Abstract: Optimization is often a critical issue for most system
design problems. Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, finding optimal solution to complex high
dimensional, multimodal problems often require highly
computationally expensive function evaluations and hence are
practically prohibitive. The Dynamic Approximate Fitness based
Hybrid EA (DAFHEA) model presented in our earlier work [14]
reduced computation time by controlled use of meta-models to
partially replace the actual function evaluation by approximate
function evaluation. However, the underlying assumption in
DAFHEA is that the training samples for the meta-model are
generated from a single uniform model. Situations like model
formation involving variable input dimensions and noisy data
certainly can not be covered by this assumption. In this paper we
present an enhanced version of DAFHEA that incorporates a
multiple-model based learning approach for the SVM approximator.
DAFHEA-II (the enhanced version of the DAFHEA framework) also
overcomes the high computational expense involved with additional
clustering requirements of the original DAFHEA framework. The
proposed framework has been tested on several benchmark functions
and the empirical results illustrate the advantages of the proposed
technique.
Abstract: The data measurement of mean velocity has been
taken for the wake of single circular cylinder with three different diameters for two different velocities. The effects of change in
diameter and in velocity are studied in self-similar coordinate system.
The spatial variations of velocity defect and that of the half-width
have been investigated. The results are compared with those
published by H.Schlichting. In the normalized coordinates, it is also observed that all cases except for the first station are self-similar. By attention to self-similarity profiles of mean velocity, it is observed for all the cases at the each station curves tend to zero at a same point.
Abstract: Shadow detection is still considered as one of the
potential challenges for intelligent automated video surveillance
systems. A pre requisite for reliable and accurate detection and
tracking is the correct shadow detection and classification. In such a
landscape of conditions, privacy issues add more and more
complexity and require reliable shadow detection.
In this work the intertwining between security, accuracy,
reliability and privacy is analyzed and, accordingly, a novel
architecture for Privacy Enhancing Video Surveillance (PEVS) is
introduced. Shadow detection and masking are dealt with through the
combination of two different approaches simultaneously. This results
in a unique privacy enhancement, without affecting security.
Subsequently, the methodology was employed successfully in a
large-scale wireless video surveillance system; privacy relevant
information was stored and encrypted on the unit, without
transferring it over an un-trusted network.
Abstract: Vertical ZnO nanowire array films were synthesized
based on aqueous method for sensing applications. ZnO nanowires
were investigated structurally using X-ray diffraction (XRD) and
scanning electron microscopy (SEM). The gas-sensing properties of
ZnO nanowires array films are studied. It is found that the ZnO
nanowires array film sensor exhibits excellent sensing properties
towards O2 and CO2 at 100 °C with the response time shorter than 5
s. High surface area / volume ratio of vertical ZnO nanowire and high
mobility accounts for the fast response and recovery. The sensor
response was measured in the range from 100 to 500 ppm O2 and CO2
in this study.
Abstract: The article is aimed at bringing information on the scope and the level of use of talent management by organizations in one of the Czech Republic regions, in the Moravian-Silesian Region. On the basis of data acquired by a questionnaire survey it has been found out that organizations in the above-mentioned region are implementing the system of talent management on a small scale: this approach is used by 3.8 % of organizations only that is 9 from 237 (100 %) of the approached respondents. The main reasons why this approach is not used is either that organizations have no knowledge of it or there is lack of financial and personnel resources. In the article recommendations suggested by the author can be found for a wider application of talent management in the Czech practice.
Abstract: The characterisation of agro-wastes fibres for composite applications from Nigeria using X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM) has been done. Fibres extracted from groundnut shell, coconut husk, rice husk, palm fruit bunch and palm fruit stalk are processed using two novel cellulose fibre production methods developed by the authors. Cellulose apparent crystallinity calculated using the deconvolution of the diffractometer trace shows that the amorphous portion of cellulose was permeable to hydrolysis yielding high crystallinity after treatment. All diffratograms show typical cellulose structure with well-defined 110, 200 and 040 peaks. Palm fruit fibres had the highest 200 crystalline cellulose peaks compared to others and it is an indication of rich cellulose content. Surface examination of the resulting fibres using SEM indicates the presence of regular cellulose network structure with some agglomerated laminated layer of thin leaves of cellulose microfibrils. The surfaces were relatively smooth indicating the removal of hemicellulose, lignin and pectin.
