Abstract: Designing modern machine tools is a complex task. A
simulation tool to aid the design work, a virtual machine, has
therefore been developed in earlier work. The virtual machine
considers the interaction between the mechanics of the machine
(including structural flexibility) and the control system. This paper
exemplifies the usefulness of the virtual machine as a tool for product
development. An optimisation study is conducted aiming at
improving the existing design of a machine tool regarding weight and
manufacturing accuracy at maintained manufacturing speed. The
problem can be categorised as constrained multidisciplinary multiobjective
multivariable optimisation. Parameters of the control and
geometric quantities of the machine are used as design variables. This
results in a mix of continuous and discrete variables and an
optimisation approach using a genetic algorithm is therefore
deployed. The accuracy objective is evaluated according to
international standards. The complete systems model shows nondeterministic
behaviour. A strategy to handle this based on statistical
analysis is suggested. The weight of the main moving parts is reduced
by more than 30 per cent and the manufacturing accuracy is
improvement by more than 60 per cent compared to the original
design, with no reduction in manufacturing speed. It is also shown
that interaction effects exist between the mechanics and the control,
i.e. this improvement would most likely not been possible with a
conventional sequential design approach within the same time, cost
and general resource frame. This indicates the potential of the virtual
machine concept for contributing to improved efficiency of both
complex products and the development process for such products.
Companies incorporating such advanced simulation tools in their
product development could thus improve its own competitiveness as
well as contribute to improved resource efficiency of society at large.
Abstract: Biochemical investigations were carried out to assess
the effect of different exposure regimes of Kazakhstan crude oil
(KCO) on hepatic antioxidant defense system in albino rats.
Contaminants were delivered under two different dosing regimes,
with all treatments receiving the same total contaminant load by the
end of the exposure period. Rats in regime A injected with KCO
once at a dose of 6 ml/kg bw while in regime B injected multiply at a
dose of 1.5 ml/kg bw on day 1, 3, 5 and 8. Antioxidant biomarkers
were measured in hepatic tissue after 1, 3, 5 and 8 days. Significant
induction was observed in serum aminotransferases (ALT, AST)
(p
Abstract: In this paper, the strength of a stabilizer is determined when the static and fatigue multiaxial loading are applied. Stabilizer is a part of suspension system in the heavy truck for stabilizing the cabin against the vibration of the road which composes of a thin-walled tube joined to a forge component by fillet weld. The component is loaded by non proportional random sequence of torsion and bending. Residual stress of welding process is considered here for static loading. This static loading with road irregularities are applied in this study as fatigue case that can affected in the fillet welded area of this part. The stresses in the welded structure are calculated using FEA. In addition, the fatigue with multi axial loading in the fillet weld is also investigated and the critical zone of the stabilizer is specified and presented by graphs. Residual stresses that have been resulted by the thermal forces are considered in FEA. Force increasing is the element of finding the critical point of the component.
Abstract: Artemia is one of the most conspicuous invertebrates
associated with aquaculture. It can be considered as a model
organism, offering numerous advantages for comprehensive and
multidisciplinary studies using morphologic or molecular methods.
Since DNA extraction is an important step of any molecular
experiment, a new and a rapid method of DNA extraction from adult
Artemia was described in this study. Besides, the efficiency of this
technique was compared with two widely used alternative techniques,
namely Chelex® 100 resin and SDS-chloroform methods. Data
analysis revealed that the new method is the easiest and the most cost
effective method among the other methods which allows a quick and
efficient extraction of DNA from the adult animal.
Abstract: This paper is devoted to a delayed periodic predatorprey system with non-monotonic numerical response on time scales. With the help of a continuation theorem based on coincidence degree theory, we establish easily verifiable criteria for the existence of multiple periodic solutions. As corollaries, some applications are listed. In particular, our results improve and generalize some known ones.
Abstract: The impact of fixed speed squirrel cage type as well as
variable speed doubly fed induction generators (DFIG) on dynamic
performance of a multimachine power system has been investigated.
