Abstract: Saudi Arabia in recent years has seen drastic increase
in traffic related crashes. With population of over 29 million, Saudi
Arabia is considered as a fast growing and emerging economy. The
rapid population increase and economic growth has resulted in rapid
expansion of transportation infrastructure, which has led to increase
in road crashes. Saudi Ministry of Interior reported more than 7,000
people killed and 68,000 injured in 2011 ranking Saudi Arabia to be
one of the worst worldwide in traffic safety. The traffic safety issues
in the country also result in distress to road users and cause and
economic loss exceeding 3.7 billion Euros annually. Keeping this in
view, the researchers in Saudi Arabia are investigating ways to
improve traffic safety conditions in the country. This paper presents a
multilevel approach to collect traffic safety related data required to do
traffic safety studies in the region. Two highway corridors including
King Fahd Highway 39 kilometre and Gulf Cooperation Council
Highway 42 kilometre long connecting the cities of Dammam and
Khobar were selected as a study area. Traffic data collected included
traffic counts, crash data, travel time data, and speed data. The
collected data was analysed using geographic information system to
evaluate any correlation. Further research is needed to investigate the
effectiveness of traffic safety related data when collected in a
concerted effort.
Abstract: The pedagogy project has been proven as an active
learning method, which is used to develop learner-s skills and
knowledge.The use of technology in the learning world, has filed
several gaps in the implementation of teaching methods, and online
evaluation of learners. However, the project methodology presents
challenges in the assessment of learners online.
Indeed, interoperability between E-learning platforms (LMS) is
one of the major challenges of project-based learning assessment.
Firstly, we have reviewed the characteristics of online assessment
in the context of project-based teaching. We addressed the
constraints encountered during the peer evaluation process.
Our approach is to propose a meta-model, which will describe a
language dedicated to the conception of peer assessment scenario in
project-based learning. Then we illustrate our proposal by an
instantiation of the meta-model through a business process in a
scenario of collaborative assessment on line.
Abstract: This research explores the links between physical
development and transportation infrastructure around Kumasi,
Ghana. It utilizes census data as well as fieldwork and interviews
carried out during July and December 2005. The results suggest that
there is a weak association between transportation investments and
physical development, and that recent housing has generally occurred
in poorly accessible locations. Road investments have generally
followed physical expansion rather than the reverse. Hence policies
designed to manage the fast growth now occurring around Ghanaian
cities should not focus exclusively on improving transportation
infrastructure but also strengthening the underlying the traditional
land management structures and the official land administrative
institutions that operate within those structures.
Abstract: The struggle between modern and postmodern
understanding is also displayed in terms of the superiorities of
quantitative and qualitative methods to each other which are
evaluated within the scope of these understandings. By way of
assuming that the quantitative researches (modern) are able to
account for structure while the qualitative researches (postmodern)
explain the process, these methods are turned into a means for
worldviews specific to a period. In fact, process is not a functioning
independent of structure. In addition to this issue, the ability of
quantitative methods to provide scientific knowledge is also
controversial so long as they exclude the dialectical method. For this
reason, the critiques charged against modernism in terms of
quantitative methods are, in a sense, legitimate. Nevertheless, the
main issue is in which parameters postmodernist critique tries to
legitimize its critiques and whether these parameters represent a point
of view enabling democratic solutions.
In this respect, the scientific knowledge covered in Turkish media
as a means through which ordinary people have access to scientific
knowledge will be evaluated by means of content analysis within a
new objectivity conception.
Abstract: This paper covered a series of key points in terms of 2D to 3D stereoscopic conversion. A successfully applied stereoscopic conversion approach in current visual effects industry was presented. The purpose of this paper is to cover a detailed workflow and concept, which has been successfully used in 3D stereoscopic conversion for feature films in visual effects industry, and therefore to clarify the process in stereoscopic conversion production and provide a clear idea for those entry-level artists to improve an overall understanding of 3D stereoscopic in digital compositing field as well as to the higher education factor of visual effects and hopefully inspire further collaboration and participants particularly between academia and industry.
Abstract: The ElectroEncephaloGram (EEG) is useful for
clinical diagnosis and biomedical research. EEG signals often
contain strong ElectroOculoGram (EOG) artifacts produced
by eye movements and eye blinks especially in EEG recorded
from frontal channels. These artifacts obscure the underlying
brain activity, making its visual or automated inspection
difficult. The goal of ocular artifact removal is to remove
ocular artifacts from the recorded EEG, leaving the underlying
background signals due to brain activity. In recent times,
Independent Component Analysis (ICA) algorithms have
demonstrated superior potential in obtaining the least
dependent source components. In this paper, the independent
components are obtained by using the JADE algorithm (best
separating algorithm) and are classified into either artifact
component or neural component. Neural Network is used for
the classification of the obtained independent components.
Neural Network requires input features that exactly represent
the true character of the input signals so that the neural
network could classify the signals based on those key
characters that differentiate between various signals. In this
work, Auto Regressive (AR) coefficients are used as the input
features for classification. Two neural network approaches
are used to learn classification rules from EEG data. First, a
Polynomial Neural Network (PNN) trained by GMDH (Group
Method of Data Handling) algorithm is used and secondly,
feed-forward neural network classifier trained by a standard
back-propagation algorithm is used for classification and the
results show that JADE-FNN performs better than JADEPNN.
