Abstract: We present a new algorithm for nonlinear dimensionality reduction that consistently uses global information, and that enables understanding the intrinsic geometry of non-convex manifolds. Compared to methods that consider only local information, our method appears to be more robust to noise. Unlike most methods that incorporate global information, the proposed approach automatically handles non-convexity of the data manifold. We demonstrate the performance of our algorithm and compare it to state-of-the-art methods on synthetic as well as real data.
Abstract: This paper presents a new and efficient approach for
capacitor placement in radial distribution systems that determine
the optimal locations and size of capacitor with an objective of
improving the voltage profile and reduction of power loss. The
solution methodology has two parts: in part one the loss sensitivity
factors are used to select the candidate locations for the capacitor
placement and in part two a new algorithm that employs Plant growth
Simulation Algorithm (PGSA) is used to estimate the optimal size
of capacitors at the optimal buses determined in part one. The main
advantage of the proposed method is that it does not require any
external control parameters. The other advantage is that it handles the
objective function and the constraints separately, avoiding the trouble
to determine the barrier factors. The proposed method is applied to 9
and 34 bus radial distribution systems. The solutions obtained by the
proposed method are compared with other methods. The proposed
method has outperformed the other methods in terms of the quality
of solution.
Abstract: To make use of the limited amounts of water in arid
region, the Iranians developed man-made underground water
channels called qanats (kanats) .In fact, qanats may be considered as
the first long-distance water transfer system. Qanats are an ancient
water transfer system found in arid regions wherein groundwater
from mountainous areas, aquifers and sometimes from rivers, was
brought to points of re-emergence such as an oasis, through one or
more underground tunnels. The tunnels, many of which were
kilometers in length, had designed for slopes to provide gravitational
flow. The tunnels allowed water to drain out to the surface by gravity
to supply water to lower and flatter agricultural land.
Qanats have been an ancient, sustainable system facilitating the
harvesting of water for centuries in Iran, and more than 35 additional
countries of the world such as India, Arabia, Egypt, North Africa,
Spain and even to New world.
There are about 22000 qanats in Iran with 274000 kilometers of
underground conduits all built by manual labor. The amount of
water of the usable qanats of Iran produce is altogether 750 to
1000 cubic meter per second. The longest chain of qanat is
situated in Gonabad region in Khorasan province. It is 70
kilometers long. Qanats are renewable water supply systems that
have sustained agricultural settlement on the Iranian plateau for
millennia. The great advantages of Qanats are no evaporation
during transit, little seepage , no raising of the water- table and no
pollution in the area surrounding the conduits. Qanat systems
have a profound influence on the lives of the water users in Iran, and
conform to Iran-s climate. Qanat allows those living in a desert
environment adjacent to a mountain watershed to create a large oasis
in an otherwise stark environment.
This paper explains qanats structure designs, their history,
objectives causing their creation, construction materials, locations
and their importance in different times, as well as their present
sustainable role in Iran.
Abstract: Heavy rains are one of the features of arid and semi
arid climates which result in flood. This kind of rainfall originates
from environmental and synoptic conditions. Mediterranean cyclones
are the major factor in heavy rainfall in Iran, but these cyclones do
not happen in some parts of Iran such as Southern and Southeastern
areas. In this study, it has been tried to pinpoint the synoptic reasons
of heavy rainfall in Isfahan through the analysis of the relationship
between this rainfall in Isfahan and atmospheric system over Iran and
the areas around it. The findings of this study show that the major
factor have is the arrival of Sudanese low pressure system in this
region from the southwest, of course if the ascent local conditions
such as heat occur, the heaviest rains happen in Isfahan. In fact this
kind of rainfall in Isfahan has a Sudanese origin and if it is
accompanied by Mediterranean system, heavier rain falls.
Abstract: This paper presents the influence of distributed generation (DG) on congestion and locational marginal price (LMP) in an optimal power flow (OPF) based wholesale electricity market. The problem of optimal placement to manage congestion and reduce LMP is formulated for the objective of social welfare maximization. From competitive electricity market standpoint, DGs have great value when they reduce load in particular locations and at particular times when feeders are heavily loaded. The paper lies on the groundwork that solution to optimal mix of generation and transmission resources can be achieved by addressing congestion and corresponding LMP. Obtained as lagrangian multiplier associated with active power flow equation for each node, LMP gives the short run marginal cost (SRMC) of electricity. Specific grid locations are examined to study the influence of DG penetration on congestion and corresponding shadow prices. The influence of DG on congestion and locational marginal prices has been demonstrated in a modified IEEE 14 bus test system.
