Abstract: Seasonal variability of nutrients concentration in the Baltic Sea using the 3D ecosystem numerical model 3D-CEMBS has been investigated. Additionally this study shows horizontal and vertical distribution of nutrients in the Baltic Sea. Model domain is an extended Baltic Sea area divided into 600x640 horizontal grid cells. Aside from standard hydrodynamic parameters 3D-CEMBS produces modeled ecological variables such as: three types of phytoplankton, two detrital classes, dissolved oxygen and the nutrients (nitrate, ammonium, phosphate and silicate). The presented model allows prediction of parameters that describe distribution of nutrients concentration and phytoplankton biomass. 3D-CEMBS can be used to study the effect of different hydrodynamic and biogeochemical processes on distributions of these variables in a larger scale.
Abstract: The world wide web coupled with the ever-increasing
sophistication of online technologies and software applications puts
greater emphasis on the need of even more sophisticated and
consistent quality requirements modeling than traditional software
applications. Web sites and Web applications (WebApps) are
becoming more information driven and content-oriented raising the
concern about their information quality (InQ). The consistent and
consolidated modeling of InQ requirements for WebApps at different
stages of the life cycle still poses a challenge. This paper proposes an
approach to specify InQ requirements for WebApps by reusing and
extending the ISO 25012:2008(E) data quality model. We also
discuss learnability aspect of information quality for the WebApps.
The proposed ISO 25012 based InQ framework is a step towards a
standardized approach to evaluate WebApps InQ.
Abstract: The identification and classification of weeds are of
major technical and economical importance in the agricultural
industry. To automate these activities, like in shape, color and
texture, weed control system is feasible. The goal of this paper is to
build a real-time, machine vision weed control system that can detect
weed locations. In order to accomplish this objective, a real-time
robotic system is developed to identify and locate outdoor plants
using machine vision technology and pattern recognition. The
algorithm is developed to classify images into broad and narrow class
for real-time selective herbicide application. The developed
algorithm has been tested on weeds at various locations, which have
shown that the algorithm to be very effectiveness in weed
identification. Further the results show a very reliable performance
on weeds under varying field conditions. The analysis of the results
shows over 90 percent classification accuracy over 140 sample
images (broad and narrow) with 70 samples from each category of
weeds.
Abstract: The incorporation of computational fluid dynamics in the design of modern hydraulic turbines appears to be necessary in order to improve their efficiency and cost-effectiveness beyond the traditional design practices. A numerical optimization methodology is developed and applied in the present work to a Turgo water turbine. The fluid is simulated by a Lagrangian mesh-free approach that can provide detailed information on the energy transfer and enhance the understanding of the complex, unsteady flow field, at very small computing cost. The runner blades are initially shaped according to hydrodynamics theory, and parameterized using Bezier polynomials and interpolation techniques. The use of a limited number of free design variables allows for various modifications of the standard blade shape, while stochastic optimization using evolutionary algorithms is implemented to find the best blade that maximizes the attainable hydraulic efficiency of the runner. The obtained optimal runner design achieves considerably higher efficiency than the standard one, and its numerically predicted performance is comparable to a real Turgo turbine, verifying the reliability and the prospects of the new methodology.
Abstract: Cloud Computing is an approach that provides computation and storage services on-demand to clients over the network, independent of device and location. In the last few years, cloud computing became a trend in information technology with many companies that transfer their business processes and applications in the cloud. Cloud computing with service oriented architecture has contributed to rapid development of Geographic Information Systems. Open Geospatial Consortium with its standards provides the interfaces for hosted spatial data and GIS functionality to integrated GIS applications. Furthermore, with the enormous processing power, clouds provide efficient environment for data intensive applications that can be performed efficiently, with higher precision, and greater reliability. This paper presents our work on the geospatial data services within the cloud computing environment and its technology. A cloud computing environment with the strengths and weaknesses of the geographic information system will be introduced. The OGC standards that solve our application interoperability are highlighted. Finally, we outline our system architecture with utilities for requesting and invoking our developed data intensive applications as a web service.
Abstract: Censored Production Rule is an extension of standard
production rule, which is concerned with problems of reasoning with
incomplete information, subject to resource constraints and problem
of reasoning efficiently with exceptions. A CPR has a form: IF A
(Condition) THEN B (Action) UNLESS C (Censor), Where C is the
exception condition. Fuzzy CPR are obtained by augmenting
ordinary fuzzy production rule “If X is A then Y is B with an
exception condition and are written in the form “If X is A then Y is B
Unless Z is C. Such rules are employed in situation in which the
fuzzy conditional statement “If X is A then Y is B" holds frequently
and the exception condition “Z is C" holds rarely. Thus “If X is A
then Y is B" part of the fuzzy CPR express important information
while the unless part acts only as a switch that changes the polarity of
“Y is B" to “Y is not B" when the assertion “Z is C" holds. The
proposed approach is an attempt to discover fuzzy censored
production rules from set of discovered fuzzy if then rules in the
form:
A(X)  B(Y) || C(Z).