Detailed models of the various components have been presented and
the integration of asynchronous and synchronous generators has been
carried out through a rotor angle based transform. Simulation studies
carried out considering the conventional dynamic model of squirrel
cage asynchronous generators show that integration, as such, could
degrade to the AC system performance transiently. This article
proposes a frequency or power controller which can effectively
control the transients and restore normal operation of fixed speed
induction generator quickly. Comparison of simulation results
between classical cage and doubly-fed induction generators indicate
that the doubly fed induction machine is more adaptable to
multimachine AC system. Frequency controller installed in the DFIG
system can also improve its transient profile.
Abstract: Geographic Profiling has successfully assisted investigations for serial crimes. Considering the multi-cluster feature of serial criminal spots, we propose a Multi-point Centrography model as a natural extension of Single-point Centrography for geographic profiling. K-means clustering is first performed on the data samples and then Single-point Centrography is adopted to derive a probability distribution on each cluster. Finally, a weighted combinations of each distribution is formed to make next-crime spot prediction. Experimental study on real cases demonstrates the effectiveness of our proposed model.
Abstract: Eye localization is necessary for face recognition and
related application areas. Most of eye localization algorithms reported
so far still need to be improved about precision and computational
time for successful applications. In this paper, we propose an eye
location method based on multi-scale Gabor feature vectors, which is
more robust with respect to initial points. The eye localization based
on Gabor feature vectors first needs to constructs an Eye Model Bunch
for each eye (left or right eye) which consists of n Gabor jets and
average eye coordinates of each eyes obtained from n model face
images, and then tries to localize eyes in an incoming face image by
utilizing the fact that the true eye coordinates is most likely to be very
close to the position where the Gabor jet will have the best Gabor jet
similarity matching with a Gabor jet in the Eye Model Bunch. Similar
ideas have been already proposed in such as EBGM (Elastic Bunch
Graph Matching). However, the method used in EBGM is known to be
not robust with respect to initial values and may need extensive search
range for achieving the required performance, but extensive search
ranges will cause much more computational burden. In this paper, we
propose a multi-scale approach with a little increased computational
burden where one first tries to localize eyes based on Gabor feature
vectors in a coarse face image obtained from down sampling of the
original face image, and then localize eyes based on Gabor feature
vectors in the original resolution face image by using the eye
coordinates localized in the coarse scaled image as initial points.
Several experiments and comparisons with other eye localization
methods reported in the other papers show the efficiency of our
proposed method.
Abstract: Wikis are considered to be part of Web 2.0
technologies that potentially support collaborative learning and
writing. Wikis provide opportunities for multiple users to work on
the same document simultaneously. Most wikis have also a page for
written group discussion. Nevertheless, wikis may be used in
different ways depending on the pedagogy being used, and the
constraints imposed by the course design. This work explores
students- uses of wiki in teacher education. The analysis is based on a
taxonomy for classifying students- activities and actions carried out
on the wiki. The article also discusses the implications for using
wikis as collaborative writing tools in teacher education.
Abstract: Nowadays Multilevel inverters are widely using in various applications. Modulation strategy at fundamental switching frequency like, SHEPWM is prominent technique to eliminate lower order of harmonics with less switching losses and better harmonic profile. The equations which are formed by SHE are highly nonlinear transcendental in nature, there may exist single, multiple or even no solutions for a particular MI. However, some loads such as electrical drives, it is required to operate in whole range of MI. In order to solve SHE equations for whole range of MI, intelligent techniques are well suited to solve equations so as to produce lest %THDV. Hence, this paper uses Continuous genetic algorithm for minimising harmonics. This paper also presents wavelet based analysis of harmonics. The developed algorithm is simulated and %THD from FFT analysis and Wavelet analysis are compared. MATLAB programming environment and SIMULINK models are used whenever necessary.
