Abstract: The Post colonial society in India has witnessed the turmoil to come out from the widespread control and influence of colonialism. The socio-cultural life of a society with all its dynamics is reflected in realistic forms of literature. The social events and human experience are drawn into a new creative form and are given to the reader as a new understanding and perspective of life. It enables the reader to understand the essence of life and motivates him to prepare for a positive change. After India becoming free from the colonial rule in 1947, systematic efforts were made by central and state governments and institutions to limit the role of English and simultaneously enlarge the function of Indian languages by planning in a strategic manner. The eighteen languages recognized as national languages are having very rich literatures. Telugu language is one among the Dravidian language family and is widely spoken by a majority of people. The post colonial socio-cultural factors were very well reflected in Telugu literature. The anti-colonial, reform oriented, progressive, post modernistic trends in Telugu literature are nothing but creative reflections of the post colonial society. This paper examines the major socio-cultural reflections in Telugu literature of the post colonial period.
Abstract: Usually, the solid-fuel flow of an iron ore sinter plant
consists of different types of the solid-fuels, which differ from each
other. Information about the composition of the solid-fuel flow
usually comes every 8-24 hours. It can be clearly seen that this
information cannot be used to control the sintering process in real
time. Due to this, we propose an expert system which uses indirect
measurements from the process in order to obtain the composition of
the solid-fuel flow by solving an optimization task. Then this
information can be used to control the sintering process. The
proposed technique can be successfully used to improve sinter
quality and reduce the amount of solid-fuel used by the process.
Abstract: This study retrospectively investigated the significance of whole body CT (WCT) for patients with sepsis. A medical chart review was retrospectively performed for all patients with systemic inflammatory response syndrome that were treated initially between April 2011 and March 2012. The subjects were divided into a WCT group that underwent WCT on arrival and a control group. Results of this study suggested that WCT for sepsis was useful for elderly patients whose chief complaint or physiological findings could not suggest the anatomical site of infection, to determine the infectious focus and indications/method for surgery, to diagnose the basic diseases associated with opportunistic infections and to evaluate complicated diseases
Abstract: In this contribution an innovative platform is being
presented that integrates intelligent agents and evolutionary
computation techniques in legacy e-learning environments. It
introduces the design and development of a scalable and
interoperable integration platform supporting:
I) various assessment agents for e-learning environments,
II) a specific resource retrieval agent for the provision of
additional information from Internet sources matching the
needs and profile of the specific user and
III) a genetic algorithm designed to extract efficient information
(classifying rules) based on the students- answering input
data.
The agents are implemented in order to provide intelligent
assessment services based on computational intelligence techniques
such as Bayesian Networks and Genetic Algorithms.
The proposed Genetic Algorithm (GA) is used in order to extract
efficient information (classifying rules) based on the students-
answering input data. The idea of using a GA in order to fulfil this
difficult task came from the fact that GAs have been widely used in
applications including classification of unknown data.
The utilization of new and emerging technologies like web
services allows integrating the provided services to any web based
legacy e-learning environment.
Abstract: Power system state estimation is the process of
calculating a reliable estimate of the power system state vector
composed of bus voltages' angles and magnitudes from telemetered
measurements on the system. This estimate of the state vector
provides the description of the system necessary for the operation
and security monitoring. Many methods are described in the
literature for solving the state estimation problem, the most important
of which are the classical weighted least squares method and the nondeterministic
genetic based method; however both showed
drawbacks. In this paper a modified version of the genetic
algorithm power system state estimation is introduced, Sensitivity of
the proposed algorithm to genetic operators is discussed, the
algorithm is applied to case studies and finally it is compared with
the classical weighted least squares method formulation.
Abstract: To compress, improve bit error performance and also enhance 2D images, a new scheme, called Iterative Cellular-Turbo System (IC-TS) is introduced. In IC-TS, the original image is partitioned into 2N quantization levels, where N is denoted as bit planes. Then each of the N-bit-plane is coded by Turbo encoder and transmitted over Additive White Gaussian Noise (AWGN) channel. At the receiver side, bit-planes are re-assembled taking into consideration of neighborhood relationship of pixels in 2-D images. Each of the noisy bit-plane values of the image is evaluated iteratively using IC-TS structure, which is composed of equalization block; Iterative Cellular Image Processing Algorithm (ICIPA) and Turbo decoder. In IC-TS, there is an iterative feedback link between ICIPA and Turbo decoder. ICIPA uses mean and standard deviation of estimated values of each pixel neighborhood. It has extra-ordinary satisfactory results of both Bit Error Rate (BER) and image enhancement performance for less than -1 dB Signal-to-Noise Ratio (SNR) values, compared to traditional turbo coding scheme and 2-D filtering, applied separately. Also, compression can be achieved by using IC-TS systems. In compression, less memory storage is used and data rate is increased up to N-1 times by simply choosing any number of bit slices, sacrificing resolution. Hence, it is concluded that IC-TS system will be a compromising approach in 2-D image transmission, recovery of noisy signals and image compression.
