Abstract: Although there has been a growing interest in the
hybrid free-space optical link and radio frequency FSO/RF
communication system, the current literature is limited to results
obtained in moderate or cold environment. In this paper, using a soft
switching approach, we investigate the effect of weather
inhomogeneities on the strength of turbulence hence the channel
refractive index under Qatar harsh environment and their influence
on the hybrid FSO/RF availability. In this approach, either FSO/RF
or simultaneous or none of them can be active. Based on soft
switching approach and a finite state Markov Chain (FSMC) process,
we model the channel fading for the two links and derive a
mathematical expression for the outage probability of the hybrid
system. Then, we evaluate the behavior of the hybrid FSO/RF under
hazy and harsh weather. Results show that the FSO/RF soft switching
renders the system outage probability less than that of each link
individually. A soft switching algorithm is being implemented on
FPGAs using Raptor code interfaced to the two terminals of a
1Gbps/100 Mbps FSO/RF hybrid system, the first being implemented
in the region. Experimental results are compared to the above
simulation results.
Abstract: In many countries, governments have been promoting the involvement of private sector entities to enter into long-term agreements for the development and delivery of large infrastructure projects, with a focus on overcoming the limitations upon public fund of the traditional approach. The involvement of private sector through public private partnerships (PPP) brings in new capital investments, value for money and additional risks to handle. Worldwide research studies have shown that an objective, systematic, reliable and useroriented risk assessment process and an optimal allocation mechanism among different stakeholders is crucial to the successful completion. In this framework, this paper, which is the first stage of a research study, aims to identify the main risks for the delivery of PPP projects. A review of cross-countries research projects and case studies was performed to map the key risks affecting PPP infrastructure delivery. The matrix of mapping offers a summary of the frequency of factors, clustered in eleven categories: construction, design, economic, legal, market, natural, operation, political, project finance, project selection and relationship. Results will highlight the most critical risk factors, and will hopefully assist the project managers in directing the managerial attention in the further stages of risk allocation.
Abstract: In this paper we studied sono catalytic oxidative desulfurization of oil and diesel fraction from “Zhanazhol” oil deposits. We have established that the combined effect of the ultrasonic field and oxidant (ozone-air mixture) in the presence of the catalyst on the oil is potentially very effective method of desulfurization of oil and oil products. This method allows increasing the degree of desulfurization of oil by 62%.
Abstract: The importance of energy efficiency within the production processes increases steadily. For a comprehensive assessment of energy efficiency within the production process, unfortunately no tools exist or have been developed yet. Therefore the Institute for Factory Automation and Production Systems at the Friedrich-Alexander-University Erlangen-Nuremberg has developed two methods with the goal of achieving transparency and a quantitative assessment of energy efficiency namely EEV (Energy Efficiency Value) and EPE (Energetic Process Efficiency). This paper describes the basics and state-of-the-art as well as the developed approaches.
Abstract: It is an indispensible strategy to adopt greenery
approach on architectural bases so as to improve ecological habitats,
decrease heat-island effect, purify air quality, and relieve surface
runoff as well as noise pollution, all of which are done in an attempt to
achieve sustainable environment. How we can do with plant design to
attain the best visual quality and ideal carbon dioxide fixation depends
on whether or not we can appropriately make use of greenery
according to the nature of architectural bases. To achieve the goal, it is
a need that architects and landscape architects should be provided with
sufficient local references. Current greenery studies focus mainly on
the heat-island effect of urban with large scale. Most of the architects
still rely on people with years of expertise regarding the adoption and
disposition of plantation in connection with microclimate scale.
Therefore, environmental design, which integrates science and
aesthetics, requires fundamental research on landscape environment
technology divided from building environment technology. By doing
so, we can create mutual benefits between green building and the
environment. This issue is extremely important for the greening design
of the bases of green buildings in cities and various open spaces. The
purpose of this study is to establish plant selection and allocation
strategies under different building sunshade levels. Initially, with the
shading of sunshine on the greening bases as the starting point, the
effects of the shades produced by different building types on the
greening strategies were analyzed. Then, by measuring the PAR
(photosynthetic active radiation), the relative DLI (daily light integral)
was calculated, while the DLI Map was established in order to
evaluate the effects of the building shading on the established
environmental greening, thereby serving as a reference for plant
selection and allocation. The discussion results were to be applied in
the evaluation of environment greening of greening buildings and
establish the “right plant, right place” design strategy of multi-level
ecological greening for application in urban design and landscape
design development, as well as the greening criteria to feedback to the
eco-city greening buildings.
