Abstract: This article describes Uruk, the virtual museum of
Iraq that we developed for visual exploration and retrieval of image
collections. The system largely exploits the loosely-structured
hierarchy of XML documents that provides a useful representation
method to store semi-structured or unstructured data, which does not
easily fit into existing database. The system offers users the
capability to mine and manage the XML-based image collections
through a web-based Graphical User Interface (GUI). Typically, at an
interactive session with the system, the user can browse a visual
structural summary of the XML database in order to select interesting
elements. Using this intermediate result, queries combining structure
and textual references can be composed and presented to the system.
After query evaluation, the full set of answers is presented in a visual
and structured way.
Abstract: The field research was carried out at the Látókép AGTC KIT research area of the University of Debrecen in Eastern-Hungary, on the area of the aeolain loess of the Hajdúság. We examined the effects of the sowing time on the phytopathogenic characteristics and yield production by applying various fertilizer treatments on two different sunflower genotypes (NK Ferti, PR64H42) in 2012 and 2013. We applied three different sowing times (early, optimal, late) and two different treatment levels of fungicides (control = no fungicides applied, double fungicide protection).
During our investigations, the studied cropyears were of different sowing time optimum in terms of yield amount (2012: early, 2013: average). By Pearson’s correlation analysis, we have found that delaying the sowing time pronouncedly decreased the extent of infection in both crop years (Diaporthe: r=0.663**, r=0.681**, Sclerotinia: r=0.465**, r=0.622**). The fungicide treatment not only decreased the extent of infection, but had yield increasing effect too (2012: r=0.498**, 2013: r=0.603**). In 2012, delaying of the sowing time increased (r=0.600**), but in 2013, it decreased (r= 0.356*) the yield amount.
Abstract: The purpose of this paper is to detect human in images.
This paper proposes a method for extracting human body feature descriptors consisting of projected edge component series. The feature descriptor can express appearances and shapes of human with local
and global distribution of edges. Our method evaluated with a linear SVM classifier on Daimler-Chrysler pedestrian dataset, and test with
various sub-region size. The result shows that the accuracy level of
proposed method similar to Histogram of Oriented Gradients(HOG)
feature descriptor and feature extraction process is simple and faster than existing methods.
Abstract: This paper reports the three-phase (gas + liquid +
hydrate) equilibrium pressure versus temperature data for a (O3 + O2 +
CO2 + H2O) system for developing the hydrate-based technology to
preserve ozone, a chemically unstable substance, for various
industrial, medical and consumer uses. These data cover the
temperature range from 272 K to 277 K, corresponding to pressures
from 1.6 MPa to 3.1 MPa, for each of the three different (O3 +
O2)-to-CO2 or O2-to-CO2 molar ratios in the gas phase, which are
approximately 4 : 6, 5 : 5, respectively. The mole fraction of ozone in
the gas phase was ~0.03 , which are the densest ozone fraction to
artificially form O3 containing hydrate ever reported in the literature.
Based on these data, the formation of hydrate containing
high-concentration ozone, as high as 1 mass %, will be expected.
Abstract: A parallel block method based on Backward
Differentiation Formulas (BDF) is developed for the parallel solution
of stiff Ordinary Differential Equations (ODEs). Most common
methods for solving stiff systems of ODEs are based on implicit
formulae and solved using Newton iteration which requires repeated
solution of systems of linear equations with coefficient matrix, I -
hβJ . Here, J is the Jacobian matrix of the problem. In this paper,
the matrix operations is paralleled in order to reduce the cost of the
iterations. Numerical results are given to compare the speedup and
efficiency of parallel algorithm and that of sequential algorithm.
Abstract: The study of the Andaman Sea can be studied by
using the oceanic model; therefore the grid covering the study area
should be generated. This research aims to generate grid covering
the Andaman Sea, situated between longitudes 90◦E to 101◦E and
latitudes 1◦N to 18◦N. A horizontal grid is an orthogonal curvilinear
with 87 × 217 grid points. The methods used in this study are
cubic spline and bilinear interpolations. The boundary grid points
are generated by spline interpolation while the interior grid points
have to be specified by bilinear interpolation method. A vertical grid
is sigma coordinate with 15 layers of water column.
