Abstract: Sensor relocation is to repair coverage holes caused by node failures. One way to repair coverage holes is to find redundant nodes to replace faulty nodes. Most researches took a long time to find redundant nodes since they randomly scattered redundant nodes around the sensing field. To record the precise position of sensor nodes, most researches assumed that GPS was installed in sensor nodes. However, high costs and power-consumptions of GPS are heavy burdens for sensor nodes. Thus, we propose a fast sensor relocation algorithm to arrange redundant nodes to form redundant walls without GPS. Redundant walls are constructed in the position where the average distance to each sensor node is the shortest. Redundant walls can guide sensor nodes to find redundant nodes in the minimum time. Simulation results show that our algorithm can find the proper redundant node in the minimum time and reduce the relocation time with low message complexity.
Abstract: This paper deals with a portfolio selection problem
based on the possibility theory under the assumption that the returns
of assets are LR-type fuzzy numbers. A possibilistic portfolio model
with transaction costs is proposed, in which the possibilistic mean
value of the return is termed measure of investment return, and the
possibilistic variance of the return is termed measure of investment
risk. Due to considering transaction costs, the existing traditional
optimization algorithms usually fail to find the optimal solution
efficiently and heuristic algorithms can be the best method. Therefore,
a particle swarm optimization is designed to solve the corresponding
optimization problem. At last, a numerical example is given to
illustrate our proposed effective means and approaches.
Abstract: Removal of Methylene Blue (MB) from aqueous
solution by adsorbing it on Gypsum was investigated by batch
method. The studies were conducted at 25°C and included the effects
of pH and initial concentration of Methylene Blue. The adsorption
data was analyzed by using the Langmuir, Freundlich and Tempkin
isotherm models. The maximum monolayer adsorption capacity was
found to be 36 mg of the dye per gram of gypsum. The data were
also analyzed in terms of their kinetic behavior and was found to
obey the pseudo second order equation.
Abstract: In a previous work, we presented the numerical
solution of the two dimensional second order telegraph partial
differential equation discretized by the centred and rotated five-point
finite difference discretizations, namely the explicit group (EG) and
explicit decoupled group (EDG) iterative methods, respectively. In
this paper, we utilize a domain decomposition algorithm on these
group schemes to divide the tasks involved in solving the same
equation. The objective of this study is to describe the development
of the parallel group iterative schemes under OpenMP programming
environment as a way to reduce the computational costs of the
solution processes using multicore technologies. A detailed
performance analysis of the parallel implementations of points and
group iterative schemes will be reported and discussed.
Abstract: Supply Chain Management (SCM) is the integration
between manufacturer, transporter and customer in order to form one
seamless chain that allows smooth flow of raw materials, information
and products throughout the entire network that help in minimizing
all related efforts and costs. The main objective of this paper is to
develop a model that can accept a specified number of spare-parts
within the supply chain, simulating its inventory operations
throughout all stages in order to minimize the inventory holding
costs, base-stock, safety-stock, and to find the optimum quantity of
inventory levels, thereby suggesting a way forward to adapt some
factors of Just-In-Time to minimizing the inventory costs throughout
the entire supply chain. The model has been developed using Micro-
Soft Excel & Visual Basic in order to study inventory allocations in
any network of the supply chain. The application and reproducibility
of this model were tested by comparing the actual system that was
implemented in the case study with the results of the developed
model. The findings showed that the total inventory costs of the
developed model are about 50% less than the actual costs of the
inventory items within the case study.
Abstract: This paper presents an approach based on the
adoption of a distributed cognition framework and a non parametric
multicriteria evaluation methodology (DEA) designed specifically to
compare e-commerce websites from the consumer/user viewpoint. In
particular, the framework considers a website relative efficiency as a
measure of its quality and usability. A website is modelled as a black
box capable to provide the consumer/user with a set of
functionalities. When the consumer/user interacts with the website to
perform a task, he/she is involved in a cognitive activity, sustaining a
cognitive cost to search, interpret and process information, and
experiencing a sense of satisfaction. The degree of ambiguity and
uncertainty he/she perceives and the needed search time determine
the effort size – and, henceforth, the cognitive cost amount – he/she
has to sustain to perform his/her task. On the contrary, task
performing and result achievement induce a sense of gratification,
satisfaction and usefulness. In total, 9 variables are measured,
classified in a set of 3 website macro-dimensions (user experience,
site navigability and structure). The framework is implemented to
compare 40 websites of businesses performing electronic commerce
in the information technology market. A questionnaire to collect
subjective judgements for the websites in the sample was purposely
designed and administered to 85 university students enrolled in
computer science and information systems engineering
undergraduate courses.
