Abstract: The polymer foil used for manufacturing of
laminated glass members behaves in a viscoelastic manner with
temperature dependance. This contribution aims at incorporating
the time/temperature-dependent behavior of interlayer to our earlier
elastic finite element model for laminated glass beams. The model
is based on a refined beam theory: each layer behaves according
to the finite-strain shear deformable formulation by Reissner and
the adjacent layers are connected via the Lagrange multipliers
ensuring the inter-layer compatibility of a laminated unit. The
time/temperature-dependent behavior of the interlayer is accounted
for by the generalized Maxwell model and by the time-temperature
superposition principle due to the Williams, Landel, and Ferry.
The resulting system is solved by the Newton method with
consistent linearization and the viscoelastic response is determined
incrementally by the exponential algorithm. By comparing the model
predictions against available experimental data, we demonstrate that
the proposed formulation is reliable and accurately reproduces the
behavior of the laminated glass units.
Abstract: Channel sections are widely used in practice as beams.
However, design rules for eccentrically loaded (not through shear
center) beams with channel cross- sections are not available in
Eurocode 3. This paper compares the ultimate loads based on the
adjusted design rules for lateral torsional buckling of eccentrically
loaded channel beams in bending to the ultimate loads obtained with
Finite Element (FE) simulations on the basis of a parameter study.
Based on the proposed design rule, this study has led to a new design
rule which conforms to Eurocode 3.
Abstract: In this paper, a model is proposed to determine the life
distribution parameters of the useful life region for the PV system
utilizing a combination of non-parametric and linear regression
analysis for the failure data of these systems. Results showed that this
method is dependable for analyzing failure time data for such reliable
systems when the data is scarce.
Abstract: As the trend in automotive technology is fast moving
towards hybridization and electrification to curb emissions as well as
to improve the fuel efficiency, air-conditioning systems in passenger
cars have not caught up with this trend and still remain as the major
energy consumers amongst others. Adsorption based air-conditioning
systems, e.g. with silica-gel water pair, which are already in use for
residential and commercial applications, are now being considered as
a technology leap once proven feasible for the passenger cars. In this
paper we discuss a methodology, challenges and feasibility of
implementing an adsorption based air-conditioning system in a
passenger car utilizing the exhaust waste heat. We also propose an
optimized control strategy with interfaces to the engine control unit
of the vehicle for operating this system with reasonable efficiency
supported by our simulation and validation results in a prototype
vehicle, additionally comparing to existing implementations,
simulation based as well as experimental. Finally we discuss the
influence of start-stop and hybrid systems on the operation strategy of
the adsorption air-conditioning system.
Abstract: We propose new multiple-channel piezoelectric (PZT)
actuated tunable optical filter based on racetrack multi-ring
resonators for wavelength de-multiplexing network applications. We
design tunable eight-channel wavelength de-multiplexer consisting of
eight cascaded PZT actuated tunable multi-ring resonator filter with a
channel spacing of 1.6nm. The filter for each channel is basically
structured on a suspended beam, sandwiched with piezoelectric
material and built in integrated ring resonators which are placed on
the middle of the beam to gain uniform stress and linearly varying
longitudinal strain. A reference single mode serially coupled multi
stage racetrack ring resonator with the same radii and coupling length
is designed with a line width of 0.8974nm with a flat top pass band at
1dB of 0.5205nm and free spectral range of about 14.9nm. In each
channel, a small change in the perimeter of the rings is introduced to
establish the shift in resonance wavelength as per the defined channel
spacing. As a result, when a DC voltage is applied, the beams will
elongate, which involves mechanical deformation of the ring
resonators that induces a stress and a strain, which brings a change in
refractive index and perimeter of the rings leading to change in the
output spectrum shift providing the tunability of central wavelength
in each channel. Simultaneous wave length shift as high as
45.54pm/
Abstract: One of the most famous techniques which affect the
efficiency of a production line is the assembly line balancing (ALB)
technique. This paper examines the balancing effect of a whole
production line of a real auto glass manufacturer in three steps. In the
first step, processing time of each activity in the workstations is
generated according to a practical approach. In the second step, the
whole production process is simulated and the bottleneck stations
have been identified, and finally in the third step, several
improvement scenarios are generated to optimize the system
throughput, and the best one is proposed. The main contribution of
the current research is the proposed framework which combines two
famous approaches including Assembly Line Balancing and
Optimization via Simulation technique (OvS). The results show that
the proposed framework could be applied in practical environments,
easily.
