Abstract: Property investment in the real estate industry has a
high risk due to the uncertainty factors that will affect the decisions
made and high cost. Analytic hierarchy process has existed for some
time in which referred to an expert-s opinion to measure the
uncertainty of the risk factors for the risk analysis. Therefore,
different level of experts- experiences will create different opinion
and lead to the conflict among the experts in the field. The objective
of this paper is to propose a new technique to measure the uncertainty
of the risk factors based on multidimensional data model and data
mining techniques as deterministic approach. The propose technique
consist of a basic framework which includes four modules: user,
technology, end-user access tools and applications. The property
investment risk analysis defines as a micro level analysis as the
features of the property will be considered in the analysis in this
paper.
Abstract: We have developed a distributed asynchronous Web
based training system. In order to improve the scalability and robustness
of this system, all contents and a function are realized on
mobile agents. These agents are distributed to computers, and they
can use a Peer to Peer network that modified Content-Addressable
Network. In this system, all computers offer the function and exercise
by themselves. However, the system that all computers do the same
behavior is not realistic. In this paper, as a solution of this issue,
we present an e-Learning system that is composed of computers
of different participation types. Enabling the computer of different
participation types will improve the convenience of the system.
Abstract: This paper presents a dynamic adaptation scheme for
the frequency of inter-deme migration in distributed genetic algorithms
(GA), and its VLSI hardware design. Distributed GA,
or multi-deme-based GA, uses multiple populations which evolve
concurrently. The purpose of dynamic adaptation is to improve
convergence performance so as to obtain better solutions. Through
simulation experiments, we proved that our scheme achieves better
performance than fixed frequency migration schemes.
Abstract: A catastrophic earthquake measuring 6.3 on the
Richter scale struck the Christchurch, New Zealand Central Business
District on February 22, 2012, abruptly disrupting the business of
teaching and learning at Christchurch Polytechnic Institute of
Technology. This paper presents the findings from a study
undertaken about the complexity of delivering an educational
programme in the face of this traumatic natural event. Nine
interconnected themes emerged from this multiple method study:
communication, decision making, leader- and follower-ship,
balancing personal and professional responsibilities, taking action,
preparedness and thinking ahead, all within a disruptive and uncertain
context. Sustainable responses that maximise business continuity, and
provide solutions to practical challenges, are among the study-s
recommendations.
Abstract: The back propagation algorithm calculates the weight
changes of artificial neural networks, and a common approach is to
use a training algorithm consisting of a learning rate and a
momentum factor. The major drawbacks of above learning algorithm
are the problems of local minima and slow convergence speeds. The
addition of an extra term, called a proportional factor reduces the
convergence of the back propagation algorithm. We have applied the
three term back propagation to multiplicative neural network
learning. The algorithm is tested on XOR and parity problem and
compared with the standard back propagation training algorithm.
Abstract: This paper is a continuation of our daily energy peak load forecasting approach using our modified network which is part of the recurrent networks family and is called feed forward and feed back multi context artificial neural network (FFFB-MCANN). The inputs to the network were exogenous variables such as the previous and current change in the weather components, the previous and current status of the day and endogenous variables such as the past change in the loads. Endogenous variable such as the current change in the loads were used on the network output. Experiment shows that using endogenous and exogenous variables as inputs to the FFFBMCANN rather than either exogenous or endogenous variables as inputs to the same network produces better results. Experiments show that using the change in variables such as weather components and the change in the past load as inputs to the FFFB-MCANN rather than the absolute values for the weather components and past load as inputs to the same network has a dramatic impact and produce better accuracy.
Abstract: As the gradual increase of the enterprise scale, the
firms may possess many manufacturing plants located in different
places geographically. This change will result in the multi-site
production planning problems under the environment of multiple
plants or production resources. Our research proposes the structural
framework to analyze the multi-site planning problems. The analytical
framework is composed of six elements: multi-site conceptual model,
product structure (bill of manufacturing), production strategy,
manufacturing capability and characteristics, production planning
constraints, and key performance indicators. As well as the discussion
of these six ingredients, we also review related literatures in this paper
to match our analytical framework. Finally we take a real-world
practical example of a TFT-LCD manufacturer in Taiwan to explain
our proposed analytical framework for the multi-site production
planning problems.
Abstract: In this paper, the application of neural networks to study the design of short-term load forecasting (STLF) Systems for Illam state located in west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STLF systems was used. Our study based on MLP was trained and tested using three years (2004-2006) data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STLF systems.