Abstract: Nowadays, energy dissipation devices are commonly
used in structures. High rate of energy absorption during earthquakes
is the benefit of using such devices, which results in damage
reduction of structural elements, specifically columns. The hysteretic
damping capacity of energy dissipation devices is the key point that it
may adversely make analysis and design process complicated. This
effect may be generally represented by Equivalent Viscous Damping
(EVD). The equivalent viscous damping might be obtained from the
expected hysteretic behavior regarding to the design or maximum
considered displacement of a structure. In this paper, the hysteretic
damping coefficient of a steel Moment Resisting Frame (MRF),
which its performance is enhanced by a Buckling Restrained Brace
(BRB) system has been evaluated. Having foresight of damping
fraction between BRB and MRF is inevitable for seismic design
procedures like Direct Displacement-Based Design (DDBD) method.
This paper presents an approach to calculate the damping fraction for
such systems by carrying out the dynamic nonlinear time history
analysis (NTHA) under harmonic loading, which is tuned to the
natural system frequency. Two MRF structures, one equipped with
BRB and the other without BRB are simultaneously studied.
Extensive analysis shows that proportion of each system damping
fraction may be calculated by its shear story portion. In this way,
contribution of each BRB in the floors and their general contribution
in the structural performance may be clearly recognized, in advance.
Abstract: Web mining is to discover and extract useful
Information. Different users may have different search goals when
they search by giving queries and submitting it to a search engine.
The inference and analysis of user search goals can be very useful for
providing an experience result for a user search query. In this project,
we propose a novel approach to infer user search goals by analyzing
search web logs. First, we propose a novel approach to infer user
search goals by analyzing search engine query logs, the feedback
sessions are constructed from user click-through logs and it
efficiently reflect the information needed for users. Second we
propose a preprocessing technique to clean the unnecessary data’s
from web log file (feedback session). Third we propose a technique
to generate pseudo-documents to representation of feedback sessions
for clustering. Finally we implement k-medoids clustering algorithm
to discover different user search goals and to provide a more optimal
result for a search query based on feedback sessions for the user.
Abstract: Automation of airport operations can greatly improve
ground movement efficiency. In this paper, we study the speed profile
design problem for advanced airport ground movement control and
guidance. The problem is constrained by the surface four-dimensional
trajectory generated in taxi planning. A decomposed approach of two
stages is presented to solve this problem efficiently. In the first stage,
speeds are allocated at control points, which ensure smooth speed
profiles can be found later. In the second stage, detailed speed profiles
of each taxi interval are generated according to the allocated control
point speeds with the objective of minimizing the overall fuel
consumption. We present a swarm intelligence based algorithm for the
first-stage problem and a discrete variable driven enumeration method
for the second-stage problem, since it only has a small set of discrete
variables. Experimental results demonstrate the presented
methodology performs well on real world speed profile design
problems.
Abstract: This study aimed to explore the practical experience
of child welfare caseworkers and professionalism in child case
management in Malaysia. This paper discussed the specific social
work practice competency and the challenges faced by child
caseworkers in the fieldwork. This research was qualitative with
grounded theory approach. Four sessions of focused group discussion
(FGD) were conducted involving a total of 27 caseworkers (child
protector and probation officers) in the Klang Valley. The study
found that the four basic principles of knowledge in child case
management namely: 1. knowledge in child case management; 2.
professional values of caseworkers towards children; 3. skills in
managing cases; and 4. culturally competent practice in child case
management. In addition, major challenges faced by the child case
manager are the capacity and commitment of the family in children’s
rehabilitation program, the credibility of caseworkers are being
challenged, and the challenges of support system from intra and interagency.
This study is important for policy makers to take into account
the capacity and the needs of the child’s caseworker in accordance
with the national social work competency framework. It is expected
that case management services for children will improve
systematically in line with national standards.
Abstract: In this paper, to model a real life wind turbine, a
probabilistic approach is proposed to model the dynamics of the
blade elements of a small axial wind turbine under extreme stochastic
wind speeds conditions. It was found that the power and the torque
probability density functions even-dough decreases at these extreme
wind speeds but are not infinite. Moreover, we also fund that it
is possible to stabilize the power coefficient (stabilizing the output
power)above rated wind speeds by turning some control parameters.
