Abstract: to simulate the phenomenon of electronic transport in semiconductors, we try to adapt a numerical method, often and most frequently it’s that of Monte Carlo. In our work, we applied this method in the case of a ternary alloy semiconductor GaInP in its cubic form; The Calculations are made using a non-parabolic effective-mass energy band model. We consider a band of conduction to three valleys (ΓLX), major of the scattering mechanisms are taken into account in this modeling, as the interactions with the acoustic phonons (elastic collisions) and optics (inelastic collisions). The polar optical phonons cause anisotropic collisions, intra-valleys, very probable in the III-V semiconductors. Other optical phonons, no polar, allow transitions inter-valleys. Initially, we present the full results obtained by the simulation of Monte Carlo in GaInP in stationary regime. We consider thereafter the effects related to the application of an electric field varying according to time, we thus study the transient phenomenon which make their appearance in ternary material
Abstract: The use of synthetic retardants in polymeric insulated
cables is not uncommon in the high voltage engineering to study
electrical treeing phenomenon. However few studies on organic
materials for the same investigation have been carried. .This paper
describes the study on the effects of Oil Palm Empty Fruit Bunch
(OPEFB) microfiller on the tree initiation and propagation in silicone
rubber with different weight percentages (wt %) of filler to insulation
bulk material. The weight percentages used were 0 wt % and 1 wt %
respectively. It was found that the OPEFB retards the propagation of
the electrical treeing development. For tree inception study, the
addition of 1(wt %) OPEFB has increase the tree inception voltage of
silicone rubber. So, OPEFB is a potential retardant to the initiation
and growth of electrical treeing occurring in polymeric materials for
high voltage application. However more studies on the effects of
physical and electrical properties of OPEFB as a tree retardant
material are required.
Abstract: Circular knitting machine makes the fabric with more than two knitting tools. Variation of yarn tension between different knitting tools causes different loop length of stitches duration knitting process. In this research, a new intelligent method is applied to control loop length of stitches in various tools based on ideal shape of stitches and real angle of stitches direction while different loop length of stitches causes stitches deformation and deviation those of angle. To measure deviation of stitch direction against variation of tensions, image processing technique was applied to pictures of different fabrics with constant front light. After that, the rate of deformation is translated to needed compensation of loop length cam degree to cure stitches deformation. A fuzzy control algorithm was applied to loop length modification in knitting tools. The presented method was experienced for different knitted fabrics of various structures and yarns. The results show that presented method is useable for control of loop length variation between different knitting tools based on stitch deformation for various knitted fabrics with different fabric structures, densities and yarn types.
Abstract: Protein-protein interactions (PPI) play a crucial role in many biological processes such as cell signalling, transcription, translation, replication, signal transduction, and drug targeting, etc. Structural information about protein-protein interaction is essential for understanding the molecular mechanisms of these processes. Structures of protein-protein complexes are still difficult to obtain by biophysical methods such as NMR and X-ray crystallography, and therefore protein-protein docking computation is considered an important approach for understanding protein-protein interactions. However, reliable prediction of the protein-protein complexes is still under way. In the past decades, several grid-based docking algorithms based on the Katchalski-Katzir scoring scheme were developed, e.g., FTDock, ZDOCK, HADDOCK, RosettaDock, HEX, etc. However, the success rate of protein-protein docking prediction is still far from ideal. In this work, we first propose a more practical measure for evaluating the success of protein-protein docking predictions,the rate of first success (RFS), which is similar to the concept of mean first passage time (MFPT). Accordingly, we have assessed the ZDOCK bound and unbound benchmarks 2.0 and 3.0. We also createda new benchmark set for protein-protein docking predictions, in which the complexes have experimentally determined binding affinity data. We performed free energy calculation based on the solution of non-linear Poisson-Boltzmann equation (nlPBE) to improve the binding mode prediction. We used the well-studied thebarnase-barstarsystem to validate the parameters for free energy calculations. Besides,thenlPBE-based free energy calculations were conducted for the badly predicted cases by ZDOCK and ZRANK. We found that direct molecular mechanics energetics cannot be used to discriminate the native binding pose from the decoys.Our results indicate that nlPBE-based calculations appeared to be one of the promising approaches for improving the success rate of binding pose predictions.
Abstract: This paper presents a new study on the applications of
optimization and regression analysis techniques for optimal
calculation of partial ratios of four-step helical gearboxes for getting
minimal gearbox length. In the paper, basing on the moment
equilibrium condition of a mechanic system including four gear units
and their regular resistance condition, models for determination of the
partial ratios of the gearboxes are proposed. In particular, explicit
models for calculation of the partial ratios are proposed by using
regression analysis. Using these models, the determination of the
partial ratios is accurate and simple.
