Abstract: Microscopic emission and fuel consumption models
have been widely recognized as an effective method to quantify real
traffic emission and energy consumption when they are applied with
microscopic traffic simulation models. This paper presents a
framework for developing the Microscopic Emission (HC, CO, NOx,
and CO2) and Fuel consumption (MEF) models for light-duty
vehicles. The variable of composite acceleration is introduced into
the MEF model with the purpose of capturing the effects of historical
accelerations interacting with current speed on emission and fuel
consumption. The MEF model is calibrated by multivariate
least-squares method for two types of light-duty vehicle using
on-board data collected in Beijing, China by a Portable Emission
Measurement System (PEMS). The instantaneous validation results
shows the MEF model performs better with lower Mean Absolute
Percentage Error (MAPE) compared to other two models. Moreover,
the aggregate validation results tells the MEF model produces
reasonable estimations compared to actual measurements with
prediction errors within 12%, 10%, 19%, and 9% for HC, CO, NOx
emissions and fuel consumption, respectively.
Abstract: An adaptive Chinese hand-talking system is presented
in this paper. By analyzing the 3 data collecting strategies for new
users, the adaptation framework including supervised and unsupervised
adaptation methods is proposed. For supervised adaptation,
affinity propagation (AP) is used to extract exemplar subsets, and enhanced
maximum a posteriori / vector field smoothing (eMAP/VFS)
is proposed to pool the adaptation data among different models. For
unsupervised adaptation, polynomial segment models (PSMs) are
used to help hidden Markov models (HMMs) to accurately label
the unlabeled data, then the "labeled" data together with signerindependent
models are inputted to MAP algorithm to generate
signer-adapted models. Experimental results show that the proposed
framework can execute both supervised adaptation with small amount
of labeled data and unsupervised adaptation with large amount
of unlabeled data to tailor the original models, and both achieve
improvements on the performance of recognition rate.
Abstract: The porous silicon (PS), formed from the anodization
of a p+ type substrate silicon, consists of a network organized in a
pseudo-column as structure of multiple side ramifications. Structural
micro-topology can be interpreted as the fraction of the interconnected
solid phase contributing to thermal transport. The
reduction of dimensions of silicon of each nanocristallite during the
oxidation induced a reduction in thermal conductivity. Integration of
thermal sensors in the Microsystems silicon requires an effective
insulation of the sensor element. Indeed, the low thermal conductivity
of PS consists in a very promising way in the fabrication of integrated
thermal Microsystems.In this work we are interesting in the
measurements of thermal conductivity (on the surface and in depth)
of PS by the micro-Raman spectroscopy. The thermal conductivity is
studied according to the parameters of anodization (initial doping and
current density. We also, determine porosity of samples by
spectroellipsometry.
Abstract: Email has become a fast and cheap means of online
communication. The main threat to email is Unsolicited Bulk Email
(UBE), commonly called spam email. The current work aims at
identification of unigrams in more than 2700 UBE that advertise
body-enhancement drugs. The identification is based on the
requirement that the unigram is neither present in dictionary, nor is a
slang term. The motives of the paper are many fold. This is an
attempt to analyze spamming behaviour and employment of wordmutation
technique. On the side-lines of the paper, we have
attempted to better understand the spam, the slang and their interplay.
The problem has been addressed by employing Tokenization
technique and Unigram BOW model. We found that the non-lexicon
words constitute nearly 66% of total number of lexis of corpus
whereas non-slang words constitute nearly 2.4% of non-lexicon
words. Further, non-lexicon non-slang unigrams composed of 2
lexicon words, form more than 71% of the total number of such
unigrams. To the best of our knowledge, this is the first attempt to
analyze usage of non-lexicon non-slang unigrams in any kind of
UBE.