Abstract: Global approximation using metamodel for complex
mathematical function or computer model over a large variable
domain is often needed in sensibility analysis, computer simulation,
optimal control, and global design optimization of complex, multiphysics
systems. To overcome the limitations of the existing
response surface (RS), surrogate or metamodel modeling methods for
complex models over large variable domain, a new adaptive and
regressive RS modeling method using quadratic functions and local
area model improvement schemes is introduced. The method applies
an iterative and Latin hypercube sampling based RS update process,
divides the entire domain of design variables into multiple cells,
identifies rougher cells with large modeling error, and further divides
these cells along the roughest dimension direction. A small number
of additional sampling points from the original, expensive model are
added over the small and isolated rough cells to improve the RS
model locally until the model accuracy criteria are satisfied. The
method then combines local RS cells to regenerate the global RS
model with satisfactory accuracy. An effective RS cells sorting
algorithm is also introduced to improve the efficiency of model
evaluation. Benchmark tests are presented and use of the new
metamodeling method to replace complex hybrid electrical vehicle
powertrain performance model in vehicle design optimization and
optimal control are discussed.
Abstract: Semnan is a city in semnan province, northern Iran
with a population estimated at 119,778 inhabitants. It is the
provincial capital of semnan province. Iran is a developing country
and construction is a basic factor of developing too. Hence, Semnan
city needs to a special programming for construction of buildings,
structures and infrastructures. Semnan municipality tries to begin this
program. In addition to, city has some historical monuments which
can be interesting for tourists. Hence, Semnan inhabitants can benefit
from tourist industry. Optimization of Energy in construction
industry is another activity of this municipality and the inhabitants
who execute these regulations receive some discounts. Many parts of
Iran such as semnan are located in highly seismic zones and
structures must be constructed safe e.g., according to recent seismic
codes. In this paper opportunities of IT in construction industry of
Iran are investigated in three categories. Pre-construction phase,
construction phase and earthquake disaster mitigation are studied.
Studies show that information technology can be used in these items
for reducing the losses and increasing the benefits. Both government
and private sectors must contribute to this strategic project for
obtaining the best result.
Abstract: In the present work, Pulsed Electro Acoustic (PEA)
technique was adopted to understand the space charge dynamics in
elastomeric material. It is observed that the polarity of the applied
DC voltage voltage and its magnitude alters the space charge
dynamics in insulation structure. It is also noticed that any addition
of compound to the base material/processing technique have
characteristic variation in the space charge injection process. It could
be concluded based on the present work that the plasticizer could
inject heterocharges into the insulation medium. Also it is realized
that space charge magnitude is less with the addition of plasticizer. In
the PEA studies, it is observed that local electric field in the
insulating material can be much more than applied electric field due
to space charge formation. One of the important conclusions arrived
at based on PEA technique is that one could understand the safe
operating electric field of an insulation material and the charge trap
sites.
Abstract: Nowadays there is a growing environmental concern
and the business communities have slowly started recognising
environmental protection and sustainable utilization of natural
resources into their marketing strategies. This paper discusses the
various Ecolabeling and Certification Systems developed world
over to regulate and introduce Fair Trade in Ornamental Fish
Industry. Ecolabeling and green certification are considered as part
of these strategies implemented partly out of compulsion from the
National and International Regulatory Bodies and Environmental
Movements. All the major markets of ornamental fishes like
European Union, USA and Japan have started putting restrictions on
the trade to impose ecolabeling as a non tariff barrier like the one
imposed on seafood and aqua cultured products. A review was done
on the available Ecolabeling and Green Certification Schemes
available at local, national and international levels for fisheries
including aquaculture and ornamental fish trade and to examine the
success and constraints faced by these schemes during its
implementation. The primary downside of certification is the
multiplicity of ecolabels and cost incurred by applicants for
certification, costs which may in turn be passed on to consumers.