Abstract: The study entitled “The Construction of Interactive
Computer Multimedia Instruction on Basic Japanese Vocabulary"
was aimed: 1) To construct the interactive computer multimedia
instruction on Basic Japanese Vocabulary, 2) To find out
multimedia-s quality, 3) To examine the student-s satisfaction and 4)
To study the learning achievement in Basic Japanese vocabulary. The
sampling group used in this study was composed of 40 1st year
student in Educational Communications and Technology Department,
Faculty of Industrial Education and Technology, King Mongkut-s
University of Technology Thonburi, in the academic year 2553 B.E.
(2010). According to research results, we found that 1). The quality
assessment by 3 mass media experts was at 4.72 on average or at high
level. 2) In terms of contents, the evaluation by 3 experts was at 4.81
on average or at high level. 3) In terms of achievement, there was a
statistical significance between before and after the treatment at the
.05 level. 4) The satisfaction of students towards the interactive
computer multimedia Instruction on “Basic Japanese Vocabulary"
was 4.35 on average, or at high level.
Abstract: This paper presents a smart-card applet that is able to
verify X.509 certificates and to use the public key contained in the
certificate for verifying digital signatures that have been created
using the corresponding private key, e.g. for the purpose of authenticating
the certificate owner against the card. The approach has been
implemented as an operating prototype on Java cards.
Abstract: The issue of classifying objects into one of predefined
groups when the measured variables are mixed with different types
of variables has been part of interest among statisticians in many
years. Some methods for dealing with such situation have been
introduced that include parametric, semi-parametric and nonparametric
approaches. This paper attempts to discuss on a problem
in classifying a data when the number of measured mixed variables is
larger than the size of the sample. A propose idea that integrates a
dimensionality reduction technique via principal component analysis
and a discriminant function based on the location model is discussed.
The study aims in offering practitioners another potential tool in a
classification problem that is possible to be considered when the
observed variables are mixed and too large.
Abstract: The objectives of this research were to explore factors
influencing knowledge management process in the manufacturing
industry and develop a model to support knowledge management
processes. The studied factors were technology infrastructure, human
resource, knowledge sharing, and the culture of the organization. The
knowledge management processes included discovery, capture,
sharing, and application. Data were collected through questionnaires
and analyzed using multiple linear regression and multiple
correlation. The results found that technology infrastructure, human
resource, knowledge sharing, and culture of the organization
influenced the discovery and capture processes. However, knowledge
sharing had no influence in sharing and application processes. A
model to support knowledge management processes was developed,
which indicated that sharing knowledge needed further improvement
in the organization.
Abstract: Two species of Physalis, P.angulataL. and P.
peruviana L. were used as models for comparative study to
understand the values of micro-morphological, -anatomical and
architectural characteristics of leaf for taxonomic purposes and
possibly breeding and commercial applications. Both speciespossess
amphistomaticleaves with 1-layer epidermis, 3-4-layer spongy
mesophyll andbicollateral bundle midrib. Palisade parenchyma cells
of P. angulatawere almost twice longer (65-75 μm) than the other
one. Type of stomata was similar as anomocyticbut stomatal
index(SI) at adaxial surface and abaxial surface of P. angulata were
less than of P. peruvianaas 3.57, 4.00 and6.25, 6.66 respectively.
Some leaf architectural characteristics such as leaf shape, order of
venationalsoprovided information of taxonomic significance
Abstract: Digital signature is a useful primitive to attain the integrity and authenticity in various wire or wireless communications. Proxy signature is one type of the digital signatures. It helps the proxy signer to sign messages on behalf of the original signer. It is very useful when the original signer (e.g. the president of a company) is not available to sign a specific document. If the original signer can not forge valid proxy signatures through impersonating the proxy signer, it will be robust in a virtual environment; thus the original signer can not shift any illegal action initiated by herself to the proxy signer. In this paper, we propose a new proxy signature scheme. The new scheme can prevent the original signer from impersonating the proxy signer to sign messages. The proposed scheme is based on the regular ElGamal signature. In addition, the fair privacy of the proxy signer is maintained. That means, the privacy of the proxy signer is preserved; and the privacy can be revealed when it is necessary.
Abstract: Combined therapy using Interferon and Ribavirin is the standard treatment in patients with chronic hepatitis C. However, the number of responders to this treatment is low, whereas its cost and side effects are high. Therefore, there is a clear need to predict patient’s response to the treatment based on clinical information to protect the patients from the bad drawbacks, Intolerable side effects and waste of money. Different machine learning techniques have been developed to fulfill this purpose. From these techniques are Associative Classification (AC) and Decision Tree (DT). The aim of this research is to compare the performance of these two techniques in the prediction of virological response to the standard treatment of HCV from clinical information. 200 patients treated with Interferon and Ribavirin; were analyzed using AC and DT. 150 cases had been used to train the classifiers and 50 cases had been used to test the classifiers. The experiment results showed that the two techniques had given acceptable results however the best accuracy for the AC reached 92% whereas for DT reached 80%.
