Abstract: The Mobile Ad-hoc Network (MANET) is a collection of self-configuring and rapidly deployed mobile nodes (routers) without any central infrastructure. Routing is one of the potential issues. Many routing protocols are reported but it is difficult to decide which one is best in all scenarios. In this paper on demand routing protocols DSR and DYMO based on IEEE 802.11 DCF MAC protocol are examined and characteristic summary of these routing protocols is presented. Their performance is analyzed and compared on performance measuring metrics throughput, dropped packets due to non availability of routes, duplicate RREQ generated for route discovery and normalized routing load by varying CBR data traffic load using QualNet 5.0.2 network simulator.
Abstract: This paper studies the mean square exponential synchronization problem of a class of stochastic neutral type chaotic neural networks with mixed delay. On the Basis of Lyapunov stability theory, some sufficient conditions ensuring the mean square exponential synchronization of two identical chaotic neural networks are obtained by using stochastic analysis and inequality technique. These conditions are expressed in the form of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. The feedback controller used in this paper is more general than those used in previous literatures. One simulation example is presented to demonstrate the effectiveness of the derived results.
Abstract: Data envelopment analysis (DEA) has gained great popularity in environmental performance measurement because it can provide a synthetic standardized environmental performance index when pollutants are suitably incorporated into the traditional DEA framework. Since some of the environmental performance indicators cannot be controlled by companies managers, it is necessary to develop the model in a way that it could be applied when discretionary and/or non-discretionary factors were involved. In this paper, we present a semi-radial DEA approach to measuring environmental performance, which consists of non-discretionary factors. The model, then, has been applied on a real case.
Abstract: In the automotive industry test drives are being conducted
during the development of new vehicle models or as a part of
quality assurance of series-production vehicles. The communication
on the in-vehicle network, data from external sensors, or internal
data from the electronic control units is recorded by automotive
data loggers during the test drives. The recordings are used for fault
analysis. Since the resulting data volume is tremendous, manually
analysing each recording in great detail is not feasible.
This paper proposes to use machine learning to support domainexperts
by preventing them from contemplating irrelevant data and
rather pointing them to the relevant parts in the recordings. The
underlying idea is to learn the normal behaviour from available
recordings, i.e. a training set, and then to autonomously detect
unexpected deviations and report them as anomalies.
The one-class support vector machine “support vector data description”
is utilised to calculate distances of feature vectors. SVDDSUBSEQ
is proposed as a novel approach, allowing to classify subsequences
in multivariate time series data. The approach allows to
detect unexpected faults without modelling effort as is shown with
experimental results on recordings from test drives.
Abstract: The trends of design and development of information systems have undergone a variety of ongoing phases and stages. These variations have been evolved due to brisk changes in user requirements and business needs. To meet these requirements and needs, a flexible and agile business solution was required to come up with the latest business trends and styles. Another obstacle in agility of information systems was typically different treatment of same diseases of two patients: business processes and information services. After the emergence of information technology, the business processes and information systems have become counterparts. But these two business halves have been treated under totally different standards. There is need to streamline the boundaries of these both pillars that are equally sharing information system's burdens and liabilities. In last decade, the object orientation has evolved into one of the major solutions for modern business needs and now, SOA is the solution to shift business on ranks of electronic platform. BPM is another modern business solution that assists to regularize optimization of business processes. This paper discusses how object orientation can be conformed to incorporate or embed SOA in BPM for improved information systems.
Abstract: With the advent of inexpensive 32 bit floating point digital signal processor-s availability in market, many computationally intensive algorithms such as Kalman filter becomes feasible to implement in real time. Dynamic simulation of a self excited DC motor using second order state variable model and implementation of Kalman Filter in a floating point DSP TMS320C6713 is presented in this paper with an objective to introduce and implement such an algorithm, for beginners. A fractional hp DC motor is simulated in both Matlab® and DSP and the results are included. A step by step approach for simulation of DC motor in Matlab® and “C" routines in CC Studio® is also given. CC studio® project file details and environmental setting requirements are addressed. This tutorial can be used with 6713 DSK, which is based on floating point DSP and CC Studio either in hardware mode or in simulation mode.
Abstract: Every organization is continually subject to new damages and threats which can be resulted from their operations or their goal accomplishment. Methods of providing the security of space and applied tools have been widely changed with increasing application and development of information technology (IT). From this viewpoint, information security management systems were evolved to construct and prevent reiterating the experienced methods. In general, the correct response in information security management systems requires correct decision making, which in turn requires the comprehensive effort of managers and everyone involved in each plan or decision making. Obviously, all aspects of work or decision are not defined in all decision making conditions; therefore, the possible or certain risks should be considered when making decisions. This is the subject of risk management and it can influence the decisions. Investigation of different approaches in the field of risk management demonstrates their progress from quantitative to qualitative methods with a process approach.