Abstract: Explosive forming is one of the unconventional
techniques in which, most commonly, the water is used as the
pressure transmission medium. One of the newest methods in
explosive forming is gas detonation forming which uses a normal
shock wave derived of gas detonation, to form sheet metals. For this
purpose a detonation is developed from the reaction of H2+O2
mixture in a long cylindrical detonation tube. The detonation wave
goes through the detonation tube and acts as a blast load on the steel
blank and forms it. Experimental results are compared with a finite
element model; and the comparison of the experimental and
numerical results obtained from strain, thickness variation and
deformed geometry is carried out. Numerical and experimental
results showed approximately 75 – 90 % similarity in formability of
desired shape. Also optimum percent of gas mixture obtained when
we mix 68% H2 with 32% O2.
Abstract: Both the minimum energy consumption and
smoothness, which is quantified as a function of jerk, are generally
needed in many dynamic systems such as the automobile and the
pick-and-place robot manipulator that handles fragile equipments.
Nevertheless, many researchers come up with either solely
concerning on the minimum energy consumption or minimum jerk
trajectory. This research paper proposes a simple yet very interesting
when combining the minimum energy and jerk of indirect jerks
approaches in designing the time-dependent system yielding an
alternative optimal solution. Extremal solutions for the cost functions
of the minimum energy, the minimum jerk and combining them
together are found using the dynamic optimization methods together
with the numerical approximation. This is to allow us to simulate
and compare visually and statistically the time history of state inputs
employed by combining minimum energy and jerk designs. The
numerical solution of minimum direct jerk and energy problem are
exactly the same solution; however, the solutions from problem of
minimum energy yield the similar solution especially in term of
tendency.
Abstract: The Kumamoto area, Kyushu, Japan has 1,041km2 in
area and about 1milion in population. This area is a greatest area in Japan which depends on groundwater for all of drinking water. Quantity of this local groundwater use is about 200MCM during the
year. It is understood that the main recharging area of groundwater exist in the rice field zone which have high infiltrate height ahead of
100mm/ day of the irrigated water located in the middle area of the Shira-River Basin. However, by decrease of the paddy-rice planting
area by urbanization and an acreage reduction policy, the groundwater income and expenditure turned worse. Then Kumamoto city and four
companies expended financial support to increase recharging water to
underground by ponded water in the field from 2004.
In this paper, the author reported the situation of recovery of groundwater by recharge and estimates the efficiency of recharge by
statistical method.
Abstract: This paper describes the speed sensorless vector control method of the parallel connected induction motor drive fed by a single inverter. Speed and rotor fluxes of the induction motor are estimated by natural observer with load torque adaptation and adaptive rotor flux observer. The performance parameters speed and rotor fluxes are estimated from the measured terminal voltages and currents. Fourth order induction motor model is used and speed is considered as a parameter. The performance of the natural observer is similar to the conventional observer. The speed of an induction motor is estimated by MATLAB simulation under different speed and load conditions. Estimated values along with other measured states are used for closed loop control. The simulation results show that the natural observer is also effective for parallel connected induction motor drive.
Abstract: This paper describes an automatic algorithm to restore
the shape of three-dimensional (3D) left ventricle (LV) models created
from magnetic resonance imaging (MRI) data using a geometry-driven
optimization approach. Our basic premise is to restore the LV shape
such that the LV epicardial surface is smooth after the restoration. A
geometrical measure known as the Minimum Principle Curvature (κ2)
is used to assess the smoothness of the LV. This measure is used to
construct the objective function of a two-step optimization process.
The objective of the optimization is to achieve a smooth epicardial
shape by iterative in-plane translation of the MRI slices.