Abstract: This paper contains the description of argumentation
approach for the problem of inductive concept formation. It is
proposed to use argumentation, based on defeasible reasoning with
justification degrees, to improve the quality of classification models,
obtained by generalization algorithms. The experiment’s results on
both clear and noisy data are also presented.
Abstract: The aim of this paper is to present the concept of an
agile enterprise model and to initiate discussion on the research
assumptions of the model presented. The implementation of the
research project "The agility of enterprises in the process of adapting
to the environment and its changes" began in August 2014 and is
planned to last three years. The article has the form of a work-inprogress
paper which aims to verify and initiate a debate over the
proposed research model. In the literature there are very few
publications relating to research into agility; it can be concluded that
the most controversial issue in this regard is the method of measuring
agility. In previous studies the operationalization of agility was often
fragmentary, focusing only on selected areas of agility, for example
manufacturing, or analysing only selected sectors. As a result the
measures created to date can only be treated as contributory to the
development of precise measurement tools. This research project
aims to fill a cognitive gap in the literature with regard to the
conceptualization and operationalization of an agile company. Thus,
the original contribution of the author of this project is the
construction of a theoretical model that integrates manufacturing
agility (consisting mainly in adaptation to the environment) and
strategic agility (based on proactive measures). The author of this
research project is primarily interested in the attributes of an agile
enterprise which indicate that the company is able to rapidly adapt to
changing circumstances and behave pro-actively.
Abstract: Edge is variation of brightness in an image. Edge
detection is useful in many application areas such as finding forests,
rivers from a satellite image, detecting broken bone in a medical
image etc. The paper discusses about finding edge of multiple aerial
images in parallel. The proposed work tested on 38 images 37
colored and one monochrome image. The time taken to process N
images in parallel is equivalent to time taken to process 1 image in
sequential. Message Passing Interface (MPI) and Open Computing
Language (OpenCL) is used to achieve task and pixel level
parallelism respectively.
Abstract: This paper is aimed at proposing a rhombus shaped
wearable fractal antenna for wireless communication systems. The
geometrical descriptors of the antenna have been obtained using
bacterial foraging optimization (BFO) for wide band operation. The
method of moment based IE3D software has been used to simulate
the antenna and observed that miniaturization of 13.08% has been
achieved without degrading the resonating properties of the proposed
antenna. An analysis with different substrates has also been done in
order to evaluate the effectiveness of electrical permittivity on the
presented structure. The proposed antenna has low profile, light
weight and has successfully demonstrated wideband and multiband
characteristics for wearable electronic applications.
Abstract: Margin-Based Principle has been proposed for a long
time, it has been proved that this principle could reduce the
structural risk and improve the performance in both theoretical
and practical aspects. Meanwhile, feed-forward neural network is
a traditional classifier, which is very hot at present with a deeper
architecture. However, the training algorithm of feed-forward neural
network is developed and generated from Widrow-Hoff Principle that
means to minimize the squared error. In this paper, we propose
a new training algorithm for feed-forward neural networks based
on Margin-Based Principle, which could effectively promote the
accuracy and generalization ability of neural network classifiers
with less labelled samples and flexible network. We have conducted
experiments on four UCI open datasets and achieved good results
as expected. In conclusion, our model could handle more sparse
labelled and more high-dimension dataset in a high accuracy while
modification from old ANN method to our method is easy and almost
free of work.
