Abstract: By the application of an improved back-propagation
neural network (BPNN), a model of current densities for a solid oxide
fuel cell (SOFC) with 10 layers is established in this study. To build
the learning data of BPNN, Taguchi orthogonal array is applied to
arrange the conditions of operating parameters, which totally 7 factors
act as the inputs of BPNN. Also, the average current densities
achieved by numerical method acts as the outputs of BPNN.
Comparing with the direct solution, the learning errors for all learning
data are smaller than 0.117%, and the predicting errors for 27
forecasting cases are less than 0.231%. The results show that the
presented model effectively builds a mathematical algorithm to predict
performance of a SOFC stack immediately in real time.
Also, the calculating algorithms are applied to proceed with the
optimization of the average current density for a SOFC stack. The
operating performance window of a SOFC stack is found to be
between 41137.11 and 53907.89. Furthermore, an inverse predicting
model of operating parameters of a SOFC stack is developed here by
the calculating algorithms of the improved BPNN, which is proved to
effectively predict operating parameters to achieve a desired
performance output of a SOFC stack.
Abstract: fibers of pure cellulose can be made from some bacteria such as acetobacter xylinum. Bacterial cellulose fibers are very pure, tens of nm across and about 0.5 micron long. The fibers are very stiff and, although nobody seems to have measured the strength of individual fibers. Their stiffness up to 70 GPa. Fundamental strengths should be at least greater than those of the best commercial polymers, but best bulk strength seems to about the same as that of steel. They can potentially be produced in industrial quantities at greatly lowered cost and water content, and with triple the yield, by a new process. This article presents a critical review of the available information on the bacterial cellulose as a biological nonwoven fabric with special emphasis on its fermentative production and applications. Characteristics of bacterial cellulose biofabric with respect to its structure and physicochemical properties are discussed. Current and potential applications of bacterial cellulose in textile, nonwoven cloth, paper, films synthetic fiber coating, food, pharmaceutical and other industries are also presented.
Abstract: Task of object localization is one of the major
challenges in creating intelligent transportation. Unfortunately, in
densely built-up urban areas, localization based on GPS only
produces a large error, or simply becomes impossible. New
opportunities arise for the localization due to the rapidly emerging
concept of a wireless ad-hoc network. Such network, allows
estimating potential distance between these objects measuring
received signal level and construct a graph of distances in which
nodes are the localization objects, and edges - estimates of the
distances between pairs of nodes. Due to the known coordinates of
individual nodes (anchors), it is possible to determine the location of
all (or part) of the remaining nodes of the graph. Moreover, road
map, available in digital format can provide localization routines
with valuable additional information to narrow node location search.
However, despite abundance of well-known algorithms for solving
the problem of localization and significant research efforts, there are
still many issues that currently are addressed only partially. In this
paper, we propose localization approach based on the graph mapped
distances on the digital road map data basis. In fact, problem is
reduced to distance graph embedding into the graph representing area
geo location data. It makes possible to localize objects, in some cases
even if only one reference point is available. We propose simple
embedding algorithm and sample implementation as spatial queries
over sensor network data stored in spatial database, allowing
employing effectively spatial indexing, optimized spatial search
routines and geometry functions.
Abstract: Building Sector is the major electricity consumer and
it is costly to building owners. Therefore the application of thermal
energy storage (TES) has gained attractive to reduce energy cost.
Many attractive tariff packages are being offered by the electricity
provider to promote TES. The tariff packages offered higher cost of
electricity during peak period and lower cost of electricity during off
peak period. This paper presented the return of initial investment by
implementing a centralized air-conditioning plant integrated with
thermal energy storage with partially operation strategies. Building
load profile will be calculated hourly according to building
specification and building usage trend. TES operation conditions will
be designed according to building load demand profile, storage
capacity, tariff packages and peak/off peak period. The Payback
Period analysis method was used to evaluate economic analysis. The
investment is considered a good investment where by the initial cost
is recovered less than ten than seven years.
