Abstract: Iran is one of the greatest producers of date in the
world. However due to lack of information about its viscoelastic
properties, much of the production downgraded during harvesting
and postharvesting processes. In this study the effect of temperature
and moisture content of product were investigated on stress
relaxation characteristics. Therefore, the freshly harvested date
(kabkab) at tamar stage were put in controlled environment chamber
to obtain different temperature levels (25, 35, 45, and 55 0C) and
moisture contents (8.5, 8.7, 9.2, 15.3, 20, 32.2 %d.b.). A texture
analyzer TAXT2 (Stable Microsystems, UK) was used to apply
uniaxial compression tests. A chamber capable to control temperature
was designed and fabricated around the plunger of texture analyzer to
control the temperature during the experiment. As a new approach a
CCD camera (A4tech, 30 fps) was mounted on a cylindrical glass
probe to scan and record contact area between date and disk.
Afterwards, pictures were analyzed using image processing toolbox
of Matlab software. Individual date fruit was uniaxially compressed
at speed of 1 mm/s. The constant strain of 30% of thickness of date
was applied to the horizontally oriented fruit. To select a suitable
model for describing stress relaxation of date, experimental data were
fitted with three famous stress relaxation models including the
generalized Maxwell, Nussinovitch, and Pelege. The constant in
mentioned model were determined and correlated with temperature
and moisture content of product using non-linear regression analysis.
It was found that Generalized Maxwell and Nussinovitch models
appropriately describe viscoelastic characteristics of date fruits as
compared to Peleg mode.
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: The protection issues in distribution systems with open and closed-loop are studied, and a generalized protection setting scheme based on the traditional over current protection theories is proposed to meet the new requirements. The setting method is expected to be easier realized using computer program, so that the on-line adaptive setting for coordination in distribution system can be implemented. An automatic setting program is created and several cases are taken into practice. The setting results are verified by the coordination curves of the protective devices which are plotted using MATLAB.
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: 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: Shot boundary detection is a fundamental step for the organization of large video data. In this paper, we propose a new method for video gradual shots detection and classification, using advantages of fractal analysis and AIS-based classifier. Proposed features are “vertical intercept" and “fractal dimension" of each frame of videos which are computed using Fourier transform coefficients. We also used a classifier based on Clonal Selection Algorithm. We have carried out our solution and assessed it according to the TRECVID2006 benchmark dataset.
Abstract: Classes on creativity, innovation, and entrepreneurship
are becoming quite popular at universities throughout the world.
However, it is not easy for business students to get involved to
innovative activities, especially patent application. The present study
investigated how to enhance business students- intention to participate
in innovative activities and which incentives universities should
consider. A 22-item research scale was used, and confirmatory factor
analysis was conducted to verify its reliability and validity. Multiple
regression and discriminant analyses were also conducted. The results
demonstrate the effect of growth-need strength on innovative behavior
and indicate that the theory of planned behavior can explain and
predict business students- intention to participate in innovative
activities. Additionally, the results suggest that applying our proposed
model in practice would effectively strengthen business students-
intentions to engage in innovative activities.
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: In this paper, a design methodology to implement low-power and high-speed 2nd order recursive digital Infinite Impulse Response (IIR) filter has been proposed. Since IIR filters suffer from a large number of constant multiplications, the proposed method replaces the constant multiplications by using addition/subtraction and shift operations. The proposed new 6T adder cell is used as the Carry-Save Adder (CSA) to implement addition/subtraction operations in the design of recursive section IIR filter to reduce the propagation delay. Furthermore, high-level algorithms designed for the optimization of the number of CSA blocks are used to reduce the complexity of the IIR filter. The DSCH3 tool is used to generate the schematic of the proposed 6T CSA based shift-adds architecture design and it is analyzed by using Microwind CAD tool to synthesize low-complexity and high-speed IIR filters. The proposed design outperforms in terms of power, propagation delay, area and throughput when compared with MUX-12T, MCIT-7T based CSA adder filter design. It is observed from the experimental results that the proposed 6T based design method can find better IIR filter designs in terms of power and delay than those obtained by using efficient general multipliers.
Abstract: Fundamental motivation of this paper is how gaze estimation can be utilized effectively regarding an application to games. In games, precise estimation is not always important in aiming targets but an ability to move a cursor to an aiming target accurately is also significant. Incidentally, from a game producing point of view, a separate expression of a head movement and gaze movement sometimes becomes advantageous to expressing sense of presence. A case that panning a background image associated with a head movement and moving a cursor according to gaze movement can be a representative example. On the other hand, widely used technique of POG estimation is based on a relative position between a center of corneal reflection of infrared light sources and a center of pupil. However, a calculation of a center of pupil requires relatively complicated image processing, and therefore, a calculation delay is a concern, since to minimize a delay of inputting data is one of the most significant requirements in games. In this paper, a method to estimate a head movement by only using corneal reflections of two infrared light sources in different locations is proposed. Furthermore, a method to control a cursor using gaze movement as well as a head movement is proposed. By using game-like-applications, proposed methods are evaluated and, as a result, a similar performance to conventional methods is confirmed and an aiming control with lower computation power and stressless intuitive operation is obtained.
