Abstract: In recent years various types of electric vehicles
has gained again increasing attention as an environmentally
benign technology in transport. Especially for urban areas with
high local pollution this Zero-emission technology (at the point
of use) is considered to provide proper solutions. Yet, the bad
economics and the limited driving ranges are still major barriers
for a broader market penetration of battery electric vehicles
(BEV) and of fuel cell vehicles (FCV). The major result of our
analyses is that the most important precondition for a further
dissemination of BEV in urban areas are emission-free zones.
This is an instrument which allows the promotion of BEV
without providing excessive subsidies. In addition, it is
important to note that the full benefits of EV can only be
harvested if the electricity used is produced from renewable
energy sources. That is to say, it has to be ensured that the use of
BEV in urban areas is clearly linked to a green electricity
purchase model. And moreover, the introduction of a CO2-
emission-based tax system would support this requirement.
Abstract: The present study is aim to prepare and evaluate the selfnanoemulsifying drug delivery (SNEDDS) system of a poorly water soluble drug valsartan in order to achieve a better dissolution rate which would further help in enhancing oral bioavailability. The present research work describes a SNEDDS of valsartan using labrafil M 1944 CS, Tween 80 and Transcutol HP. The pseudoternary phase diagrams with presence and absence of drug were plotted to check for the emulsification range and also to evaluate the effect of valsartan on the emulsification behavior of the phases. The mixtures consisting of oil (labrafil M 1944 CS) with surfactant (tween 80), co-surfactant (Transcutol HP) were found to be optimum formulations. Prepared formulations were evaluated for its particle size distribution, nanoemulsifying properties, robustness to dilution, self emulsication time, turbidity measurement, drug content and invitro dissolution. The optimized formulations are further evaluated for heating cooling cycle, centrifugation studies, freeze thaw cycling, particle size distribution and zeta potential were carried out to confirm the stability of the formed SNEDDS formulations. The prepared formulation revealed t a significant improvement in terms of the drug solubility as compared with marketed tablet and pure drug.
Abstract: In this paper, the data correction algorithm is suggested
when the environmental air temperature varies. To correct the infrared
data in this paper, the initial temperature or the initial infrared image
data is used so that a target source system may not be necessary. The
temperature data obtained from infrared detector show nonlinear
property depending on the surface temperature. In order to handle this
nonlinear property, Taylor series approach is adopted. It is shown that
the proposed algorithm can reduce the influence of environmental
temperature on the components in the board. The main advantage of
this algorithm is to use only the initial temperature of the components
on the board rather than using other reference device such as black
body sources in order to get reference temperatures.
Abstract: This paper shows the results of empirical research. It
presents experiences of Polish companies from the Podkarpackie
voivodeship connected with implementing EMS according to the
requirements of the ISO 14001 international standard. The incentives
to introduce and certify organizational eco-innovation, which formal
EMSs are treated as, are presented in this paper.
Abstract: Spectrum is a scarce commodity, and considering the spectrum scarcity faced by the wireless-based service providers led to high congestion levels. Technical inefficiencies from pooled, since all networks share a common pool of channels, exhausting the available channels will force networks to block the services. Researchers found that cognitive radio (CR) technology may resolve the spectrum scarcity. A CR is a self-configuring entity in a wireless networking that senses its environment, tracks changes, and frequently exchanges information with their networks. However, CRN facing challenges and condition become worst while tracks changes i.e. reallocation of another under-utilized channels while primary network user arrives. In this paper, channels or resource reallocation technique based on DNA-inspired computing algorithm for CRN has been proposed.
Abstract: An unsupervised classification algorithm is derived
by modeling observed data as a mixture of several mutually
exclusive classes that are each described by linear combinations of
independent non-Gaussian densities. The algorithm estimates the
data density in each class by using parametric nonlinear functions
that fit to the non-Gaussian structure of the data. This improves
classification accuracy compared with standard Gaussian mixture
models. When applied to textures, the algorithm can learn basis
functions for images that capture the statistically significant structure
intrinsic in the images. We apply this technique to the problem of
unsupervised texture classification and segmentation.
Abstract: This paper presents an algorithm to estimate the parameters of two closely spaced sinusoids, providing a frequency resolution that is more than 800 times greater than that obtained by using the Discrete Fourier Transform (DFT). The strategy uses a highly optimized grid search approach to accurately estimate frequency, amplitude and phase of both sinusoids, keeping at the same time the computational effort at reasonable levels. The proposed method has three main characteristics: 1) a high frequency resolution; 2) frequency, amplitude and phase are all estimated at once using one single package; 3) it does not rely on any statistical assumption or constraint. Potential applications to this strategy include the difficult task of resolving coincident partials of instruments in musical signals.
