Abstract: Among the chemicals used for ammunition production, TNT (Trinitrotoluene) play a significant role since World War I and II. Various types of military weapon utilize TNT in casting process. However, the TNT casting process for warhead is difficult to control the cooling rate of the liquid TNT. This problem occurs because the casting process lacks the equipment to detect the temperature during the casting procedure This study presents the temperature detected by infrared camera to illustrate the cooling rate and cooling zone of curing, and demonstrates the optimization of TNT condition to reduce the risk of air gap occurred in the warhead which can result in the destruction afterward. Premature initiation of explosive-filled projectiles in response to set-back forces during gunfiring cause by casting defects. Finally the study can help improving the process of the TNT casting. The operators can control the curing of TNT inside the case by rising up the heating rod at the proper time. Consequently this can reduce tremendous time of rework if the air gaps occur and increase strength to lower elastic modulus. Therefore, it can be clearly concluded that the use of Infrared Cameras in this process is another method to improve the casting procedure.
Abstract: Biological data has several characteristics that strongly differentiate it from typical business data. It is much more complex, usually large in size, and continuously changes. Until recently business data has been the main target for discovering trends, patterns or future expectations. However, with the recent rise in biotechnology, the powerful technology that was used for analyzing business data is now being applied to biological data. With the advanced technology at hand, the main trend in biological research is rapidly changing from structural DNA analysis to understanding cellular functions of the DNA sequences. DNA chips are now being used to perform experiments and DNA analysis processes are being used by researchers. Clustering is one of the important processes used for grouping together similar entities. There are many clustering algorithms such as hierarchical clustering, self-organizing maps, K-means clustering and so on. In this paper, we propose a clustering algorithm that imitates the ecosystem taking into account the features of biological data. We implemented the system using an Ant-Colony clustering algorithm. The system decides the number of clusters automatically. The system processes the input biological data, runs the Ant-Colony algorithm, draws the Topic Map, assigns clusters to the genes and displays the output. We tested the algorithm with a test data of 100 to1000 genes and 24 samples and show promising results for applying this algorithm to clustering DNA chip data.
Abstract: This paper presents a new fingerprint coding technique
based on contourlet transform and multistage vector quantization.
Wavelets have shown their ability in representing natural images that
contain smooth areas separated with edges. However, wavelets
cannot efficiently take advantage of the fact that the edges usually
found in fingerprints are smooth curves. This issue is addressed by
directional transforms, known as contourlets, which have the
property of preserving edges. The contourlet transform is a new
extension to the wavelet transform in two dimensions using
nonseparable and directional filter banks. The computation and
storage requirements are the major difficulty in implementing a
vector quantizer. In the full-search algorithm, the computation and
storage complexity is an exponential function of the number of bits
used in quantizing each frame of spectral information. The storage
requirement in multistage vector quantization is less when compared
to full search vector quantization. The coefficients of contourlet
transform are quantized by multistage vector quantization. The
quantized coefficients are encoded by Huffman coding. The results
obtained are tabulated and compared with the existing wavelet based
ones.
Abstract: International markets driven forces are changing
continuously, therefore companies need to gain a competitive edge in
such markets. Improving the company's products, processes and
practices is no longer auxiliary. Lean production is a production
management philosophy that consolidates work tasks with minimum
waste resulting in improved productivity. Lean production practices
can be mapped into many production areas. One of these is
Manufacturing Equipment and Technology (MET). Many lean
production practices can be implemented in MET, namely, specific
equipment configurations, total preventive maintenance, visual
control, new equipment/ technologies, production process
reengineering and shared vision of perfection.The purpose of this
paper is to investigate the implementation level of these six practices
in Jordanian industries. To achieve that a questionnaire survey has
been designed according to five-point Likert scale. The questionnaire
is validated through pilot study and through experts review. A sample
of 350 Jordanian companies were surveyed, the response rate was
83%. The respondents were asked to rate the extent of
implementation for each of practices. A relationship conceptual
model is developed, hypotheses are proposed, and consequently the
essential statistical analyses are then performed. An assessment tool
that enables management to monitor the progress and the
effectiveness of lean practices implementation is designed and
presented. Consequently, the results show that the average
implementation level of lean practices in MET is 77%, Jordanian
companies are implementing successfully the considered lean
production practices, and the presented model has Cronbach-s alpha
value of 0.87 which is good evidence on model consistency and
results validation.
Abstract: This study, focusing on the importance of encouraging
outdoor activities for children, aims to propose and implement a Web-GIS based outdoor education program for junior high schools,
which will then be evaluated by users. Specifically, for the purpose of improved outdoor activities in the junior high school education, the
outdoor education program, with chiefly using the Web-GIS that provides a good information provision and sharing tool, is proposed
and implemented before being evaluated by users. The conclusion of
this study can be summarized in the following two points.