Abstract: This paper develops a quality estimation method with
the application of fuzzy hierarchical clustering. Quality estimation is
essential to quality control and quality improvement as a precise
estimation can promote a right decision-making in order to help
better quality control. Normally the quality of finished products in
manufacturing system can be differentiated by quality standards. In
the real life situation, the collected data may be vague which is not
easy to be classified and they are usually represented in term of fuzzy
number. To estimate the quality of product presented by fuzzy
number is not easy. In this research, the trapezoidal fuzzy numbers
are collected in manufacturing process and classify the collected data
into different clusters so as to get the estimation. Since normal
hierarchical clustering methods can only be applied for real numbers,
fuzzy hierarchical clustering is selected to handle this problem based
on quality standards.
Abstract: The use of electronic sensors in the electronics
industry has become increasingly popular over the past few years,
and it has become a high competition product. The frequency
adjustment process is regarded as one of the most important process
in the electronic sensor manufacturing process. Due to inaccuracies
in the frequency adjustment process, up to 80% waste can be caused
due to rework processes; therefore, this study aims to provide a
preliminary understanding of the role of parameters used in the
frequency adjustment process, and also make suggestions in order to
further improve performance. Four parameters are considered in this
study: air pressure, dispensing time, vacuum force, and the distance
between the needle tip and the product. A full factorial design for
experiment 2k was considered to determine those parameters that
significantly affect the accuracy of the frequency adjustment process,
where a deviation in the frequency after adjustment and the target
frequency is expected to be 0 kHz. The experiment was conducted on
two levels, using two replications and with five center-points added.
In total, 37 experiments were carried out. The results reveal that air
pressure and dispensing time significantly affect the frequency
adjustment process. The mathematical relationship between these
two parameters was formulated, and the optimal parameters for air
pressure and dispensing time were found to be 0.45 MPa and 458 ms,
respectively. The optimal parameters were examined by carrying out
a confirmation experiment in which an average deviation of 0.082
kHz was achieved.
Abstract: This paper studies ruin probabilities in two discrete-time
risk models with premiums, claims and rates of interest modelled by
three autoregressive moving average processes. Generalized Lundberg
inequalities for ruin probabilities are derived by using recursive
technique. A numerical example is given to illustrate the applications
of these probability inequalities.
Abstract: The present work was conducted to find out the effect
of biofertilizer formulated with four species of bacteria (two species
of Azotobacter and two species of Lysobacter) and zinc sulphate.
Field experiments with mustard plant were conducted to study the
effectiveness of soil application of zinc sulphate and biofertilizer at
0, 10, 20, 30, 40, 50 days after sowing. Plant height and condition of
plant was found to be increased significantly using a mixture of
biofertilizer and zinc sulphate than other treatments after 40 days
sowing. Three treatments were also used in this field experiment such
as bacteria only, zinc sulphate only and mixture of biofertilizer and
zinc sulphate. The treatment using a mixture of zinc sulphate and
biofertilizer had the best yield (4688.008 kg/ha) within 50 days of
sowing and performed better than other treatments. Field experiment
using zinc sulphate only was second best yield (3380.75Kg/ha) and
biofertilizer only treatment gave (2639.04kg/ha).
Abstract: The Proton Exchange Membrane Fuel Cell (PEMFC)
control system has an important effect on operation of cell.
Traditional controllers couldn-t lead to acceptable responses because
of time- change, long- hysteresis, uncertainty, strong- coupling and
nonlinear characteristics of PEMFCs, so an intelligent or adaptive
controller is needed. In this paper a neural network predictive
controller have been designed to control the voltage of at the
presence of fluctuations of temperature. The results of
implementation of this designed NN Predictive controller on a
dynamic electrochemical model of a small size 5 KW, PEM fuel cell
have been simulated by MATLAB/SIMULINK.
