Abstract: In this paper we discuss on the security module for the
car appliances to prevent stealing and illegal use on other cars. We
proposed an open structure including authentication and encryption by
embed a security module in each to protect car appliances. Illegal
moving and use a car appliance with the security module without
permission will lead the appliance to useless. This paper also presents
the component identification and deal with relevant procedures. It is at
low cost to recover from destroys by the burglar. Expect this paper to
offer the new business opportunity to the automotive and technology
industry.
Abstract: A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.
Abstract: Economic Load Dispatch (ELD) is a method of determining
the most efficient, low-cost and reliable operation of a power
system by dispatching available electricity generation resources to
supply load on the system. The primary objective of economic
dispatch is to minimize total cost of generation while honoring
operational constraints of available generation resources. In this paper
an intelligent water drop (IWD) algorithm has been proposed to
solve ELD problem with an objective of minimizing the total cost of
generation. Intelligent water drop algorithm is a swarm-based natureinspired
optimization algorithm, which has been inspired from natural
rivers. A natural river often finds good paths among lots of possible
paths in its ways from source to destination and finally find almost
optimal path to their destination. These ideas are embedded into
the proposed algorithm for solving economic load dispatch problem.
The main advantage of the proposed technique is easy is implement
and capable of finding feasible near global optimal solution with
less computational effort. In order to illustrate the effectiveness of
the proposed method, it has been tested on 6-unit and 20-unit test
systems with incremental fuel cost functions taking into account the
valve point-point loading effects. Numerical results shows that the
proposed method has good convergence property and better in quality
of solution than other algorithms reported in recent literature.
Abstract: We have developed an analytic model for the radial pn-junction in a nanowire (NW) core-shell structure utilizing as a new
building block in different semiconductor devices. The potential distribution through the p-n-junction is calculated and the analytical expressions are derived to compute the depletion region widths. We
show that the widths of space charge layers, surrounding the core, are
the functions of core radius, which is the manifestation of so called classical size effect. The relationship between the depletion layer width and the built-in potential in the asymptotes of infinitely large
core radius transforms to square-root dependence specific for conventional planar p-n-junctions. The explicit equation is derived to
compute the capacitance of radial p-n-junction. The current-voltage behavior is also carefully determined taking into account the “short
base" effects.
Abstract: Modern highly automated production systems faces
problems of reliability. Machine function reliability results in
changes of productivity rate and efficiency use of expensive
industrial facilities. Predicting of reliability has become an important
research and involves complex mathematical methods and
calculation. The reliability of high productivity technological
automatic machines that consists of complex mechanical, electrical
and electronic components is important. The failure of these units
results in major economic losses of production systems. The
reliability of transport and feeding systems for automatic
technological machines is also important, because failure of transport
leads to stops of technological machines. This paper presents
reliability engineering on the feeding system and its components for
transporting a complex shape parts to automatic machines. It also
discusses about the calculation of the reliability parameters of the
feeding unit by applying the probability theory. Equations produced
for calculating the limits of the geometrical sizes of feeders and the
probability of sticking the transported parts into the chute represents
the reliability of feeders as a function of its geometrical parameters.
Abstract: The only relevant basis for the design of an educational application are objectives of learning for the content area. This study analyses the process in which the real – not only the formal – objectives could work as the starting point for the construction of an educational game. The application context is the education of perioperative nursing. The process is based on the panel discussions of nursing teachers. In the panels, the teachers elaborated the objectives. The transcribed discussions were analysed in terms of the conceptions of learning and teaching of perioperative nursing. The outcome of the study is first the elaborated objectives, which will be used in the implementation of an educational game for the needs of pre-, intra and post-operative nursing skills learning. Second, the study shows that different views of learning are necessary to be understood in order to design an appropriate educational application.
Abstract: We introduce a novel approach to measuring how
humans learn based on techniques from information theory and
apply it to the oriental game of Go. We show that the total amount
of information observable in human strategies, called the strategic
information, remains constant for populations of players of differing
skill levels for well studied patterns of play. This is despite the very
large amount of knowledge required to progress from the recreational
players at one end of our spectrum to the very best and most
experienced players in the world at the other and is in contrast to
the idea that having more knowledge might imply more 'certainty'
in what move to play next. We show this is true for very local
up to medium sized board patterns, across a variety of different
moves using 80,000 game records. Consequences for theoretical and
practical AI are outlined.
