Abstract: One of the most ancient humankind concerns is knowledge formalization i.e. what a concept is. Concept Analysis, a branch of analytical philosophy, relies on the purpose of decompose the elements, relations and meanings of a concept. This paper aims at presenting a method to make a concept analysis obtaining a knowledge representation suitable to be processed by a computer system using either object-oriented or ontology technologies. Security notion is, usually, known as a set of different concepts related to “some kind of protection". Our method concludes that a more general framework for the concept, despite it is dynamic, is possible and any particular definition (instantiation) depends on the elements used by its construction instead of the concept itself.
Abstract: This paper presents the study of hardness profile of spur gear heated by induction heating process in function of the machine parameters, such as the power (kW), the heating time (s) and the generator frequency (kHz). The global work is realized by 3D finite-element simulation applied to the process by coupling and resolving the electromagnetic field and the heat transfer problems, and it was performed in three distinguished steps. First, a Comsol 3D model was built using an adequate formulation and taking into account the material properties and the machine parameters. Second, the convergence study was conducted to optimize the mesh. Then, the surface temperatures and the case depths were deeply analyzed in function of the initial current density and the heating time in medium frequency (MF) and high frequency (HF) heating modes and the edge effect were studied. Finally, the simulations results are validated using experimental tests.
Abstract: The avian phytohaemagglutinin skin test is being
proved as an in vivo system for the evaluation an avian in vivo T cell
mitogenicity. The test system was one week old Gallus domesticus
broiler Chickens. Five replicates were done for each of the whole,
1:10 dilutions of each of 0.05 IU tuberculin, tetanus immunoglobulin
and DPT vaccine as test materials. The evaluation parameters were
the skin indurations and lymphoblast percentages in bone marrow
lymphocytes.
Tuberculin indurations were 2.06 and 1.26mm for 0.05 IU
respectively while lymphoblast percent were 0.234 and 0.1
accordingly.
The skin indurations of 135mg/ml and 1.35mg/ml tetanus
immunoglobulin were 4.86 and 3.96mm while lymphoblast
percentages were 0.3 and 0.14 respectively.
The whole DPT and 1:10 concentration were with 4.5 and 3.2mm
while their lymphoblast percentages were 0.28 and 0.12 accordingly.
Thus the mitogenicity of the test materials was of dependant type.
Abstract: Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. In this paper both PSO and GA optimization are employed for finding stable reduced order models of single-input- single-output large-scale linear systems. Both the techniques guarantee stability of reduced order model if the original high order model is stable. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example from literature and the results are compared with recently published conventional model reduction technique.
Abstract: One of the processes of slope that occurs every year in Iran and some parts of world and cause a lot of criminal and financial harms is called landslide. They are plenty of method to stability landslide in soil and rock slides. The use of the best method with the least cost and in the shortest time is important for researchers. In this research, determining the best method of stability is investigated by using of Decision Support systems. DSS is made for this purpose and was used (for Hasan Salaran area in Kurdistan). Field study data from topography, slope, geology, geometry of landslide and the related features was used. The related data entered decision making managements programs (DSS) (ALES).Analysis of mass stability indicated the instability potential at present. Research results show that surface and sub surface drainage the best method of stabilizing. Analysis of stability shows that acceptable increase in security coefficient is a consequence of drainage.
Abstract: The objective of this research is to develop the
performance indicators (PIs) in operational level for the Pre-hospital Emergency Medical Service (EMS) system employing in Thailand. This research started with ascertaining the current pre-hospital care
system. The team analyzed the strategies of Narerthorn, a government unit under the ministry of public health, and the existing PIs of the pre-hospital care. Afterwards, the current National Strategic Plan of EMS development (2008-2012) of the Emergency
Medical Institute of Thailand (EMIT) was considered using strategic
analysis to developed Strategy Map (SM) and identified the Success
Factors (SFs). The analysis results from strategy map and SFs were used to develop the Performance Indicators (PIs). To verify the set of
PIs, the team has interviewed with the relevant practitioners for the possibilities to implement the PIs. To this paper, it was to ascertain
that all the developed PIs support the objectives of the strategic plan. Nevertheless, the results showed that the operational level PIs suited
only with the first dimension of National Strategic Plan
(infrastructure and information technology development). Besides,
the SF was the infrastructure development (to contribute the EMS system to people throughout with standard and efficiency both in normally and disaster conditions). Finally, twenty-nine indicators
were developed from the analysis results of SM and SFs.
