Abstract: International trade involves both large and small firms
engaged in business overseas. Possible drivers that force companies
to enter international markets include increasing competition at the
domestic market, maturing domestic markets, and limited domestic
market opportunities. Technology is an important driving factor in
shaping international marketing strategy as well as in driving force
towards a more global marketplace, especially technology in
communication. It includes telephones, the internet, computer
systems and e-mail. There are three main marketing strategy choices,
namely standardization approach, adaptation approach and middleof-
the-road approach that companies implement to overseas markets.
The decision depends on situations and factors facing the companies
in the international markets. In this paper, the contingency concept is
considered that no single strategy can be effective in all contexts.
The effect of strategy on performance depends on specific situational
variables. Strategic fit is employed to investigate export marketing
strategy adaptation under certain environmental conditions, which in
turn can lead to superior performance.
Abstract: In today scenario, to meet enhanced demand imposed
by domestic, commercial and industrial consumers, various
operational & control activities of Radial Distribution Network
(RDN) requires a focused attention. Irrespective of sub-domains
research aspects of RDN like network reconfiguration, reactive
power compensation and economic load scheduling etc, network
performance parameters are usually estimated by an iterative process
and is commonly known as load (power) flow algorithm. In this
paper, a simple mechanism is presented to implement the load flow
analysis (LFA) algorithm. The reported algorithm utilizes graph
theory principles and is tested on a 69- bus RDN.
Abstract: Water level forecasting using records of past time series is of importance in water resources engineering and management. For example, water level affects groundwater tables in low-lying coastal areas, as well as hydrological regimes of some coastal rivers. Then, a reliable prediction of sea-level variations is required in coastal engineering and hydrologic studies. During the past two decades, the approaches based on the Genetic Programming (GP) and Artificial Neural Networks (ANN) were developed. In the present study, the GP is used to forecast daily water level variations for a set of time intervals using observed water levels. The measurements from a single tide gauge at Urmia Lake, Northwest Iran, were used to train and validate the GP approach for the period from January 1997 to July 2008. Statistics, the root mean square error and correlation coefficient, are used to verify model by comparing with a corresponding outputs from Artificial Neural Network model. The results show that both these artificial intelligence methodologies are satisfactory and can be considered as alternatives to the conventional harmonic analysis.
Abstract: In this article, the flow behavior around a NACA 0012 airfoil which is oscillating with different Reynolds numbers and in various amplitudes has been investigated numerically. Numerical simulations have been performed with ANSYS software. First, the 2- D geometry has been studied in different Reynolds numbers and angles of attack with various numerical methods in its static condition. This analysis was to choose the best turbulent model and comparing the grids to have the optimum one for dynamic simulations. Because the analysis was to study the blades of wind turbines, the Reynolds numbers were not arbitrary. They were in the range of 9.71e5 to 22.65e5. The angle of attack was in the range of -41.81° to 41.81°. By choosing the forward wind speed as the independent parameter, the others like Reynolds and the amplitude of the oscillation would be known automatically. The results show that the SST turbulent model is the best choice that leads the least numerical error with respect the experimental ones. Also, a dynamic stall phenomenon is more probable at lower wind speeds in which the lift force is less.
Abstract: Due to environmental concerns, the recent regulation on automobile fuel economy has been strengthened. The market demand for efficient vehicles is growing and automakers to improve engine fuel efficiency in the industry have been paying a lot of effort. To improve the fuel efficiency, it is necessary to reduce losses or to improve combustion efficiency of the engine. VVA (Variable Valve Actuation) technology enhances the engine's intake air flow, reduce pumping losses and mechanical friction losses. And also, VVA technology is the engine's low speed and high speed operation to implement each of appropriate valve lift. It improves the performance of engine in the entire operating range. This paper presents a design procedure of DC motor and drive for VVA system and shows the validity of the design result by experimental result with prototype.
Abstract: The mosques have been appearance in Thailand since
Ayutthaya Kingdom (1350 to 1767 A.D.) Until today, more than 400 years later; there are many styles of art form behind their structure.