(1) A five -step outdoor education program based on Web-GIS was
proposed for a “second school" at junior high schools that was then implemented before being evaluated by teachers as users.
(2) Based on the results of evaluation by teachers, it was clear that the general operation of Web-GIS based outdoor education program with them only is difficult due to their lack of knowledge regarding Web-GIS and that support staff who can effectively utilize Web-GIS are essential.
Abstract: Self-organizing map (SOM) provides both clustering and visualization capabilities in mining data. Dynamic self-organizing maps such as Growing Self-organizing Map (GSOM) has been developed to overcome the problem of fixed structure in SOM to enable better representation of the discovered patterns. However, in mining large datasets or historical data the hierarchical structure of the data is also useful to view the cluster formation at different levels of abstraction. In this paper, we present a technique to generate concept trees from the GSOM. The formation of tree from different spread factor values of GSOM is also investigated and the quality of the trees analyzed. The results show that concept trees can be generated from GSOM, thus, eliminating the need for re-clustering of the data from scratch to obtain a hierarchical view of the data under study.
Abstract: Sedimentation formation is a complex hydraulic phenomenon that has emerged as a major operational and maintenance consideration in modern hydraulic engineering in general and river engineering in particular. Sediments accumulation along the river course and their eventual storage in a form of islands affect water intake in the canal systems that are fed by the storage reservoirs. Without proper management, sediment transport can lead to major operational challenges in water distribution system of arid regions like the Dez and Hamidieh command areas. The paper aims to investigate sedimentation in the Western Canal of Dez Diversion Weir using the SHARC model and compare the results with the two intake structures of the Hamidieh dam in Iran using SSIIM model. The objective was to identify the factors which influence the process, check reliability of outcome and provide ways in which to mitigate the implications on operation and maintenance of the structures. Results estimated sand and silt bed loads concentrations to be 193 ppm and 827ppm respectively. This followed ,ore or less similar pattern in Hamidieh where the sediment formation impeded water intake in the canal system. Given the available data on average annual bed loads and average suspended sediment loads of 165ppm and 837ppm in the Dez, there was a significant statistical difference (16%) between the sand grains, whereas no significant difference (1.2%) was find in the silt grain sizes. One explanation for such finding being that along the 6 Km river course there was considerable meandering effects which explains recent shift in the hydraulic behavior along the stream course under investigation. The sand concentration in downstream relative to present state of the canal showed a steep descending curve. Sediment trapping on the other hand indicated a steep ascending curve. These occurred because the diversion weir was not considered in the simulation model. The comparative study showed very close similarities in the results which explains the fact that both software can be used as accurate and reliable analytical tools for simulation of the sedimentation in hydraulic engineering.
Abstract: Swarm principles are increasingly being used to design controllers for the coordination of multi-robot systems or, in general, multi-agent systems. This paper proposes a two-dimensional Lagrangian swarm model that enables the planar agents, modeled as point masses, to swarm whilst effectively avoiding each other and obstacles in the environment. A novel method, based on an extended Lyapunov approach, is used to construct the model. Importantly, the Lyapunov method ensures a form of practical stability that guarantees an emergent behavior, namely, a cohesive and wellspaced swarm with a constant arrangement of individuals about the swarm centroid. Computer simulations illustrate this basic feature of collective behavior. As an application, we show how multiple planar mobile unicycle-like robots swarm to eventually form patterns in which their velocities and orientations stabilize.
Abstract: The task of face recognition has been actively
researched in recent years. This paper provides an up-to-date review of major human face recognition research. We first present an
overview of face recognition and its applications. Then, a literature review of the most recent face recognition techniques is presented.
Description and limitations of face databases which are used to test
the performance of these face recognition algorithms are given. A
brief summary of the face recognition vendor test (FRVT) 2002, a
large scale evaluation of automatic face recognition technology, and
its conclusions are also given. Finally, we give a summary of the research results.
Abstract: This paper presents a new algorithm for the channel estimation of the OFDM system based on a pilot signal for the new generation of high data rate communication systems. In orthogonal frequency division multiplexing (OFDM) systems over fast-varying fading channels, channel estimation and tracking is generally carried out by transmitting known pilot symbols in given positions of the frequency-time grid. In this paper, we propose to derive an improved algorithm based on the calculation of the mean and the variance of the adjacent pilot signals for a specific distribution of the pilot signals in the OFDM frequency-time grid then calculating of the entire unknown channel coefficients from the equation of the mean and the variance. Simulation results shows that the performance of the OFDM system increase as the length of the channel increase where the accuracy of the estimated channel will be increased using this low complexity algorithm, also the number of the pilot signal needed to be inserted in the OFDM signal will be reduced which lead to increase in the throughput of the signal over the OFDM system in compared with other type of the distribution such as Comb type and Block type channel estimation.