Abstract: Identifying and classifying intersections according to
severity is very important for implementation of safety related
counter measures and effective models are needed to compare and
assess the severity. Highway safety organizations have considered
intersection safety among their priorities. In spite of significant
advances in highways safety, the large numbers of crashes with high
severities still occur in the highways. Investigation of influential
factors on crashes enables engineers to carry out calculations in order
to reduce crash severity. Previous studies lacked a model capable of
simultaneous illustration of the influence of human factors, road,
vehicle, weather conditions and traffic features including traffic
volume and flow speed on the crash severity. Thus, this paper is
aimed at developing the models to illustrate the simultaneous
influence of these variables on the crash severity in urban highways.
The models represented in this study have been developed using
binary Logit Models. SPSS software has been used to calibrate the
models. It must be mentioned that backward regression method in
SPSS was used to identify the significant variables in the model.
Consider to obtained results it can be concluded that the main
factor in increasing of crash severity in urban highways are driver
age, movement with reverse gear, technical defect of the vehicle,
vehicle collision with motorcycle and bicycle, bridge, frontal impact
collisions, frontal-lateral collisions and multi-vehicle crashes in
urban highways which always increase the crash severity in urban
highways.
Abstract: Introduction applicability of high-speed cutting stock problem (CSP) is presented in this paper. Due to the orders continued coming in from various on-line ways for a professional cutting company, to stay competitive, such a business has to focus on sustained production at high levels. In others words, operators have to keep the machine running to stay ahead of the pack. Therefore, the continuous stock cutting problem with setup is proposed to minimize the cutting time and pattern changing time to meet the on-line given demand. In this paper, a novel method is proposed to solve the problem directly by using cutting patterns directly. A major advantage of the proposed method in series on-line production is that the system can adjust the cutting plan according to the floating orders. Examples with multiple items are demonstrated. The results show considerable efficiency and reliability in high-speed cutting of CSP.
Abstract: This paper presents a tested research concept that
implements a complex evolutionary algorithm, genetic algorithm
(GA), in a multi-microcontroller environment. Parallel Distributed
Genetic Algorithm (PDGA) is employed in adaptive beam forming
technique to reduce power usage of adaptive antenna at WCDMA
base station. Adaptive antenna has dynamic beam that requires more
advanced beam forming algorithm such as genetic algorithm which
requires heavy computation and memory space. Microcontrollers are
low resource platforms that are normally not associated with GAs,
which are typically resource intensive. The aim of this project was to
design a cooperative multiprocessor system by expanding the role of
small scale PIC microcontrollers to optimize WCDMA base station
transmitter power. Implementation results have shown that PDGA
multi-microcontroller system returned optimal transmitted power
compared to conventional GA.
Abstract: Multilevel inverters supplied from equal and constant
dc sources almost don-t exist in practical applications. The variation
of the dc sources affects the values of the switching angles required
for each specific harmonic profile, as well as increases the difficulty
of the harmonic elimination-s equations. This paper presents an
extremely fast optimal solution of harmonic elimination of multilevel
inverters with non-equal dc sources using Tanaka's fuzzy linear
regression formulation. A set of mathematical equations describing
the general output waveform of the multilevel inverter with nonequal
dc sources is formulated. Fuzzy linear regression is then
employed to compute the optimal solution set of switching angles.
Abstract: In this paper, a method based on Non-Dominated
Sorting Genetic Algorithm (NSGA) has been presented for the Volt /
Var control in power distribution systems with dispersed generation
(DG). Genetic algorithm approach is used due to its broad
applicability, ease of use and high accuracy. The proposed method is
better suited for volt/var control problems. A multi-objective
optimization problem has been formulated for the volt/var control of
the distribution system. The non-dominated sorting genetic algorithm
based method proposed in this paper, alleviates the problem of tuning
the weighting factors required in solving the multi-objective volt/var
control optimization problems. Based on the simulation studies
carried out on the distribution system, the proposed scheme has been
found to be simple, accurate and easy to apply to solve the multiobjective
volt/var control optimization problem of the distribution
system with dispersed generation.