Abstract: This paper may be considered as combination of both pervasive computing and Differential GPS (global positioning satellite) which relates to control automatic traffic signals in such a
way as to pre-empt normal signal operation and permit lifesaving vehicles. Before knowing the arrival of the lifesaving vehicles from
the signal there is a chance of clearing the traffic. Traffic signal
preemption system includes a vehicle equipped with onboard computer system capable of capturing diagnostic information and
estimated location of the lifesaving vehicle using the information provided by GPS receiver connected to the onboard computer system
and transmitting the information-s using a wireless transmitter via a
wireless network. The fleet management system connected to a
wireless receiver is capable of receiving the information transmitted
by the lifesaving vehicle .A computer is also located at the
intersection uses corrected vehicle position, speed & direction
measurements, in conjunction with previously recorded data defining
approach routes to the intersection, to determine the optimum time to
switch a traffic light controller to preemption mode so that lifesaving
vehicles can pass safely. In case when the ambulance need to take a
“U" turn in a heavy traffic area we suggest a solution. Now we are
going to make use of computerized median which uses LINKED
BLOCKS (removable) to solve the above problem.
Abstract: The drug discovery process starts with protein
identification because proteins are responsible for many functions
required for maintenance of life. Protein identification further needs
determination of protein function. Proposed method develops a
classifier for human protein function prediction. The model uses
decision tree for classification process. The protein function is
predicted on the basis of matched sequence derived features per each
protein function. The research work includes the development of a
tool which determines sequence derived features by analyzing
different parameters. The other sequence derived features are
determined using various web based tools.
Abstract: The objective of this paper is to support the application of Open Innovation practices in firms and organizations by the assessment and management of Intellectual Capital. Intellectual Capital constituents are analyzed in order to verify their capability of acting as key drivers of Open Innovation processes and, therefore, of creating value. A methodology is defined to settle a procedure which helps to select the most relevant Intellectual Capital value drivers and to provide Communities of Innovation with strategic and managerial guidelines in sustaining Open Innovation paradigm. An application of the methodology is developed within a specifically addressed project and its results are hereafter examined.
Abstract: Despite the internet, which is one of the mass media
that has become quite common in recent years, the relationship of
Advertisement with Television and Cinema, which have always
drawn attention of researchers as basic media and where visual use is
in the foreground, have also become the subject of various studies.
Based on the assumption that the known fundamental effects of
advertisements on consumers are closely related to the creative
process of advertisements as well as the nature and characteristics of
the medium where they are used, these basic mass media (Television
and Cinema) and the consumer motivations of the advertisements
they broadcast have become a focus of study.
Given that the viewers of the mass media in question have shifted
from a passive position to a more active one especially in recent years
and approach contents of advertisements, as they do all contents, in a
more critical and “pitiless" manner, it is possible to say that
individuals make more use of advertisements than in the past and
combine their individual goals with the goals of the advertisements.
This study, which aims at finding out what the goals of these new
individual advertisement use are, how they are shaped by the distinct
characteristics of Television and Cinema, where visuality takes
precedence as basic mass media, and what kind of places they occupy
in the minds of consumers, has determined consumers- motivations
as: “Entertainment", “Escapism", “Play", “Monitoring/Discovery",
“Opposite Sex" and “Aspirations and Role Models".
This study intends to reveal the differences or similarities among
the needs and hence the gratifications of viewers who consume
advertisements on Television or at the Cinema, which are two basic
media where visuality is prioritized.
Abstract: The present work is motivated by the idea that the
layer deformation in anisotropic elasticity can be estimated from the
theory of interfacial dislocations. In effect, this work which is an
extension of a previous approach given by one of the authors
determines the anisotropic displacement fields and the critical
thickness due to a complex biperiodic network of MDs lying just
below the free surface in view of the arrangement of dislocations.
The elastic fields of such arrangements observed along interfaces
play a crucial part in the improvement of the physical properties of
epitaxial systems. New results are proposed in anisotropic elasticity
for hexagonal networks of MDs which contain intrinsic and extrinsic
stacking faults. We developed, using a previous approach based on
the relative interfacial displacement and a Fourier series formulation
of the displacement fields, the expressions of elastic fields when
there is a possible dissociation of MDs. The numerical investigations
in the case of the observed system Si/(111)Si with low twist angles
show clearly the effect of the anisotropy and thickness when the
misfit networks are dissociated.
Abstract: The purposes of the study are to study and to
investigate the relationship among exposure, uses and gratifications
of television morning news among undergraduate students in
Bangkok. This study also compares differences in information
exposure, uses and gratifications of television morning news among
these students.