Abstract: The internet is constantly expanding. Identifying web
links of interest from web browsers requires users to visit each of the
links listed, individually until a satisfactory link is found, therefore
those users need to evaluate a considerable amount of links before
finding their link of interest; this can be tedious and even
unproductive. By incorporating web assistance, web users could be
benefited from reduced time searching on relevant websites. In this
paper, a rough set approach is presented, which facilitates
classification of unlimited available e-vocabulary, to assist web users
in reducing search times looking for relevant web sites. This
approach includes two methods for identifying relevance data on web
links based on the priority and percentage of relevance. As a result of
these methods, a list of web sites is generated in priority sequence
with an emphasis of the search criteria.
Abstract: In this paper we present a novel error model for
packet loss and subsequent error description. The proposed model
simulates the error performance of wireless communication link. The
model is designed as two independent Markov chains, where the first
one is used for packet generation and the second one generates
correctly and incorrectly transmitted bits for received packets from
the first chain. The statistical analyses of real communication on the
wireless link are used for determination of model-s parameters. Using
the obtained parameters and the implementation of the generator, we
collected generated traffic. The obtained results generated by
proposed model are compared with the real data collection.
Abstract: In view of growing competition in the service sector,
services are as much in need of modeling, analysis and improvement
as business or working processes. Graphical process models are
important means to capture process-related know-how for an
effective management of the service process. In this contribution, a
human performance analysis of process model development paying
special attention to model development time and the working method
was conducted. It was found that modelers with higher application
experience need significantly less time for mental activities than
modelers with lower application experience, spend more time on
labeling graphical elements, and achieved higher process model
quality in terms of activity label quality.
Abstract: This study was conducted to examine the effects of ketum extract on development of Chrysomya rufifacies and to analyze the presence of mitragynine in the larvae samples. 110 newly emerged first instar larvae of C. rufifacies were introduced on ketum extract-mixed cow liver at doses of 0, 20, 40 and 60g. Blowfly development rate was determined with 12 hour intervals and
mitragynine in larvae was extracted and quantitated. C. rufifacies in control group took about 192 hours to complete their development from first instar larvae to adult blowfly; meanwhile blowfly form from the highest dose of ketum was 264 hours. Mitragynine was detected in all groups of treatment, except for control. In conclusion, the presence of mitragynine in C. rufifacies is affected in delaying development rates of the blowfly for up to 62 hours or 3 days. Chemical analysis of mitragynine from larvae samples showed that this alkaloid present in all specimens analyzed.
Abstract: This paper presents a solution for a robotic
manipulation problem. We formulate the problem as combining
target identification, tracking and interception. The task in our
solution is sensing a target on a conveyor belt and then intercepting
robot-s end-effector at a convenient rendezvous point. We used
an object recognition method which identifies the target and finds
its position from visualized scene picture, then the robot system
generates a solution for rendezvous problem using the target-s initial
position and belt velocity . The interception of the target and the
end-effector is executed at a convenient rendezvous point along the
target-s calculated trajectory. Experimental results are obtained using
a real platform with an industrial robot and a vision system over it.
Abstract: Estimates of temperature values at a specific time of day, from daytime and daily profiles, are needed for a number of environmental, ecological, agricultural and technical applications, ranging from natural hazards assessments, crop growth forecasting to design of solar energy systems. The scope of this research is to investigate the efficiency of data mining techniques in estimating minimum, maximum and mean temperature values. For this reason, a number of experiments have been conducted with well-known regression algorithms using temperature data from the city of Patras in Greece. The performance of these algorithms has been evaluated using standard statistical indicators, such as Correlation Coefficient, Root Mean Squared Error, etc.
Abstract: The concerns of education and practice of architecture
do not necessarily overlap. Indeed the gap between them could be
seen increasingly and less frequently bridged. We suggest that
changing in architecture education and clarifying the relationship
between these two can help to find and address the opportunities and
unique positions to bridge this gulf.
Abstract: A novel feature selection strategy to improve the recognition accuracy on the faces that are affected due to nonuniform illumination, partial occlusions and varying expressions is proposed in this paper. This technique is applicable especially in scenarios where the possibility of obtaining a reliable intra-class probability distribution is minimal due to fewer numbers of training samples. Phase congruency features in an image are defined as the points where the Fourier components of that image are maximally inphase. These features are invariant to brightness and contrast of the image under consideration. This property allows to achieve the goal of lighting invariant face recognition. Phase congruency maps of the training samples are generated and a novel modular feature selection strategy is implemented. Smaller sub regions from a predefined neighborhood within the phase congruency images of the training samples are merged to obtain a large set of features. These features are arranged in the order of increasing distance between the sub regions involved in merging. The assumption behind the proposed implementation of the region merging and arrangement strategy is that, local dependencies among the pixels are more important than global dependencies. The obtained feature sets are then arranged in the decreasing order of discriminating capability using a criterion function, which is the ratio of the between class variance to the within class variance of the sample set, in the PCA domain. The results indicate high improvement in the classification performance compared to baseline algorithms.