Abstract: Due to the limited lifetime of the nodes in ad hoc and sensor networks, energy efficiency needs to be an important design consideration in any routing algorithm. It is known that by employing a virtual backbone in a wireless network, the efficiency of any routing scheme for the network can be improved. One common design for routing protocols in mobile ad hoc networks is to use positioning information; we use the node-s geometric locations to introduce an algorithm that can construct the virtual backbone structure locally in 3D environment. The algorithm construction has a constant time.
Abstract: In this paper, a set of experimental data has been used to assess the influence of abrasive water jet (AWJ) process parameters in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. The effects of these input parameters are studied on depth of cut (h); one of most important characteristics of AWJ. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. In the next stage, the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the AWJ process parameters. The objective is to determine a suitable set of process parameters that can produce a desired depth of cut, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure.
Abstract: The predictability of masonry arch bridges and their
behaviour is widely considered doubtful due to the lack of knowledge
about the conditions of a given masonry arch bridge. The assessment
methods for masonry arch bridges are MEXE, ARCHIE, RING and
Frame Analysis Method. The material properties of the masonry and
fill material are extremely difficult to determine accurately.
Consequently, it is necessary to examine the effect of load dispersal
angle through the fill material, the effect of variations in the stiffness
of the masonry, the tensile strength of the masonry mortar continuum
and the compressive strength of the masonry mortar continuum. It is
also important to understand the effect of fill material on load
dispersal angle to determine their influence on ratings. In this paper a
series of parametric studies, to examine the sensitivity of assessment
ratings to the various sets of input data required by the frame analysis
method, are carried out.
Abstract: In this paper, algorithms for the automatic localisation
of two anatomical soft tissue landmarks of the head the medial
canthus (inner corner of the eye) and the tragus (a small, pointed,
cartilaginous flap of the ear), in CT images are describet. These
landmarks are to be used as a basis for an automated image-to-patient
registration system we are developing. The landmarks are localised
on a surface model extracted from CT images, based on surface
curvature and a rule based system that incorporates prior knowledge
of the landmark characteristics. The approach was tested on a dataset
of near isotropic CT images of 95 patients. The position of the
automatically localised landmarks was compared to the position of
the manually localised landmarks. The average difference was 1.5
mm and 0.8 mm for the medial canthus and tragus, with a maximum
difference of 4.5 mm and 2.6 mm respectively.The medial canthus
and tragus can be automatically localised in CT images, with
performance comparable to manual localisation
Abstract: The measurements of 226Ra, 232Th and 40K using
gamma spectrometry and radon concentration and exhalation rates
measurements using solid state nuclear track (LR-115, Type-II
plastic) detectors are used to asses a first order exposure risk for the
persons residing in Fatehbad and Hissar districts of Western Haryana,
India. The concentration of Radium, Thorium and Potassium in the
soil samples varies from 13.37 Bq m-3 to 24.67 Bq m-3, 34.67 Bq m-3
to 67.34 Bq m-3 and 298.78 Bq m-3 to 405.67 Bq m-3 respectively
with average values of 18.78, 47.35 and 361.57 Bq m-3 respectively.
The radium equivalent activity (Raeq) calculated for the same soil
samples varies from 92.72 Bq m-3 to 140.6 Bq m-3 with an average
value of 111.80 Bq m-3. The values of absorbed dose and annual
effective dose (indoors and outdoors) are found to vary from 44.18
nGy h-1 to 65.23 nGy h-1, 0.22 mSv y-1 to 0.32 mSv y-1 and 0.05 mSv
y-1 to 0.08 mSv y-1 respectively. The radon concentration and
exhalation rates have also been reported. The radium equivalent
activities in all the soil samples were found to be lower than the limit
(370 Bq kg-1) set in the Organization for Economic Cooperation and
Development (OECD) report and the value of Hex in all the samples
is less than unity.
Abstract: Ontologies and tagging systems are two different ways to organize the knowledge present in the current Web. In this paper we propose a simple method to model folksonomies, as tagging systems, with ontologies. We show the scalability of the method using real data sets. The modeling method is composed of a generic ontology that represents any folksonomy and an algorithm to transform the information contained in folksonomies to the generic ontology. The method allows representing folksonomies at any instant of time.
Abstract: A stack with a small critical temperature gradient is
desirable for a standing wave thermoacoustic engine to obtain a low
onset temperature difference (the minimum temperature difference to
start engine-s self-oscillation). The viscous and heat relaxation loss in
the stack determines the critical temperature gradient. In this work, a
dimensionless critical temperature gradient factor is obtained based
on the linear thermoacoustic theory. It is indicated that the
impedance determines the proportion between the viscous loss, heat
relaxation losses and the power production from the heat energy. It
reveals the effects of the channel dimensions, geometrical
configuration and the local acoustic impedance on the critical
temperature gradient in stacks. The numerical analysis shows that
there exists a possible optimum combination of these parameters
which leads to the lowest critical temperature gradient. Furthermore,
several different geometries have been tested and compared
numerically.