This method helps to explain the effect of turbulence on the quality
and quantity of the harness power and aerodynamic torque.
Abstract: In the present paper the design of plate heat exchangers
is formulated as an optimization problem considering two
mathematical modelling. The number of plates is the objective
function to be minimized, considering implicitly some parameters
configuration. Screening is the optimization method used to solve the
problem. Thermal and hydraulic constraints are verified, not viable
solutions are discarded and the method searches for the convergence to
the optimum, case it exists. A case study is presented to test the
applicability of the developed algorithm. Results show coherency with
the literature.
Abstract: The goal of the modern education system is to prepare
students to be able to adapt to ever-changing life situations. They
must be able to acquire required knowledge independently; apply
such knowledge in practice to solve various problems by using
modern technologies; think critically and creatively; competently use
information; be communicative, work in a team; and develop their
own moral values, intellect and cultural awareness. As a result, the
status of education significantly increases; new requirements to its
quality have been formed. In recent years the competency-based
approach in education has become of significant interest. This
approach is a strengthening of applied and practical characteristics of
a school education and leads to the forming of the key students’
competencies which define their success in future life. In this article,
the authors’ attention focuses on a range of key competencies,
educational, informational and communicative and on the possibility
to develop such competencies via STEM education. This research
shows the change in students’ attitude towards scientific disciplines
such as mathematics, general science, technology and engineering as
a result of STEM education. Two staged analyzed questionnaires
completed by students of forms II to IV in the republic of Trinidad
and Tobago allowed the authors to categorize students between two
levels that represent students’ attitude to various disciplines. The
significance of differences between selected levels was confirmed
with the use of Pearson’s chi-squared test. In summary, the analysis
of obtained data makes it possible to conclude that STEM education
has a great potential for development of core students’ competencies
and encourage the development of positive student attitude towards
the above mentioned above scientific disciplines.
Abstract: In this article, a method is presented to effectively
estimate the deformed shape of a thick plate due to line heating. The
method uses a fifth order spline interpolation, with up to C3
continuity at specific points to compute the shape of the deformed
geometry. First and second order derivatives over a surface are the
resulting parameters of a given heating line on a plate. These
parameters are determined through experiments and/or finite element
simulations. Very accurate kriging models are fitted to real or virtual
surfaces to build-up a database of maps. Maps of first and second
order derivatives are then applied on numerical plate models to
evaluate their evolving shapes through a sequence of heating lines.
Adding an optimization process to this approach would allow
determining the trajectories of heating lines needed to shape complex
geometries, such as Francis turbine blades.
Abstract: Facility location is a complex real-world problem
which needs a strategic management decision. This paper provides a
general review on studies, efforts and developments in Facility
Location Problems which are classical optimization problems having
a wide-spread applications in various areas such as transportation,
distribution, production, supply chain decisions and
telecommunication. Our goal is not to review all variants of different
studies in FLPs or to describe very detailed computational techniques
and solution approaches, but rather to provide a broad overview of
major location problems that have been studied, indicating how they
are formulated and what are proposed by researchers to tackle the
problem. A brief, elucidative table based on a grouping according to
“General Problem Type” and “Methods Proposed” used in the studies
is also presented at the end of the work.
Abstract: As smartphones are equipped with various sensors,
there have been many studies focused on using these sensors to create
valuable applications. Human activity recognition is one such
application motivated by various welfare applications, such as the
support for the elderly, measurement of calorie consumption, lifestyle
and exercise patterns analyses, and so on. One of the challenges one
faces when using smartphone sensors for activity recognition is that
the number of sensors should be minimized to save battery power. In
this paper, we show that a fairly accurate classifier can be built that
can distinguish ten different activities by using only a single sensor
data, i.e., the smartphone accelerometer data. The approach that we
adopt to deal with this twelve-class problem uses various methods.
The features used for classifying these activities include not only the
magnitude of acceleration vector at each time point, but also the
maximum, the minimum, and the standard deviation of vector
magnitude within a time window. The experiments compared the
performance of four kinds of basic multi-class classifiers and the
performance of four kinds of ensemble learning methods based on
three kinds of basic multi-class classifiers. The results show that
while the method with the highest accuracy is ECOC based on
Random forest.