This research intended to identify Islamic Art in Thai mosques. A framework was applied using qualitative research methods; Thai
Muslims with dynamic roles in Islamic culture were interviewed. In
addition, a field survey of 40 selected mosques from 175 Thai
mosques was studied. Data analysis will be according to the pattern
of each period. The identification of Islamic Art in Thai Mosques are
1) the image of Thai identity: with Thai traditional art style and Government policy. 2) The image of the Ethnological identity: with
the traditional culture of Asian Muslims in Thailand. 3) The image of
the Nostalgia identity: with Islamic and Arabian conservative style.
4) The image of the Neo Classic identity: with Neo – Classic and
Contemporary art. 5) The image of the new identity: with Post
Modern and Deconstruction art.
Abstract: the data of Taiwanese 8th grader in the 4th cycle of
Trends in International Mathematics and Science Study (TIMSS) are
analyzed to examine the influence of the science teachers- preference
in experimental teaching on the relationships between the affective
variables ( the perceived usefulness of science, ease of using science
and science learning interest) and the academic achievement in science.
After dealing with the missing data, 3711 students and 145 science
teacher-s data were analyzed through a Hierarchical Linear Modeling
technique. The major objective of this study was to determine the role
of the experimental teaching moderates the relationship between
perceived usefulness and achievement.
Abstract: The structural interpretation of a part of eastern Potwar
(Missa Keswal) has been carried out with available seismological,
seismic and well data. Seismological data contains both the source
parameters and fault plane solution (FPS) parameters and seismic data
contains ten seismic lines that were re-interpreted by using well data.
Structural interpretation depicts two broad types of fault sets namely,
thrust and back thrust faults. These faults together give rise to pop up
structures in the study area and also responsible for many structural
traps and seismicity. Seismic interpretation includes time and depth
contour maps of Chorgali Formation while seismological interpretation
includes focal mechanism solution (FMS), depth, frequency,
magnitude bar graphs and renewal of Seismotectonic map. The Focal
Mechanism Solutions (FMS) that surrounds the study area are
correlated with the different geological and structural maps of the area
for the determination of the nature of subsurface faults. Results of
structural interpretation from both seismic and seismological data
show good correlation. It is hoped that the present work will help in
better understanding of the variations in the subsurface structure and
can be a useful tool for earthquake prediction, planning of oil field and
reservoir monitoring.
Abstract: In this paper, an optimal design of linear phase digital
high pass finite impulse response (FIR) filter using Particle Swarm
Optimization with Constriction Factor and Inertia Weight Approach
(PSO-CFIWA) has been presented. In the design process, the filter
length, pass band and stop band frequencies, feasible pass band and
stop band ripple sizes are specified. FIR filter design is a multi-modal
optimization problem. The conventional gradient based optimization
techniques are not efficient for digital filter design. Given the filter
specifications to be realized, the PSO-CFIWA algorithm generates a
set of optimal filter coefficients and tries to meet the ideal frequency
response characteristic. In this paper, for the given problem, the
designs of the optimal FIR high pass filters of different orders have
been performed. The simulation results have been compared to those
obtained by the well accepted algorithms such as Parks and
McClellan algorithm (PM), genetic algorithm (GA). The results
justify that the proposed optimal filter design approach using PSOCFIWA
outperforms PM and GA, not only in the accuracy of the
designed filter but also in the convergence speed and solution
quality.
Abstract: The importance of supply chain and logistics
management has been widely recognised. Effective management of
the supply chain can reduce costs and lead times and improve
responsiveness to changing customer demands. This paper proposes a
multi-matrix real-coded Generic Algorithm (MRGA) based
optimisation tool that minimises total costs associated within supply
chain logistics. According to finite capacity constraints of all parties
within the chain, Genetic Algorithm (GA) often produces infeasible
chromosomes during initialisation and evolution processes. In the
proposed algorithm, chromosome initialisation procedure, crossover
and mutation operations that always guarantee feasible solutions
were embedded. The proposed algorithm was tested using three sizes
of benchmarking dataset of logistic chain network, which are typical
of those faced by most global manufacturing companies. A half
fractional factorial design was carried out to investigate the influence
of alternative crossover and mutation operators by varying GA
parameters. The analysis of experimental results suggested that the
quality of solutions obtained is sensitive to the ways in which the
genetic parameters and operators are set.