Abstract: The current-voltage characteristics of a PtSi/p-Si
Schottky barrier diode was measured at the temperature of 85 K and
from the forward bias region of the I-V curve, the electrical
parameters of the diode were measured by three methods. The results
obtained from the two methods which considered the series resistance
were in close agreement with each other and from them barrier height
(), ideality factor (n) and series resistance () were found to be
0.2045 eV, 2.877 and 14.556 K respectively. By measuring the I-V
characteristics in the temperature range of 85-136 K the electrical
parameters were observed to have strong dependency on temperature.
The increase of barrier height and decrease of ideality factor with
increasing temperature is attributed to the existence of barrier height
inhomogeneities in the silicide-semiconductor structure.
Abstract: Let Xi be a Lacunary System, we established large
deviations inequality for Lacunary System. Furthermore, we gained
Marcinkiewicz Larger Number Law with dependent random variables
sequences.
Abstract: In this work, the influence of temperature on the
different parameters of solar cells based on organic semiconductors
are studied. The short circuit current Isc increases so monotonous
with temperature and then saturates to a maximum value before
decreasing at high temperatures. The open circuit voltage Vco
decreases linearly with temperature. The fill factor FF and efficiency,
which are directly related with Isc and Vco follow the variations of
the letters. The phenomena are explained by the behaviour of the
mobility which is a temperature activated process.
Abstract: Text categorization is the problem of classifying text
documents into a set of predefined classes. After a preprocessing
step, the documents are typically represented as large sparse vectors.
When training classifiers on large collections of documents, both the
time and memory restrictions can be quite prohibitive. This justifies
the application of feature selection methods to reduce the
dimensionality of the document-representation vector. In this paper,
we present three feature selection methods: Information Gain,
Support Vector Machine feature selection called (SVM_FS) and
Genetic Algorithm with SVM (called GA_SVM). We show that the
best results were obtained with GA_SVM method for a relatively
small dimension of the feature vector.
Abstract: Superelastic Shape Memory Alloy (SMA) is accepted
when it used as connection in steel structures. The seismic behaviour
of steel frames with SMA is being assessed in this study. Three eightstorey
steel frames with different SMA systems are suggested, the
first one of which is braced with diagonal bracing system, the second
one is braced with nee bracing system while the last one is which the
SMA is used as connection at the plastic hinge regions of beams.
Nonlinear time history analyses of steel frames with SMA subjected
to two different ground motion records have been performed using
Seismostruct software. To evaluate the efficiency of suggested
systems, the dynamic responses of the frames were compared. From
the comparison results, it can be concluded that using SMA element
is an effective way to improve the dynamic response of structures
subjected to earthquake excitations. Implementing the SMA braces
can lead to a reduction in residual roof displacement. The shape
memory alloy is effective in reducing the maximum displacement at
the frame top and it provides a large elastic deformation range. SMA
connections are very effective in dissipating energy and reducing the
total input energy of the whole frame under severe seismic ground
motion. Using of the SMA connection system is more effective in
controlling the reaction forces at the base frame than other bracing
systems. Using SMA as bracing is more effective in reducing the
displacements. The efficiency of SMA is dependant on the input
wave motions and the construction system as well.
Abstract: A novel behavioral detection framework is proposed
to detect zero day buffer overflow vulnerabilities (based on network
behavioral signatures) using zero-day exploits, instead of the
signature-based or anomaly-based detection solutions currently
available for IDPS techniques. At first we present the detection
model that uses shadow honeypot. Our system is used for the online
processing of network attacks and generating a behavior detection
profile. The detection profile represents the dataset of 112 types of
metrics describing the exact behavior of malware in the network. In
this paper we present the examples of generating behavioral
signatures for two attacks – a buffer overflow exploit on FTP server
and well known Conficker worm. We demonstrated the visualization
of important aspects by showing the differences between valid
behavior and the attacks. Based on these metrics we can detect
attacks with a very high probability of success, the process of
detection is however very expensive.