Abstract: The paper compares different channel models used for
modeling Broadband Power-Line Communication (BPLC) system.
The models compared are Zimmermann and Dostert, Philipps,
Anatory et al and Anatory et al generalized Transmission Line (TL)
model. The validity of each model was compared in time domain
with ATP-EMTP software which uses transmission line approach. It
is found that for a power-line network with minimum number of
branches all the models give similar signal/pulse time responses
compared with ATP-EMTP software; however, Zimmermann and
Dostert model indicates the same amplitude but different time delay.
It is observed that when the numbers of branches are increased only
generalized TL theory approach results are comparable with ATPEMTP
results. Also the Multi-Carrier Spread Spectrum (MC-SS)
system was applied to check the implication of such behavior on the
modulation schemes. It is observed that using Philipps on the
underground cable can predict the performance up to 25dB better
than other channel models which can misread the actual performance
of the system. Also modified Zimmermann and Dostert under
multipath can predict a better performance of about 5dB better than
the actual predicted by Generalized TL theory. It is therefore
suggested for a realistic BPLC system design and analyses the model
based on generalized TL theory be used.
Abstract: Meta-reasoning is essential for multi-agent communication. In this paper we propose a framework of multi-agent communication in which agents employ meta-reasoning to reason with agent and ontology locations in order to communicate semantic information with other agents on the semantic web and also reason with multiple distributed ontologies. We shall argue that multi-agent communication of Semantic Web information cannot be realized without the need to reason with agent and ontology locations. This is because for an agent to be able to communicate with another agent, it must know where and how to send a message to that agent. Similarly, for an agent to be able to reason with an external semantic web ontology, it must know where and how to access to that ontology. The agent framework and its communication mechanism are formulated entirely in meta-logic.
Abstract: In recent years, copulas have become very popular in
financial research and actuarial science as they are more flexible in
modelling the co-movements and relationships of risk factors as compared
to the conventional linear correlation coefficient by Pearson.
However, a precise estimation of the copula parameters is vital in
order to correctly capture the (possibly nonlinear) dependence structure
and joint tail events. In this study, we employ two optimization
heuristics, namely Differential Evolution and Threshold Accepting to
tackle the parameter estimation of multivariate t distribution models
in the EML approach. Since the evolutionary optimizer does not rely
on gradient search, the EML approach can be applied to estimation of
more complicated copula models such as high-dimensional copulas.
Our experimental study shows that the proposed method provides
more robust and more accurate estimates as compared to the IFM
approach.
Abstract: Most of the academics connect a theory of
multiculturalism with globalization and limit it by last decades of
20th century. However, Kazakh society encountered with this
problem when the Soviet-s rule emerged. As a result of repression,
the Second World War, development of virgin lands representatives
of more than 100 nationalities lives in Kazakhstan. Communist
ideology propagandized internationalism, which would defined
principles of multicultural community but a common ideology
demands a single culture. As a result multicultural society in the
USSR developed under control of Russian culture. Education in the
USSR was conducted in two departments: autochthonous and
Russian. Autochthonous education narrowed student capabilities.
Also because of soviet ideology science was conducted in Russian
Universities provided education in Russian and all science literature
were in Russian. Exceptions were humanitarian fields where Kazakh
departments were admitted. Naturally non-Kazakhs studied in
Russian departments, moreover Kazakhs preferred to study in
Russian as most do nowadays preferring English. As a result Kazakh
society consisted of Kazakhs, Kazakhs who recognized Russian as a
mother tongue and other nationalities who were also Russian
speakers. This aspect continues to distinguish particular qualities of
multicultural community in Kazakhstan.
Abstract: This paper discusses the design characteristics management accounting systems should have to be useful for strategic planning and control and provides brief introductions to strategic variance analysis, profit-linked performance measurement models and balanced scorecard. It shows two multi-period, multiproduct models are specified, can be related to Porter's strategy framework and cost and revenue drivers, and can be used to support strategic planning, control and cost management.