Abstract: The research aims to study the quality of surface water
for consumer in Samut Songkram province. Water sample were
collected from 217 sampling sites conclude 72 sampling sites in
Amphawa, 67 sampling sites in Bangkhonthee and 65 sampling sites
in Muang. Water sample were collected in December 2011 for
winter, March 2012 for summer and August 2012 for rainy season.
From the investigation of surface water quality in Mae Klong
River, main and tributaries canals in Samut Songkram province, we
found that water quality meet the type III of surface water quality
standard issued by the National Environmental Quality Act B.E.
1992. Seasonal variations of pH, Temperature, nitrate, lead and
cadmium have statistical differences between 3 seasons.
Abstract: The number of electronic participation (eParticipation) projects introduced by different governments and international organisations is considerably high and increasing. In order to have an overview of the development of these projects, various evaluation frameworks have been proposed. In this paper, a five-level participation model, which takes into account the advantages of the Social Web or Web 2.0, together with a quantitative approach for the evaluation of eParticipation projects is presented. Each participation level is evaluated independently, taking into account three main components: Web evolution, media richness, and communication channels. This paper presents the evaluation of a number of existing Voting Advice Applications (VAAs). The results provide an overview of the main features implemented by each project, their strengths and weaknesses, and the participation levels reached.
Abstract: Intrusion Detection Systems are increasingly a key
part of systems defense. Various approaches to Intrusion Detection
are currently being used, but they are relatively ineffective. Artificial
Intelligence plays a driving role in security services. This paper
proposes a dynamic model Intelligent Intrusion Detection System,
based on specific AI approach for intrusion detection. The
techniques that are being investigated includes neural networks and
fuzzy logic with network profiling, that uses simple data mining
techniques to process the network data. The proposed system is a
hybrid system that combines anomaly, misuse and host based
detection. Simple Fuzzy rules allow us to construct if-then rules that
reflect common ways of describing security attacks. For host based
intrusion detection we use neural-networks along with self
organizing maps. Suspicious intrusions can be traced back to its
original source path and any traffic from that particular source will
be redirected back to them in future. Both network traffic and system
audit data are used as inputs for both.
Abstract: The removal efficiency of 4-chlorophenol with
different advanced oxidation processes have been studied. Oxidation
experiments were carried out using two 4-chlorophenol
concentrations: 100 mg L-1 and 250 mg L-1 and UV generated from a
KrCl excilamp with (molar ratio H2O2: 4-chlorophenol = 25:1) and
without H2O2, and, with Fenton process (molar ratio H2O2:4-
chlorophenol of 25:1 and Fe2+ concentration of 5 mg L-1).
The results show that there is no significant difference in the 4-
chlorophenol conversion when using one of the three assayed
methods. However, significant concentrations of the photoproductos
still remained in the media when the chosen treatment involves UV
without hydrogen peroxide. Fenton process removed all the
intermediate photoproducts except for the hydroquinone and the
1,2,4-trihydroxybenzene. In the case of UV and hydrogen peroxide
all the intermediate photoproducts are removed.
Microbial bioassays were carried out utilising the naturally
luminescent bacterium Vibrio fischeri and a genetically modified
Pseudomonas putida isolated from a waste treatment plant receiving
phenolic waste. The results using V. fischeri show that with samples
after degradation, only the UV treatment showed toxicity (IC50 =38)
whereas with H2O2 and Fenton reactions the samples exhibited no
toxicity after treatment in the range of concentrations studied. Using
the Pseudomonas putida biosensor no toxicity could be detected for
all the samples following treatment due to the higher tolerance of the
organism to phenol concentrations encountered.
Abstract: This study aims at investigating factors in research
and development (R&D) growth and exploring the role of R&D
management in enhancing social innovation and productivity
improvement in Iran-s industrial sector. It basically explores the
common types of R&D activities and the industries which benefited
the most from active R&D units in Iran. The researchers generated
qualitative analyses obtained from primary and secondary data.