Abstract: This paper presents a compact thermoelectric power generator system based on temperature difference across the element. The system can transfer the burning heat energy to electric energy directly. The proposed system has a thermoelectric generator and a power control box. In the generator, there are 4 thermoelectric modules (TEMs), each of which uses 2 thermoelectric chips (TEs) and 2 cold sinks, 1 thermal absorber, and 1 thermal conduction flat board. In the power control box, there are 1 storing energy device, 1 converter, and 1 inverter. The total net generating power is about 11W. This system uses commercial portable gas stoves or burns timber or the coal as the heat source, which is easily obtained. It adopts solid-state thermoelectric chips as heat inverter parts. The system has the advantages of being light-weight, quite, and mobile, requiring no maintenance, and havng easily-supplied heat source. The system can be used a as long as burning is allowed. This system works well for highly-mobilized outdoors situations by providing a power for illumination, entertainment equipment or the wireless equipment at refuge. Under heavy storms such as typhoon, when the solar panels become ineffective and the wind-powered machines malfunction, the thermoelectric power generator can continue providing the vital power.
Abstract: The issue of unintentional islanding in PV grid
interconnection still remains as a challenge in grid-connected
photovoltaic (PV) systems. This paper discusses the overview of
popularly used anti-islanding detection methods, practically applied
in PV grid-connected systems. Anti-islanding methods generally can
be classified into four major groups, which include passive methods,
active methods, hybrid methods and communication base methods.
Active methods have been the preferred detection technique over the
years due to very small non-detected zone (NDZ) in small scale
distribution generation. Passive method is comparatively simpler
than active method in terms of circuitry and operations. However, it
suffers from large NDZ that significantly reduces its performance.
Communication base methods inherit the advantages of active and
passive methods with reduced drawbacks. Hybrid method which
evolved from the combination of both active and passive methods
has been proven to achieve accurate anti-islanding detection by many
researchers. For each of the studied anti-islanding methods, the
operation analysis is described while the advantages and
disadvantages are compared and discussed. It is difficult to pinpoint a
generic method for a specific application, because most of the
methods discussed are governed by the nature of application and
system dependent elements. This study concludes that the setup and
operation cost is the vital factor for anti-islanding method selection in
order to achieve minimal compromising between cost and system
quality.
Abstract: The objective of this paper is to estimate realistic
principal extrusion process parameters by means of artificial neural
network. Conventionally, finite element analysis is used to derive
process parameters. However, the finite element analysis of the
extrusion model does not consider the manufacturing process
constraints in its modeling. Therefore, the process parameters
obtained through such an analysis remains highly theoretical.
Alternatively, process development in industrial extrusion is to a
great extent based on trial and error and often involves full-size
experiments, which are both expensive and time-consuming. The
artificial neural network-based estimation of the extrusion process
parameters prior to plant execution helps to make the actual extrusion
operation more efficient because more realistic parameters may be
obtained. And so, it bridges the gap between simulation and real
manufacturing execution system. In this work, a suitable neural
network is designed which is trained using an appropriate learning
algorithm. The network so trained is used to predict the
manufacturing process parameters.
Abstract: This paper introduces a temporal epistemic logic
CBCTL that updates agent-s belief states through communications
in them, based on computational tree logic (CTL). In practical
environments, communication channels between agents may not be
secure, and in bad cases agents might suffer blackouts. In this study,
we provide inform* protocol based on ACL of FIPA, and declare the
presence of secure channels between two agents, dependent on time.
Thus, the belief state of each agent is updated along with the progress
of time. We show a prover, that is a reasoning system for a given
formula in a given a situation of an agent ; if it is directly provable
or if it could be validated through the chains of communications, the
system returns the proof.
Abstract: Software Development Risks Identification (SDRI),
using Fault Tree Analysis (FTA), is a proposed technique to identify
not only the risk factors but also the causes of the appearance of the
risk factors in software development life cycle. The method is based
on analyzing the probable causes of software development failures
before they become problems and adversely affect a project. It uses
Fault tree analysis (FTA) to determine the probability of a particular
system level failures that are defined by A Taxonomy for Sources of
Software Development Risk to deduce failure analysis in which an
undesired state of a system by using Boolean logic to combine a
series of lower-level events. The major purpose of this paper is to use
the probabilistic calculations of Fault Tree Analysis approach to
determine all possible causes that lead to software development risk
occurrence
Abstract: The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations.
As a results of this, Computational Fluid Dynamic (CFD) solvers are
widely used in the aeronautical field. These solvers require the correct
selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on
the proper choice of these parameters.
In this paper we create an expert system capable of making an
accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver.
Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time
required for the convergence of a CFD solver.
Abstract: The authors present an algorithm for order reduction of linear dynamic systems using the combined advantages of stability equation method and the error minimization by Genetic algorithm. The denominator of the reduced order model is obtained by the stability equation method and the numerator terms of the lower order transfer function are determined by minimizing the integral square error between the transient responses of original and reduced order models using Genetic algorithm. The reduction procedure is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. The proposed algorithm has also been extended for the order reduction of linear multivariable systems. Two numerical examples are solved to illustrate the superiority of the algorithm over some existing ones including one example of multivariable system.