Abstract: The purpose of this research was to study the inspector performance by using computer based training (CBT). Visual inspection task was printed circuit board (PCB) simulated on several types of defects. Subjects were 16 undergraduate randomly selected from King Mongkut-s University of Technology Thonburi and test for 20/20. Then, they were equally divided on performance into two groups (control and treatment groups) and were provided information before running the experiment. Only treatment group was provided feedback information after first experiment. Results revealed that treatment group was showed significantly difference at the level of 0.01. The treatment group showed high percentage on defects detected. Moreover, the attitude of inspectors on using the CBT to inspection was showed on good. These results have been showed that CBT could be used for training to improve inspector performance.
Abstract: Network-Centric Air Defense Missile Systems
(NCADMS) represents the superior development of the air defense
missile systems and has been regarded as one of the major research
issues in military domain at present. Due to lack of knowledge and
experience on NCADMS, modeling and simulation becomes an effective
approach to perform operational analysis, compared with
those equation based ones. However, the complex dynamic interactions
among entities and flexible architectures of NCADMS put forward
new requirements and challenges to the simulation framework
and models. ABS (Agent-Based Simulations) explicitly addresses
modeling behaviors of heterogeneous individuals. Agents have capability
to sense and understand things, make decisions, and act on the
environment. They can also cooperate with others dynamically to
perform the tasks assigned to them. ABS proves an effective approach
to explore the new operational characteristics emerging in
NCADMS. In this paper, based on the analysis of network-centric
architecture and new cooperative engagement strategies for
NCADMS, an agent-based simulation framework by expanding the
simulation framework in the so-called System Effectiveness Analysis
Simulation (SEAS) was designed. The simulation framework specifies
components, relationships and interactions between them, the
structure and behavior rules of an agent in NCADMS. Based on scenario
simulations, information and decision superiority and operational
advantages in NCADMS were analyzed; meanwhile some
suggestions were provided for its future development.
Abstract: The automatic discrimination of seismic signals is an important practical goal for the earth-science observatories due to the large amount of information that they receive continuously. An essential discrimination task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present new techniques for seismic signals classification: local, regional and global discrimination. These techniques were tested on seismic signals from the data base of the National Geophysical Institute of the Centre National pour la Recherche Scientifique et Technique (Morocco) by using the Moroccan software for seismic signals analysis.
Abstract: The purpose of Grid computing is to utilize
computational power of idle resources which are distributed in
different areas. Given the grid dynamism and its decentralize
resources, there is a need for an efficient scheduler for scheduling
applications. Since task scheduling includes in the NP-hard problems
various researches have focused on invented algorithms especially
the genetic ones. But since genetic is an inherent algorithm which
searches the problem space globally and does not have the efficiency
required for local searching, therefore, its combination with local
searching algorithms can compensate for this shortcomings. The aim
of this paper is to combine the genetic algorithm and GELS (GAGELS)
as a method to solve scheduling problem by which
simultaneously pay attention to two factors of time and number of
missed tasks. Results show that the proposed algorithm can decrease
makespan while minimizing the number of missed tasks compared
with the traditional methods.
Abstract: A fuzzy classifier using multiple ellipsoids approximating decision regions for classification is to be designed in this paper. An algorithm called Gustafson-Kessel algorithm (GKA) with an adaptive distance norm based on covariance matrices of prototype data points is adopted to learn the ellipsoids. GKA is able toadapt the distance norm to the underlying distribution of the prototypedata points except that the sizes of ellipsoids need to be determined a priori. To overcome GKA's inability to determine appropriate size ofellipsoid, the genetic algorithm (GA) is applied to learn the size ofellipsoid. With GA combined with GKA, it will be shown in this paper that the proposed method outperforms the benchmark algorithms as well as algorithms in the field.
Abstract: Fuzzy logic system (FLS) is used in this study to
predict the tractive performance in terms of traction force, and
motion resistance for an intelligent air cushion track vehicle while it
operates in the swamp peat. The system is effective to control the
intelligent air –cushion system with measuring the vehicle traction
force (TF), motion resistance (MR), cushion clearance height (CH)
and cushion pressure (CP). Ultrasonic displacement sensor, pull-in
solenoid electromagnetic switch, pressure control sensor, micro
controller, and battery pH sensor are incorporated with the Fuzzy
logic system to investigate experimentally the TF, MR, CH, and CP.