Abstract: The acoustic and articulatory properties of fricative speech sounds are being studied using magnetic resonance imaging (MRI) and acoustic recordings from a single subject. Area functions were derived from a complete set of axial and coronal MR slices using two different methods: the Mermelstein technique and the Blum transform. Area functions derived from the two techniques were shown to differ significantly in some cases. Such differences will lead to different acoustic predictions and it is important to know which is the more accurate. The vocal tract acoustic transfer function (VTTF) was derived from these area functions for each fricative and compared with measured speech signals for the same fricative and same subject. The VTTFs for /f/ in two vowel contexts and the corresponding acoustic spectra are derived here; the Blum transform appears to show a better match between prediction and measurement than the Mermelstein technique.
Abstract: Unsteady boundary layer flow of an incompressible
micropolar fluid over a stretching sheet when the sheet is stretched in
its own plane is studied in this paper. The stretching velocity is
assumed to vary linearly with the distance along the sheet. Two equal
and opposite forces are impulsively applied along the x-axis so that the
sheet is stretched, keeping the origin fixed in a micropolar fluid. The
transformed unsteady boundary layer equations are solved
numerically using the Keller-box method for the whole transient from
the initial state to final steady-state flow. Numerical results are
obtained for the velocity and microrotation distributions as well as the
skin friction coefficient for various values of the material parameter K.
It is found that there is a smooth transition from the small-time
solution to the large-time solution.
Abstract: This paper studies the effect of different compression
constraints and schemes presented in a new and flexible paradigm to
achieve high compression ratios and acceptable signal to noise ratios
of Arabic speech signals. Compression parameters are computed for
variable frame sizes of a level 5 to 7 Discrete Wavelet Transform
(DWT) representation of the signals for different analyzing mother
wavelet functions. Results are obtained and compared for Global
threshold and level dependent threshold techniques. The results
obtained also include comparisons with Signal to Noise Ratios, Peak
Signal to Noise Ratios and Normalized Root Mean Square Error.
Abstract: This study describes the relationship between motivation factors and academic performance among distance education students enrolled in a postgraduate nursing course. Students (n=96) participated in a survey that assesses student's motivational orientations from a cognitive perspective using a selfadministered questionnaire based on Pintrich-s Motivation Strategies for Learning Questionnaire (MLSQ). Results showed students- motivational factors are highest on task value (6.44, 0.71); followed by intrinsic goal orientation (6.20, 0.76), control beliefs (6.02, 0.89); extrinsic goal orientation (5.85, 1.13); self-efficacy for learning and performance (5.62, 0.84), and finally, test anxiety (4.21, 1.37). Weak positive correlations were found between academic performance and intrinsic goal orientation (r=0.13), extrinsic goal orientation (r=0.04), task value (r=0.09), control beliefs (r=0.02), and self-efficacy (r=0.05), while there was weak negative correlation with test anxiety (r=-0.04). Conclusions from the study indicate the need to focus on improving tasks and targeting intrinsic goal orientations of students to courses since these were positively correlated with academic performance and downplay the use of tests since these were negatively correlated with academic performance.
Abstract: Natural outdoor scene classification is active and
promising research area around the globe. In this study, the
classification is carried out in two phases. In the first phase, the
features are extracted from the images by wavelet decomposition
method and stored in a database as feature vectors. In the second
phase, the neural classifiers such as back-propagation neural network
(BPNN) and resilient back-propagation neural network (RPNN) are
employed for the classification of scenes. Four hundred color images
are considered from MIT database of two classes as forest and street.
A comparative study has been carried out on the performance of the
two neural classifiers BPNN and RPNN on the increasing number of
test samples. RPNN showed better classification results compared to
BPNN on the large test samples.