Abstract: The technological concepts such as wireless hospital
and portable cardiac telemetry system require the development of
physiological signal acquisition devices to be easily integrated into
the hospital database. In this paper we present the low cost, portable
wireless ECG acquisition hardware that transmits ECG signals to a
dedicated computer.The front end of the system obtains and
processes incoming signals, which are then transmitted via a
microcontroller and wireless Bluetooth module. A monitoring
purpose Bluetooth based end user application integrated with patient
database management module is developed for the computers. The
system will act as a continuous event recorder, which can be used to
follow up patients who have been resuscitatedfrom cardiac arrest,
ventricular tachycardia but also for diagnostic purposes for patients
with arrhythmia symptoms. In addition, cardiac information can be
saved into the patient-s database of the hospital.
Abstract: The standard investigational method for obstructive
sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG),
which consists of a simultaneous, usually overnight recording of
multiple electro-physiological signals related to sleep and
wakefulness. This is an expensive, encumbering and not a readily
repeated protocol, and therefore there is need for simpler and easily
implemented screening and detection techniques. Identification of
apnea/hypopnea events in the screening recordings is the key factor
for the diagnosis of OSAS. The analysis of a solely single-lead
electrocardiographic (ECG) signal for OSAS diagnosis, which may
be done with portable devices, at patient-s home, is the challenge of
the last years. A novel artificial neural network (ANN) based
approach for feature extraction and automatic identification of
respiratory events in ECG signals is presented in this paper. A
nonlinear principal component analysis (NLPCA) method was
considered for feature extraction and support vector machine for
classification/recognition. An alternative representation of the
respiratory events by means of Kohonen type neural network is
discussed. Our prospective study was based on OSAS patients of the
Clinical Hospital of Pneumology from Iaşi, Romania, males and
females, as well as on non-OSAS investigated human subjects. Our
computed analysis includes a learning phase based on cross signal
PSG annotation.
Abstract: Malting is usually carried out on intact barley seed,
while hull is still attached to it. In this study, oat grain with and
without hull was subjected to controlled germination to optimize its
enzymes activity, in such a way that lipase has the lowest and α-
amylase and proteinase the highest activities. Since pH has a great
impact on the activity of the enzymes, the pH of germination media
was set up to 3 to 8. In dehulled oats, lipase and α-amylase had the
lowest and highest activities in pHs 3 and 6, respectively whereas the
highest proteinase activity was evidenced at pH 7 and 4 in the oats
with and without hull respectively. While measurements indicated
that the effect of hull on the enzyme activities particularly in lipase
and amylase at each level of the pH are significantly different, the
best results were obtained in those samples in which their hull had
been removed. However, since the similar lipase activity in
germinated dehulled oat were recorded at the pHs 4 and 5, therefore
it was concluded that pH 5 in dehulled oat seed may provide the
optimum enzyme activity for all the enzymes.
Abstract: We derive simple sets of equations to describe the microwave response of a thin film of magnetized hydrogen plasma in the presence of carbon nanotubes, which were grown by ironcatalyzed high-pressure disproportionation (HiPco). By considering the interference effects due to multiple reflections between thin plasma film interfaces, we present the effects of the continuously changing external magnetic field and plasma parameters on the reflected power, absorbed power, and transmitted power in the system. The simulation results show that the interference effects play an important role in the reflectance, transmittance and absorptance of microwave radiation at the magnetized plasma slab. As a consequence, the interference effects lead to a sinusoidal variation of the reflected intensity and can greatly reduce the amount of reflection power, but the absorption power increases.
Abstract: Poly (ethylene glycol) (PEG) molecules attached to surfaces have shown high potential as a protein repellent due to their flexibility and highly water solubility. A quartz crystal microbalance recording frequency and dissipation changes (QCM-D) has been used to study the adsorption from aqueous solutions, of lysozyme and α-lactalbumin proteins (the last with and without calcium) onto modified stainless steel surfaces. Surfaces were coated with poly(ethylene imine) (PEI) and silicate before grafting on PEG molecules. Protein adsorption was also performed on the bare stainless steel surface as a control. All adsorptions were conducted at 23°C and pH 7.2. The results showed that the presence of PEG molecules significantly reduced the adsorption of lysozyme and α- lactalbumin (with calcium) onto the stainless steel surface. By contrast, and unexpected, PEG molecules enhanced the adsorption of α-lactalbumin (without calcium). It is suggested that the PEG -α- lactalbumin hydrophobic interaction plays a dominant role which leads to protein aggregation at the surface for this latter observation. The findings also lead to the general conclusion that PEG molecules are not a universal protein repellent. PEG-on-PEI surfaces were better at inhibiting the adsorption of lysozyme and α-lactalbumin (with calcium) than with PEG-on-silicate surfaces.