Abstract: The problems arising from unbalanced data sets
generally appear in real world applications. Due to unequal class
distribution, many researchers have found that the performance of
existing classifiers tends to be biased towards the majority class. The
k-nearest neighbors’ nonparametric discriminant analysis is a method
that was proposed for classifying unbalanced classes with good
performance. In this study, the methods of discriminant analysis are
of interest in investigating misclassification error rates for classimbalanced
data of three diabetes risk groups. The purpose of this
study was to compare the classification performance between
parametric discriminant analysis and nonparametric discriminant
analysis in a three-class classification of class-imbalanced data of
diabetes risk groups. Data from a project maintaining healthy
conditions for 599 employees of a government hospital in Bangkok
were obtained for the classification problem. The employees were
divided into three diabetes risk groups: non-risk (90%), risk (5%),
and diabetic (5%). The original data including the variables of
diabetes risk group, age, gender, blood glucose, and BMI were
analyzed and bootstrapped for 50 and 100 samples, 599 observations
per sample, for additional estimation of the misclassification error
rate. Each data set was explored for the departure of multivariate
normality and the equality of covariance matrices of the three risk
groups. Both the original data and the bootstrap samples showed nonnormality
and unequal covariance matrices. The parametric linear
discriminant function, quadratic discriminant function, and the
nonparametric k-nearest neighbors’ discriminant function were
performed over 50 and 100 bootstrap samples and applied to the
original data. Searching the optimal classification rule, the choices of
prior probabilities were set up for both equal proportions (0.33: 0.33:
0.33) and unequal proportions of (0.90:0.05:0.05), (0.80: 0.10: 0.10)
and (0.70, 0.15, 0.15). The results from 50 and 100 bootstrap samples
indicated that the k-nearest neighbors approach when k=3 or k=4 and
the defined prior probabilities of non-risk: risk: diabetic as 0.90:
0.05:0.05 or 0.80:0.10:0.10 gave the smallest error rate of
misclassification. The k-nearest neighbors approach would be
suggested for classifying a three-class-imbalanced data of diabetes
risk groups.
Abstract: In this work, we explore the capability of the mean
shift algorithm as a powerful preprocessing tool for improving the
quality of spatial data, acquired from airborne scanners, from densely
built urban areas. On one hand, high resolution image data corrupted
by noise caused by lossy compression techniques are appropriately
smoothed while at the same time preserving the optical edges and, on
the other, low resolution LiDAR data in the form of normalized
Digital Surface Map (nDSM) is upsampled through the joint mean
shift algorithm. Experiments on both the edge-preserving smoothing
and upsampling capabilities using synthetic RGB-z data show that the
mean shift algorithm is superior to bilateral filtering as well as to
other classical smoothing and upsampling algorithms. Application of
the proposed methodology for 3D reconstruction of buildings of a
pilot region of Athens, Greece results in a significant visual
improvement of the 3D building block model.
Abstract: Networking is important among students to achieve
better understanding. Social networking plays an important role in the
education. Realizing its huge potential, various organizations,
including institutions of higher learning have moved to the area of
social networks to interact with their students especially through
Facebook. Therefore, measuring the effectiveness of Facebook as a
learning tool has become an area of interest to academicians and
researchers. Therefore, this study tried to integrate and propose new
theoretical and empirical evidences by linking the western idea of
adopting Facebook as an alternative learning platform from a
Malaysian perspective. This study, thus, aimed to fill a gap by being
among the pioneering research that tries to study the effectiveness of
adopting Facebook as a learning platform across other cultural
settings, namely Malaysia. Structural equation modeling was
employed for data analysis and hypothesis testing. This study finding
has provided some insights that would likely affect students’
awareness towards using Facebook as an alternative learning
platform in the Malaysian higher learning institutions. At the end,
future direction is proposed.
Abstract: The aim of this exploratory research is to understand
further how organisations can evaluate their activities, which
generate knowledge creation, to meet changing stakeholder
expectations. A Scale of Knowledge (SoK) Framework is proposed
which links knowledge management and organisational activities to
changing stakeholder expectations. The framework was informed by
the knowledge management literature, as well as empirical work
conducted via a single case study of a multi-site hospital organisation
in Saudi Arabia. Eight in-depth semi-structured interviews were
conducted with managers from across the organisation regarding
current and future stakeholder expectations, organisational
strategy/activities and knowledge management. Data were analysed
using thematic analysis and a hierarchical value map technique to
identify activities that can produce further knowledge and
consequently impact on how stakeholder expectations are met.
The SoK Framework developed may be useful to practitioners as
an analytical aid to determine if current organisational activities
produce organisational knowledge which helps them meet
(increasingly higher levels of) stakeholder expectations. The
limitations of the research and avenues for future development of the
proposed framework are discussed.
