Abstract: In this study, a system of encryption based on chaotic
sequences is described. The system is used for encrypting digital
image data for the purpose of secure image transmission. An image
secure communication scheme based on Logistic map chaotic
sequences with a nonlinear function is proposed in this paper.
Encryption and decryption keys are obtained by one-dimensional
Logistic map that generates secret key for the input of the nonlinear
function. Receiver can recover the information using the received
signal and identical key sequences through the inverse system
technique. The results of computer simulations indicate that the
transmitted source image can be correctly and reliably recovered by
using proposed scheme even under the noisy channel. The
performance of the system will be discussed through evaluating the
quality of recovered image with and without channel noise.
Abstract: Tourism industries are rapidly increased for the last
few years especially in Malaysia. In order to attract more tourists,
Malaysian Governance encourages any effort to increase Malaysian
tourism industry. One of the efforts in attracting more tourists in
Malacca, Malaysia is a duck tour. Duck tour is an amphibious
sightseeing tour that works in two types of engines, hence, it required
a huge cost to operate and maintain the vehicle. To other country, it is
not so new but in Malaysia, it is just introduced, thus it does not have
any systematic routing yet. Therefore, this paper proposed an
optimization technique to formulate and schedule this tour to
minimize the operating costs by considering it into Travelling
Salesman Problem (TSP). The problem is then can be solved by one
of the optimization technique especially meta-heuristics approach
such as Tabu Search (TS) and Reactive Tabu Search (RTS).
Abstract: The present study investigated the relationship
between personality characteristics of drivers and the number and
amount of fines they have in a year .This study was carried out on
120 male taxi drivers that worked at least seven hours in a day in
Lamerd - a city in the south of IRAN. Subjects were chosen
voluntarily among those available. Predictive variables were the NEO
–five great personality factors (1. conscientiousness 2. Openness to
Experience 3.Neuroticism4 .Extraversion 5.Agreeableness )
thecriterion variables were the number and amount of fines the
drivers have had the last three years. the result of regression analysis
showed that conscientiousness factor was able to negatively predict
the number and amount of financial fines the drivers had during the
last three years. The openness factor positively predicted the number
of fines they had in last 3 years and the amount of financial fines
during the last year. The extraversion factor both meaningfully and
positively could predict only the amount of financial fines they had
during the last year. Increasing age was associated with decreasing
driving offenses as well as financial loss.The findings can be useful
in recognizing the high-risk drivers and leading them to counseling
centers .They can also be used to inform the drivers about their
personality and it’s relation with their accident rate. Such criteria
would be of great importance in employing drivers in different places
such as companies, offices etc…
Abstract: Next generation wireless/mobile networks will be IP based cellular networks integrating the internet with cellular networks. In this paper, we propose a new architecture for a high speed transport system and a mobile management protocol for mobile internet users in a transport system. Existing mobility management protocols (MIPv6, HMIPv6) do not consider real world fast moving wireless hosts (e.g. passengers in a train). For this reason, we define a virtual organization (VO) and proposed the VO architecture for the transport system. We also classify mobility as VO mobility (intra VO) and macro mobility (inter VO). Handoffs in VO are locally managed and transparent to the CH while macro mobility is managed with Mobile IPv6. And, from the features of the transport system, such as fixed route and steady speed, we deduce the movement route and the handoff disruption time of each handoff. To reduce packet loss during handoff disruption time, we propose pre-registration scheme using pre-registration. Moreover, the proposed protocol can eliminate unnecessary binding updates resulting from sequence movement at high speed. The performance evaluations demonstrate our proposed protocol has a good performance at transport system environment. Our proposed protocol can be applied to the usage of wireless internet on the train, subway, and high speed train.
