Abstract: Urban road network traffic has become one of the
most studied research topics in the last decades. This is mainly due to
the enlargement of the cities and the growing number of motor
vehicles traveling in this road network. One of the most sensitive
problems is to verify if the network is congestion-free. Another
related problem is the automatic reconfiguration of the network
without building new roads to alleviate congestions. These problems
require an accurate model of the traffic to determine the steady state
of the system. An alternative is to simulate the traffic to see if there
are congestions and when and where they occur. One key issue is to
find an adequate model for road intersections. Once the model
established, either a large scale model is built or the intersection is
represented by its performance measures and simulation for analysis.
In both cases, it is important to seek the queueing model to represent
the road intersection. In this paper, we propose to model the road
intersection as a BCMP queueing network and we compare this
analytical model against a simulation model for validation.
Abstract: Weblog is an Internet tool that is believed to possess
great potential to facilitate learning in education. This study wants to
know if weblog can be used to promote students- critical thinking. It
used a group of secondary two students from a Singapore school to
write weblogs as a means of substitution for their traditional
handwritten assignments. The topics for the weblogging are taken
from History syllabus but modified to suit the purpose of this study.
Weblogs from the students were collected and analysed using a
known coding system for measuring critical thinking. Results show
that the topic for blogging is crucial in determining the types of
critical thinking employed by the students. Students are seen to
display critical thinking traits in the areas of information sourcing,
linking information to arguments and viewpoints justification.
Students- criticalness is more profound when the information for
writing a topic is readily available. Otherwise, they tend to be less
critical and subjective. The study also found that students lack the
ability to source for external information suggesting that students
may need to be taught information literacy in order to widen their use
of critical thinking skills.
Abstract: The Integrated Performance Modelling Environment
(IPME) is a powerful simulation engine for task simulation and
performance analysis. However, it has no high level cognition such
as memory and reasoning for complex simulation. This article
introduces a knowledge representation and reasoning scheme that can
accommodate uncertainty in simulations of military personnel with
IPME. This approach demonstrates how advanced reasoning models
that support similarity-based associative process, rule-based abstract
process, multiple reasoning methods and real-time interaction can be
integrated with conventional task network modelling to provide
greater functionality and flexibility when modelling operator
performance.
Abstract: In this paper, the application of GRNN in
modeling of SOFC fuel cells were studied. The parameters
are of interested as voltage and power value and the current
changes are investigated. In addition, the comparison between
GRNN neural network application and conventional method
was made. The error value showed the superlative results.
Abstract: Modeling and simulation of fixed bed three-phase
catalytic reactors are considered for wet air catalytic oxidation of
phenol to perform a comparative numerical analysis between tricklebed
and packed-bubble column reactors. The modeling involves
material balances both for the catalyst particle as well as for different
fluid phases. Catalyst deactivation is also considered in a transient
reactor model to investigate the effects of various parameters
including reactor temperature on catalyst deactivation. The
simulation results indicated that packed-bubble columns were
slightly superior in performance than trickle beds. It was also found
that reaction temperature was the most effective parameter in catalyst
deactivation.
Abstract: A novel typical day prediction model have been built and validated by the measured data of a grid-connected solar photovoltaic (PV) system in Macau. Unlike conventional statistical method used by previous study on PV systems which get results by averaging nearby continuous points, the present typical day statistical method obtain the value at every minute in a typical day by averaging discontinuous points at the same minute in different days. This typical day statistical method based on discontinuous point averaging makes it possible for us to obtain the Gaussian shape dynamical distributions for solar irradiance and output power in a yearly or monthly typical day. Based on the yearly typical day statistical analysis results, the maximum possible accumulated output energy in a year with on site climate conditions and the corresponding optimal PV system running time are obtained. Periodic Gaussian shape prediction models for solar irradiance, output energy and system energy efficiency have been built and their coefficients have been determined based on the yearly, maximum and minimum monthly typical day Gaussian distribution parameters, which are obtained from iterations for minimum Root Mean Squared Deviation (RMSD). With the present model, the dynamical effects due to time difference in a day are kept and the day to day uncertainty due to weather changing are smoothed but still included. The periodic Gaussian shape correlations for solar irradiance, output power and system energy efficiency have been compared favorably with data of the PV system in Macau and proved to be an improvement than previous models.
Abstract: Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound (TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a novel method for automatic prostate segmentation in TRUS images is presented. This method involves preprocessing (edge preserving noise reduction and smoothing) and prostate segmentation. The speckle reduction has been achieved by using stick filter and top-hat transform has been implemented for smoothing. A feed forward neural network and local binary pattern together have been use to find a point inside prostate object. Finally the boundary of prostate is extracted by the inside point and an active contour algorithm. A numbers of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with MSE less than 4.6% relative to boundary provided manually by physicians.
Abstract: This paper presents a novel control strategy of a threephase
four-wire Unified Power Quality (UPQC) for an improvement
in power quality. The UPQC is realized by integration of series and
shunt active power filters (APFs) sharing a common dc bus capacitor.