Abstract: We present a system that finds road boundaries and
constructs the virtual lane based on fusion data from a laser and a
monocular sensor, and detects forward vehicle position even in no lane
markers or bad environmental conditions. When the road environment
is dark or a lot of vehicles are parked on the both sides of the road, it is
difficult to detect lane and road boundary. For this reason we use
fusion of laser and vision sensor to extract road boundary to acquire
three dimensional data. We use parabolic road model to calculate road
boundaries which is based on vehicle and sensors state parameters and
construct virtual lane. And then we distinguish vehicle position in each
lane.
Abstract: The purpose of this article is to analyze economic and
political tendencies of development of integration processes with
different developing level and speed on the Eurasian space, by considering two organizations at the region – Eurasian Economic
Community and Shanghai Cooperation Organization, by considering the interests of participations in organizations of Russia and China as
a global powers and Kazakhstan as a leader among the Central Asian
countries. This article investigates what certain goals Eurasian
countries (especially Russia, Kazakhstan and China) are waiting from integration within the SCO and the EurAsEC, linking the process
with the theories of regional integration. After European debt crisis it is more topically to research the integration within the specific
region's conditions.
Abstract: Knowledge sharing in general and the contextual
access to knowledge in particular, still represent a key challenge in
the knowledge management framework. Researchers on semantic
web and human machine interface study techniques to enhance this
access. For instance, in semantic web, the information retrieval is
based on domain ontology. In human machine interface, keeping
track of user's activity provides some elements of the context that can
guide the access to information. We suggest an approach based on
these two key guidelines, whilst avoiding some of their weaknesses.
The approach permits a representation of both the context and the
design rationale of a project for an efficient access to knowledge. In
fact, the method consists of an information retrieval environment
that, in the one hand, can infer knowledge, modeled as a semantic
network, and on the other hand, is based on the context and the
objectives of a specific activity (the design). The environment we
defined can also be used to gather similar project elements in order to
build classifications of tasks, problems, arguments, etc. produced in a
company. These classifications can show the evolution of design
strategies in the company.
Abstract: This purpose of this paper is to develop and validate a
model to accurately predict the cell temperature of a PV module that
adapts to various mounting configurations, mounting locations, and
climates while only requiring readily available data from the module
manufacturer. Results from this model are also compared to results
from published cell temperature models. The models were used to
predict real-time performance from a PV water pumping systems in
the desert of Medenine, south of Tunisia using 60-min intervals of
measured performance data during one complete year. Statistical
analysis of the predicted results and measured data highlight possible
sources of errors and the limitations and/or adequacy of existing
models, to describe the temperature and efficiency of PV-cells and
consequently, the accuracy of performance of PV water pumping
systems prediction models.
Abstract: Results of Chilean wine classification based on the
information provided by an electronic nose are reported in this paper.
The classification scheme consists of two parts; in the first stage,
Principal Component Analysis is used as feature extraction method to
reduce the dimensionality of the original information. Then, Radial
Basis Functions Neural Networks is used as pattern recognition
technique to perform the classification. The objective of this study is
to classify different Cabernet Sauvignon, Merlot and Carménère wine
samples from different years, valleys and vineyards of Chile.
Abstract: The aim of this study was to investigate the
environmental conservation behavior of the Applied Health Science
students of Suranaree University of Technology, a green and clean
university. The sample group was 184 Applied Health Science
students (medical, nursing, and public health). A questionnaire was
used to collect information.
The result of the study found that the students had more negative
than positive behaviors towards energy, water, and forest
conservation. This result can be used as basic information for
designing long-term behavior modification activities or research
projects on environmental conservation. Thus Applied Health
Science students will be encouraged to be conscious and also be a
good example of environmental conservation behavior.
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: The present study was designed to investigate the
cardio protective role of chronic oral administration of alcoholic
extract of Terminalia arjuna in in-vivo ischemic reperfusion injury
and the induction of HSP72. Rabbits, divided into three groups, and
were administered with the alcoholic extract of the bark powder of
Terminalia arjuna (TAAE) by oral gavage [6.75mg/kg: (T1) and
9.75mg/kg: (T2), 6 days /week for 12 weeks]. In open-chest
Ketamine pentobarbitone anaesthetized rabbits, the left anterior
descending coronary artery was occluded for 15 min of ischemia
followed by 60 min of reperfusion. In the vehicle-treated group,
ischemic-reperfusion injury (IRI) was evidenced by depression of
global hemodynamic function (MAP, HR, LVEDP, peak LV (+) & (-
) (dP/dt) along with depletion of HEP compounds. Oxidative stress
in IRI was evidenced by, raised levels of myocardial TBARS and
depletion of endogenous myocardial antioxidants GSH, SOD and
catalase. Western blot analysis showed a single band corresponding
to 72 kDa in homogenates of hearts from rabbits treated with both the
doses. In the alcoholic extract of the bark powder of Terminalia
arjuna treatment groups, both the doses had better recovery of
myocardial hemodynamic function, with significant reduction in
TBARS, and rise in SOD, GSH, catalase were observed. The results
of the present study suggest that the alcoholic extract of the bark
powder of Terminalia arjuna in rabbit induces myocardial HSP 72
and augments myocardial endogenous antioxidants, without causing
any cellular injury and offered better cardioprotection against
oxidative stress associated with myocardial IR injury.
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.