Abstract: A dual-reciprocity boundary element method is presented
for the numerical solution of a class of axisymmetric elastodynamic
problems. The domain integrals that arise in the integrodifferential
formulation are converted to line integrals by using the
dual-reciprocity method together suitably constructed interpolating
functions. The second order time derivatives of the displacement
in the governing partial differential equations are suppressed by
using Laplace transformation. In the Laplace transform domain, the
problem under consideration is eventually reduced to solving a system
of linear algebraic equations. Once the linear algebraic equations are
solved, the displacement and stress fields in the physical domain can
be recovered by using a numerical technique for inverting Laplace
transforms.
Abstract: Transport and logistics are the lifeblood of societies.
There is a strong correlation between overall growth in economic
activity and growth of transport. The movement of people and goods
has the potential for creating wealth and prosperity, therefore the
state of transportation infrastructure and especially the condition of
road networks is often a governmental priority. The design, building
and maintenance of national roads constitute a substantial share of
government budgets. Taking into account the magnitude and
importance of these investments, the expedience, efficiency and
sustainability of these projects are of great public interest. This paper
provides an overview of supply chain management principles applied
to road construction. In addition, road construction performance
measurement systems and ICT solutions are discussed. Road
construction in Estonia is analyzed. The authors propose the
development of a national performance measurement system for road
construction.
Abstract: This study presents an active vibration control
technique to reduce the earthquake responses of a retained structural
system. The proposed technique is a synthesis of the adaptive input
estimation method (AIEM) and linear quadratic Gaussian (LQG)
controller. The AIEM can estimate an unknown system input online.
The LQG controller offers optimal control forces to suppress
wall-structural system vibration. The numerical results show robust
performance in the active vibration control technique.
Abstract: Due to heightened concerns over environmental and economic issues the growing important of air pollution, and the importance of conserving fossil fuel resources in the world, the automotive industry is now forced to produce more fuel efficient, low emission vehicles and new drive system technologies. One of the most promising technologies to receive attention is the hybrid electric vehicle (HEV), which consists of two or more energy sources that supply energy to electric traction motors that in turn drive the wheels. This paper presents the various structures of HEV systems, the basic theoretical knowledge for describing their operation and the general behaviour of the HEV in acceleration, cruise and deceleration phases. The conventional design and sizing of a series HEV is studied. A conventional bus and its series configuration are defined and evaluated using the ADVISOR. In this section the simulation of a standard driving cycle and prediction of its fuel consumption and emissions of the HEV are discussed. Finally the bus performance is investigated to establish whether it can satisfy the performance, fuel consumption and emissions requested. The validity of the simulation has been established by the close conformity between the fuel consumption of the conventional bus reported by the manufacturer to what has achieved from the simulation.
Abstract: Documents retrieval in Information Retrieval
Systems (IRS) is generally about understanding of
information in the documents concern. The more the system
able to understand the contents of documents the more
effective will be the retrieval outcomes. But understanding of the
contents is a very complex task. Conventional IRS apply algorithms
that can only approximate the meaning of document contents through
keywords approach using vector space model. Keywords may be
unstemmed or stemmed. When keywords are stemmed and conflated
in retrieving process, we are a step forwards in applying semantic
technology in IRS. Word stemming is a process in morphological
analysis under natural language processing, before syntactic and
semantic analysis. We have developed algorithms for Malay and
Arabic and incorporated stemming in our experimental systems in
order to measure retrieval effectiveness. The results have shown that
the retrieval effectiveness has increased when stemming is used in
the systems.
Abstract: In this paper, the detection of a fault in the Global Positioning System (GPS) measurement is addressed. The class of faults considered is a bias in the GPS pseudorange measurements. This bias is modeled as an unknown constant. The fault could be the result of a receiver fault or signal fault such as multipath error. A bias bank is constructed based on set of possible fault hypotheses. Initially, there is equal probability of occurrence for any of the biases in the bank. Subsequently, as the measurements are processed, the probability of occurrence for each of the biases is sequentially updated. The fault with a probability approaching unity will be declared as the current fault in the GPS measurement. The residual formed from the GPS and Inertial Measurement Unit (IMU) measurements is used to update the probability of each fault. Results will be presented to show the performance of the presented algorithm.
Abstract: Scene interpretation systems need to match (often ambiguous)
low-level input data to concepts from a high-level ontology.
In many domains, these decisions are uncertain and benefit greatly
from proper context. This paper demonstrates the use of decision
trees for estimating class probabilities for regions described by feature
vectors, and shows how context can be introduced in order to improve
the matching performance.
Abstract: Many real-world optimization problems involve multiple conflicting objectives and the use of evolutionary algorithms to solve the problems has attracted much attention recently. This paper investigates the application of multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the performance of a power system. The design objective is to improve both rotor angle stability and system voltage profile. A Genetic Algorithm (GA) based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimisation problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.