Abstract: The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.
Abstract: In this paper, we present user pattern learning
algorithm based MDSS (Medical Decision support system) under
ubiquitous. Most of researches are focus on hardware system, hospital
management and whole concept of ubiquitous environment even
though it is hard to implement. Our objective of this paper is to design
a MDSS framework. It helps to patient for medical treatment and
prevention of the high risk patient (COPD, heart disease, Diabetes).
This framework consist database, CAD (Computer Aided diagnosis
support system) and CAP (computer aided user vital sign prediction
system). It can be applied to develop user pattern learning algorithm
based MDSS for homecare and silver town service. Especially this
CAD has wise decision making competency. It compares current vital
sign with user-s normal condition pattern data. In addition, the CAP
computes user vital sign prediction using past data of the patient. The
novel approach is using neural network method, wireless vital sign
acquisition devices and personal computer DB system. An intelligent
agent based MDSS will help elder people and high risk patients to
prevent sudden death and disease, the physician to get the online
access to patients- data, the plan of medication service priority (e.g.
emergency case).
Abstract: The main purpose of this study is to provide a detailed
statistical overview of the time and regional distribution, relative
timing occurrence of economic crises and government changes in 51
economies over the 1990–2007 periods. At the same time, the
predictive power of the economic crises on set government changes
will be examined using “signal approach".
The result showed that the percentage of government changes is
highest in transition economies (86 percent of observations) and
lowest in Latin American economies (39 percent of observations).
The percentages of government changes are same in both developed
and developing countries (43 percent of observations). However,
average crises per year (frequency of crises) are higher (lower) in
developing (developed) countries than developed (developing)
countries. Also, the predictive power of economic crises about the
onset of a government change is highest in Transition economies (81
percent) and lowest in Latin American countries (30 percent). The
predictive power of economic crises in developing countries (43
percent) is lower than developed countries (55 percent).
Abstract: The modern telecommunication industry demands
higher capacity networks with high data rate. Orthogonal frequency
division multiplexing (OFDM) is a promising technique for high data
rate wireless communications at reasonable complexity in wireless
channels. OFDM has been adopted for many types of wireless
systems like wireless local area networks such as IEEE 802.11a, and
digital audio/video broadcasting (DAB/DVB). The proposed research
focuses on a concatenated coding scheme that improve the
performance of OFDM based wireless communications. It uses a
Redundant Residue Number System (RRNS) code as the outer code
and a convolutional code as the inner code. Here, a direct conversion
of analog signal to residue domain is done to reduce the conversion
complexity using sigma-delta based parallel analog-to-residue
converter. The bit error rate (BER) performances of the proposed
system under different channel conditions are investigated. These
include the effect of additive white Gaussian noise (AWGN),
multipath delay spread, peak power clipping and frame start
synchronization error. The simulation results show that the proposed
RRNS-Convolutional concatenated coding (RCCC) scheme provides
significant improvement in the system performance by exploiting the
inherent properties of RRNS.
Abstract: Small tanks, the ancient man-made rain water storage
systems, support the pheasant life and agriculture of the dry zone of
Sri Lanka. Many small tanks were abandoned with time due to
various reasons. Such tanks, rehabilitated in the recent past, were
found to be less sustainable and most of these rehabilitation
approaches have failed. The objective of this research is to assess the
impact of the rehabilitation approaches in the management of small
tanks in the Kurunegala District of Sri Lanka with respect to eight
small tanks. A Sustainability index was developed using seven
indicators representing the ability and commitment of the villagers to
maintain these tanks. The sustainability index of the eight tanks
varied between 79.2 and 47.2 out of a total score of 100. The
conclusion is that, the approaches used for tank rehabilitation have a
significant effect on the sustainability of the management of these
small tanks.
Abstract: In this paper we present a novel approach for human
Body configuration based on the Silhouette. We propose to address
this problem under the Bayesian framework. We use an effective
Model based MCMC (Markov Chain Monte Carlo) method to solve
the configuration problem, in which the best configuration could be
defined as MAP (maximize a posteriori probability) in Bayesian
model. This model based MCMC utilizes the human body model to
drive the MCMC sampling from the solution space. It converses the
original high dimension space into a restricted sub-space constructed
by the human model and uses a hybrid sampling algorithm. We
choose an explicit human model and carefully select the likelihood
functions to represent the best configuration solution. The
experiments show that this method could get an accurate
configuration and timesaving for different human from multi-views.
