Abstract: Recent environmental turbulence including financial
crisis, intensified competitive forces, rapid technological change and
high market turbulence have dramatically changed the current
business climate. The managers firms have to plan and decide what
the best approaches that best fit their firms in order to pursue superior
performance. This research aims to examine the influence of strategic
reasoning and top level managers- individual characteristics on the
effectiveness of organizational improvisation and firm performance.
Given the lack of studies on these relationships in the previous
literature, there is significant contribution to the body of knowledge
as well as for managerial practices. 128 responses from top
management of technology-based companies in Malaysia were used
as a sample. Three hypotheses were examined and the findings
confirm that (a) there is no relationship between intuitive reasoning
and organizational improvisation but there is a link between rational
reasoning and organizational improvisation, (b) top level managers-
individual characteristics as a whole affect organizational
improvisation; and (c) organizational improvisation positively affects
firm performance. The theoretical and managerial implications were
discussed in the conclusions.
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: We propose a phenomenological model for the
process of polymer desorption. In so doing, we omit the usual
theoretical approach of incorporating a fictitious viscoelastic
stress term into the flux equation. As a result, we obtain a
model that captures the essence of the phenomenon of trapping
skinning, while preserving the integrity of the experimentally
verified Fickian law for diffusion. An appropriate asymptotic
analysis is carried out, and a parameter is introduced to represent
the speed of the desorption front. Numerical simulations are
performed to illustrate the desorption dynamics of the model.
Recommendations are made for future modifications of the
model, and provisions are made for the inclusion of experimentally
determined frontal speeds.
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: This paper presents a new Quality-Controlled, wavelet based, compression method for electrocardiogram (ECG) signals. Initially, an ECG signal is decomposed using the wavelet transform. Then, the resulting coefficients are iteratively thresholded to guarantee that a predefined goal percent root mean square difference (GPRD) is matched within tolerable boundaries. The quantization strategy of extracted non-zero wavelet coefficients (NZWC), according to the combination of RLE, HUFFMAN and arithmetic encoding of the NZWC and a resulting look up table, allow the accomplishment of high compression ratios with good quality reconstructed signals.
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 main objective of this paper is to identify and
disseminate good practice in quality assurance and enhancement as
well as in teaching and learning at master level. This paper focuses
on the experience of the Erasmus Mundus Master program CIMET
(Color in Informatics and Media Technology). Amongst topics
covered, we discuss the adjustments necessary to a curriculum
designed for excellent international students and their preparation for
a global labor market.
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: In this paper, we investigated the characteristic of a
clinical dataseton the feature selection and classification
measurements which deal with missing values problem.And also
posed the appropriated techniques to achieve the aim of the activity;
in this research aims to find features that have high effect to mortality
and mortality time frame. We quantify the complexity of a clinical
dataset. According to the complexity of the dataset, we proposed the
data mining processto cope their complexity; missing values, high
dimensionality, and the prediction problem by using the methods of
missing value replacement, feature selection, and classification.The
experimental results will extend to develop the prediction model for
cardiology.
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: 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: We evaluate the average energy consumption per bit
in Optical Packet Switches equipped with BENES switching fabric
realized in Semiconductor Optical Amplifier (SOA) technology. We
also study the impact that the Amplifier Spontaneous Emission
(ASE) noise generated by a transmission system has on the power
consumption of the BENES switches due to the gain saturation of the
SOAs used to realize the switching fabric. As a matter of example for
32×32 switches supporting 64 wavelengths and offered traffic equal
to 0,8, the average energy consumption per bit is 2, 34 · 10-1 nJ/bit
and increases if ASE noise introduced by the transmission systems
is increased.
Abstract: Knowledge sharing culture contributes to a positive
working environment. Currently, there is no platform for the Faculty
of Industrial Information Technology (FIIT), Unisel academic staff to
share knowledge among them. As it is done manually, the sharing
process is through common meeting or by any offline discussions.
There is no repository for future retrieval. However, with open
source solution the development of knowledge based application may
reduce the cost tremendously. In this paper we discuss about the
domain on which this knowledge portal is being developed and also
the deployment of open source tools such as JOOMLA, PHP
programming language and MySQL. This knowledge portal is
evidence that open source tools also reliable in developing
knowledge based portal. These recommendations will be useful to
the open source community to produce more open source products in
future.
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: 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: 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: 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: In this paper, we present a non-blind technique of
adding the watermark to the Fourier spectral components of audio
signal in a way such that the modified amplitude does not exceed the
maximum amplitude spread (MAS). This MAS is due to individual
Discrete fourier transform (DFT) coefficients in that particular frame,
which is derived from the Energy Spreading function given by
Schroeder. Using this technique one can store double the information
within a given frame length i.e. overriding the watermark on the
host of equal length with least perceptual distortion. The watermark
is uniformly floating on the DFT components of original signal.
This helps in detecting any intentional manipulations done on the
watermarked audio. Also, the scheme is found robust to various signal
processing attacks like presence of multiple watermarks, Additive
white gaussian noise (AWGN) and mp3 compression.