Abstract: The shortest path routing problem is a multiobjective
nonlinear optimization problem with constraints. This problem has
been addressed by considering Quality of service parameters, delay
and cost objectives separately or as a weighted sum of both
objectives. Multiobjective evolutionary algorithms can find multiple
pareto-optimal solutions in one single run and this ability makes them
attractive for solving problems with multiple and conflicting
objectives. This paper uses an elitist multiobjective evolutionary
algorithm based on the Non-dominated Sorting Genetic Algorithm
(NSGA), for solving the dynamic shortest path routing problem in
computer networks. A priority-based encoding scheme is proposed
for population initialization. Elitism ensures that the best solution
does not deteriorate in the next generations. Results for a sample test
network have been presented to demonstrate the capabilities of the
proposed approach to generate well-distributed pareto-optimal
solutions of dynamic routing problem in one single run. The results
obtained by NSGA are compared with single objective weighting
factor method for which Genetic Algorithm (GA) was applied.
Abstract: In Image processing the Image compression can improve
the performance of the digital systems by reducing the cost and
time in image storage and transmission without significant reduction
of the Image quality. This paper describes hardware architecture of
low complexity Discrete Cosine Transform (DCT) architecture for
image compression[6]. In this DCT architecture, common computations
are identified and shared to remove redundant computations
in DCT matrix operation. Vector processing is a method used for
implementation of DCT. This reduction in computational complexity
of 2D DCT reduces power consumption. The 2D DCT is performed
on 8x8 matrix using two 1-Dimensional Discrete cosine transform
blocks and a transposition memory [7]. Inverse discrete cosine
transform (IDCT) is performed to obtain the image matrix and
reconstruct the original image. The proposed image compression
algorithm is comprehended using MATLAB code. The VLSI design
of the architecture is implemented Using Verilog HDL. The proposed
hardware architecture for image compression employing DCT was
synthesized using RTL complier and it was mapped using 180nm
standard cells. . The Simulation is done using Modelsim. The
simulation results from MATLAB and Verilog HDL are compared.
Detailed analysis for power and area was done using RTL compiler
from CADENCE. Power consumption of DCT core is reduced to
1.027mW with minimum area[1].
Abstract: The pipe inspection operation is the difficult detective
performance. Almost applications are mainly relies on a manual
recognition of defective areas that have carried out detection by an
engineer. Therefore, an automation process task becomes a necessary
in order to avoid the cost incurred in such a manual process. An
automated monitoring method to obtain a complete picture of the
sewer condition is proposed in this work. The focus of the research is
the automated identification and classification of discontinuities in
the internal surface of the pipe. The methodology consists of several
processing stages including image segmentation into the potential
defect regions and geometrical characteristic features. Automatic
recognition and classification of pipe defects are carried out by means
of using an artificial neural network technique (ANN) based on
Radial Basic Function (RBF). Experiments in a realistic environment
have been conducted and results are presented.
Abstract: The design of a pattern classifier includes an attempt
to select, among a set of possible features, a minimum subset of
weakly correlated features that better discriminate the pattern classes.