Abstract: This paper presents anapproach of hybridizing two or more artificial intelligence (AI) techniques which arebeing used to
fuzzify the workstress level ranking and categorize the rating accordingly. The use of two or more techniques (hybrid approach)
has been considered in this case, as combining different techniques may lead to neutralizing each other-s weaknesses generating a
superior hybrid solution. Recent researches have shown that there is a
need for a more valid and reliable tools, for assessing work stress. Thus artificial intelligence techniques have been applied in this
instance to provide a solution to a psychological application. An overview about the novel and autonomous interactive model for analysing work-stress that has been developedusing multi-agent
systems is also presented in this paper. The establishment of the intelligent multi-agent decision analyser (IMADA) using hybridized technique of neural networks and fuzzy logic within the multi-agent based framework is also described.
Abstract: In the current Grid environment, efficient workload
management presents a significant challenge, for which there are
exorbitant de facto standards encompassing resource discovery,
brokerage, and data transfer, among others. In addition, the real-time
resource status, essential for an optimal resource allocation strategy,
is often not readily accessible. To address these issues and provide a
cleaner abstraction of the Grid with the potential of generalizing into
arbitrary resource-sharing environment, this paper proposes a new
Condor-based pilot mechanism applied in the PanDA architecture,
PanDA-PF WMS, with the goal of providing a more generic yet
efficient resource allocating strategy. In this architecture, the PanDA
server primarily acts as a repository of user jobs, responding to pilot
requests from distributed, remote resources. Scheduling decisions are
subsequently made according to the real-time resource information
reported by pilots. Pilot Factory is a Condor-inspired solution for a
scalable pilot dissemination and effectively functions as a resource
provisioning mechanism through which the user-job server, PanDA,
reaches out to the candidate resources only on demand.
Abstract: Cutting tools are widely used in manufacturing processes and drilling is the most commonly used machining process. Although drill-bits used in drilling may not be expensive, their breakage can cause damage to expensive work piece being drilled and at the same time has major impact on productivity. Predicting drill-bit breakage, therefore, is important in reducing cost and improving productivity. This study uses twenty features extracted from two degradation signals viz., thrust force and torque. The methodology used involves developing and comparing decision tree, random forest, and multinomial logistic regression models for classifying and predicting drill-bit breakage using degradation signals.
Abstract: Selecting the data modeling technique for an
information system is determined by the objective of the resultant
data model. Dimensional modeling is the preferred modeling
technique for data destined for data warehouses and data mining,
presenting data models that ease analysis and queries which are in
contrast with entity relationship modeling. The establishment of data
warehouses as components of information system landscapes in
many organizations has subsequently led to the development of
dimensional modeling. This has been significantly more developed
and reported for the commercial database management systems as
compared to the open sources thereby making it less affordable for
those in resource constrained settings. This paper presents
dimensional modeling of HIV patient information using open source
modeling tools. It aims to take advantage of the fact that the most
affected regions by the HIV virus are also heavily resource
constrained (sub-Saharan Africa) whereas having large quantities of
HIV data. Two HIV data source systems were studied to identify
appropriate dimensions and facts these were then modeled using two
open source dimensional modeling tools. Use of open source would
reduce the software costs for dimensional modeling and in turn make
data warehousing and data mining more feasible even for those in
resource constrained settings but with data available.
Abstract: Scarcity of water resources and huge costs of
establishing new hydraulic installations necessitate optimal
exploitation from existing reservoirs. Sustainable management and
efficient exploitation from existing finite water resources are
important factors in water resource management, particularly in the
periods of water insufficiency and in dry regions, and on account of
competitive allocations in the view of exploitation management. This
study aims to minimize reservoir water release from a determined
rate of demand. A numerical model for water optimal exploitation
has been developed using GAMS introduced by the World Bank and
applied to the case of Meijaran dam, northern Iran. The results
indicate that this model can optimize the function of reservoir
exploitation while required water for lower parts of the region will be
supplied. Further, allocating optimal water from reservoir, the
optimal rate of water allocated to any group of the users were
specified to increase benefits in curve dam exploitation.