Abstract: This paper presents the novel Rao-Blackwellised
particle filter (RBPF) for mobile robot simultaneous localization and
mapping (SLAM) using monocular vision. The particle filter is
combined with unscented Kalman filter (UKF) to extending the path
posterior by sampling new poses that integrate the current observation
which drastically reduces the uncertainty about the robot pose. The
landmark position estimation and update is also implemented through
UKF. Furthermore, the number of resampling steps is determined
adaptively, which seriously reduces the particle depletion problem,
and introducing the evolution strategies (ES) for avoiding particle
impoverishment. The 3D natural point landmarks are structured with
matching Scale Invariant Feature Transform (SIFT) feature pairs. The
matching for multi-dimension SIFT features is implemented with a
KD-Tree in the time cost of O(log2
N). Experiment results on real robot
in our indoor environment show the advantages of our methods over
previous approaches.
Abstract: Deep Brain Stimulation or DBS is a surgical treatment for Parkinson-s Disease with three stimulation parameters: frequency, pulse width, and voltage. The parameters should be selected appropriately to achieve effective treatment. This selection now, performs clinically. The aim of this research is to study chaotic behavior of recorded tremor of patients under DBS in order to present a computational method to recognize stimulation optimum voltage. We obtained some chaotic features of tremor signal, and discovered embedding space of it has an attractor, and its largest Lyapunov exponent is positive, which show tremor signal has chaotic behavior, also we found out, in optimal voltage, entropy and embedding space variance of tremor signal have minimum values in comparison with other voltages. These differences can help neurologists recognize optimal voltage numerically, which leads to reduce patients' role and discomfort in optimizing stimulation parameters and to do treatment with high accuracy.
Abstract: Wireless sensor network can be applied to both abominable
and military environments. A primary goal in the design of
wireless sensor networks is lifetime maximization, constrained by
the energy capacity of batteries. One well-known method to reduce
energy consumption in such networks is data aggregation. Providing
efcient data aggregation while preserving data privacy is a challenging
problem in wireless sensor networks research. In this paper,
we present privacy-preserving data aggregation scheme for additive
aggregation functions. The Cluster-based Private Data Aggregation
(CPDA)leverages clustering protocol and algebraic properties of
polynomials. It has the advantage of incurring less communication
overhead. The goal of our work is to bridge the gap between
collaborative data collection by wireless sensor networks and data
privacy. We present simulation results of our schemes and compare
their performance to a typical data aggregation scheme TAG, where
no data privacy protection is provided. Results show the efficacy and
efficiency of our schemes.
Abstract: Social ideology, cultural values and principles shaping environment are inferred by environment and structural characteristics of construction site. In other words, this inference manifestation also indicates ideology and culture of its foundation and also applies its principles and values and somehow plays an important role in Cultural Revolution. All human behaviors and artifacts are affected and being influenced by culture. Culture is not abstract concept, it is a spiritual domain that an individual and society grow and develop in it. Social behaviors are affected by environmental comprehension, so the architecture work influences on its audience and it is the environment that fosters social behaviors. Indeed, sustainable architecture should be considered as background of culture for establishing optimal sustainable culture. Since unidentified architecture roots in cultural non identity and abnormalities, so the society possesses identity characteristics and life and as a consequence, the society and architecture are changed by transformation of life style. This article aims to investigate the interaction of architecture, society, environment and sustainable architecture formation in its cultural basis and analyzes the results approaching behavior and sustainable culture in recent era.
Abstract: In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.