Abstract: Uncertainties of a serial production line affect on the
production throughput. The uncertainties cannot be prevented in a
real production line. However the uncertain conditions can be
controlled by a robust prediction model. Thus, a hybrid model
including autoregressive integrated moving average (ARIMA) and
multiple polynomial regression, is proposed to model the nonlinear
relationship of production uncertainties with throughput. The
uncertainties under consideration of this study are demand, breaktime,
scrap, and lead-time. The nonlinear relationship of production
uncertainties with throughput are examined in the form of quadratic
and cubic regression models, where the adjusted R-squared for
quadratic and cubic regressions was 98.3% and 98.2%. We optimized
the multiple quadratic regression (MQR) by considering the time
series trend of the uncertainties using ARIMA model. Finally the
hybrid model of ARIMA and MQR is formulated by better adjusted
R-squared, which is 98.9%.
Abstract: As more people from non-technical backgrounds
are becoming directly involved with large-scale ontology
development, the focal point of ontology research has shifted
from the more theoretical ontology issues to problems
associated with the actual use of ontologies in real-world,
large-scale collaborative applications. Recently the National
Science Foundation funded a large collaborative ontology
development project for which a new formal ontology model,
the Ontology Abstract Machine (OAM), was developed to
satisfy some unique functional and data representation
requirements. This paper introduces the OAM model and the
related algorithms that enable maintenance of an ontology that
supports node-based user access. The successful software
implementation of the OAM model and its subsequent
acceptance by a large research community proves its validity
and its real-world application value.
Abstract: In this study, aeroelastic response and performance
analyses have been conducted for a 5MW-Class composite wind
turbine blade model. Advanced coupled numerical method based on
computational fluid dynamics (CFD) and computational flexible
multi-body dynamics (CFMBD) has been developed in order to
investigate aeroelastic responses and performance characteristics of
the rotating composite blade. Reynolds-Averaged Navier-Stokes
(RANS) equations with k-ω SST turbulence model were solved for
unsteady flow problems on the rotating turbine blade model. Also,
structural analyses considering rotating effect have been conducted
using the general nonlinear finite element method. A fully implicit
time marching scheme based on the Newmark direct integration
method is applied to solve the coupled aeroelastic governing equations
of the 3D turbine blade for fluid-structure interaction (FSI) problems.
Detailed dynamic responses and instantaneous velocity contour on the
blade surfaces which considering flow-separation effects were
presented to show the multi-physical phenomenon of the huge rotating
wind- turbine blade model.
Abstract: This research project is developed in order to study
managerial styles of modern Thai executives. The thorough
understanding will lead to continuous improvement and efficient
performance of Thai business organizations. Regarding managerial
skills, Thai executives focus heavily upon human skills. Also, the
negotiator roles are most emphasis in their management. In addition,
Thai executives pay most attention to the fundamental management
principles including Harmony and Unity of Direction of the
organizations. Moreover, the management techniques, consisting of
Team work and Career Planning are of their main concern. Finally,
Thai executives wish to enhance their firms- image and employees-
morale through conducting the ethical and socially responsible
activities. The major tactic deployed to stimulate employees- ethical
behaviors and mindset is Code of Ethics development.
Abstract: Maize and Indian mustard are significant crops in
semi-arid climate zones of India. Improved water management
requires precise scheduling of irrigation, which in turn requires an
accurate computation of daily crop evapotranspiration (ETc). Daily
crop evapotranspiration comes as a product of reference
evapotranspiration (ET0) and the growth stage specific crop
coefficients modified for daily variation. The first objective of
present study is to develop crop coefficients Kc for Maize and Indian
mustard. The estimated values of Kc for maize at the four crop
growth stages (initial, development, mid-season, and late season) are
0.55, 1.08, 1.25, and 0.75, respectively, and for Indian mustard the Kc
values at the four growth stages are 0.3, 0.6, 1.12, and 0.35,
respectively. The second objective of the study is to compute daily
crop evapotranspiration from ET0 and crop coefficients. Average
daily ETc of maize varied from about 2.5 mm/d in the early growing
period to > 6.5 mm/d at mid season. The peak ETc of maize is 8.3
mm/d and it occurred 64 days after sowing at the reproductive growth
stage when leaf area index was 4.54. In the case of Indian mustard,
average ETc is 1 mm/d at the initial stage, >1.8 mm/d at mid season
and achieves a peak value of 2.12 mm/d on 56 days after sowing.
Improved schedules of irrigation have been simulated based on daily
crop evapo-transpiration and field measured data. Simulation shows a
close match between modeled and field moisture status prevalent
during crop season.