This is usually a difficult task in practice, normally requiring the
application of heuristic knowledge about the specific problem
domain. The selection and quality of the features representing each
pattern have a considerable bearing on the success of subsequent
pattern classification. Feature extraction is the process of deriving
new features from the original features in order to reduce the cost of
feature measurement, increase classifier efficiency, and allow higher
classification accuracy. Many current feature extraction techniques
involve linear transformations of the original pattern vectors to new
vectors of lower dimensionality. While this is useful for data
visualization and increasing classification efficiency, it does not
necessarily reduce the number of features that must be measured
since each new feature may be a linear combination of all of the
features in the original pattern vector. In this paper a new approach is
presented to feature extraction in which feature selection, feature
extraction, and classifier training are performed simultaneously using
a genetic algorithm. In this approach each feature value is first
normalized by a linear equation, then scaled by the associated weight
prior to training, testing, and classification. A knn classifier is used to
evaluate each set of feature weights. The genetic algorithm optimizes
a vector of feature weights, which are used to scale the individual
features in the original pattern vectors in either a linear or a nonlinear
fashion. By this approach, the number of features used in classifying
can be finely reduced.
Abstract: In this study, a nickel film with nano-crystalline grains,
high hardness and smooth surface was electrodeposited using a post
supercritical carbon dioxide (CO2) mixed Watts electrolyte. Although
the hardness was not as high as its Sc-CO2 counterpart, the thin coating
contained significantly less number of nano-sized pinholes. By
measuring the escape concentration of the dissolved CO2 in post
Sc-CO2 mixed electrolyte with the elapsed time, it was believed that
the residue of dissolved CO2 bubbles should closely relate to the
improvement in hardness and surface roughness over its conventional
plating counterpart. Therefore, shortening the duration of
electroplating with the raise of current density up to 0.5 A/cm2 could
effectively retain more post Sc-CO2 mixing effect. This study not only
confirms the roles of dissolved CO2 bubbles in electrolyte but also
provides a potential process to overcome most issues associated with
the cost in building high-pressure chamber for large size products and
continuous plating using supercritical method.
Abstract: This paper describes the experimental efficiency of a
compact organic Rankine cycle (ORC) system with a compact
rotary-vane-type expander. The compact ORC system can be used for
power generation from low-temperature heat sources such as waste
heat from various small-scale heat engines, fuel cells, electric devices,
and solar thermal energy. The purpose of this study is to develop an
ORC system with a low power output of less than 1 kW with a hot
temperature source ranging from 60°C to 100°C and a cold
temperature source ranging from 10°C to 30°C. The power output of
the system is rather less due to limited heat efficiency. Therefore, the
system should have an economically optimal efficiency. In order to
realize such a system, an efficient and low-cost expander is
indispensable. An experimental ORC system was developed using the
rotary-vane-type expander which is one of possible candidates of the
expander. The experimental results revealed the expander
performance for various rotation speeds, expander efficiencies, and
thermal efficiencies. Approximately 30 W of expander power output
with 48% expander efficiency and 4% thermal efficiency with a
temperature difference between the hot and cold sources of 80°C was
achieved.
Abstract: Productivity has been one of the major concerns with the increasingly high cost of software development. Choosing the right development language with high productivity is one approach to reduce development costs. Working on the large database with 4106 projects ever developed, we found the factors significant to productivity. After the removal of the effects of other factors on productivity, we compare the productivity differences of the ten general development programs. The study supports the fact that fourth-generation languages are more productive than thirdgeneration languages.
Abstract: The demand for higher performance graphics
continues to grow because of the incessant desire towards realism.
And, rapid advances in fabrication technology have enabled us to
build several processor cores on a single die. Hence, it is important to
develop single chip parallel architectures for such data-intensive
applications. In this paper, we propose an efficient PIM architectures
tailored for computer graphics which requires a large number of
memory accesses. We then address the two important tasks necessary
for maximally exploiting the parallelism provided by the architecture,
namely, partitioning and placement of graphic data, which affect
respectively load balances and communication costs. Under the
constraints of uniform partitioning, we develop approaches for optimal
partitioning and placement, which significantly reduce search space.
We also present heuristics for identifying near-optimal placement,
since the search space for placement is impractically large despite our
optimization. We then demonstrate the effectiveness of our partitioning
and placement approaches via analysis of example scenes; simulation
results show considerable search space reductions, and our heuristics
for placement performs close to optimal – the average ratio of
communication overheads between our heuristics and the optimal was
1.05. Our uniform partitioning showed average load-balance ratio of
1.47 for geometry processing and 1.44 for rasterization, which is
reasonable.