Abstract: The construction industry is the pillar industry in
China, accounting for about 6% of the gross domestic product. Along
with changes in the external environment of the construction industry
in China, the construction firm faces fierce competition. The paper
aims to investigate the relationship between diversified types of
construction firm and its performance in China. Based on generalist
and specialist strategy in organizational ecology, we think a generalist
organization can be applied to an enterprise with diversified
developments, while specialist groups are extended to professional
enterprises .This study takes advantage of annual financial data of
listed construction firm to empirically verify the relationship between
diversification and corporation performance establishing a regression
equation to econometric analysis. We find that: 1) Specialization can
significantly improve the level of profitability of listed construction
firms, and there is a significant positive relationship with corporate
performance; 2) The level of operating performance of listed
construction enterprises which engage in unrelated diversification is
higher than those with related diversification; 3) The relationship
between state-owned construction firms and corporate performance is
negative. The more the year of foundation is, the higher performance
will be; however, the more the year of being listed, the lower
performance will be.
Abstract: Many studies have shown that Artificial Neural
Networks (ANN) have been widely used for forecasting financial
markets, because of many financial and economic variables are nonlinear,
and an ANN can model flexible linear or non-linear
relationship among variables.
The purpose of the study was to employ an ANN models to
predict the direction of the Istanbul Stock Exchange National 100
Indices (ISE National-100).
As a result of this study, the model forecast the direction of the
ISE National-100 to an accuracy of 74, 51%.
Abstract: This study proposes and tests a rescapturing elements of perceived gain and loss that, by perceived value of medical tourism products, influencintention of potential customers. Data from 301 usable qwere tested against the research model using the structmodeling approach. The results indicated that perceivedkey predictor of customer intentions. As for benefimedical quality, service quality and enjoyment wcomponents that significantly influenced the perceptiRegarding sacrifice, the effects of perceived risk on pewere significant. The findings can provide insights intohow destination countries can make medical tourism a wfor themselves and international patients.KeywordsMedical tourism, perceived valueintention.
Abstract: The effect of dry milling on the carbothermic
reduction of celestite was investigated. Mixtures of celestite
concentrate (98% SrSO4) and activated carbon (99% carbon) was
milled for 1 and 24 hours in a planetary ball mill. Un-milled and
milled mixtures and their products after carbothermic reduction were
studied by a combination of XRD and TGA/DTA experiments. The
thermogravimetric analyses and XRD results showed that by milling
celestite-carbon mixtures for one hour, the formation temperature of
strontium sulfide decreased from about 720°C (in un-milled sample)
to about 600°C, after 24 hours milling it decreased to 530°C. It was
concluded that milling induces increasingly thorough mixing of the
reactants to reduction occurring at lower temperatures
Abstract: Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.
Abstract: Reliability Centered Maintenance(RCM) is one of
most widely used methods in the modern power system to schedule a
maintenance cycle and determine the priority of inspection. In order
to apply the RCM method to the Smart Grid, a precedence study for
the new structure of rearranged system should be performed due to
introduction of additional installation such as renewable and
sustainable energy resources, energy storage devices and advanced
metering infrastructure. This paper proposes a new method to
evaluate the priority of maintenance and inspection of the power
system facilities in the Smart Grid using the Risk Priority Number. In
order to calculate that risk index, it is required that the reliability
block diagram should be analyzed for the Smart Grid system. Finally,
the feasible technical method is discussed to estimate the risk
potential as part of the RCM procedure.
Abstract: Key management is a vital component in any modern security protocol. Due to scalability and practical implementation considerations automatic key management seems a natural choice in significantly large virtual private networks (VPNs). In this context IETF Internet Key Exchange (IKE) is the most promising protocol under permanent review. We have made a humble effort to pinpoint IKEv2 net gain over IKEv1 due to recent modifications in its original structure, along with a brief overview of salient improvements between the two versions. We have used US National Institute of Technology NIIST VPN simulator to get some comparisons of important performance metrics.
Abstract: This research elaborates decision models for product
innovation in the early phases, focusing on one of the most widely
implemented method in marketing research: conjoint analysis and the
related conjoint-based models with special focus on heuristics
programming techniques for the development of optimal product
innovation. The concept, potential, requirements and limitations of
conjoint analysis and its conjoint-based heuristics successors are
analysed and the development of conceptual framework of Genetic
Algorithm (GA) as one of the most widely implemented heuristic
methods for developing product innovations are discussed.