The research methodology employed a questionnaire as a
quantitative method. The respondents were undergraduate students at
public and private universities in Bangkok. Totally, 400 usable
questionnaires were received. Descriptive and inferential statistics
were used in data analysis.
The results indicated that information exposure of undergraduate
students in Bangkok was at a high level. Students’ uses and
gratifications were also at high level. Information exposure was
positively correlated with uses and gratifications. Uses of information
were positively correlated with satisfaction with information. The
results also showed that students with differences in sex and type of
university were not significantly different in information exposure,
and uses and gratifications.
Abstract: This paper proposes a novel architecture for developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be incorporated into a computerized system and, at the same time, to preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.
Abstract: Computer game industry has experienced exponential
growth in recent years. A game is a recreational activity involving
one or more players. Game input is information such as data,
commands, etc., which is passed to the game system at run time from
an external source. Conversely, game outputs are information which
are generated by the game system and passed to an external target,
but which is not used internally by the game. This paper identifies a
new classification scheme for game input and output, which is based
on player-s input and output. Using this, relationship table for game
input classifier and output classifier is developed.
Abstract: We present an explicit expression to estimate driving voltage attenuation through RC networks representation of an ultrahigh- speed image sensor. Elmore delay metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE simulation data, we found a simple expression that significantly improves the accuracy of the approximation. Estimation error of the resultant expression for uniform RC networks is less than 2%. Similarly, another simple closed-form model to estimate 50 % delay through fundamental RC networks is also derived with sufficient accuracy. The framework of this analysis can be extended to address delay or attenuation issues of other VLSI structures.
Abstract: Keystroke authentication is a new access control system
to identify legitimate users via their typing behavior. In this paper,
machine learning techniques are adapted for keystroke authentication.
Seven learning methods are used to build models to differentiate user
keystroke patterns. The selected classification methods are Decision
Tree, Naive Bayesian, Instance Based Learning, Decision Table, One
Rule, Random Tree and K-star. Among these methods, three of them
are studied in more details. The results show that machine learning
is a feasible alternative for keystroke authentication. Compared to
the conventional Nearest Neighbour method in the recent research,
learning methods especially Decision Tree can be more accurate. In
addition, the experiment results reveal that 3-Grams is more accurate
than 2-Grams and 4-Grams for feature extraction. Also, combination
of attributes tend to result higher accuracy.
Abstract: In this paper, the effect of bolt clamping force on the fatigue behavior of bolted single lap joints of aluminum alloy 2024- T3 have been studied using numerical finite element method. To do so, a three dimensional model according to the bolted single lap joint has been created and numerical analysis has been carried out using finite element based package. Then the stress distribution and also the slip amplitudes have been calculated in the critical regions and the outcome have been compared with the available experimental fatigue tests results. The numerical results show that in low applied clamping force, the fatigue failure of the specimens occur around the stress concentration location (the bolted hole edge) due to the tensile stresses and thus fatigue crack propagation, but with increase of the clamping force, the fatigue life increases and the cracks nucleate and propagate far from the hole edge because of fretting fatigue. In other words, with the further increase of clamping force value of the joint, the fatigue life reduces due to occurrence of the fretting fatigue in the critical location where the slip amplitude is within its critical occurs earlier.
Abstract: The main goal of the study is to analyze all relevant
properties of the electro hydraulic systems and based on that to make
a proper choice of the control strategy that may be used for the
control of the servomechanism system. A combination of electronic
and hydraulic systems is widely used since it combines the
advantages of both. Hydraulic systems are widely spread because of
their properties as accuracy, flexibility, high horsepower-to-weight
ratio, fast starting, stopping and reversal with smoothness and
precision, and simplicity of operations. On the other hand, the
modern control of hydraulic systems is based on control of the circuit
fed to the inductive solenoid that controls the position of the
hydraulic valve. Since this circuit may be easily handled by PWM
(Pulse Width Modulation) signal with a proper frequency, the
combination of electrical and hydraulic systems became very fruitful
and usable in specific areas as airplane and military industry.
The study shows and discusses the experimental results obtained
by the control strategy (classical feedback (PID) & neural network)
using MATLAB and SIMULINK [1]. Finally, the special attention
was paid to the possibility of neuro-controller design and its
application to control of electro-hydraulic systems and to make
comparative with classical control.