The studies reveal serious inadequacies in a number of ecolabels
and cast doubt on their overall contribution to effective fisheries
management and sustainability. The paper also discusses the
inititive taken in India to develop guidelines for Green Certification
of Fresh water ornamental fishes.
Abstract: Discrete Wavelet Transform (DWT) has demonstrated
far superior to previous Discrete Cosine Transform (DCT) and
standard JPEG in natural as well as medical image compression. Due
to its localization properties both in special and transform domain,
the quantization error introduced in DWT does not propagate
globally as in DCT. Moreover, DWT is a global approach that avoids
block artifacts as in the JPEG. However, recent reports on natural
image compression have shown the superior performance of
contourlet transform, a new extension to the wavelet transform in two
dimensions using nonseparable and directional filter banks,
compared to DWT. It is mostly due to the optimality of contourlet in
representing the edges when they are smooth curves. In this work, we
investigate this fact for medical images, especially for CT images,
which has not been reported yet. To do that, we propose a
compression scheme in transform domain and compare the
performance of both DWT and contourlet transform in PSNR for
different compression ratios (CR) using this scheme. The results
obtained using different type of computed tomography images show
that the DWT has still good performance at lower CR but contourlet
transform performs better at higher CR.
Abstract: Extreme temperature of several stations in Malaysia is
modelled by fitting the monthly maximum to the Generalized
Extreme Value (GEV) distribution. The Mann-Kendall (MK) test
suggests a non-stationary model. Two models are considered for
stations with trend and the Likelihood Ratio test is used to determine
the best-fitting model. Results show that half of the stations favour a
model which is linear for the location parameters. The return level is
the level of events (maximum temperature) which is expected to be
exceeded once, on average, in a given number of years, is obtained.
Abstract: Malaria is a serious, acute and chronic relapsing
infection to humans. It is characterized by periodic attacks of chills,
fever, nausea, vomiting, back pain, increased sweating anemia,
splenomegaly (enlargement of the spleen) and often-fatal
complications.The malaria disease is caused by the multiplication of
protozoa parasite of the genus Plasmodium. Malaria in humans is due
to 4 types of malaria parasites such that Plasmodium falciparum,
Plasmodium vivax, Plasmodium malariae and Plasmodium ovale.
P.vivax malaria differs from P. falciparum malaria in that a person
suffering from P. vivax malaria can experience relapses of the
disease. Between the relapses, the malaria parasite will remain
dormant in the liver of the patient, leading to the patient being
classified as being in the dormant class. A mathematical model for
the transmission of P. vivax is developed in which the human
population is divided into four classes, the susceptible, the infected,
the dormant and the recovered. In this paper, we formulate the
dynamical model of P. vivax malaria to see the distribution of this
disease at the district level.
Abstract: Middle-gate is located in Hasankeyf, Batman dating
back to 1800 BC and is one of the important historical structures in
Turkey. The ancient structure has suffered major structural cracks
due to aging as well as lateral pressure of a cracked rock which is
predicted to be about 100 tons. The existing support system was
found to be inadequate to support the load especially after a recent
rock fall in the close vicinity. Concerns were increased since the
existing support system that is integral with a damaged and cracked
gate wall needed to be replaced by a new support system. The
replacement process must be carefully monitored by crackmeters and
control mechanisms should be integrated to prevent cracks to expand
while the same crack width needs to be maintained after the
operation. The control system and actions taken during the
intervention are explained in this paper.
Abstract: In non destructive testing by radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptability or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of thresholding methods must be done judiciously. In this paper, performance criteria are used to conduct a comparative study of thresholding methods based on gray level histogram, 2-D histogram and locally adaptive approach for weld defect extraction in radiographic images.
Abstract: Protein subchloroplast locations are correlated with its
functions. In contrast to the large amount of available protein
sequences, the information of their locations and functions is less
known. The experiment works for identification of protein locations
and functions are costly and time consuming. The accurate prediction
of protein subchloroplast locations can accelerate the study of
functions of proteins in chloroplast. This study proposes a Random
Forest based method, ChloroRF, to predict protein subchloroplast
locations using interpretable physicochemical properties. In addition
to high prediction accuracy, the ChloroRF is able to select important
physicochemical properties. The important physicochemical
properties are also analyzed to provide insights into the underlying
mechanism.