Abstract: This study presents three different approaches to
estimate bubble point pressures for the binary system of CO2 and
ethyl palmitate fatty acid ethyl ester. The first method involves the
Peng-Robinson (PR) Equation of State (EoS) with the conventional
mixing rule of Van der Waals. The second approach involves the PR
EOS together with the Wong Sandler (WS) mixing rule, coupled with
the UNIQUAC GE model. In order to model the bubble point
pressures with this approach, the volume and area parameter for ethyl
palmitate were estimated by the Hansen group contribution method.
The last method involved the Peng-Robinson, combined with the
Wong-Sandler method, but using NRTL as the GE model. Results
using the Van der Waals mixing rule clearly indicated that this
method has the largest errors among all three methods, with errors in
the range of 3.96-6.22%. The PR-WS-UNIQUAC method exhibited
small errors, with average absolute deviations between 0.95 to 1.97
percent. The PR-WS-NRTL method led to the least errors, where
average absolute deviations ranged between 0.65-1.7%.
Abstract: In this paper, we present a new segmentation approach
for focal liver lesions in contrast enhanced ultrasound imaging. This
approach, based on a two-cluster Fuzzy C-Means methodology,
considers type-II fuzzy sets to handle uncertainty due to the image
modality (presence of speckle noise, low contrast, etc.), and to
calculate the optimum inter-cluster threshold. Fine boundaries are
detected by a local recursive merging of ambiguous pixels. The
method has been tested on a representative database. Compared to
both Otsu and type-I Fuzzy C-Means techniques, the proposed
method significantly reduces the segmentation errors.
Abstract: One of the most critical decision points in the design of a
face recognition system is the choice of an appropriate face representation.
Effective feature descriptors are expected to convey sufficient, invariant
and non-redundant facial information. In this work we propose a set of
Hahn moments as a new approach for feature description. Hahn moments
have been widely used in image analysis due to their invariance, nonredundancy
and the ability to extract features either globally and locally.
To assess the applicability of Hahn moments to Face Recognition we
conduct two experiments on the Olivetti Research Laboratory (ORL)
database and University of Notre-Dame (UND) X1 biometric collection.
Fusion of the global features along with the features from local facial
regions are used as an input for the conventional k-NN classifier. The
method reaches an accuracy of 93% of correctly recognized subjects for
the ORL database and 94% for the UND database.
Abstract: Conductivity properties of DNA molecule is
investigated in a simple, but chemically specific approach that is
intimately related to the Su-Schrieffer-Heeger (SSH) model. This
model is a tight-binding linear nanoscale chain. We have tried to
study the electrical current flowing in DNA and investigated the
characteristic I-V diagram. As a result, It is shown that there are the
(quasi-) ohmic areas in I-V diagram. On the other hand, the regions
with a negative differential resistance (NDR) are detectable in
diagram.
Abstract: Speaker Identification (SI) is the task of establishing
identity of an individual based on his/her voice characteristics. The SI
task is typically achieved by two-stage signal processing: training and
testing. The training process calculates speaker specific feature
parameters from the speech and generates speaker models
accordingly. In the testing phase, speech samples from unknown
speakers are compared with the models and classified. Even though
performance of speaker identification systems has improved due to
recent advances in speech processing techniques, there is still need of
improvement. In this paper, a Closed-Set Tex-Independent Speaker
Identification System (CISI) based on a Multiple Classifier System
(MCS) is proposed, using Mel Frequency Cepstrum Coefficient
(MFCC) as feature extraction and suitable combination of vector
quantization (VQ) and Gaussian Mixture Model (GMM) together
with Expectation Maximization algorithm (EM) for speaker
modeling. The use of Voice Activity Detector (VAD) with a hybrid
approach based on Short Time Energy (STE) and Statistical
Modeling of Background Noise in the pre-processing step of the
feature extraction yields a better and more robust automatic speaker
identification system. Also investigation of Linde-Buzo-Gray (LBG)
clustering algorithm for initialization of GMM, for estimating the
underlying parameters, in the EM step improved the convergence rate
and systems performance. It also uses relative index as confidence
measures in case of contradiction in identification process by GMM
and VQ as well. Simulation results carried out on voxforge.org
speech database using MATLAB highlight the efficacy of the
proposed method compared to earlier work.