In this study, a comparison for tractive performance of an intelligent
air cushion track vehicle has been performed with the results obtained
from the predicted values of FLS and experimental actual values. The
mean relative error of actual and predicted values from the FLS
model on traction force, and total motion resistance are found as 5.58
%, and 6.78 % respectively. For all parameters, the relative error of
predicted values are found to be less than the acceptable limits. The
goodness of fit of the prediction values from the FLS model on TF,
and MR are found as 0.90, and 0.98 respectively.
Abstract: The elimination of ranitidine (a pharmaceutical
compound) has been carried out in the presence of UV-C radiation.
After some preliminary experiments, it has been experienced the no
influence of the gas nature (air or oxygen) bubbled in photolytic
experiments. From simple photolysis experiments the quantum yield
of this compound has been determined. Two photolytic
approximation has been used, the linear source emission in parallel
planes and the point source emission in spherical planes. The
quantum yield obtained was in the proximity of 0.05 mol Einstein-1
regardless of the method used. Addition of free radical promoters
(hydrogen peroxide) increases the ranitidine removal rate while the
use of photocatalysts (TiO2) negatively affects the process.
Abstract: In this study, the precision heading process of
spur gears has been investigated by means of numerical
analysis. The effect of some parameters such as teeth number
and module on the forming force and material flow were
presented. The simulation works were performed rigid-plastic
finite element method using DEFORM 3D software. In order
to validate the estimated numerical results, they were
compared with those obtained experimentally during heading
of spur gear using lead as a model material. Results showed
that the optimum number of gear teeth is between 10 to 20,
that is because of being the specific pressure in its minimum
value.
Abstract: Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. A convenient method for solving these problems is based on using of auxiliary problem. In this paper a new method for solving fuzzy variable linear programming problems directly using linear ranking functions is proposed. This method uses simplex tableau which is used for solving linear programming problems in crisp environment before.
Abstract: Accounts of language acquisition differ significantly in their treatment of the role of prediction in language learning. In particular, nativist accounts posit that probabilistic learning about words and word sequences has little to do with how children come to use language. The accuracy of this claim was examined by testing whether distributional probabilities and frequency contributed to how well 3-4 year olds repeat simple word chunks. Corresponding chunks were the same length, expressed similar content, and were all grammatically acceptable, yet the results of the study showed marked differences in performance when overall distributional frequency varied. It was found that a distributional model of language predicted the empirical findings better than a number of other models, replicating earlier findings and showing that children attend to distributional probabilities in an adult corpus. This suggested that language is more prediction-and-error based, rather than on abstract rules which nativist camps suggest.
Abstract: Intradiscal and intervertebral pressure transducers
were developed. They were used to map the pressures in the nucleus
and within the annulus of the human spinal segments. Their stressrelaxation
were recorded over a period of time for nucleus
pressure, applied load, and peripherial strain against time. The
results show that for normal discs, pressures in the nucleus are
viscoelastic in nature with the applied compressive load.
Mechanical strains which develop around the periphery of the
vertebral body are also viscoelastic with the applied compressive
load. Applied compressive load against time also shows viscoelastic
behavior. However, annulus does not respond viscoelastically with
the applied load. It showed a linear response to compressive loading.
Abstract: Hypernetworks are a generalized graph structure
representing higher-order interactions between variables. We present a
method for self-organizing hypernetworks to learn an associative
memory of sentences and to recall the sentences from this memory.
This learning method is inspired by the “mental chemistry" model of
cognition and the “molecular self-assembly" technology in
biochemistry. Simulation experiments are performed on a corpus of
natural-language dialogues of approximately 300K sentences
collected from TV drama captions. We report on the sentence
completion performance as a function of the order of word-interaction
and the size of the learning corpus, and discuss the plausibility of this
architecture as a cognitive model of language learning and memory.
Abstract: The purpose of this paper is to shed light on the
controversial subject of tax incentives to promote regional
development. Although extensive research has been conducted, a
review of the literature gives an inconclusive answer to whether
economic incentives are effective. One reason is the fact that for
some researchers “effective" means the significant location of new
firms in targeted areas, while for others the creation of jobs
regardless if new firms are arriving in a significant fashion. We
present this dichotomy by analyzing a tax incentive program via both
alternatives: location and job creation. The contribution of the paper
is to inform policymakers about the potential opportunities and
pitfalls when designing incentive strategies. This is particularly
relevant, given that both the US and Europe have been promoting
incentives as a tool for regional economic development.