The shunt APF is realized using a thee-phase, four leg voltage source
inverter (VSI) and the series APF is realized using a three-phase,
three leg VSI. A control technique based on unit vector template
technique (UTT) is used to get the reference signals for series APF,
while instantaneous sequence component theory (ISCT) is used for
the control of Shunt APF. The performance of the implemented
control algorithm is evaluated in terms of power-factor correction,
load balancing, neutral source current mitigation and mitigation of
voltage and current harmonics, voltage sag and swell in a three-phase
four-wire distribution system for different combination of linear and
non-linear loads. In this proposed control scheme of UPQC, the
current/voltage control is applied over the fundamental supply
currents/voltages instead of fast changing APFs currents/voltages,
there by reducing the computational delay and the required sensors.
MATLAB/Simulink based simulations are obtained, which support
the functionality of the UPQC. MATLAB/Simulink based
simulations are obtained, which support the functionality of the
UPQC.
Abstract: The increasing interest on processing data created by
sensor networks has evolved into approaches to implement sensor
networks as databases. The aggregation operator, which calculates a
value from a large group of data such as computing averages or sums,
etc. is an essential function that needs to be provided when
implementing such sensor network databases. This work proposes to
add the DURING clause into TinySQL to calculate values during a
specific long period and suggests a way to implement the aggregation
service in sensor networks by applying materialized view and
incremental view maintenance techniques that is used in data
warehouses. In sensor networks, data values are passed from child
nodes to parent nodes and an aggregation value is computed at the root
node. As such root nodes need to be memory efficient and low
powered, it becomes a problem to recompute aggregate values from all
past and current data. Therefore, applying incremental view
maintenance techniques can reduce the memory consumption and
support fast computation of aggregate values.
Abstract: The objective of the present communication is to
develop new genuine exponentiated mean codeword lengths and to
study deeply the problem of correspondence between well known
measures of entropy and mean codeword lengths. With the help of
some standard measures of entropy, we have illustrated such a
correspondence. In literature, we usually come across many
inequalities which are frequently used in information theory.
Keeping this idea in mind, we have developed such inequalities via
coding theory approach.
Abstract: According as the Architecture, Engineering and Construction (AEC) Industry projects have grown more complex and larger, the number of utilization of BIM for 3D design and simulation is increasing significantly. Therefore, typical applications of BIM such as clash detection and alternative measures based on 3-dimenstional planning are expanded to process management, cost and quantity management, structural analysis, check for regulation, and various domains for virtual design and construction. Presently, commercial BIM software is operated on single-user environment, so initial cost is so high and the investment may be wasted frequently. Cloud computing that is a next-generation internet technology enables simple internet devices (such as PC, Tablet, Smart phone etc) to use services and resources of BIM software. In this paper, we suggested developing method of the BIM software based on cloud computing environment in order to expand utilization of BIM and reduce cost of BIM software. First, for the benchmarking, we surveyed successful case of BIM and cloud computing. And we analyzed needs and opportunities of BIM and cloud computing in AEC Industry. Finally, we suggested main functions of BIM software based on cloud computing environment and developed a simple prototype of cloud computing BIM software for basic BIM model viewing.
Abstract: As business environments are rapidly changing,
the manufacturing system must be reconfigured to adapt to
various customer needs. In order to cope with this challenge, it
is quintessential to test industrial control logic rapidly and
easily in the design time, and monitor operational behavior in
the run time of automated manufacturing system. Proposed
integrated model for virtual prototyping and operational
monitoring of industrial control logic is to improve limitations
of current ladder programming practices and general discrete
event simulation method. Each plant layout model using HMI
package and object-oriented control logic model is designed
independently and is executed simultaneously in integrated
manner to reflect design practices of automation system in the
design time. Control logic is designed and executed using UML
activity diagram without considering complicated control
behavior to deal with current trend of reconfigurable
manufacturing. After the physical installation, layout model of
virtual prototype constructed in the design time is reused for
operational monitoring of system behavior during run time.
Abstract: System-level design based on high-level abstractions
is becoming increasingly important in hardware and embedded
system design. This paper analyzes meta-design techniques oriented
at developing meta-programs and meta-models for well-understood
domains. Meta-design techniques include meta-programming and
meta-modeling. At the programming level of design process, metadesign
means developing generic components that are usable in a
wider context of application than original domain components. At the
modeling level, meta-design means developing design patterns that
describe general solutions to the common recurring design problems,
and meta-models that describe the relationship between different
types of design models and abstractions. The paper describes and
evaluates the implementation of meta-design in hardware design
domain using object-oriented and meta-programming techniques.
The presented ideas are illustrated with a case study.
Abstract: The counting and analysis of blood cells allows the
evaluation and diagnosis of a vast number of diseases. In particular,
the analysis of white blood cells (WBCs) is a topic of great interest to
hematologists. Nowadays the morphological analysis of blood cells is
performed manually by skilled operators. This involves numerous
drawbacks, such as slowness of the analysis and a nonstandard
accuracy, dependent on the operator skills. In literature there are only
few examples of automated systems in order to analyze the white
blood cells, most of which only partial. This paper presents a
complete and fully automatic method for white blood cells
identification from microscopic images. The proposed method firstly
individuates white blood cells from which, subsequently, nucleus and
cytoplasm are extracted. The whole work has been developed using
MATLAB environment, in particular the Image Processing Toolbox.