Abstract: Particle Swarm Optimization (PSO) with elite PSO
parameters has been developed for power flow analysis under
practical constrained situations. Multiple solutions of the power flow
problem are useful in voltage stability assessment of power system.
A method of determination of multiple power flow solutions is
presented using a hybrid of Particle Swarm Optimization (PSO) and
local search technique. The unique and innovative learning factors of
the PSO algorithm are formulated depending upon the node power
mismatch values to be highly adaptive with the power flow problems.
The local search is applied on the pbest solution obtained by the PSO
algorithm in each iteration. The proposed algorithm performs reliably
and provides multiple solutions when applied on standard and illconditioned
systems. The test results show that the performances of
the proposed algorithm under critical conditions are better than the
conventional methods.
Abstract: Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.
Abstract: A general stochastic spatial MIMO channel model is
proposed for evaluating various MIMO techniques in this paper. It can
generate MIMO channels complying with various MIMO
configurations such as smart antenna, spatial diversity and spatial
multiplexing. The modeling method produces the stochastic fading
involving delay spread, Doppler spread, DOA (direction of arrival),
AS (angle spread), PAS (power azimuth Spectrum) of the scatterers,
antenna spacing and the wavelength. It can be applied in various
MIMO technique researches flexibly with low computing complexity.
Abstract: Recently, it has been suggested that thought control strategies aimed at controlling unwanted thoughts may be used to cope with paranoid thoughts in both clinical and nonclinical samples. The current study aims to examine the type of thought control strategies that were associated with the frequency of paranoid thoughts in nonclinical samples. A total of 159 Japanese undergraduate students completed the two scales–the Paranoia Checklist and the Thought Control Questionnaire. A hierarchical multiple regression analysis demonstrated that worry-based control strategies were associated with paranoid thoughts, whereas distraction- and social-based control strategies were inversely associated with paranoid thoughts. Our findings suggest that in a nonclinical population, worry-based strategies may be especially maladaptive, whereas distraction- and social-based strategies may be adaptive to paranoid thoughts.
Abstract: A scalable QoS aware multicast deployment in
DiffServ networks has become an important research dimension in
recent years. Although multicasting and differentiated services are
two complementary technologies, the integration of the two
technologies is a non-trivial task due to architectural conflicts
between them. A popular solution proposed is to extend the
functionality of the DiffServ components to support multicasting. In
this paper, we propose an algorithm to construct an efficient QoSdriven
multicast tree, taking into account the available bandwidth per
service class. We also present an efficient way to provision the
limited available bandwidth for supporting heterogeneous users. The
proposed mechanism is evaluated using simulated tests. The
simulated result reveals that our algorithm can effectively minimize
the bandwidth use and transmission cost
Abstract: In this paper we study the use of a new code called
Random Diagonal (RD) code for Spectral Amplitude Coding (SAC)
optical Code Division Multiple Access (CDMA) networks, using
Fiber Bragg-Grating (FBG), FBG consists of a fiber segment whose
index of reflection varies periodically along its length. RD code is
constructed using code level and data level, one of the important
properties of this code is that the cross correlation at data level is
always zero, which means that Phase intensity Induced Phase (PIIN)
is reduced. We find that the performance of the RD code will be
better than Modified Frequency Hopping (MFH) and Hadamard code
It has been observed through experimental and theoretical simulation
that BER for RD code perform significantly better than other codes.
Proof –of-principle simulations of encoding with 3 channels, and 10
Gbps data transmission have been successfully demonstrated together
with FBG decoding scheme for canceling the code level from SAC-signal.
Abstract: The purpose of this study is to identify ideal urban
design elements of waterfronts and to analyze the differences in users-
cognition among these elements. This study follows three steps as
following: first is identifying the urban design elements of waterfronts
from literature review and second is evaluating intended users-
cognition of urban design elements in urban waterfronts. Lastly, third
is analyzing the users- cognition differences. As the result, evaluations
of waterfront areas by users show similar features that non-waterfront
urban design elements contain the highest degree of importance. This
indicates the difference of users- cognition has dimensions of
frequency and distance, and demonstrates differences in the aspect of
importance than of satisfaction. Multi-Dimensional Scaling Method
verifies differences among their cognition. This study provides
elements to increase satisfaction of users from differences of their
cognition on design elements for waterfronts. It also suggests
implications on elements when waterfronts are built.