Abstract: The rapidly increasing costs of power line extensions
and fossil fuel, combined with the desire to reduce carbon dioxide
emissions pushed the development of hybrid power system suited for
remote locations, the purpose in mind being that of autonomous local
power systems. The paper presents the suggested solution for a “high
penetration" hybrid power system, it being determined by the
location of the settlement and its “zero policy" on carbon dioxide
emissions. The paper focuses on the technical solution and the power
flow management algorithm of the system, taking into consideration
local conditions of development.
Abstract: Using efficient classification methods is necessary for automatic fingerprint recognition system. This paper introduces a new structural approach to fingerprint classification by using the directional image of fingerprints to increase the number of subclasses. In this method, the directional image of fingerprints is segmented into regions consisting of pixels with the same direction. Afterwards the relational graph to the segmented image is constructed and according to it, the super graph including prominent information of this graph is formed. Ultimately we apply a matching technique to compare obtained graph with the model graphs in order to classify fingerprints by using cost function. Increasing the number of subclasses with acceptable accuracy in classification and faster processing in fingerprints recognition, makes this system superior.
Abstract: This paper concerns the study of sustainable construction materials applied on the "Health Post", a prototype for the primary health care situated in alienated areas of the world. It's suitable for social and climatic Sub-Saharan context; however, it could be moved in other countries of the world with similar urgent needs. The idea is to create a Health Post with local construction materials that have a low environmental impact and promote the local workforce allowing reuse of traditional building techniques lowering production costs and transport. The aim of Primary Health Care Centre is to be a flexible and expandable structure identifying a modular form that can be repeated several times to expand its existing functions. In this way it could be not only a health care centre but also a socio-cultural facility.
Abstract: Optimizing equipment selection in heavy earthwork
operations is a critical key in the success of any construction project.
The objective of this research incentive was geared towards
developing a computer model to assist contractors and construction
managers in estimating the cost of heavy earthwork operations.
Economical operation analysis was conducted for an equipment fleet
taking into consideration the owning and operating costs involved in
earthwork operations. The model is being developed in a Microsoft
environment and is capable of being integrated with other estimating
and optimization models. In this study, Caterpillar® Performance
Handbook [5] was the main resource used to obtain specifications of
selected equipment. The implementation of the model shall give
optimum selection of equipment fleet not only based on cost
effectiveness but also in terms of versatility. To validate the model, a
case study of an actual dam construction project was selected to
quantify its degree of accuracy.
Abstract: The effects of dynamic subgrid scale (SGS) models are
investigated in variational multiscale (VMS) LES simulations of bluff
body flows. The spatial discretization is based on a mixed finite
element/finite volume formulation on unstructured grids. In the VMS
approach used in this work, the separation between the largest and the
smallest resolved scales is obtained through a variational projection
operator and a finite volume cell agglomeration. The dynamic version
of Smagorinsky and WALE SGS models are used to account for
the effects of the unresolved scales. In the VMS approach, these
effects are only modeled in the smallest resolved scales. The dynamic
VMS-LES approach is applied to the simulation of the flow around a
circular cylinder at Reynolds numbers 3900 and 20000 and to the flow
around a square cylinder at Reynolds numbers 22000 and 175000. It
is observed as in previous studies that the dynamic SGS procedure
has a smaller impact on the results within the VMS approach than in
LES. But improvements are demonstrated for important feature like
recirculating part of the flow. The global prediction is improved for
a small computational extra cost.
Abstract: This paper presents the development of low cost Nano membrane fabrication system. The system is specially designed for anodic aluminum oxide membrane. This system is capable to perform the processes such as anodization and electro-polishing. The designed machine was successfully tested for 'mild anodization' (MA) for 48 hours and 'hard anodization' (HA) for 3 hours at constant 0oC. The system is digitally controlled and guided for temperature maintenance during anodization and electro-polishing. The total cost of the developed machine is 20 times less than the multi-cooling systems available in the market which are generally used for this purpose.