Abstract: Surveillance system is widely used in the traffic
monitoring. The deployment of cameras is moving toward a
ubiquitous camera (UbiCam) environment. In our previous study, a
novel service, called GPS-VT, was firstly proposed by incorporating
global positioning system (GPS) and visual tracking techniques for
the UbiCam environment. The first prototype is called GODTA
(GPS-based Moving Object Detection and Tracking Approach). For a
moving person carried GPS-enabled mobile device, he can be
tracking when he enters the field-of-view (FOV) of a camera
according to his real-time GPS coordinate. In this paper, GPS-VT
service is applied to the tracking of vehicles. The moving speed of a
vehicle is much faster than a person. It means that the time passing
through the FOV is much shorter than that of a person. Besides, the
update interval of GPS coordinate is once per second, it is
asynchronous with the frame rate of the real-time image. The above
asynchronous is worsen by the network transmission delay. These
factors are the main challenging to fulfill GPS-VT service on a
vehicle.In order to overcome the influence of the above factors, a
back-propagation neural network (BPNN) is used to predict the
possible lane before the vehicle enters the FOV of a camera. Then, a
template matching technique is used for the visual tracking of a target
vehicle. The experimental result shows that the target vehicle can be
located and tracking successfully. The success location rate of the
implemented prototype is higher than that of the previous GODTA.
Abstract: Least Development Countries (LDC) like
Bangladesh, whose 25% revenue earning is achieved from Textile
export, requires producing less defective textile for minimizing
production cost and time. Inspection processes done on these
industries are mostly manual and time consuming. To reduce error
on identifying fabric defects requires more automotive and
accurate inspection process. Considering this lacking, this research
implements a Textile Defect Recognizer which uses computer
vision methodology with the combination of multi-layer neural
networks to identify four classifications of textile defects. The
recognizer, suitable for LDC countries, identifies the fabric defects
within economical cost and produces less error prone inspection
system in real time. In order to generate input set for the neural
network, primarily the recognizer captures digital fabric images by
image acquisition device and converts the RGB images into binary
images by restoration process and local threshold techniques.
Later, the output of the processed image, the area of the faulty
portion, the number of objects of the image and the sharp factor of
the image, are feed backed as an input layer to the neural network
which uses back propagation algorithm to compute the weighted
factors and generates the desired classifications of defects as an
output.
Abstract: Due to the limited energy resources, energy efficient operation of sensor node is a key issue in wireless sensor networks. Clustering is an effective method to prolong the lifetime of energy constrained wireless sensor network. However, clustering in wireless sensor network faces several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network. In this paper, we propose a protocol supporting an energy efficient clustering, cluster head selection/rotation and data routing method to prolong the lifetime of sensor network. Simulation results demonstrate that the proposed protocol prolongs network lifetime due to the use of efficient clustering, cluster head selection/rotation and data routing.
Abstract: K-Means (KM) is considered one of the major
algorithms widely used in clustering. However, it still has some
problems, and one of them is in its initialization step where it is
normally done randomly. Another problem for KM is that it
converges to local minima. Genetic algorithms are one of the
evolutionary algorithms inspired from nature and utilized in the field
of clustering. In this paper, we propose two algorithms to solve the
initialization problem, Genetic Algorithm Initializes KM (GAIK) and
KM Initializes Genetic Algorithm (KIGA). To show the effectiveness
and efficiency of our algorithms, a comparative study was done
among GAIK, KIGA, Genetic-based Clustering Algorithm (GCA),
and FCM [19].
Abstract: In this paper, we propose improved versions of DVHop
algorithm as QDV-Hop algorithm and UDV-Hop algorithm for
better localization without the need for additional range measurement
hardware. The proposed algorithm focuses on third step of DV-Hop,
first error terms from estimated distances between unknown node and
anchor nodes is separated and then minimized. In the QDV-Hop
algorithm, quadratic programming is used to minimize the error to
obtain better localization. However, quadratic programming requires
a special optimization tool box that increases computational
complexity. On the other hand, UDV-Hop algorithm achieves
localization accuracy similar to that of QDV-Hop by solving
unconstrained optimization problem that results in solving a system
of linear equations without much increase in computational
complexity. Simulation results show that the performance of our
proposed schemes (QDV-Hop and UDV-Hop) is superior to DV-Hop
and DV-Hop based algorithms in all considered scenarios.