Abstract: A lot of research has been done in the past decade in the field of audio content analysis for extracting various information from audio signal. One such significant information is the "perceived mood" or the "emotions" related to a music or audio clip. This information is extremely useful in applications like creating or adapting the play-list based on the mood of the listener. This information could also be helpful in better classification of the music database. In this paper we have presented a method to classify music not just based on the meta-data of the audio clip but also include the "mood" factor to help improve the music classification. We propose an automated and efficient way of classifying music samples based on the mood detection from the audio data. We in particular try to classify the music based on mood for Indian bollywood music. The proposed method tries to address the following problem statement: Genre information (usually part of the audio meta-data) alone does not help in better music classification. For example the acoustic version of the song "nothing else matters by Metallica" can be classified as melody music and thereby a person in relaxing or chill out mood might want to listen to this track. But more often than not this track is associated with metal / heavy rock genre and if a listener classified his play-list based on the genre information alone for his current mood, the user shall miss out on listening to this track. Currently methods exist to detect mood in western or similar kind of music. Our paper tries to solve the issue for Indian bollywood music from an Indian cultural context
Abstract: In this study, an analysis has been performed for
conjugate heat and mass transfer of a steady laminar boundary-layer
mixed convection of magnetic hydrodynamic (MHD) flow with
radiation effect of second grade subject to suction past a stretching
sheet. Parameters E Nr, Gr, Gc, Ec and Sc represent the dominance of
the viscoelastic fluid heat and mass transfer effect which have
presented in governing equations, respectively. The similar
transformation and the finite-difference method have been used to
analyze the present problem. The conjugate heat and mass transfer
results show that the non-Newtonian viscoelastic fluid has a better heat
transfer effect than the Newtonian fluid. The free convection with a
larger r G or c G has a good heat transfer effect better than a smaller
r G or c G , and the radiative convection has a good heat transfer
effect better than non-radiative convection.
Abstract: The expectation of network performance from the
early days of ARPANET until now has been changed significantly.
Every day, new advancement in technological infrastructure opens
the doors for better quality of service and accordingly level of
perceived quality of network services have been increased over the
time. Nowadays for many applications, late information has no value
or even may result in financial or catastrophic loss, on the other hand,
demands for some level of guarantee in providing and maintaining
quality of service are ever increasing. Based on this history, having a
QoS aware routing system which is able to provide today's required
level of quality of service in the networks and effectively adapt to the
future needs, seems as a key requirement for future Internet. In this
work we have extended the traditional AntNet routing system to
support QoS with multiple metrics such as bandwidth and delay
which is named Q-Net. This novel scalable QoS routing system aims
to provide different types of services in the network simultaneously.
Each type of service can be provided for a period of time in the
network and network nodes do not need to have any previous
knowledge about it. When a type of quality of service is requested,
Q-Net will allocate required resources for the service and will
guarantee QoS requirement of the service, based on target objectives.
Abstract: In this paper a new concept named Intuitionistic Fuzzy
Multiset is introduced. The basic operations on Intuitionistic Fuzzy
Multisets such as union, intersection, addition, multiplication etc. are
discussed. An application of Intuitionistic Fuzzy Multiset in Medical diagnosis problem using a distance function is discussed in detail.
Abstract: In this paper we propose a segmentation system for unconstrained Arabic online handwriting. An essential problem addressed by analytical-based word recognition system. The system is composed of two-stages the first is a newly special designed hidden Markov model (HMM) and the second is a rules based stage. In our system, handwritten words are broken up into characters by simultaneous segmentation-recognition using HMMs of unique design trained using online features most of which are novel. The HMM output characters boundaries represent the proposed segmentation points (PSP) which are then validated by rules-based post stage without any contextual information help to solve different segmentation errors. The HMM has been designed and tested using a self collected dataset (OHASD) [1]. Most errors cases are cured and remarkable segmentation enhancement is achieved. Very promising word and character segmentation rates are obtained regarding the unconstrained Arabic handwriting difficulty and not using context help.