Abstract: In this paper, an automatic system of diagnosis was
developed to detect and locate in real time the defects of the wound
rotor asynchronous machine associated to electronic converter. For
this purpose, we have treated the signals of the measured parameters
(current and speed) to use them firstly, as indicating variables of the
machine defects under study and, secondly, as inputs to the Artificial
Neuron Network (ANN) for their classification in order to detect the
defect type in progress. Once a defect is detected, the interpretation
system of information will give the type of the defect and its place of
appearance.
Abstract: Preparation of hydrogel based on carrageenan
extracted from Kappaphycus alvarezii was conducted with film
immersion in glutaraldehyde solution (GA 4%w/w) for 2min and
then followed by thermal curing at 110°C for 25min. The method of
carrageenan recovery strongly determines the properties of
crosslinked carrageenan. Hydrogel obtained from alkali treated
carrageenan showed higher swelling ability compared to hydrogel
from nonalkali treated carrageenan. Hydrogel from alkali treated
showed the ability of sensitive to pH media.
Abstract: In the present study the efficiency of Big Bang-Big
Crunch (BB-BC) algorithm is investigated in discrete structural
design optimization. It is shown that a standard version of the BB-BC
algorithm is sometimes unable to produce reasonable solutions to
problems from discrete structural design optimization. Two
reformulations of the algorithm, which are referred to as modified
BB-BC (MBB-BC) and exponential BB-BC (EBB-BC), are
introduced to enhance the capability of the standard algorithm in
locating good solutions for steel truss and frame type structures,
respectively. The performances of the proposed algorithms are
experimented and compared to its standard version as well as some
other algorithms over several practical design examples. In these
examples, steel structures are sized for minimum weight subject to
stress, stability and displacement limitations according to the
provisions of AISC-ASD.
Abstract: This study presents design of a carbon silicon electrode
for iontophorsis treatment towards alopecia. The alopecia is a medical
description means loss of hair from the body. For solving this problem,
the drug need to be delivered into the scalp, therefore, the
iontophoresis was chosen to use in this treatment. However, almost
common electrodes of iontophoresis device are made with metal
material, the electrodes could give patients hurt when they using it, and
it is hard to avoid the hair for attaching the hair. For this reason, an
electrode is made with silicon material to decrease the hurt from the
electrodes, and the carbon material is mixed in it for increasing
conductance. The several cones with stainless material on the
electrode make the electrode is able to void hair to attach the affected
part. According to the results of a vivo-experiment, the carbon silicon
electrode showed a good performance and in treatment comfortably.
Abstract: Calcium oxide (CaO) as carbon dioxide (CO2)
adsorbent at the elevated temperature has been very well-received
thus far. The CaO can be synthesized from natural calcium carbonate
(CaCO3) sources through the reversible calcination-carbonation
process. In the study, cockle shell has been selected as CaO
precursors. The objectives of the study are to investigate the
performance of calcination and carbonation with respect to different
temperature, heating rate, particle size and the duration time. Overall,
better performance is shown at the calcination temperature of 850oC
for 40 minutes, heating rate of 20oC/min, particle size of < 0.125mm
and the carbonation temperature is at 650oC. The synthesized
materials have been characterized by nitrogen physisorption and
surface morphology analysis. The effectiveness of the synthesized
cockle shell in capturing CO2 (0.72 kg CO2/kg adsorbent) which is
comparable to the commercialized adsorbent (0.60 kg CO2/kg
adsorbent) makes them as the most promising materials for CO2
capture.
Abstract: An adaptive dynamic cerebellar model articulation
controller (DCMAC) neural network used for solving the prediction
and identification problem is proposed in this paper. The proposed
DCMAC has superior capability to the conventional cerebellar model
articulation controller (CMAC) neural network in efficient learning
mechanism, guaranteed system stability and dynamic response. The
recurrent network is embedded in the DCMAC by adding feedback
connections in the association memory space so that the DCMAC
captures the dynamic response, where the feedback units act as
memory elements. The dynamic gradient descent method is adopted to
adjust DCMAC parameters on-line. Moreover, the analytical method
based on a Lyapunov function is proposed to determine the
learning-rates of DCMAC so that the variable optimal learning-rates
are derived to achieve most rapid convergence of identifying error.