Abstract: In literature, there are metrics for identifying the
quality of reusable components but the framework that makes use of
these metrics to precisely predict reusability of software components
is still need to be worked out. These reusability metrics if identified
in the design phase or even in the coding phase can help us to reduce
the rework by improving quality of reuse of the software component
and hence improve the productivity due to probabilistic increase in
the reuse level. As CK metric suit is most widely used metrics for
extraction of structural features of an object oriented (OO) software;
So, in this study, tuned CK metric suit i.e. WMC, DIT, NOC, CBO
and LCOM, is used to obtain the structural analysis of OO-based
software components. An algorithm has been proposed in which the
inputs can be given to K-Means Clustering system in form of
tuned values of the OO software component and decision tree is
formed for the 10-fold cross validation of data to evaluate the in
terms of linguistic reusability value of the component. The developed
reusability model has produced high precision results as desired.
Abstract: This paper presents and evaluates a new classification
method that aims to improve classifiers performances and speed up
their training process. The proposed approach, called labeled
classification, seeks to improve convergence of the BP (Back
propagation) algorithm through the addition of an extra feature
(labels) to all training examples. To classify every new example, tests
will be carried out each label. The simplicity of implementation is the
main advantage of this approach because no modifications are
required in the training algorithms. Therefore, it can be used with
others techniques of acceleration and stabilization. In this work, two
models of the labeled classification are proposed: the LMLP
(Labeled Multi Layered Perceptron) and the LNFC (Labeled Neuro
Fuzzy Classifier). These models are tested using Iris, wine, texture
and human thigh databases to evaluate their performances.
Abstract: Although automotive industry has brought different beneficiaries to human life, it is being pointed out as one of the major cause of global air pollution which resulted in climate change, smog, green house gases (GHGs), and human diseases by many reasons. Since auto industry is one of the largest consumers of fossil fuels, the realization of green innovations is becoming a crucial choice to meet the challenges towards sustainable development. Recently, many auto manufacturers have embarked on green technology initiatives to gain a competitive advantage in the global market; however, innovative manufacturing systems and technologies can enhance operational performance only if the human resource management is in place to elicit the motivation of the employees and develop their organizational expertise. No organization can perform at peak levels unless each employee is committed to the company goals and works as an effective team member. Strategic human resource practices are the primary means by which firms can shape the skills, attitudes, and behavior of individuals to align with the business strategic objectives. This study investigates on the comprehensive approach of multiple advanced technology innovations and human resource management at Toyota Motor Corporation as the market leader of full hybrid technology in the automotive industry. Then, HRM framework of the company is described and three sets of human resource practices that support the innovation-oriented HR system, presented. Finally, a conceptual framework for innovativeness in green technology in automotive industry by applying a deliberate strategic HR management system and knowledge management with the intervening factors of organizational culture, knowledge application and knowledge sharing is proposed.
Abstract: Multicarrier transmission system such as Orthogonal
Frequency Division Multiplexing (OFDM) is a promising technique
for high bit rate transmission in wireless communication system.
OFDM is a spectrally efficient modulation technique that can achieve
high speed data transmission over multipath fading channels without
the need for powerful equalization techniques. However the price
paid for this high spectral efficiency and less intensive equalization
is low power efficiency. OFDM signals are very sensitive to nonlinear
effects due to the high Peak-to-Average Power Ratio (PAPR),
which leads to the power inefficiency in the RF section of the
transmitter. This paper investigates the effect of PAPR reduction on
the performance parameter of multicarrier communication system.
Performance parameters considered are power consumption of Power
Amplifier (PA) and Digital-to-Analog Converter (DAC), power amplifier
efficiency, SNR of DAC and BER performance of the system.
From our analysis it is found that irrespective of PAPR reduction
technique being employed, the power consumption of PA and DAC
reduces and power amplifier efficiency increases due to reduction in
PAPR. Moreover, it has been shown that for a given BER performance
the requirement of Input-Backoff (IBO) reduces with reduction in
PAPR.
Abstract: A measurement system for pH array sensors is
introduced to increase accuracy, and decrease non-ideal effects
successfully. An array readout circuit reads eight potentiometric
signals at the same time, and obtains an average value. The deviation
value or the extreme value is counteracted and the output voltage is a
relatively stable value. The errors of measuring pH buffer solutions are
decreased obviously with this measurement system, and the non-ideal
effects, drift and hysteresis, are lowered to 1.638mV/hr and 1.118mV,
respectively. The efficiency and stability are better than single sensor.
The whole sensing characteristics are improved.
Abstract: Safety Critical hard Real-Time Systems are ever
present in the avionics industry. The Model Driven Architecture
(MDA) offers different levels of model abstraction and generation.
This paper discusses our concerns relating to model development and
generation when using the MDA approach in the avionics industry.
These concerns are based on our experience when looking into
adopting the MDA as part of avionics systems development. We
place emphasis on transformations between model types and discuss
possible benefits of adopting an MDA approach as part of the
software development life cycle.