Abstract: the intension in this work is to investigate the effect of
different bending manifold pipes on engine performance for different
engine speed. Power, Torque, and BSFC were calculated and
presented to show the effect of varying bending pipes angles on them
for all cases considered. A special program used to carry out the
calculations. A simulation model for 4-cylinders spark ignition
engine with turbocharger has been built and calculated. The analysis
of the results shows that for 120o angle the torque increases about
40% at 3000 rpm and 25% at 4000 rpm without changing in fuel
consumption. For 90o angle the increment in torque is about 10 %.
For the same bending angle the increment in brake power is around
40% at 3000 rpm and 25% at 4000 rpm. The increment in fuel
consumption is about 12% for 60o and 30% for 90o between (6000-
7000) rpm.
Abstract: The automatic transmission (AT) is one of the most
important components of many automobile transmission systems. The
shift quality has a significant influence on the ride comfort of the
vehicle. During the AT shift process, the joint elements such as the
clutch and bands engage or disengage, linking sets of gears to create a
fixed gear ratio. Since these ratios differ between gears in a fixed gear
ratio transmission, the motion of the vehicle could change suddenly
during the shift process if the joint elements are engaged or disengaged
inappropriately, additionally impacting the entire transmission system
and increasing the temperature of connect elements.The objective was
to establish a system model for an AT powertrain using
Matlab/Simulink. This paper further analyses the effect of varying
hydraulic pressure and the associated impact on shift quality during
both engagment and disengagement of the joint elements, proving that
shift quality improvements could be achieved with appropriate
hydraulic pressure control.
Abstract: This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.
Abstract: It is well known that the abrasive particles in the
abrasive water suspension has significant effect on the erosion
characteristics of the inside surface of the nozzle. Abrasive particles
moving with the flow cause severe skin friction effect, there by
altering the nozzle diameter due to wear which in turn reflects on the
life of the nozzle for effective machining. Various commercial
abrasives are available for abrasive water jet machining. The erosion
characteristic of each abrasive is different. In consideration of this
aspect, in the present work, the effect of abrasive materials namely
garnet, aluminum oxide and silicon carbide on skin friction
coefficient due to wall shear stress and jet kinetic energy has been
analyzed. It is found that the abrasive material of lower density
produces a relatively higher skin friction effect and higher jet exit
kinetic energy.
Abstract: Aldehydes as secondary lipid oxidation products are highly specific to the oxidative degradation of particular polyunsaturated fatty acids present in foods. Gas chromatographic analysis of those volatile compounds has been widely used for monitoring of the deterioration of food products. Developed static headspace gas chromatography method using flame ionization detector (SHS GC FID) was applied to monitor the aldehydes present in processed foods such as bakery, meat and confectionary products.
Five selected aldehydes were determined in samples without any sample preparation, except grinding for bakery and meat products. SHS–GC analysis allows the separation of propanal, pentanal, hexanal, heptanal and octanal, within 15min. Aldehydes were quantified in fresh and stored samples, and the obtained range of aldehydes in crackers was 1.62±0.05 – 9.95±0.05mg/kg, in sausages 6.62±0.46 – 39.16±0.39mg/kg; and in cocoa spread cream 0.48±0.01 – 1.13±0.02mg/kg. Referring to the obtained results, the following can be concluded, proposed method is suitable for different types of samples, content of aldehydes varies depending on the type of a sample, and differs in fresh and stored samples of the same type.
Abstract: To offer a large variety of products while maintaining
low costs, high speed, and high quality in a mass customization
product development environment, platform based product
development has much benefit and usefulness in many industry fields.
This paper proposes a product configuration strategy by similarity
measure, incorporating the knowledge engineering principles such as
product information model, ontology engineering, and formal concept
analysis.
Abstract: Today many developers use the Java components
collected from the Internet as external LIBs to design and
develop their own software. However, some unknown security
bugs may exist in these components, such as SQL injection bug
may comes from the components which have no specific check
for the input string by users. To check these bugs out is very
difficult without source code. So a novel method to check the
bugs in Java bytecode based on points-to dataflow analysis is in
need, which is different to the common analysis techniques base
on the vulnerability pattern check. It can be used as an assistant
tool for security analysis of Java bytecode from unknown
softwares which will be used as extern LIBs.
Abstract: This paper presents a comparative analysis of a new
unsupervised PCA-based technique for steel plates texture segmentation
towards defect detection. The proposed scheme called Variance
Based Component Analysis or VBCA employs PCA for feature
extraction, applies a feature reduction algorithm based on variance of
eigenpictures and classifies the pixels as defective and normal. While
the classic PCA uses a clusterer like Kmeans for pixel clustering,
VBCA employs thresholding and some post processing operations to
label pixels as defective and normal. The experimental results show
that proposed algorithm called VBCA is 12.46% more accurate and
78.85% faster than the classic PCA.