Finally, the adaptive DCMAC is applied in two computer simulations.
Simulation results show that accurate identifying response and
superior dynamic performance can be obtained because of the
powerful on-line learning capability of the proposed DCMAC.
Abstract: An electric utility-s main concern is to plan, design, operate and maintain its power supply to provide an acceptable level of reliability to its users. This clearly requires that standards of reliability be specified and used in all three sectors of the power system, i.e., generation, transmission and distribution. That is why reliability of a power system is always a major concern to power system planners. This paper presents the reliability analysis of Bangladesh Power System (BPS). Reliability index, loss of load probability (LOLP) of BPS is evaluated using recursive algorithm and considering no de-rated states of generators. BPS has sixty one generators and a total installed capacity of 5275 MW. The maximum demand of BPS is about 5000 MW. The relevant data of the generators and hourly load profiles are collected from the National Load Dispatch Center (NLDC) of Bangladesh and reliability index 'LOLP' is assessed for the period of last ten years.
Abstract: Fault tolerance is critical in many of today's large computer systems. This paper focuses on improving fault tolerance through testing. Moreover, it concentrates on the memory faults: how to access the editable part of a process memory space and how this part is affected. A special Software Fault Injection Technique (SFIT) is proposed for this purpose. This is done by sequentially scanning the memory of the target process, and trying to edit maximum number of bytes inside that memory. The technique was implemented and tested on a group of programs in software packages such as jet-audio, Notepad, Microsoft Word, Microsoft Excel, and Microsoft Outlook. The results from the test sample process indicate that the size of the scanned area depends on several factors. These factors are: process size, process type, and virtual memory size of the machine under test. The results show that increasing the process size will increase the scanned memory space. They also show that input-output processes have more scanned area size than other processes. Increasing the virtual memory size will also affect the size of the scanned area but to a certain limit.
Abstract: Synchronous cooperative systems (SCS) bring together users that are geographically distributed and connected through a network to carry out a task. Examples of SCS include Tele- Immersion and Tele-Conferences. In SCS, the coordination is the core of the system, and it has been defined as the act of managing interdependencies between activities performed to achieve a goal. Some of the main problems that SCS present deal with the management of constraints between simultaneous activities and the execution ordering of these activities. In order to resolve these problems, orderings based on Lamport-s happened-before relation have been used, namely, causal, Δ-causal, and causal-total orderings. They mainly differ in the degree of asynchronous execution allowed. One of the most important orderings is the causal order, which establishes that the events must be seen in the cause-effect order as they occur in the system. In this paper we show that for certain SCS (e.g. videoconferences, tele-immersion) where some degradation of the system is allowed, ensuring the causal order is still rigid, which can render negative affects to the system. In this paper, we illustrate how a more relaxed ordering, which we call Fuzzy Causal Order (FCO), is useful for such kind of systems by allowing a more asynchronous execution than the causal order. The benefit of the FCO is illustrated by applying it to a particular scenario of intermedia synchronization of an audio-conference system.
Abstract: We investigate sonic cues for binaural sound localization within classrooms and present a structural model for the same. Two of the primary cues for localization, interaural time difference (ITD) and interaural level difference (ILD) created between the two ears by sounds from a particular point in space, are used. Although these cues do not lend any information about the elevation of a sound source, the torso, head, and outer ear carry out elevation dependent spectral filtering of sounds before they reach the inner ear. This effect is commonly captured in head related transfer function (HRTF) which aids in resolving the ambiguity from the ITDs and ILDs alone and helps localize sounds in free space. The proposed structural model of HRTF produces well controlled horizontal as well as vertical effects. The implemented HRTF is a signal processing model which tries to mimic the physical effects of the sounds interacting with different parts of the body. The effectiveness of the method is tested by synthesizing spatial audio, in MATLAB, for use in listening tests with human subjects and is found to yield satisfactory results in comparison with existing models.