Abstract: Average current analysis checking the impact of
current flow is very important to guarantee the reliability of
semiconductor systems. As semiconductor process technologies
improve, the coupling capacitance often become bigger than self
capacitances. In this paper, we propose an analytic technique for
analyzing average current on interconnects in multi-conductor
structures. The proposed technique has shown to yield the acceptable
errors compared to HSPICE results while providing computational
efficiency.
Abstract: The Internet is the global data communications
infrastructure based on the interconnection of both public and private
networks using protocols that implement Internetworking on a global
scale. Hence the control of protocol and infrastructure development,
resource allocation and network operation are crucial and interlinked
aspects. Internet Governance is the hotly debated and contentious
subject that refers to the global control and operation of key Internet
infrastructure such as domain name servers and resources such as
domain names. It is impossible to separate technical and political
positions as they are interlinked. Furthermore the existence of a
global market, transparency and competition impact upon Internet
Governance and related topics such as network neutrality and
security. Current trends and developments regarding Internet
governance with a focus on the policy-making process, security and
control have been observed to evaluate current and future
implications on the Internet. The multi stakeholder approach to
Internet Governance discussed in this paper presents a number of
opportunities, issues and developments that will affect the future
direction of the Internet. Internet operation, maintenance and
advisory organisations such as the Internet Corporation for Assigned
Names and Numbers (ICANN) or the Internet Governance Forum
(IGF) are currently in the process of formulating policies for future
Internet Governance. Given the controversial nature of the issues at
stake and the current lack of agreement it is predicted that
institutional as well as market governance will remain present for the
network access and content.
Abstract: In this paper electrical characteristics of various kinds
of multiple-gate silicon nanowire transistors (SNWT) with the
channel length equal to 7 nm are compared. A fully ballistic quantum
mechanical transport approach based on NEGF was employed to
analyses electrical characteristics of rectangular and cylindrical
silicon nanowire transistors as well as a Double gate MOS FET. A
double gate, triple gate, and gate all around nano wires were studied
to investigate the impact of increasing the number of gates on the
control of the short channel effect which is important in nanoscale
devices. Also in the case of triple gate rectangular SNWT inserting
extra gates on the bottom of device can improve the application of
device. The results indicate that by using gate all around structures
short channel effects such as DIBL, subthreshold swing and delay
reduces.
Abstract: Series of tellurite glass of the system 78TeO2-10PbO-
10Li2O-(2-x)Nd2O3-xEr2O3, where x = 0.5, 1.0, 1.5 and 2.0 was
successfully been made. A study of upconversion luminescence of
the Nd3+/Er3+ co-doped tellurite glass has been carried out. From
Judd-Ofelt analysis, the experimental lifetime, exp. τ of the glass
serie are found higher in the visible region as they varies from
65.17ms to 114.63ms, whereas in the near infrared region (NIR) the
lifetime are varies from 2.133ms to 2.270ms. Meanwhile, the
emission cross section,σ results are found varies from 0.004 x 1020
cm2 to 1.007 x 1020 cm2 with respect to composition. The emission
spectra of the glass are found been contributed from Nd3+ and Er3+
ions by which nine significant transition peaks are observed. The
upconversion mechanism of the co-doped tellurite glass has been
shown in the schematic energy diagrams. In this works, it is found
that the excited state-absorption (ESA) is still dominant in the
upconversion excitation process as the upconversion excitation
mechanism of the Nd3+ excited-state levels is accomplished through a
stepwise multiphonon process. An efficient excitation energy transfer
(ET) has been observed between Nd3+ as a donor and Er3+ as the
acceptor. As a result, respective emission spectra had been observed.
Abstract: Cancers could normally be marked by a number of
differentially expressed genes which show enormous potential as
biomarkers for a certain disease. Recent years, cancer classification
based on the investigation of gene expression profiles derived by
high-throughput microarrays has widely been used. The selection of
discriminative genes is, therefore, an essential preprocess step in
carcinogenesis studies. In this paper, we have proposed a novel gene
selector using information-theoretic measures for biological
discovery. This multivariate filter is a four-stage framework through
the analyses of feature relevance, feature interdependence, feature
redundancy-dependence and subset rankings, and having been
examined on the colon cancer data set. Our experimental result show
that the proposed method outperformed other information theorem
based filters in all aspect of classification errors and classification
performance.