Abstract: A simultaneous study on indoor and outdoor particulate matter concentrations was done in five elementary schools in central parts of Tehran, Iran. Three sizes of particles including PM10, PM2.5 and PM1.0 were measured in 13 classrooms within this schools during winter (January, February and March) 2009. A laserbased portable aerosol spectrometer Model Grimm-1.108, was used for the continuous measurement of particles. The average indoor concentration of PM10, PM2.5 and PM1.0 in studied schools were 274 μg/m3, 42 μg/m3 and 19 μg/m3 respectively; and average outdoor concentrations of PM10, PM2.5 and PM1.0 were evaluated to be 22 μg/m3, 38 μg/m3 and 140 μg/m3 respectively.
Abstract: The mobile systems are powered by batteries.
Reducing the system power consumption is a key to increase its
autonomy. It is known that mostly the systems are dealing with time
varying signals. Thus, we aim to achieve power efficiency by smartly
adapting the system processing activity in accordance with the input
signal local characteristics. It is done by completely rethinking the
processing chain, by adopting signal driven sampling and processing.
In this context, a signal driven filtering technique, based on the level
crossing sampling is devised. It adapts the sampling frequency and
the filter order by analysing the input signal local variations. Thus, it
correlates the processing activity with the signal variations. It leads
towards a drastic computational gain of the proposed technique
compared to the classical one.
Abstract: In this paper we have proposed three and two
stage still gray scale image compressor based on BTC. In our
schemes, we have employed a combination of four techniques
to reduce the bit rate. They are quad tree segmentation, bit
plane omission, bit plane coding using 32 visual patterns and
interpolative bit plane coding. The experimental results show
that the proposed schemes achieve an average bit rate of 0.46
bits per pixel (bpp) for standard gray scale images with an
average PSNR value of 30.25, which is better than the results
from the exiting similar methods based on BTC.
Abstract: A new method identifies coupled fluid-structure system with a reduced set of state variables is presented. Assuming that the structural model is known a priori either from an analysis or a test and using linear transformations between structural and aeroelastic states, it is possible to deduce aerodynamic information from sampled time histories of the aeroelastic system. More specifically given a finite set of structural modes the method extracts generalized aerodynamic force matrix corresponding to these mode shapes. Once the aerodynamic forces are known, an aeroelastic reduced-order model can be constructed in discrete-time, state-space format by coupling the structural model and the aerodynamic system. The resulting reduced-order model is suitable for constant Mach, varying density analysis.
Abstract: This study examines the inelastic behavior of adjacent planar reinforced concrete (R.C.) frames subjected to strong ground motions. The investigation focuses on the effects of vertical ground motion on the seismic pounding. The examined structures are modeled and analyzed by RUAUMOKO dynamic nonlinear analysis program using reliable hysteretic models for both structural members and contact elements. It is found that the vertical ground motion mildly affects the seismic response of adjacent buildings subjected to structural pounding and, for this reason, it can be ignored from the displacement and interstorey drifts assessment. However, the structural damage is moderately affected by the vertical component of earthquakes.
Abstract: The purpose of this study was to investigate relationships between satisfaction with major and career decision efficacy and career attitude maturity of engineering college students by performing correlation analysis. Gender differences in between satisfaction with major and career decision efficacy and career attitude maturity were also examined by T-test. The results T-test revealed gender differences in only career decision efficacy. Male Students scored significantly higher than did female students on career decision efficacy and satisfaction with major. The results of correlation analysis showed a) satisfaction with major were significantly associated with career decision efficacy, b) satisfaction with major were significantly associated with career attitude maturity, and c) career decision efficacy were significantly associated with career attitude maturity. As a result,we found the importance of satisfaction in engineering college students- major studies when deciding their career.