The primary data have been retrieved through interviews with five
key players (Managing Director, Internal Manager, General Manager,
Executive Manager, and Project Manager) in the industrial sector.
The secondary data acquired from an investigation on Mazandaran, a
province of northern Iran. The findings highlight Iran-s focuses of R
& D on cost reduction and upgrading productivity. Industries that
have benefited the most from active R&D units are metallic,
machinery and equipment design, and automotive.
We rank order the primary effects of R&D on productivity
improvement as follows, industry improvement, economic growth,
using professional human resources, generating productivity and
creativity culture, creating a competitive and innovative environment,
and increasing people-s knowledge.
Generally, low budget dedication and insufficient supply of highly
skilled scientists and engineers are two important obstacles for R&D
in Iran. Whereas, R&D has resulted in improvement in Iranian
society, transfer of contemporary knowledge into the international
market is still lacking.
Abstract: In the present work, behavior of inoxydable steel as
reinforcement bar in composite concrete is being investigated. The
bar-concrete adherence in reinforced concrete (RC) beam is studied
and focus is made on the tension stiffening parameter. This study
highlighted an approach to observe this interaction behavior in
bending test instead of direct tension as per reported in many
references. The approach resembles actual loading condition of the
structural RC beam. The tension stiffening properties are then
applied to numerical finite element analysis (FEA) to verify their
correlation with laboratory results. Comparison with laboratory
shows a good correlation between the two. The experimental settings
is able to determine tension stiffening parameters in RC beam and
the modeling strategies made in ABAQUS can closely represent the
actual condition. Tension stiffening model used can represent the
interaction properties between inoxydable steel and concrete.
Abstract: Prior to the use of detectors, characteristics
comparison study was performed and baseline established. In patient
specific QA, the portal dosimetry mean values of area gamma,
average gamma and maximum gamma were 1.02, 0.31 and 1.31 with
standard deviation of 0.33, 0.03 and 0.14 for IMRT and the
corresponding values were 1.58, 0.48 and 1.73 with standard
deviation of 0.31, 0.06 and 0.66 for VMAT. With ImatriXX 2-D
array system, on an average 99.35% of the pixels passed the criteria
of 3%-3 mm gamma with standard deviation of 0.24 for dynamic
IMRT. For VMAT, the average value was 98.16% with a standard
deviation of 0.86. The results showed that both the systems can be
used in patient specific QA measurements for IMRT and VMAT.
The values obtained with the portal dosimetry system were found to
be relatively more consistent compared to those obtained with
ImatriXX 2-D array system.
Abstract: In this paper, the action research driven design of a
context relevant, developmental peer review of teaching model, its
implementation strategy and its impact at an Australian university is
presented. PRO-Teaching realizes an innovative process that
triangulates contemporaneous teaching quality data from a range of
stakeholders including students, discipline academics, learning and
teaching expert academics, and teacher reflection to create reliable
evidence of teaching quality. Data collected over multiple classroom
observations allows objective reporting on development differentials
in constructive alignment, peer, and student evaluations. Further
innovation is realized in the application of this highly structured
developmental process to provide summative evidence of sufficient
validity to support claims for professional advancement and learning
and teaching awards. Design decision points and contextual triggers
are described within the operating domain. Academics and
developers seeking to introduce structured peer review of teaching
into their organization will find this paper a useful reference.
Abstract: In this paper, a decision aid method for preoptimization
is presented. The method is called “negotiation", and it
is based on the identification, formulation, modeling and use of
indicators defined as “negotiation indicators". These negotiation
indicators are used to explore the solution space by means of a classbased
approach. The classes are subdomains for the negotiation
indicators domain. They represent equivalent cognitive solutions in
terms of the negotiation indictors being used. By this method, we
reduced the size of the solution space and the criteria, thus aiding the
optimization methods. We present an example to show the method.