Abstract: Ultrasonic machining (USM) is a non-traditional
machining process being widely used for commercial machining of
brittle and fragile materials such as glass, ceramics and
semiconductor materials. However, USM could be a viable
alternative for machining a tough material such as titanium; and this
aspect needs to be explored through experimental research. This
investigation is focused on exploring the use of ultrasonic machining
for commercial machining of pure titanium (ASTM Grade-I) and
evaluation of tool wear rate (TWR) under controlled experimental
conditions. The optimal settings of parameters are determined
through experiments planned, conducted and analyzed using Taguchi
method. In all, the paper focuses on parametric optimization of
ultrasonic machining of pure titanium metal with TWR as response,
and validation of the optimized value of TWR by conducting
confirmatory experiments.
Abstract: Coal fly ash (CFA) generated by coal-based thermal
power plants is mainly composed of some oxides having high
crystallinity, like quartz and mullite. In this study, the effect of CFA
crystallinity toward lead adsorption capacity was investigated. To get
solid with various crystallinity, the solution of sodium hydroxide
(NaOH) of 1-7 M was used to treat CFA at various temperature and
reflux time. Furthermore, to evaluate the effect of NaOH-treated CFA
with respect to adsorption capacity, the treated CFA were examine as
adsorbent for removing lead in the solution. The result shows that
using NaOH to treat CFA causes crystallinity of quartz and mullite
decrease. At higher NaOH concentration (>3M), in addition the
damage of quartz and mullite crystallinity is followed by crystal
formation called hydroxysodalite. The lower crystalllinity, the higher
adsorption capacity.
Abstract: Soft topological spaces are considered as mathematical tools for dealing with uncertainties, and a fuzzy topological space
is a special case of the soft topological space. The purpose of this paper is to study soft topological spaces. We introduce some new concepts in soft topological spaces such as soft closed mapping, soft open mappings, soft connected spaces and soft paracompact spaces. We also redefine the concept of soft points such that it is reasonable in soft topological spaces. Moreover, some basic properties of these concepts are explored.
Abstract: In large datasets, identifying exceptional or rare cases
with respect to a group of similar cases is considered very significant
problem. The traditional problem (Outlier Mining) is to find
exception or rare cases in a dataset irrespective of the class label of
these cases, they are considered rare events with respect to the whole
dataset. In this research, we pose the problem that is Class Outliers
Mining and a method to find out those outliers. The general
definition of this problem is “given a set of observations with class
labels, find those that arouse suspicions, taking into account the
class labels". We introduce a novel definition of Outlier that is Class
Outlier, and propose the Class Outlier Factor (COF) which measures
the degree of being a Class Outlier for a data object. Our work
includes a proposal of a new algorithm towards mining of the Class
Outliers, presenting experimental results applied on various domains
of real world datasets and finally a comparison study with other
related methods is performed.
Abstract: Quantitative researching on the degree of incidence between the logistics industry and relevant macroscopic system elements is the basis of reasonable and scientific policy on industrial development. In the light of the macro-level, the logistics industry system is consisted of multiple macroscopic agents such as macro-economic, infrastructure, social environment, market demanding, the traditional industry, industry life cycle, policy , system and so on. This paper studies the grey incidence among the macroscopic agents in the logistics industry system. It is demonstrated that the releasing of the logistics services from the logistics outsourcing enterprises determines the growth of the logistics size. Although the information and communication technology is able to promote the formation of the modern logistics industry to some extent, the development of the modern logistics industry depends more on the development of national economy and the investment in the capital assets of the logistics industry.
Abstract: High redundancy and strong uncertainty are two main characteristics for underwater robotic manipulators with unlimited workspace and mobility, but they also make the motion planning and control difficult and complex. In order to setup the groundwork for the research on control schemes, the mathematical representation is built by using the Denavit-Hartenberg (D-H) method [9]&[12]; in addition to the geometry of the manipulator which was studied for establishing the direct and inverse kinematics. Then, the dynamic model is developed and used by employing the Lagrange theorem. Furthermore, derivation and computer simulation is accomplished using the MATLAB environment. The result obtained is compared with mechanical system dynamics analysis software, ADAMS. In addition, the creation of intelligent artificial skin using Interlink Force Sensing ResistorTM technology is presented as groundwork for future work
Abstract: Complex assemblies of interacting proteins carry out
most of the interesting jobs in a cell, such as metabolism, DNA
synthesis, mitosis and cell division. These physiological properties
play out as a subtle molecular dance, choreographed by underlying
regulatory networks that control the activities of cyclin-dependent
kinases (CDK). The network can be modeled by a set of nonlinear
differential equations and its behavior predicted by numerical
simulation. In this paper, an innovative approach has been proposed
that uses genetic algorithms to mine a set of behavior data output by
a biological system in order to determine the kinetic parameters of
the system. In our approach, the machine learning method is
integrated with the framework of existent biological information in a
wiring diagram so that its findings are expressed in a form of system
dynamic behavior. By numerical simulations it has been illustrated
that the model is consistent with experiments and successfully shown
that such application of genetic algorithms will highly improve the
performance of mathematical model of the cell division cycle to
simulate such a complicated bio-system.