Abstract: MinC plays an important role in bacterial cell division
system by inhibiting FtsZ assembly. However, the molecular
mechanism of the action is poorly understood. E. coli MinC Nterminus
domain was purified and crystallized using 1.4 M sodium
citrate pH 6.5 as a precipitant. X-ray diffraction data was collected
and processed to 2.3 Å from a native crystal. The crystal belonged to
space group P212121, with the unit cell parameters a = 52.7, b = 54.0,
c = 64.7 Å. Assuming the presence of two molecules in the
asymmetric unit, the Matthews coefficient value is 1.94 Å3 Da-1,
which corresponds to a solvent content of 36.5%. The overall
structure of MinCN is observed as a dimer form through anti-parallel
ß-strand interaction.
Abstract: In this paper we compare the response of linear and
nonlinear neural network-based prediction schemes in prediction of
received Signal-to-Interference Power Ratio (SIR) in Direct
Sequence Code Division Multiple Access (DS/CDMA) systems. The
nonlinear predictor is Multilayer Perceptron MLP and the linear
predictor is an Adaptive Linear (Adaline) predictor. We solve the
problem of complexity by using the Minimum Mean Squared Error
(MMSE) principle to select the optimal predictors. The optimized
Adaline predictor is compared to optimized MLP by employing
noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an
urban environment. The results show that the Adaline predictor can
estimates SIR with the same error as MLP when the user has the
velocity of 5 km/h and 60 km/h but by increasing the velocity up-to
120 km/h the mean squared error of MLP is two times more than
Adaline predictor. This makes the Adaline predictor (with lower
complexity) more suitable than MLP for closed-loop power control
where efficient and accurate identification of the time-varying
inverse dynamics of the multi path fading channel is required.
Abstract: Supplier selection is a multi criteria decision-making process that comprises tangible and intangible factors. The majority of previous supplier selection techniques do not consider strategic perspective. Besides, uncertainty is one of the most important obstacles in supplier selection. For the first, time in this paper, the idea of the algorithm " Knapsack " is used to select suppliers Moreover, an attempt has to be made to take the advantage of a simple numerical method for solving model .This is an innovation to resolve any ambiguity in choosing suppliers. This model has been tried in the suppliers selected in a competitive environment and according to all desired standards of quality and quantity to show the efficiency of the model, an industry sample has been uses.
Abstract: In this paper back-propagation artificial neural network
(BPANN) is employed to predict the deformation of the upsetting
process. To prepare a training set for BPANN, some finite element
simulations were carried out. The input data for the artificial neural
network are a set of parameters generated randomly (aspect ratio d/h,
material properties, temperature and coefficient of friction). The
output data are the coefficient of polynomial that fitted on barreling
curves. Neural network was trained using barreling curves generated
by finite element simulations of the upsetting and the corresponding
material parameters. This technique was tested for three different
specimens and can be successfully employed to predict the
deformation of the upsetting process
Abstract: Foundation of tower crane serves to ensure stability
against vertical and horizontal forces. If foundation stress is not
sufficient, tower crane may be subject to overturning, shearing or
foundation settlement. Therefore, engineering review of stable support
is a highly critical part of foundation design. However, there are not
many professionals who can conduct engineering review of tower
crane foundation and, if any, they have information only on a small
number of cranes in which they have hands-on experience. It is also
customary to rely on empirical knowledge and tower crane renter-s
recommendations rather than designing foundation on the basis of
engineering knowledge. Therefore, a foundation design automation
system considering not only lifting conditions but also overturning
risk, shearing and vertical force may facilitate production of foolproof
foundation design for experts and enable even non-experts to utilize
professional knowledge that only experts can access now. This study
proposes Automatic Design Algorithm for the Tower Crane
Foundations considering load and horizontal force.
Abstract: The bypass exhaust system of a 160 MW combined cycle has been modeled and analyzed using numerical simulation in 2D prospective. Analysis was carried out using the commercial numerical simulation software, FLUENT 6.2. All inputs were based on the technical data gathered from working conditions of a Siemens V94.2 gas turbine, installed in the Yazd power plant. This paper deals with reduction of pressure drop in bypass exhaust system using turning vanes mounted in diverter box in order to alleviate turbulent energy dissipation rate above diverter box. The geometry of such turning vanes has been optimized based on the flow pattern at diverter box inlet. The results show that the use of optimized turning vanes in diverter box can improve the flow pattern and eliminate vortices around sharp edges just before the silencer. Furthermore, this optimization could decrease the pressure drop in bypass exhaust system and leads to higher plant efficiency.
Abstract: Through the time, the higher education has changed
the learning system since mother tongue to bilingual, and in this new
century has been coming develop a multilingual education. All as
part of globalization process of the countries and the education.
Nevertheless, this change only has been effectively in countries of the
first world, the rest have been lagging. Therefore, these countries
require strengthen their higher education systems through models that
give way to multilingual and bilingual education. In this way, shows
a new model adapted from a systemic form to allow a higher
bilingual and multilingual education in Latin America. This
systematization aims to increase the skills and competencies
student’s, decrease the time learning of a second tongue, add to
multilingualism in the American Latin Universities, also, contribute
to position the region´s countries in a better global status, and
stimulate the development of new research in this area.