Abstract: Web-based technologies have created numerous
opportunities for electronic word-of-mouth (eWOM) communication.
There are many factors that affect customer adoption and decisionmaking
process. However, only a few researches focus on some
factors such as the membership time of forum and propensity to trust.
Using a discrete-time event simulation to simulate a diffusion model
along with a consumer decision model, the study shows the effect of
each factor on adoption of opinions on on-line discussion forum. The
purpose of this study is to examine the effect of factor affecting
information adoption and decision making process. The model is
constructed to test quantitative aspects of each factor. The simulation
study shows the membership time and the propensity to trust has an
effect on information adoption and purchasing decision. The result of
simulation shows that the longer the membership time in the
communities and the higher propensity to trust could lead to the
higher demand rates because consumers find it easier and faster to
trust the person in the community and then adopt the eWOM. Other
implications for both researchers and practitioners are provided.
Abstract: This article provides empirical evidence on the effect
of domestic and international factors on the U.S. current account
deficit. Linear dynamic regression and vector autoregression models
are employed to estimate the relationships during the period from 1986
to 2011. The findings of this study suggest that the current and lagged
private saving rate and foreign current account for East Asian
economies have played a vital role in affecting the U.S. current
account. Additionally, using Granger causality tests and variance
decompositions, the change of the productivity growth and foreign
domestic demand are determined to influence significantly the change
of the U.S. current account. To summarize, the empirical relationship
between the U.S. current account deficit and its determinants is
sensitive to alternative regression models and specifications.
Abstract: These days people love to travel around the world.
Regardless of their location and time, they especially Muslims still
need to perform their prayers. Normally for travelers, they need to
bring maps, compass and for Muslim, they even have to bring Qibla
pointer when they travel. It is slightly difficult to determine the Qibla
direction and to know the time for each prayer. As the technology
grows, many PDA equip with maps and GPS to locate their location.
In this paper we present a new electronic device called Mobile Qibla
and Prayer Time Finder to locate the Qibla direction and to
determine each prayer time based on the current user-s location using
PDA. This device use PIC microcontroller equipped with digital
compass where it will communicate with PDA using Bluetooth
technology and display the exact Qibla direction and prayer time
automatically at any place in the world. This device is reliable and
accurate in determining the Qibla direction and prayer time.
Abstract: Previous the 3D model texture generation from multi-view images and mapping algorithms has issues in the texture chart generation which are the self-intersection and the concentration of the texture in texture space. Also we may suffer from some problems due to the occluded areas, such as inside parts of thighs. In this paper we propose a texture mapping technique for 3D models using multi-view images on the GPU. We do texture mapping directly on the GPU fragment shader per pixel without generation of the texture map. And we solve for the occluded area using the 3D model depth information. Our method needs more calculation on the GPU than previous works, but it has shown real-time performance and previously mentioned problems do not occur.
Abstract: A key to success of high quality software development
is to define valid and feasible requirements specification. We have
proposed a method of model-driven requirements analysis using
Unified Modeling Language (UML). The main feature of our method
is to automatically generate a Web user interface mock-up from UML
requirements analysis model so that we can confirm validity of
input/output data for each page and page transition on the system by
directly operating the mock-up. This paper proposes a support method
to check the validity of a data life cycle by using a model checking tool
“UPPAAL" focusing on CRUD (Create, Read, Update and Delete).
Exhaustive checking improves the quality of requirements analysis
model which are validated by the customers through automatically
generated mock-up. The effectiveness of our method is discussed by a
case study of requirements modeling of two small projects which are a
library management system and a supportive sales system for text
books in a university.
Abstract: This research work is aimed at speech recognition
using scaly neural networks. A small vocabulary of 11 words were
established first, these words are “word, file, open, print, exit, edit,
cut, copy, paste, doc1, doc2". These chosen words involved with
executing some computer functions such as opening a file, print
certain text document, cutting, copying, pasting, editing and exit.
It introduced to the computer then subjected to feature extraction
process using LPC (linear prediction coefficients). These features are
used as input to an artificial neural network in speaker dependent
mode. Half of the words are used for training the artificial neural
network and the other half are used for testing the system; those are
used for information retrieval.