Abstract: Promoting critical thinking (CT) in an educational
setting has been appraised in order to enhance learning and
intellectual skills. In this study, a pedagogical course in a vocational
teacher education program in Turkey was designed by integrating CT
skill-based strategies/activities into the course content and CT skills
were means leading to intended course objectives. The purpose of the
study was to evaluate the importance of the course objectives, the
attainment of the objectives, and the effectiveness of teachinglearning
strategies/activities from prospective teachers- points of
view. The results revealed that although the students mostly
considered the course objectives important, they did not feel
competent in the attainment of all objectives especially in those
related to the main topic of Learning and those requiring higher order
thinking skills. On the other hand, the students considered the course
activities effective for learning and for the development of thinking
skills, especially, in interpreting, comparing, questioning,
contrasting, and forming relationships.
Abstract: Optimal design of structure has a main role in reduction of material usage which leads to deduction in the final cost of construction projects. Evolutionary approaches are found to be more successful techniques for solving size and shape structural optimization problem since it uses a stochastic random search instead of a gradient search. By reviewing the recent literature works the problem found was the optimization of weight. A new meta-heuristic algorithm called as Cuckoo Search (CS) Algorithm has used for the optimization of the total weight of the truss structures. This paper has used set of 10 bars and 25 bars trusses for the testing purpose. The main objective of this work is to reduce the number of iterations, weight and the total time consumption. In order to demonstrate the effectiveness of the present method, minimum weight design of truss structures is performed and the results of the CS are compared with other algorithms.
Abstract: Low-density parity-check (LDPC) codes have been shown to deliver capacity approaching performance; however, problematic graphical structures (e.g. trapping sets) in the Tanner graph of some LDPC codes can cause high error floors in bit-error-ratio (BER) performance under conventional sum-product algorithm (SPA). This paper presents a serial concatenation scheme to avoid the trapping sets and to lower the error floors of LDPC code. The outer code in the proposed concatenation is the LDPC, and the inner code is a high rate array code. This approach applies an interactive hybrid process between the BCJR decoding for the array code and the SPA for the LDPC code together with bit-pinning and bit-flipping techniques. Margulis code of size (2640, 1320) has been used for the simulation and it has been shown that the proposed concatenation and decoding scheme can considerably improve the error floor performance with minimal rate loss.
Abstract: Data Envelopment Analysis (DEA) is one of the most
widely used technique for evaluating the relative efficiency of a set
of homogeneous decision making units. Traditionally, it assumes that
input and output variables are known in advance, ignoring the critical
issue of data uncertainty. In this paper, we deal with the problem
of efficiency evaluation under uncertain conditions by adopting the
general framework of the stochastic programming. We assume that
output parameters are represented by discretely distributed random
variables and we propose two different models defined according to a
neutral and risk-averse perspective. The models have been validated
by considering a real case study concerning the evaluation of the
technical efficiency of a sample of individual firms operating in
the Italian leather manufacturing industry. Our findings show the
validity of the proposed approach as ex-ante evaluation technique
by providing the decision maker with useful insights depending on
his risk aversion degree.
Abstract: Binder drainage test is widely used to set an upper
limit to the design binder content of porous asphalt. However, the
presence of high amount of fine particles in the drained binder may
affect the accuracy of the test result. This paper presents a study to
characterize the composition and particle size distribution of fine
particles accumulated in the drained binder. Fine aggregates and filler
in the drained binder were extracted using a suitable solvent. Then,
wet and dry sieve analysis was carried out to identify the actual
composition of the extracted fine aggregates and filler. From the
results, almost half of the drained binder consisted of fine aggregates
and this significantly affects the accuracy of the design binder content
of porous asphalt mix. This simple finding highlights the importance
of taking into account the presence of fine aggregates in the
calculation of drained binder.
Abstract: The recognition of human faces, especially those with
different orientations is a challenging and important problem in image
analysis and classification. This paper proposes an effective scheme
for rotation invariant face recognition using Log-Polar Transform and
Discrete Cosine Transform combined features. The rotation invariant
feature extraction for a given face image involves applying the logpolar
transform to eliminate the rotation effect and to produce a row
shifted log-polar image. The discrete cosine transform is then applied
to eliminate the row shift effect and to generate the low-dimensional
feature vector. A PSO-based feature selection algorithm is utilized to
search the feature vector space for the optimal feature subset.
Evolution is driven by a fitness function defined in terms of
maximizing the between-class separation (scatter index).
Experimental results, based on the ORL face database using testing
data sets for images with different orientations; show that the
proposed system outperforms other face recognition methods. The
overall recognition rate for the rotated test images being 97%,
demonstrating that the extracted feature vector is an effective rotation
invariant feature set with minimal set of selected features.