Abstract: PARADIGMA (PARticipative Approach to DIsease
Global Management) is a pilot project which aims to develop and
demonstrate an Internet based reference framework to share scientific
resources and findings in the treatment of major diseases.
PARADIGMA defines and disseminates a common methodology and
optimised protocols (Clinical Pathways) to support service functions
directed to patients and individuals on matters like prevention, posthospitalisation
support and awareness. PARADIGMA will provide a
platform of information services - user oriented and optimised
against social, cultural and technological constraints - supporting the
Health Care Global System of the Euro-Mediterranean Community
in a continuous improvement process.
Abstract: The objective of this study was to improve our
understanding of vulnerability and environmental change; it's causes
basically show the intensity, its distribution and human-environment
effect on the ecosystem in the Apodi Valley Region, This paper is
identify, assess and classify vulnerability and environmental change
in the Apodi valley region using a combined approach of landscape
pattern and ecosystem sensitivity. Models were developed using the
following five thematic layers: Geology, geomorphology, soil,
vegetation and land use/cover, by means of a Geographical
Information Systems (GIS)-based on hydro-geophysical parameters.
In spite of the data problems and shortcomings, using ESRI-s ArcGIS
9.3 program, the vulnerability score, to classify, weight and combine
a number of 15 separate land cover classes to create a single indicator
provides a reliable measure of differences (6 classes) among regions
and communities that are exposed to similar ranges of hazards.
Indeed, the ongoing and active development of vulnerability
concepts and methods have already produced some tools to help
overcome common issues, such as acting in a context of high
uncertainties, taking into account the dynamics and spatial scale of
asocial-ecological system, or gathering viewpoints from different
sciences to combine human and impact-based approaches. Based on
this assessment, this paper proposes concrete perspectives and
possibilities to benefit from existing commonalities in the
construction and application of assessment tools.
Abstract: Indoor air distribution has great impact on people-s thermal sensation. Therefore, how to remove the indoor excess heat becomes an important issue to create a thermally comfortable indoor environment. To expel the extra indoor heat effectively, this paper used a dynamic CFD approach to study the effect of an air-supply guide vane swinging periodically on the indoor air distribution within a model room. The numerical results revealed that the indoor heat transfer performance caused by the swing guide vane had close relation with the number of vortices developing under the inlet cold jet. At larger swing amplitude, two smaller vortices continued to shed outward under the cold jet and remove the indoor heat load more effectively. As a result, it can be found that the average Nusselt number on the floor increased with the increase of the swing amplitude of the guide vane.
Abstract: carbonylation of methanol in homogenous phase is
one of the major routesfor production of acetic acid. Amongst group
VIII metal catalysts used in this process iridium has displayed the
best capabilities. To investigate effect of operating parameters like:
temperature, pressure, methyl iodide, methyl acetate, iridium,
ruthenium, and water concentrations on the reaction rate,
experimental design for this system based upon central composite
design (CCD) was utilized. Statistical rate equation developed by this
method contained individual, interactions and curvature effects of
parameters on the reaction rate. The model with p-value less than
0.0001 and R2 values greater than 0.9; confirmeda satisfactory fitness
of the experimental and theoretical studies. In other words, the
developed model and experimental data obtained passed all
diagnostic tests establishing this model as a statistically significant.