Abstract: The objective of this paper is to characterize the spontaneous Electroencephalogram (EEG) signals of four different motor imagery tasks and to show hereby a possible solution for the present binary communication between the brain and a machine ora Brain-Computer Interface (BCI). The processing technique used in this paper was the fractal analysis evaluated by the Critical Exponent Method (CEM). The EEG signal was registered in 5 healthy subjects,sampling 15 measuring channels at 1024 Hz.Each channel was preprocessed by the Laplacian space ltering so as to reduce the space blur and therefore increase the spaceresolution. The EEG of each channel was segmented and its Fractaldimension (FD) calculated. The FD was evaluated in the time interval corresponding to the motor imagery and averaged out for all the subjects (each channel). In order to characterize the FD distribution,the linear regression curves of FD over the electrodes position were applied. The differences FD between the proposed mental tasks are quantied and evaluated for each experimental subject. The obtained results of the proposed method are a substantial fractal dimension in the EEG signal of motor imagery tasks and can be considerably utilized as the multiple-states BCI applications.
Abstract: Background: Blunt aortic trauma (BAT) includes
various morphological changes that occur during deceleration,
acceleration and/or body compression in traffic accidents. The
various forms of BAT, from limited laceration of the intima to
complete transection of the aorta, depends on the force acting on the
vessel wall and the tolerance of the aorta to injury. The force depends
on the change in velocity, the dynamics of the accident and of the
seating position in the car. Tolerance to aortic injury depends on the
anatomy, histological structure and pathomorphological alterations
due to aging or disease of the aortic wall.
An overview of the literature and medical documentation reveals
that different terms are used to describe certain forms of BAT, which
can lead to misinterpretation of findings or diagnoses. We therefore,
propose a classification that would enable uniform systematic
screening of all forms of BAT. We have classified BAT into three
morphologycal types: TYPE I (intramural), TYPE II (transmural) and
TYPE III (multiple) aortic ruptures with appropriate subtypes.
Methods: All car accident casualties examined at the Institute of
Forensic Medicine from 2001 to 2009 were included in this
retrospective study. Autopsy reports were used to determine the
occurrence of each morphological type of BAT in deceased drivers,
front seat passengers and other passengers in cars and to define the
morphology of BAT in relation to the accident dynamics and the age
of the fatalities.
Results: A total of 391 fatalities in car accidents were included in
the study. TYPE I, TYPE II and TYPE III BAT were observed in
10,9%, 55,6% and 33,5%, respectively. The incidence of BAT in
drivers, front seat and other passengers was 36,7%, 43,1% and
28,6%, respectively. In frontal collisions, the incidence of BAT was
32,7%, in lateral collisions 54,2%, and in other traffic accidents
29,3%. The average age of fatalities with BAT was 42,8 years and of
those without BAT 39,1 years.
Conclusion: Identification and early recognition of the risk factors
of BAT following a traffic accident is crucial for successful treatment
of patients with BAT. Front seat passengers over 50 years of age who
have been injured in a lateral collision are the most at risk of BAT.
Abstract: One of the most important applications of
wireless sensor networks is data collection. This paper
proposes as efficient approach for data collection in wireless
sensor networks by introducing Member Forward List. This list
includes the nodes with highest priority for forwarding the data.
When a node fails or dies, this list is used to select the next node
with higher priority. The benefit of this node is that it prevents
the algorithm from repeating when a node fails or dies. The
results show that Member Forward List decreases power
consumption and latency in wireless sensor networks.
Abstract: Real-time hand tracking is a challenging task in many
computer vision applications such as gesture recognition. This paper
proposes a robust method for hand tracking in a complex environment
using Mean-shift analysis and Kalman filter in conjunction with 3D
depth map. The depth information solve the overlapping problem
between hands and face, which is obtained by passive stereo measuring
based on cross correlation and the known calibration data of
the cameras. Mean-shift analysis uses the gradient of Bhattacharyya
coefficient as a similarity function to derive the candidate of the hand
that is most similar to a given hand target model. And then, Kalman
filter is used to estimate the position of the hand target. The results
of hand tracking, tested on various video sequences, are robust to
changes in shape as well as partial occlusion.