The system components are consist of three parts, speech
processing and feature extraction, training and testing by using neural
networks and information retrieval.
The retrieve process proved to be 79.5-88% successful, which is
quite acceptable, considering the variation to surrounding, state of
the person, and the microphone type.
Abstract: In ad hoc networks, the main issue about designing of protocols is quality of service, so that in wireless sensor networks the main constraint in designing protocols is limited energy of sensors. In fact, protocols which minimize the power consumption in sensors are more considered in wireless sensor networks. One approach of reducing energy consumption in wireless sensor networks is to reduce the number of packages that are transmitted in network. The technique of collecting data that combines related data and prevent transmission of additional packages in network can be effective in the reducing of transmitted packages- number. According to this fact that information processing consumes less power than information transmitting, Data Aggregation has great importance and because of this fact this technique is used in many protocols [5]. One of the Data Aggregation techniques is to use Data Aggregation tree. But finding one optimum Data Aggregation tree to collect data in networks with one sink is a NP-hard problem. In the Data Aggregation technique, related information packages are combined in intermediate nodes and form one package. So the number of packages which are transmitted in network reduces and therefore, less energy will be consumed that at last results in improvement of longevity of network. Heuristic methods are used in order to solve the NP-hard problem that one of these optimization methods is to solve Simulated Annealing problems. In this article, we will propose new method in order to build data collection tree in wireless sensor networks by using Simulated Annealing algorithm and we will evaluate its efficiency whit Genetic Algorithm.
Abstract: This paper considers the effect of heat generation
proportional l to (T - T∞ )p , where T is the local temperature and T∞
is the ambient temperature, in unsteady free convection flow near the
stagnation point region of a three-dimensional body. The fluid is
considered in an ambient fluid under the assumption of a step change
in the surface temperature of the body. The non-linear coupled partial
differential equations governing the free convection flow are solved
numerically using an implicit finite-difference method for different
values of the governing parameters entering these equations. The
results for the flow and heat characteristics when p ≤ 2 show that
the transition from the initial unsteady-state flow to the final steadystate
flow takes place smoothly. The behavior of the flow is seen
strongly depend on the exponent p.
Abstract: We investigated oxidative DNA damage caused by
radio frequency radiation using 8-oxo-7, 8-dihydro-2'-
deoxyguanosine (8-oxodG) generated in mice tissues after exposure
to 900 MHz mobile phone radio frequency in three independent
experiments. The RF was generated by a Global System for Mobile
Communication (GSM) signal generator. The radio frequency field
was adjusted to 25 V/m. The whole body specific absorption rate
(SAR) was 1.0 W/kg. Animals were exposed to this field for 30 min
daily for 30 days. 24 h post-exposure, blood serum, brain and spleen
were removed and DNA was isolated. Enzyme-linked
immunosorbent assay (ELISA) was used to measure 8-oxodG
concentration. All animals survived the whole experimental period.
The body weight of animals did not change significantly at the end of
the experiment. No statistically significant differences observed in
the levels of oxidative stress. Our results are not in favor of the
hypothesis that 900 MHz RF induces oxidative damage.
Abstract: Researchers have been applying tional intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI
methods with respect to each game application. In th
our experimental result on the comparison of three evolutionary algorithms – evolution strategy, genetic algorithm, and their hybrid
applied to evolving controller agents for the CIG 2007 Simulated Car Racing competition. Our experimental result shows that, premature
convergence of solutions was observed in the case of ES, and GA outperformed ES in the last half of generations. Besides, a hybrid
which uses GA first and ES next evolved the best solution among the whole solutions being generated. This result shows the ability of GA in
globally searching promising areas in the early stage and the ability of ES in locally searching the focused area (fine-tuning solutions).