Abstract: Multimedia information availability has increased
dramatically with the advent of video broadcasting on handheld
devices. But with this availability comes problems of maintaining the
security of information that is displayed in public. ISMA Encryption
and Authentication (ISMACryp) is one of the chosen technologies for
service protection in DVB-H (Digital Video Broadcasting-
Handheld), the TV system for portable handheld devices. The
ISMACryp is encoded with H.264/AVC (advanced video coding),
while leaving all structural data as it is. Two modes of ISMACryp are
available; the CTR mode (Counter type) and CBC mode (Cipher
Block Chaining) mode. Both modes of ISMACryp are based on 128-
bit AES algorithm. AES algorithms are more complex and require
larger time for execution which is not suitable for real time
application like live TV. The proposed system aims to gain a deep
understanding of video data security on multimedia technologies and
to provide security for real time video applications using selective
encryption for H.264/AVC. Five level of security proposed in this
paper based on the content of NAL unit in Baseline Constrain profile
of H.264/AVC. The selective encryption in different levels provides
encryption of intra-prediction mode, residue data, inter-prediction
mode or motion vectors only. Experimental results shown in this
paper described that fifth level which is ISMACryp provide higher
level of security with more encryption time and the one level provide
lower level of security by encrypting only motion vectors with lower
execution time without compromise on compression and quality of
visual content. This encryption scheme with compression process
with low cost, and keeps the file format unchanged with some direct
operations supported. Simulation was being carried out in Matlab.
Abstract: Stable nonzero populations without random deaths
caused by the Verhulst factor (Verhulst-free) are a rarity. Majority
either grow without bounds or die of excessive harmful mutations.
To delay the accumulation of bad genes or diseases, a new
environmental parameter Γ is introduced in the simulation. Current
results demonstrate that stability may be achieved by setting Γ = 0.1.
These steady states approach a maximum size that scales inversely
with reproduction age.
Abstract: The design of Automatic Generation Control (AGC) system plays a vital role in automation of power system. This paper proposes Hybrid Neuro Fuzzy (HNF) approach for AGC of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The advantage of proposed controller is that it can handle the system non-linearities and at the same time the proposed approach is faster than conventional controllers. The performance of HNF controller has been compared with that of both conventional Proportional Integral (PI) controller as well as Fuzzy Logic Controller (FLC) both in the absence and presence of Generation Rate Constraint (GRC). System performance is examined considering disturbance in each area of interconnected power system.
Abstract: The review performed on the condition of energy
consumption & rate in Iran, shows that unfortunately the subject of
optimization and conservation of energy in active industries of
country lacks a practical & effective method and in most factories,
the energy consumption and rate is more than in similar industries of
industrial countries. The increasing demand of electrical energy and
the overheads which it imposes on the organization, forces
companies to search for suitable approaches to optimize energy
consumption and demand management. Application of value
engineering techniques is among these approaches. Value
engineering is considered a powerful tool for improving profitability.
These tools are used for reduction of expenses, increasing profits,
quality improvement, increasing market share, performing works in
shorter durations, more efficient utilization of sources & etc.
In this article, we shall review the subject of value engineering and
its capabilities for creating effective transformations in industrial
organizations, in order to reduce energy costs & the results have
been investigated and described during a case study in Mazandaran
wood and paper industries, the biggest consumer of energy in north
of Iran, for the purpose of presenting the effects of performed tasks
in optimization of energy consumption by utilizing value engineering
techniques in one case study.
Abstract: The paper presents an approach for handling uncertain
information in deductive databases using multivalued logics. Uncertainty
means that database facts may be assigned logical values other
than the conventional ones - true and false. The logical values represent
various degrees of truth, which may be combined and propagated
by applying the database rules. A corresponding multivalued database
semantics is defined. We show that it extends successful conventional
semantics as the well-founded semantics, and has a polynomial time
data complexity.
Abstract: In this study, the Taguchi method was used to optimize the effect of HALO structure or halo implant variations on threshold voltage (VTH) and leakage current (ILeak) in 45nm p-type Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) device. Besides halo implant dose, the other process parameters which used were Source/Drain (S/D) implant dose, oxide growth temperature and silicide anneal temperature. This work was done using TCAD simulator, consisting of a process simulator, ATHENA and device simulator, ATLAS. These two simulators were combined with Taguchi method to aid in design and optimize the process parameters. In this research, the most effective process parameters with respect to VTH and ILeak are halo implant dose (40%) and S/D implant dose (52%) respectively. Whereas the second ranking factor affecting VTH and ILeak are oxide growth temperature (32%) and halo implant dose (34%) respectively. The results show that after optimizations approaches is -0.157V at ILeak=0.195mA/μm.