Quantitatively, this yields a minimum sum in terms of the magnitude
of κ
2, when κ2 is negative. A limited memory quasi-Newton algorithm,
L-BFGS-B, is used to solve the optimization problem. We tested our
algorithm on an in vitro theoretical LV model and 10 in vivo
patient-specific models which contain significant motion artifacts. The
results show that our method is able to automatically restore the shape
of LV models back to smoothness without altering the general shape of
the model. The magnitudes of in-plane translations are also consistent
with existing registration techniques and experimental findings.
Abstract: The aim of this research is to design a collaborative
framework that integrates risk analysis activities into the geospatial
database design (GDD) process. Risk analysis is rarely undertaken
iteratively as part of the present GDD methods in conformance to
requirement engineering (RE) guidelines and risk standards.
Accordingly, when risk analysis is performed during the GDD, some
foreseeable risks may be overlooked and not reach the output
specifications especially when user intentions are not systematically
collected. This may lead to ill-defined requirements and ultimately in
higher risks of geospatial data misuse. The adopted approach consists
of 1) reviewing risk analysis process within the scope of RE and
GDD, 2) analyzing the challenges of risk analysis within the context
of GDD, and 3) presenting the components of a risk-based
collaborative framework that improves the collection of the
intended/forbidden usages of the data and helps geo-IT experts to
discover implicit requirements and risks.
Abstract: In order to develop forest management strategies in
tropical forest in Malaysia, surveying the forest resources and
monitoring the forest area affected by logging activities is essential.
There are tremendous effort has been done in classification of land
cover related to forest resource management in this country as it is a
priority in all aspects of forest mapping using remote sensing and
related technology such as GIS. In fact classification process is a
compulsory step in any remote sensing research. Therefore, the main
objective of this paper is to assess classification accuracy of
classified forest map on Landsat TM data from difference number of
reference data (200 and 388 reference data). This comparison was
made through observation (200 reference data), and interpretation
and observation approaches (388 reference data). Five land cover
classes namely primary forest, logged over forest, water bodies, bare
land and agricultural crop/mixed horticultural can be identified by
the differences in spectral wavelength. Result showed that an overall
accuracy from 200 reference data was 83.5 % (kappa value
0.7502459; kappa variance 0.002871), which was considered
acceptable or good for optical data. However, when 200 reference
data was increased to 388 in the confusion matrix, the accuracy
slightly improved from 83.5% to 89.17%, with Kappa statistic
increased from 0.7502459 to 0.8026135, respectively. The accuracy
in this classification suggested that this strategy for the selection of
training area, interpretation approaches and number of reference data
used were importance to perform better classification result.
Abstract: Construction projects generally take place in
uncontrolled and dynamic environments where construction waste is
a serious environmental problem in many large cities. The total
amount of waste and carbon dioxide emissions from transportation
vehicles are still out of control due to increasing construction
projects, massive urban development projects and the lack of
effective tools for minimizing adverse environmental impacts in
construction. This research is about utilization of the integrated
applications of automated advanced tracking and data storage
technologies in the area of environmental management to monitor
and control adverse environmental impacts such as construction
waste and carbon dioxide emissions. Radio Frequency Identification
(RFID) integrated with the Global Position System (GPS) provides
an opportunity to uniquely identify materials, components, and
equipments and to locate and track them using minimal or no worker
input. The transmission of data to the central database will be carried
out with the help of Global System for Mobile Communications
(GSM).
Abstract: In this work, we developed the concept of
supercompression, i.e., compression above the compression standard
used. In this context, both compression rates are multiplied. In fact,
supercompression is based on super-resolution. That is to say,
supercompression is a data compression technique that superpose
spatial image compression on top of bit-per-pixel compression to
achieve very high compression ratios. If the compression ratio is very
high, then we use a convolutive mask inside decoder that restores the
edges, eliminating the blur. Finally, both, the encoder and the
complete decoder are implemented on General-Purpose computation
on Graphics Processing Units (GPGPU) cards. Specifically, the
mentio-ned mask is coded inside texture memory of a GPGPU.