Abstract: A ten-year grazing study was conducted at the
Agriculture and Agri-Food Canada Brandon Research Centre in
Manitoba to study the effect of alfalfa inclusion and fertilizer (N, P,
K, and S) addition on economics and efficiency of non-renewable
energy use in meadow brome grass-based pasture systems for beef
production. Fertilizing grass-only or alfalfa-grass pastures to full soil
test recommendations improved pasture productivity, but did not
improve profitability compared to unfertilized pastures. Fertilizing
grass-only pastures resulted in the highest net loss of any pasture
management strategy in this study. Adding alfalfa at the time of
seeding, with no added fertilizer, was economically the best pasture
improvement strategy in this study. Because of moisture limitations,
adding commercial fertilizer to full soil test recommendations is
probably not economically justifiable in most years, especially with
the rising cost of fertilizer. Improving grass-only pastures by adding
fertilizer and/or alfalfa required additional non-renewable energy
inputs; however, the additional energy required for unfertilized
alfalfa-grass pastures was minimal compared to the fertilized
pastures. Of the four pasture management strategies, adding alfalfa
to grass pastures without adding fertilizer had the highest efficiency
of energy use. Based on energy use and economic performance, the
unfertilized alfalfa-grass pasture was the most efficient and
sustainable pasture system.
Abstract: Nevertheless the widespread application of finite
mixture models in segmentation, finite mixture model selection is
still an important issue. In fact, the selection of an adequate number
of segments is a key issue in deriving latent segments structures and
it is desirable that the selection criteria used for this end are effective.
In order to select among several information criteria, which may
support the selection of the correct number of segments we conduct a
simulation study. In particular, this study is intended to determine
which information criteria are more appropriate for mixture model
selection when considering data sets with only categorical
segmentation base variables. The generation of mixtures of
multinomial data supports the proposed analysis. As a result, we
establish a relationship between the level of measurement of
segmentation variables and some (eleven) information criteria-s
performance. The criterion AIC3 shows better performance (it
indicates the correct number of the simulated segments- structure
more often) when referring to mixtures of multinomial segmentation
base variables.
Abstract: Image Compression using Artificial Neural Networks
is a topic where research is being carried out in various directions
towards achieving a generalized and economical network.
Feedforward Networks using Back propagation Algorithm adopting
the method of steepest descent for error minimization is popular and
widely adopted and is directly applied to image compression.
Various research works are directed towards achieving quick
convergence of the network without loss of quality of the restored
image. In general the images used for compression are of different
types like dark image, high intensity image etc. When these images
are compressed using Back-propagation Network, it takes longer
time to converge. The reason for this is, the given image may
contain a number of distinct gray levels with narrow difference with
their neighborhood pixels. If the gray levels of the pixels in an image
and their neighbors are mapped in such a way that the difference in
the gray levels of the neighbors with the pixel is minimum, then
compression ratio as well as the convergence of the network can be
improved. To achieve this, a Cumulative distribution function is
estimated for the image and it is used to map the image pixels. When
the mapped image pixels are used, the Back-propagation Neural
Network yields high compression ratio as well as it converges
quickly.
Abstract: This paper presents the region based segmentation method for ultrasound images using local statistics. In this segmentation approach the homogeneous regions depends on the image granularity features, where the interested structures with dimensions comparable to the speckle size are to be extracted. This method uses a look up table comprising of the local statistics of every pixel, which are consisting of the homogeneity and similarity bounds according to the kernel size. The shape and size of the growing regions depend on this look up table entries. The algorithms are implemented by using connected seeded region growing procedure where each pixel is taken as seed point. The region merging after the region growing also suppresses the high frequency artifacts. The updated merged regions produce the output in formed of segmented image. This algorithm produces the results that are less sensitive to the pixel location and it also allows a segmentation of the accurate homogeneous regions.
Abstract: It well recognized that one feature that makes a
successful company is its ability to successfully align its business goals with its information communication technologies platform.
Enterprise Resource Planning (ERP) systems contribute to achieve better performance by integrating various business functions and
providing support for information flows. However, the technological
systems complexity is known to prevent the business users to exploit in an efficient way the Enterprise Resource Planning Systems (ERP).