Abstract: Road crashes not only claim lives and inflict injuries but also create economic burden to the society due to loss of productivity. The problem of deaths and injuries as a result of road traffic crashes is now acknowledged to be a global phenomenon with authorities in virtually all countries of the world concerned about the growth in the number of people killed and seriously injured on their roads. However, the road crash scenario of a developing country like Bangladesh is much worse comparing with this of developed countries. For developing proper countermeasures it is necessary to identify the factors affecting crash occurrences. The objectives of the study is to examine the effect of district wise road infrastructure, socioeconomic and demographic features on crash occurrence .The unit of analysis will be taken as individual district which has not been explored much in the past. Reported crash data obtained from Bangladesh Road Transport Authority (BRTA) from the year 2004 to 2010 are utilized to develop negative binomial model. The model result will reveal the effect of road length (both paved and unpaved), road infrastructure and several socio economic characteristics on district level crash frequency in Bangladesh.
Abstract: In this paper, the implementation of a rule-based
intuitive reasoner is presented. The implementation included two
parts: the rule induction module and the intuitive reasoner. A large
weather database was acquired as the data source. Twelve weather
variables from those data were chosen as the “target variables"
whose values were predicted by the intuitive reasoner. A “complex"
situation was simulated by making only subsets of the data available
to the rule induction module. As a result, the rules induced were
based on incomplete information with variable levels of certainty.
The certainty level was modeled by a metric called "Strength of
Belief", which was assigned to each rule or datum as ancillary
information about the confidence in its accuracy. Two techniques
were employed to induce rules from the data subsets: decision tree
and multi-polynomial regression, respectively for the discrete and the
continuous type of target variables. The intuitive reasoner was tested
for its ability to use the induced rules to predict the classes of the
discrete target variables and the values of the continuous target
variables. The intuitive reasoner implemented two types of
reasoning: fast and broad where, by analogy to human thought, the
former corresponds to fast decision making and the latter to deeper
contemplation. . For reference, a weather data analysis approach
which had been applied on similar tasks was adopted to analyze the
complete database and create predictive models for the same 12
target variables. The values predicted by the intuitive reasoner and
the reference approach were compared with actual data. The intuitive
reasoner reached near-100% accuracy for two continuous target
variables. For the discrete target variables, the intuitive reasoner
predicted at least 70% as accurately as the reference reasoner. Since
the intuitive reasoner operated on rules derived from only about 10%
of the total data, it demonstrated the potential advantages in dealing
with sparse data sets as compared with conventional methods.
Abstract: Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).
Abstract: This paper presents the development of an electricity simulation model taking into account electrical network constraints, applied on the Belgian power system. The base of the model is optimizing an extensive Unit Commitment (UC) problem through the use of Mixed Integer Linear Programming (MILP). Electrical constraints are incorporated through the implementation of a DC load flow. The model encloses the Belgian power system in a 220 – 380 kV high voltage network (i.e., 93 power plants and 106 nodes). The model features the use of pumping storage facilities as well as the inclusion of spinning reserves in a single optimization process. Solution times of the model stay below reasonable values.
Abstract: In this paper, we present a novel statistical approach to
corpus-based speech synthesis. Classically, phonetic information is
defined and considered as acoustic reference to be respected. In this
way, many studies were elaborated for acoustical unit classification.
This type of classification allows separating units according to their
symbolic characteristics. Indeed, target cost and concatenation cost
were classically defined for unit selection.
In Corpus-Based Speech Synthesis System, when using large text
corpora, cost functions were limited to a juxtaposition of symbolic
criteria and the acoustic information of units is not exploited in the
definition of the target cost.
In this manuscript, we token in our consideration the unit phonetic
information corresponding to acoustic information. This would be realized
by defining a probabilistic linguistic Bi-grams model basically
used for unit selection. The selected units would be extracted from
the English TIMIT corpora.
