced many challenges and problems that
need to be resolved. For example, the amount of pirated software has
been rising, and Thailand still has a large gap in the digital divide.
Additionally, the adoption among SMEs has been slow. This paper
investigates various issues in the software industry in Thailand, using
information acquired through analysis of secondary sources,
observation, and focus groups. The results of this study can be used
as “lessons learned" for the development of the software industry in
any developing country.
Abstract: Active vibration control is an important problem in
structures. The objective of active vibration control is to reduce the vibrations of a system by automatic modification of the system-s
structural response. In this paper, the modeling and design of a fast
output sampling feedback controller for a smart flexible beam system embedded with shear sensors and actuators for SISO system using
Timoshenko beam theory is proposed. FEM theory, Timoshenko beam theory and the state space techniques are used to model the
aluminum cantilever beam. For the SISO case, the beam is divided into 5 finite elements and the control actuator is placed at finite
element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. Controllers are
designed using FOS method and the performance of the designed FOS controller is evaluated for vibration control for 4 SISO models
of the same plant. The effect of placing the sensor at different locations on the beam is observed and the performance of the
controller is evaluated for vibration control. Some of the limitations of the Euler-Bernoulli theory such as the neglection of shear and
axial displacement are being considered here, thus giving rise to an accurate beam model. Embedded shear sensors and actuators have
been considered in this paper instead of the surface mounted sensors
and actuators for vibration suppression because of lot of advantages. In controlling the vibration modes, the first three dominant modes of
vibration of the system are considered.
Abstract: In this paper, based on the past project cost and time
performance, a model for forecasting project cost performance is
developed. This study presents a probabilistic project control concept
to assure an acceptable forecast of project cost performance. In this
concept project activities are classified into sub-groups entitled
control accounts. Then obtain the Stochastic S-Curve (SS-Curve), for
each sub-group and the project SS-Curve is obtained by summing
sub-groups- SS-Curves. In this model, project cost uncertainties are
considered through Beta distribution functions of the project
activities costs required to complete the project at every selected time
sections through project accomplishment, which are extracted from a
variety of sources. Based on this model, after a percentage of the
project progress, the project performance is measured via Earned
Value Management to adjust the primary cost probability distribution
functions. Then, accordingly the future project cost performance is
predicted by using the Monte-Carlo simulation method.
Abstract: Principle component analysis is often combined with
the state-of-art classification algorithms to recognize human faces.
However, principle component analysis can only capture these
features contributing to the global characteristics of data because it is a
global feature selection algorithm. It misses those features
contributing to the local characteristics of data because each principal
component only contains some levels of global characteristics of data.
In this study, we present a novel face recognition approach using
non-negative principal component analysis which is added with the
constraint of non-negative to improve data locality and contribute to
elucidating latent data structures. Experiments are performed on the
Cambridge ORL face database. We demonstrate the strong
performances of the algorithm in recognizing human faces in
comparison with PCA and NREMF approaches.
Abstract: Internet is nowadays included to all National Curriculums of the elementary school. A comparative study of their
goals leads to the conclusion that a complete curriculum should aim to student-s acquisition of the abilities to navigate and search for
information and additionally to emphasize on the evaluation of the information provided by the World Wide Web. In a constructivistic knowledge framework the design of a course has to take under
consideration the conceptual representations of students. The following paper presents the conceptual representation of students of eleven years old, attending the Sixth Grade of Greek Elementary School about World Wide Web and their use in the design and
implementation of an innovative course.
Abstract: This paper and its companion (Part 2) deal with
modeling and optimization of two NP-hard problems in production
planning of flexible manufacturing system (FMS), part type selection
problem and loading problem. The part type selection problem and
the loading problem are strongly related and heavily influence the
system-s efficiency and productivity. The complexity of the problems
is harder when flexibilities of operations such as the possibility of
operation processed on alternative machines with alternative tools are
considered. These problems have been modeled and solved
simultaneously by using real coded genetic algorithms (RCGA)
which uses an array of real numbers as chromosome representation.
These real numbers can be converted into part type sequence and
machines that are used to process the part types. This first part of the
papers focuses on the modeling of the problems and discussing how
the novel chromosome representation can be applied to solve the
problems. The second part will discuss the effectiveness of the
RCGA to solve various test bed problems.
Abstract: Improving performance measures in the construction
processes has been a major concern for managers and decision
makers in the industry. They seek for ways to recognize the key
factors which have the largest effect on the process. Identifying such
factors can guide them to focus on the right parts of the process in
order to gain the best possible result. In the present study design of
experiment (DOE) has been applied to a computer simulation model
of brick laying process to determine significant factors while
productivity has been chosen as the response of the experiment. To
this end, four controllable factors and their interaction have been
experimented and the best factor level has been calculated for each
one. The results indicate that three factors, namely, labor of brick,
labor of mortar and inter arrival time of mortar along with interaction
of labor of brick and labor of mortar are significant.