Abstract: Ethanol is generally used as a therapeutic reagent against Hepatocellular carcinoma (HCC or hepatoma) worldwide, as it can induce Hepatocellular carcinoma cell apoptosis at low concentration through a multifactorial process regulated by several unknown proteins. This paper provides a simple and available proteomic strategy for exploring differentially expressed proteins in the apoptotic pathway. The appropriate concentrations of ethanol required to induce HepG2 cell apoptosis were first assessed by MTT assay, Gisma and fluorescence staining. Next, the central proteins involved in the apoptosis pathway processs were determined using 2D-PAGE, SDS-PAGE, and bio-software analysis. Finally the downregulation of two proteins, AFP and survivin, were determined by immunocytochemistry and reverse transcriptase PCR (RT-PCR) technology. The simple, useful method demonstrated here provides a new approach to proteomic analysis in key bio-regulating process including proliferation, differentiation, apoptosis, immunity and metastasis.
Abstract: In this paper, a novel approach for the multidisciplinary design optimization (MDO) of complex mechatronic systems. This approach, which is a part of a global project aiming to include the MDO aspect inside an innovative design process. As a first step, the paper considers the MDO as a redesign approach which is limited to the parametric optimization. After defining and introducing the different keywords, the proposed method which is based on the V-Model which is commonly used in mechatronics.
Abstract: The P-Bigram method is a string comparison methods
base on an internal two characters-based similarity measure. The edit
distance between two strings is the minimal number of elementary
editing operations required to transform one string into the other. The
elementary editing operations include deletion, insertion, substitution
two characters. In this paper, we address the P-Bigram method to
sole the similarity problem in DNA sequence. This method provided
an efficient algorithm that locates all minimum operation in a string.
We have been implemented algorithm and found that our program
calculated that smaller distance than one string. We develop PBigram
edit distance and show that edit distance or the similarity and
implementation using dynamic programming. The performance of
the proposed approach is evaluated using number edit and percentage
similarity measures.
Abstract: Recent years have seen a growing trend towards the
integration of multiple information sources to support large-scale
prediction of protein-protein interaction (PPI) networks in model
organisms. Despite advances in computational approaches, the
combination of multiple “omic" datasets representing the same type
of data, e.g. different gene expression datasets, has not been
rigorously studied. Furthermore, there is a need to further investigate
the inference capability of powerful approaches, such as fullyconnected
Bayesian networks, in the context of the prediction of PPI
networks. This paper addresses these limitations by proposing a
Bayesian approach to integrate multiple datasets, some of which
encode the same type of “omic" data to support the identification of
PPI networks. The case study reported involved the combination of
three gene expression datasets relevant to human heart failure (HF).
In comparison with two traditional methods, Naive Bayesian and
maximum likelihood ratio approaches, the proposed technique can
accurately identify known PPI and can be applied to infer potentially
novel interactions.
Abstract: The multidelays linear control systems described by
difference differential equations are often studied in modern control
theory. In this paper, the delay-independent stabilization algebraic
criteria and the theorem of delay-independent stabilization for linear
systems with multiple time-delays are established by using the
Lyapunov functional and the Riccati algebra matrix equation in the
matrix theory. An illustrative example and the simulation result, show
that the approach to linear systems with multiple time-delays is
effective.
Abstract: Most Decision Support Systems (DSS) for waste
management (WM) constructed are not widely marketed and lack
practical applications. This is due to the number of variables and
complexity of the mathematical models which include the
assumptions and constraints required in decision making. The
approach made by many researchers in DSS modelling is to isolate a
few key factors that have a significant influence to the DSS. This
segmented approach does not provide a thorough understanding of
the complex relationships of the many elements involved. The
various elements in constructing the DSS must be integrated and
optimized in order to produce a viable model that is marketable and
has practical application. The DSS model used in assisting decision
makers should be integrated with GIS, able to give robust prediction
despite the inherent uncertainties of waste generation and the plethora
of waste characteristics, and gives optimal allocation of waste stream
for recycling, incineration, landfill and composting.
Abstract: In this paper we propose a computational model for the representation and processing of morpho-phonological phenomena in a natural language, like Modern Greek. We aim at a unified treatment of inflection, compounding, and word-internal phonological changes, in a model that is used for both analysis and generation. After discussing certain difficulties cuase by well-known finitestate approaches, such as Koskenniemi-s two-level model [7] when applied to a computational treatment of compounding, we argue that a morphology-based model provides a more adequate account of word-internal phenomena. Contrary to the finite state approaches that cannot handle hierarchical word constituency in a satisfactory way, we propose a unification-based word grammar, as the nucleus of our strategy, which takes into consideration word representations that are based on affixation and [stem stem] or [stem word] compounds. In our formalism, feature-passing operations are formulated with the use of the unification device, and phonological rules modeling the correspondence between lexical and surface forms apply at morpheme boundaries. In the paper, examples from Modern Greek illustrate our approach. Morpheme structures, stress, and morphologically conditioned phoneme changes are analyzed and generated in a principled way.
Abstract: Grid computing provides an effective infrastructure for massive computation among flexible and dynamic collection of individual system for resource discovery. The major challenge for grid computing is to prevent breaches and secure the data from trespassers. To overcome such conflicts a semantic approach can be designed which will filter the access requests of peers by checking the resource description specifying the data and the metadata as factual statements. Between every node in the grid a semantic firewall as a middleware will be present The intruder will be required to present an application specifying there needs to the firewall and hence accordingly the system will grant or deny the application request.