Abstract: Recently, there are significant improvements in the
capabilities of mobile devices; rendering large terrain is tedious
because of the constraint in resources of mobile devices. This
paper focuses on the implementation of terrain rendering on
mobile device to observe some issues and current constraints
occurred. Experiments are performed using two datasets with
results based on rendering speed and appearance to ascertain both
the issues and constraints. The result shows a downfall of frame
rate performance because of the increase of triangles. Since the
resolution between computer and mobile device is different, the
terrain surface on mobile device looks more unrealistic compared
to on a computer. Thus, more attention in the development of
terrain rendering on mobile devices is required. The problems
highlighted in this paper will be the focus of future research and
will be a great importance for 3D visualization on mobile device.
Abstract: Avoidable unscheduled maintenance events and unnecessary
spare parts deliveries are mostly caused by an incorrect choice
of the underlying maintenance strategy. For a faster and more efficient
supply of spare parts for aircrafts of an airline we examine options for
improving the underlying logistics network integrated in an existing
aviation industry network. This paper presents a dynamic prediction
model as decision support for maintenance method selection considering
requirements of an entire flight network. The objective is
to guarantee a high supply of spare parts by an optimal interaction
of various network levels and thus to reduce unscheduled maintenance
events and minimize total costs. By using a prognostics-based
preventive maintenance strategy unscheduled component failures are
avoided for an increase in availability and reliability of the entire
system. The model is intended for use in an aviation company that
utilizes a structured planning process based on collected failures data
of components.
Abstract: e-mail has become an important means of electronic
communication but the viability of its usage is marred by Unsolicited
Bulk e-mail (UBE) messages. UBE consists of many types
like pornographic, virus infected and 'cry-for-help' messages as well
as fake and fraudulent offers for jobs, winnings and medicines. UBE
poses technical and socio-economic challenges to usage of e-mails.
To meet this challenge and combat this menace, we need to
understand UBE. Towards this end, the current paper presents a
content-based textual analysis of more than 2700 body enhancement
medicinal UBE. Technically, this is an application of Text Parsing
and Tokenization for an un-structured textual document and we
approach it using Bag Of Words (BOW) and Vector Space Document
Model techniques. We have attempted to identify the most
frequently occurring lexis in the UBE documents that advertise
various products for body enhancement. The analysis of such top
100 lexis is also presented. We exhibit the relationship between
occurrence of a word from the identified lexis-set in the given UBE
and the probability that the given UBE will be the one advertising for
fake medicinal product. To the best of our knowledge and survey of
related literature, this is the first formal attempt for identification of
most frequently occurring lexis in such UBE by its textual analysis.
Finally, this is a sincere attempt to bring about alertness against and
mitigate the threat of such luring but fake UBE.
Abstract: Bond Graph as a unified multidisciplinary tool is widely
used not only for dynamic modelling but also for Fault Detection and
Isolation because of its structural and causal proprieties. A binary
Fault Signature Matrix is systematically generated but to make the
final binary decision is not always feasible because of the problems
revealed by such method. The purpose of this paper is introducing a
methodology for the improvement of the classical binary method of
decision-making, so that the unknown and identical failure signatures
can be treated to improve the robustness. This approach consists of
associating the evaluated residuals and the components reliability data
to build a Hybrid Bayesian Network. This network is used in two
distinct inference procedures: one for the continuous part and the
other for the discrete part. The continuous nodes of the network are
the prior probabilities of the components failures, which are used by
the inference procedure on the discrete part to compute the posterior
probabilities of the failures. The developed methodology is applied
to a real steam generator pilot process.
Abstract: This paper includes two novel techniques for skew
estimation of binary document images. These algorithms are based on
connected component analysis and Hough transform. Both these
methods focus on reducing the amount of input data provided to
Hough transform. In the first method, referred as word centroid
approach, the centroids of selected words are used for skew detection.
In the second method, referred as dilate & thin approach, the selected
characters are blocked and dilated to get word blocks and later
thinning is applied. The final image fed to Hough transform has the
thinned coordinates of word blocks in the image. The methods have
been successful in reducing the computational complexity of Hough
transform based skew estimation algorithms. Promising experimental
results are also provided to prove the effectiveness of the proposed
methods.