Abstract: A numerical method is developed for simulating
the motion of particles with arbitrary shapes in an effectively
infinite or bounded viscous flow. The particle translational and
angular motions are numerically investigated using a fluid-structure
interaction (FSI) method based on the Arbitrary-Lagrangian-Eulerian
(ALE) approach and the dynamic mesh method (smoothing and
remeshing) in FLUENT ( ANSYS Inc., USA). Also, the effects of
arbitrary shapes on the dynamics are studied using the FSI method
which could be applied to the motions and deformations of a single
blood cell and multiple blood cells, and the primary thrombogenesis
caused by platelet aggregation. It is expected that, combined with a
sophisticated large-scale computational technique, the simulation
method will be useful for understanding the overall properties of blood
flow from blood cellular level (microscopic) to the resulting
rheological properties of blood as a mass (macroscopic).
Abstract: During the last years, the genomes of more and more
species have been sequenced, providing data for phylogenetic recon-
struction based on genome rearrangement measures. A main task in
all phylogenetic reconstruction algorithms is to solve the median of
three problem. Although this problem is NP-hard even for the sim-
plest distance measures, there are exact algorithms for the breakpoint
median and the reversal median that are fast enough for practical use.
In this paper, this approach is extended to the transposition median as
well as to the weighted reversal and transposition median. Although
there is no exact polynomial algorithm known even for the pairwise
distances, we will show that it is in most cases possible to solve
these problems exactly within reasonable time by using a branch and
bound algorithm.
Abstract: This paper presents a new method for the
implementation of a direct rotor flux control (DRFOC) of induction
motor (IM) drives. It is based on the rotor flux components
regulation. The d and q axis rotor flux components feed proportional
integral (PI) controllers. The outputs of which are the target stator
voltages (vdsref and vqsref). While, the synchronous speed is depicted at
the output of rotor speed controller. In order to accomplish variable
speed operation, conventional PI like controller is commonly used.
These controllers provide limited good performances over a wide
range of operations even under ideal field oriented conditions. An
alternate approach is to use the so called fuzzy logic controller. The
overall investigated system is implemented using dSpace system
based on digital signal processor (DSP). Simulation and experimental
results have been presented for a one kw IM drives to confirm the
validity of the proposed algorithms.
Abstract: Specification-based testing enables us to detect errors
in the implementation of functions defined in given specifications.
Its effectiveness in achieving high path coverage and efficiency in
generating test cases are always major concerns of testers. The automatic
test cases generation approach based on formal specifications
proposed by Liu and Nakajima is aimed at ensuring high effectiveness
and efficiency, but this approach has not been empirically assessed.
In this paper, we present an experiment for assessing Liu-s testing
approach. The result indicates that this testing approach may not be
effective in some circumstances. We discuss the result, analyse the
specific causes for the ineffectiveness, and describe some suggestions
for improvement.
Abstract: Knowledge is attributed to human whose problemsolving
behavior is subjective and complex. In today-s knowledge
economy, the need to manage knowledge produced by a community
of actors cannot be overemphasized. This is due to the fact that
actors possess some level of tacit knowledge which is generally
difficult to articulate. Problem-solving requires searching and sharing
of knowledge among a group of actors in a particular context.
Knowledge expressed within the context of a problem resolution
must be capitalized for future reuse. In this paper, an approach that
permits dynamic capitalization of relevant and reliable actors-
knowledge in solving decision problem following Economic
Intelligence process is proposed. Knowledge annotation method and
temporal attributes are used for handling the complexity in the
communication among actors and in contextualizing expressed
knowledge. A prototype is built to demonstrate the functionalities of
a collaborative Knowledge Management system based on this
approach. It is tested with sample cases and the result showed that
dynamic capitalization leads to knowledge validation hence
increasing reliability of captured knowledge for reuse. The system
can be adapted to various domains.