Abstract: This paper is intended to assist anyone with some general technical experience, but perhaps limited specific knowledge of heat transfer equipment. A characteristic of heat exchanger design is the procedure of specifying a design, heat transfer area and pressure drops and checking whether the assumed design satisfies all requirements or not. The purpose of this paper is how to design the oil cooler (heat exchanger) especially for shell-and-tube heat exchanger which is the majority type of liquid-to-liquid heat exchanger. General design considerations and design procedure are also illustrated in this paper and a flow diagram is provided as an aid of design procedure. In design calculation, the MatLAB and AutoCAD software are used. Fundamental heat transfer concepts and complex relationships involved in such exchanger are also presented in this paper. The primary aim of this design is to obtain a high heat transfer rate without exceeding the allowable pressure drop. This computer program is highly useful to design the shell-and-tube type heat exchanger and to modify existing deign.
Abstract: In this paper, we propose a fully-utilized, block-based 2D DWT (discrete wavelet transform) architecture, which consists of four 1D DWT filters with two-channel QMF lattice structure. The proposed architecture requires about 2MN-3N registers to save the intermediate results for higher level decomposition, where M and N stand for the filter length and the row width of the image respectively. Furthermore, the proposed 2D DWT processes in horizontal and vertical directions simultaneously without an idle period, so that it computes the DWT for an N×N image in a period of N2(1-2-2J)/3. Compared to the existing approaches, the proposed architecture shows 100% of hardware utilization and high throughput rates. To mitigate the long critical path delay due to the cascaded lattices, we can apply the pipeline technique with four stages, while retaining 100% of hardware utilization. The proposed architecture can be applied in real-time video signal processing.
Abstract: Flow movement in unsaturated soil can be expressed
by a partial differential equation, named Richards equation. The
objective of this study is the finding of an appropriate implicit
numerical solution for head based Richards equation. Some of the
well known finite difference schemes (fully implicit, Crank Nicolson
and Runge-Kutta) have been utilized in this study. In addition, the
effects of different approximations of moisture capacity function,
convergence criteria and time stepping methods were evaluated. Two
different infiltration problems were solved to investigate the
performance of different schemes. These problems include of vertical
water flow in a wet and very dry soils. The numerical solutions of
two problems were compared using four evaluation criteria and the
results of comparisons showed that fully implicit scheme is better
than the other schemes. In addition, utilizing of standard chord slope
method for approximation of moisture capacity function, automatic
time stepping method and difference between two successive
iterations as convergence criterion in the fully implicit scheme can
lead to better and more reliable results for simulation of fluid
movement in different unsaturated soils.
Abstract: The competitive learning is an adaptive process in
which the neurons in a neural network gradually become sensitive to
different input pattern clusters. The basic idea behind the Kohonen-s
Self-Organizing Feature Maps (SOFM) is competitive learning.
SOFM can generate mappings from high-dimensional signal spaces
to lower dimensional topological structures. The main features of this
kind of mappings are topology preserving, feature mappings and
probability distribution approximation of input patterns. To overcome
some limitations of SOFM, e.g., a fixed number of neural units and a
topology of fixed dimensionality, Growing Self-Organizing Neural
Network (GSONN) can be used. GSONN can change its topological
structure during learning. It grows by learning and shrinks by
forgetting. To speed up the training and convergence, a new variant
of GSONN, twin growing cell structures (TGCS) is presented here.
This paper first gives an introduction to competitive learning, SOFM
and its variants. Then, we discuss some GSONN with fixed
dimensionality, which include growing cell structures, its variants
and the author-s model: TGCS. It is ended with some testing results
comparison and conclusions.
Abstract: Image enhancement is the most important challenging preprocessing for almost all applications of Image Processing. By now, various methods such as Median filter, α-trimmed mean filter, etc. have been suggested. It was proved that the α-trimmed mean filter is the modification of median and mean filters. On the other hand, ε-filters have shown excellent performance in suppressing noise. In spite of their simplicity, they achieve good results. However, conventional ε-filter is based on moving average. In this paper, we suggested a new ε-filter which utilizes α-trimmed mean. We argue that this new method gives better outcomes compared to previous ones and the experimental results confirmed this claim.