Abstract: In this study, we proposed two techniques to track the
maximum power point (MPPT) of a photovoltaic system. The first is
an intelligent control technique, and the second is robust used for
variable structure system. In fact the characteristics I-V and P–V of
the photovoltaic generator depends on the solar irradiance and
temperature. These climate changes cause the fluctuation of
maximum power point; a maximum power point tracking technique
(MPPT) is required to maximize the output power. For this we have
adopted a control by fuzzy logic (FLC) famous for its stability and
robustness. And a Siding Mode Control (SMC) widely used for
variable structure system. The system comprises a photovoltaic panel
(PV), a DC-DC converter, which is considered as an adaptation stage
between the PV and the load. The modelling and simulation of the
system is developed using MATLAB/Simulink. SMC technique
provides a good tracking speed in fast changing irradiation and when
the irradiation changes slowly or it is constant the panel power of
FLC technique presents a much smoother signal with less
fluctuations.
Abstract: This paper is aimed to the use of different types of
industrial wastes in concrete production. From examined waste
(crushed concrete waste) our tested concrete samples with dimension
150 mm were prepared. In these samples, fractions 4/8 mm and 8/16
mm by recycled concrete aggregate with a range of variation from 0
to 100% were replaced. Experiment samples were tested for
compressive strength after 2, 7, 14 and 28 days of hardening.
From obtained results it is evident that all samples prepared with
washed recycled concrete aggregates met the requirement of standard
for compressive strength of 20 MPa already after 14 days of
hardening. Sample prepared with recycled concrete aggregates (4/8
mm: 100% and 8/16 mm: 60%) reached 101% of compressive
strength value (34.7 MPa) after 28 days of hardening in comparison
with the reference sample (34.4 MPa). The lowest strength after 28
days of hardening (27.42 MPa) was obtained for sample consisting of
recycled concrete in proportion of 40% for 4/8 fraction and 100% for
8/16 fraction of recycled concrete.
Abstract: Evolutionary optimization methods such as genetic
algorithms have been used extensively for the construction site layout
problem. More recently, ant colony optimization algorithms, which
are evolutionary methods based on the foraging behavior of ants,
have been successfully applied to benchmark combinatorial
optimization problems. This paper proposes a formulation of the site
layout problem in terms of a sequencing problem that is suitable for
solution using an ant colony optimization algorithm.
In the construction industry, site layout is a very important
planning problem. The objective of site layout is to position
temporary facilities both geographically and at the correct time such
that the construction work can be performed satisfactorily with
minimal costs and improved safety and working environment. During
the last decade, evolutionary methods such as genetic algorithms
have been used extensively for the construction site layout problem.
This paper proposes an ant colony optimization model for
construction site layout. A simple case study for a highway project is
utilized to illustrate the application of the model.
Abstract: An efficient remanufacturing network lead to an
efficient design of sustainable manufacturing enterprise. In
remanufacturing network, products are collected from the customer
zone, disassembled and remanufactured at a suitable remanufacturing
facility. In this respect, another issue to consider is how the returned
product to be remanufactured, in other words, what is the best layout
for such facility. In order to achieve a sustainable manufacturing
system, Cellular Manufacturing System (CMS) designs are highly
recommended, CMSs combine high throughput rates of line layouts
with the flexibility offered by functional layouts (job shop).
Introducing the CMS while designing a remanufacturing network will
benefit the utilization of such a network. This paper presents and
analyzes a comprehensive mathematical model for the design of
Dynamic Cellular Remanufacturing Systems (DCRSs). In this paper,
the proposed model is the first one to date that considers CMS and
remanufacturing system simultaneously. The proposed DCRS model
considers several manufacturing attributes such as multi period
production planning, dynamic system reconfiguration, duplicate
machines, machine capacity, available time for workers, worker
assignments, and machine procurement, where the demand is totally
satisfied from a returned product. A numerical example is presented
to illustrate the proposed model.
Abstract: In this paper we propose a novel methodology for
extracting a road network and its nodes from satellite images of
Algeria country.
This developed technique is a progress of our previous research
works. It is founded on the information theory and the mathematical
morphology; the information theory and the mathematical
morphology are combined together to extract and link the road
segments to form a road network and its nodes.
We therefore have to define objects as sets of pixels and to study
the shape of these objects and the relations that exist between them.
In this approach, geometric and radiometric features of roads are
integrated by a cost function and a set of selected points of a crossing
road. Its performances were tested on satellite images of Algeria
country.