Abstract: A new technique based on Pattern search optimization is proposed for estimating different solar cell parameters in this paper. The estimated parameters are the generated photocurrent, saturation current, series resistance, shunt resistance, and ideality factor. The proposed approach is tested and validated using double diode model to show its potential. Performance of the developed approach is quite interesting which signifies its potential as a promising estimation tool.
Abstract: Today, cancer remains one of the major diseases that
lead to death. The main obstacle in chemotherapy as a main cancer
treatment is the toxicity to normal cells due to Multidrug Resistance
(MDR) after the use of anticancer drugs. Proposed solution to
overcome this problem is the use of MDR efflux inhibitor of cinchona
alkaloids which is delivered together with anticancer drugs
encapsulated in the form of polymeric nanoparticles. The particles
were prepared by the hydration method. The characterization of
nanoparticles was particle size, zeta potential, entrapment efficiency
and in vitro drug release. Combination nanoparticle size ranged 29-45
nm with a neutral surface charge. Entrapment efficiency was above
87% for the use quinine, quinidine or cinchonidine in combination
with etoposide. The release test results exhibited that the cinchona
alkaloids release released faster than that of etoposide. Collectively,
cinchona alkaloids can be packaged along with etoposide in
nanomicelles for better cancer therapy.
Abstract: The recent development of humanoid robots has led robot designers to imagine a great variety of anthropomorphic forms for human-like machine. Which form is the best ? We try to answer this question from a double meaning of the anthropomorphism : a positive anthropomorphism corresponing to the realization of an effective anthropomorphic form object and a negative one corresponding to our natural tendency in certain circumstances to give human attributes to non-human beings. We postulate that any humanoid robot is concerned by both these two anthropomorphism kinds. We propose to use gestalt theory and Heider-s balance theory in order to analyze how negative anthropomorphism can influence our perception of human-like robots. From our theoretical approach we conclude that an “even shape" as defined by gestalt theory is not a sufficient condition for a good integration of future humanoid robots into a human community. Aesthetic perception of the robot cannot be splitted from a social perception : a humanoid robot, any how the efforts made for improving its appearance, could be rejected if it is devoted to a task with too high affective implications.
Abstract: The purpose of this study was to develop and examine a
Teaching Commitment Scale of Health and Physical Education
(TCS-HPE) for Taiwanese elementary school teachers. First of all,
based on teaching commitment related theory and literatures to
develop a original scale with 40 items, later both stratified random
sampling and cluster sampling were used to sample participants.
During the first stage, 300 teachers were sampled and 251 valid scales
(83.7%) returned. Later, the data was analyzed by exploratory factor
analysis to obtain 74.30% of total variance for the construct validity.
The Cronbach-s alpha coefficient of sum scale reliability was 0.94, and
subscale coefficients were between 0.80 and 0.96. In the second stage,
400 teachers were sampled and 318 valid scales (79.5%) returned.
Finally, this study used confirmatory factor analysis to test validity and
reliability of TCS-HPE. The result showed that the fit indexes reached
acceptable criteria(¤ç2
(246 ) =557.64 , p
Abstract: Repetitive systems stand for a kind of systems that
perform a simple task on a fixed pattern repetitively, which are
widely spread in industrial fields. Hence, many researchers have been
interested in those systems, especially in the field of iterative learning
control (ILC). In this paper, we propose a finite-horizon tracking
control scheme for linear time-varying repetitive systems with uncertain
initial conditions. The scheme is derived both analytically
and numerically for state-feedback systems and only numerically for
output-feedback systems. Then, it is extended to stable systems with
input constraints. All numerical schemes are developed in the forms
of linear matrix inequalities (LMIs). A distinguished feature of the
proposed scheme from the existing iterative learning control is that
the scheme guarantees the tracking performance exactly even under
uncertain initial conditions. The simulation results demonstrate the
good performance of the proposed scheme.
Abstract: Two short sediment cores collected from mangrove
areas of Manori and Thane creeks along Mumbai coast were analysed
for sediment composition and metals (Fe, Mn, Cu, Pb, Co, Ni, Zn, Cr
and V). The statistical analysis of Pearson correlation matrix proved
that there is a significant relationship between metal concentration
and finer grain size in Manori creek while poor correlation was
observed in Thane creek. Based on the enrichment factor, the present
metal to background metal ratios clearly reflected maximum
enrichment of Cu and Pb in Manori creek and Mn in Thane creek.
Geoaccumulation index calculated indicate that the study area is
unpolluted with respect to Fe, Mn, Co, Ni, Zn and Cr in both the
cores while moderately polluted with Cu and Pb in Manori creek.
Based on contamination degree, both the core sediments were found
to be considerably contaminated with metals.