This paper aims to investigate the role of training in improving the
usage of ERP systems. To this end, we have designed an instrument
survey to employees of a Norwegian multinational global provider of
technology solutions. Based on the analysis of collected data, we have delineated a training model that could be high relevance for
both researchers and practitioners as a step towards a better
understanding of ERP system implementation.
Abstract: This paper present the harmonic elimination of hybrid
multilevel inverters (HMI) which could be increase the number of
output voltage level. Total Harmonic Distortion (THD) is one of the
most important requirements concerning performance indices.
Because of many numbers output levels of HMI, it had numerous
unknown variables of eliminate undesired individual harmonic and
THD nonlinear equations set. Optimized harmonic stepped waveform
(OHSW) is solving switching angles conventional method, but most
complicated for solving as added level. The artificial intelligent
techniques are deliberation to solve this problem. This paper presents
the Particle Swarm Optimization (PSO) technique for solving
switching angles to get minimum THD and eliminate undesired
individual harmonics of 15-levels hybrid multilevel inverters.
Consequently it had many variables and could eliminate numerous
harmonics. Both advantages including high level of inverter and
Particle Swarm Optimization (PSO) are used as powerful tools for
harmonics elimination.
Abstract: Urban disaster risks and vulnerabilities are great problems for Turkey. The annual loss of life and property through disaster in the world-s major metropolitan areas is increasing. Urban concentrations of the poor and less-informed in environmentally fragile locations suffer the impact of disaster disproportionately. Gecekondu (squatter) developments will compound the inherent risks associated with high-density environments, in appropriate technologies, and inadequate infrastructure. On the other hand, there are many geological disadvantages such as sitting on top of active tectonic plate boundaries, and why having avalanche, flood, and landslide and drought prone areas in Turkey. However, this natural formation is inevitable; the only way to survive in such a harsh geography is to be aware of importance of these natural events and to take political and physical measures. The main aim of this research is to bring up the magnitude of natural hazard risks in Izmir built-up zone, not being taken into consideration adequately. Because the dimensions of the peril are not taken seriously enough, the natural hazard risks, which are commonly well known, are not considered important or they are being forgotten after some time passes. Within this research, the magnitude of natural hazard risks for Izmir is being presented in the scope of concrete and local researches over Izmir risky areas.
Abstract: Knowledge development in companies relies on
knowledge-intensive business processes, which are characterized by
a high complexity in their execution, weak structuring,
communication-oriented tasks and high decision autonomy, and often the need for creativity and innovation. A foundation of knowledge development is provided, which is based on a new conception of
knowledge and knowledge dynamics. This conception consists of a three-dimensional model of knowledge with types, kinds and qualities. Built on this knowledge conception, knowledge dynamics is
modeled with the help of general knowledge conversions between
knowledge assets. Here knowledge dynamics is understood to cover
all of acquisition, conversion, transfer, development and usage of
knowledge. Through this conception we gain a sound basis for
knowledge management and development in an enterprise. Especially
the type dimension of knowledge, which categorizes it according to
its internality and externality with respect to the human being, is crucial for enterprise knowledge management and development,
because knowledge should be made available by converting it to
more external types.
Built on this conception, a modeling approach for knowledgeintensive
business processes is introduced, be it human-driven,e-driven or task-driven processes. As an example for this approach, a model of the creative activity for the renewal planning of
a product is given.
Abstract: In this paper, the dynamics of a system of two van der Pol oscillators with delayed position and velocity is studied. We provide an approximate solution for this system using parameterexpansion method. Also, we obtain approximate values for frequencies of the system. The parameter-expansion method is more efficient than the perturbation method for this system because the method is independent of perturbation parameter assumption.
Abstract: Let (U;D) be a Gr-covering approximation space
(U; C) with covering lower approximation operator D and covering
upper approximation operator D. For a subset X of U, this paper
investigates the following three conditions: (1) X is a definable subset
of (U;D); (2) X is an inner definable subset of (U;D); (3) X is an
outer definable subset of (U;D). It is proved that if one of the above
three conditions holds, then the others hold. These results give a
positive answer of an open problem for definable subsets of covering
approximation spaces.