Abstract: The paper presents an optimization study based on
genetic algorithms (GA-s) for a radio-frequency applicator used in
heating dielectric band products. The weakly coupled electro-thermal
problem is analyzed using 2D-FEM. The design variables in the
optimization process are: the voltage of a supplementary “guard"
electrode and six geometric parameters of the applicator. Two
objective functions are used: temperature uniformity and total active
power absorbed by the dielectric. Both mono-objective and multiobjective
formulations are implemented in GA optimization.
Abstract: Rotation or tilt present in an image capture by digital
means can be detected and corrected using Artificial Neural Network
(ANN) for application with a Face Recognition System (FRS). Principal
Component Analysis (PCA) features of faces at different angles
are used to train an ANN which detects the rotation for an input image
and corrected using a set of operations implemented using another
system based on ANN. The work also deals with the recognition
of human faces with features from the foreheads, eyes, nose and
mouths as decision support entities of the system configured using
a Generalized Feed Forward Artificial Neural Network (GFFANN).
These features are combined to provide a reinforced decision for
verification of a person-s identity despite illumination variations. The
complete system performing facial image rotation detection, correction
and recognition using re-enforced decision support provides a
success rate in the higher 90s.
Abstract: Owing to extensive use of hydrogen in refining or
petrochemical units, it is essential to manage hydrogen network in
order to make the most efficient utilization of hydrogen. On the other
hand, hydrogen is an important byproduct not properly used through
petrochemical complexes and mostly sent to the fuel system. A few
works have been reported in literature to improve hydrogen network
for petrochemical complexes. In this study a comprehensive analysis
is carried out on petrochemical units using a modified automated
targeting technique which is applied to determine the minimum
hydrogen consumption. Having applied the modified targeting
method in two petrochemical cases, the results showed a significant
reduction in required fresh hydrogen.
Abstract: Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.
Abstract: This article proposes modeling, simulation and
kinematic and workspace analysis of a spatial cable suspended robot
as incompletely Restrained Positioning Mechanism (IRPM). These
types of robots have six cables equal to the number of degrees of
freedom. After modeling, the kinds of workspace are defined then an
statically reachable combined workspace for different geometric
structures of fixed and moving platform is obtained. This workspace
is defined as the situations of reference point of the moving platform
(center of mass) which under external forces such as weight and with
ignorance of inertial effects, the moving platform should be in static
equilibrium under conditions that length of all cables must not be
exceeded from the maximum value and all of cables must be at
tension (they must have non-negative tension forces). Then the effect
of various parameters such as the size of moving platform, the size of
fixed platform, geometric configuration of robots, magnitude of
applied forces and moments to moving platform on workspace of
these robots with different geometric configuration are investigated.
Obtained results should be effective in employing these robots under
different conditions of applied wrench for increasing the workspace
volume.
Abstract: The paper discusses the results obtained to predict
reinforcement in singly reinforced beam using Neural Net (NN),
Support Vector Machines (SVM-s) and Tree Based Models. Major
advantage of SVM-s over NN is of minimizing a bound on the
generalization error of model rather than minimizing a bound on
mean square error over the data set as done in NN. Tree Based
approach divides the problem into a small number of sub problems to
reach at a conclusion. Number of data was created for different
parameters of beam to calculate the reinforcement using limit state
method for creation of models and validation. The results from this
study suggest a remarkably good performance of tree based and
SVM-s models. Further, this study found that these two techniques
work well and even better than Neural Network methods. A
comparison of predicted values with actual values suggests a very
good correlation coefficient with all four techniques.
Abstract: Recently research on human wayfinding has focused
mainly on mental representations rather than processes of
wayfinding. The objective of this paper is to demonstrate the
rationality behind applying multi-agent simulation paradigm to the
modeling of rescuer team wayfinding in order to develop
computational theory of perceptual wayfinding in crisis situations
using image schemata and affordances, which explains how people
find a specific destination in an unfamiliar building such as a
hospital. The hypothesis of this paper is that successful navigation is
possible if the agents are able to make the correct decision through
well-defined cues in critical cases, so the design of the building
signage is evaluated through the multi-agent-based simulation. In
addition, a special case of wayfinding in a building, finding one-s
way through three hospitals, is used to demonstrate the model.
Thereby, total rescue time for rescue operation during building fire is
computed. This paper discuses the computed rescue time for various
signage localization and provides experimental result for
optimization of building signage design. Therefore the most
appropriate signage design resulted in the shortest total rescue time in
various situations.