Abstract: The purpose of this study is comparing and analysing
of the financial characteristics for development methods of the urban development project in the established area, focusing on the
multi-level replotting.
Analysis showed that the type of the lowest expenditure was
'combination type of group-land and multi-level replotting' and the type of the highest profitability was 'multi-level replotting type'. But
'multi-level replotting type' has still risk of amount of cost for the additional architecture. In addition, we subdivided standard amount
for liquidation of replotting and analysed income-expenditure flow.
Analysis showed that both of 'multi-level replotting type' and 'combination type of group-land and multi-level replotting' improved
profitability of project and property change ratio. However, when the
standard was under a certain amount, amount of original property for the replotting was increased exponentially, and profitability of project.
Abstract: In this paper, three dimensional flow characteristic was
presented by a revision of an impeller of an axial turbo fan for
improving the airflow rate and the static pressure. TO consider an
incompressible steady three-dimensional flow, the RANS equations
are used as the governing equations, and the standard k-ε turbulence
model is chosen. The pitch angles of 44°, 54°, 59°, and 64° are
implemented for the numerical model. The numerical results show that
airflow rates of each pitch angle are 1,175 CMH, 1,270 CMH, 1,340
CMH, and 800 CMH, respectively. The difference of the static
pressure at impeller inlet and outlet are 120 Pa, 214 Pa, 242 Pa, and 60
Pa according to respective pitch angles. It means that the 59° of the
impeller pitch angle is optimal to improve the airflow rate and the
static pressure.
Abstract: A new approach for protection of power transformer is
presented using a time-frequency transform known as Wavelet transform.
Different operating conditions such as inrush, Normal, load,
External fault and internal fault current are sampled and processed
to obtain wavelet coefficients. Different Operating conditions provide
variation in wavelet coefficients. Features like energy and Standard
deviation are calculated using Parsevals theorem. These features
are used as inputs to PNN (Probabilistic neural network) for fault
classification. The proposed algorithm provides more accurate results
even in the presence of noise inputs and accurately identifies inrush
and fault currents. Overall classification accuracy of the proposed
method is found to be 96.45%. Simulation of the fault (with and
without noise) was done using MATLAB AND SIMULINK software
taking 2 cycles of data window (40 m sec) containing 800 samples.
The algorithm was evaluated by using 10 % Gaussian white noise.
Abstract: Telemedicine is brought to life by contemporary changes of our world and summarizes the entire range of services that are at the crossroad of traditional healthcare and information technology. It is believed that eHealth can help in solving critical issues of rising costs, care for ageing and housebound population, staff shortage. It is a feasible tool to provide routine as well as specialized health service as it has the potential to improve both the access to and the standard of care. eHealth is no more an optional choice. It has already made quite a way but it still remains a fantastic challenge for the future requiring cooperation and coordination at all possible levels. The strategic objectives of this paper are: 1. To start with an attempt to clarify the mass of terms used nowadays; 2. To answer the question “Who needs eHealth"; 3. To focus on the necessity of bridging telemedicine and medical (health) informatics as well as on the dual relationship between them; as well as 4. To underline the need of networking in understanding, developing and implementing eHealth.
Abstract: A laboratory study on the influence of compactive
effort on expansive black cotton specimens treated with up to 8%
ordinary Portland cement (OPC) admixed with up to 8% bagasse ash
(BA) by dry weight of soil and compacted using the energies of the
standard Proctor (SP), West African Standard (WAS) or
“intermediate” and modified Proctor (MP) were undertaken. The
expansive black cotton soil was classified as A-7-6 (16) or CL using
the American Association of Highway and Transportation Officials
(AASHTO) and Unified Soil Classification System (USCS),
respectively. The 7day unconfined compressive strength (UCS)
values of the natural soil for SP, WAS and MP compactive efforts are
286, 401 and 515kN/m2 respectively, while peak values of 1019,
1328 and 1420kN/m2 recorded at 8% OPC/ 6% BA, 8% OPC/ 2% BA
and 6% OPC/ 4% BA treatments, respectively were less than the
UCS value of 1710kN/m2 conventionally used as criterion for
adequate cement stabilization. The soaked California bearing ratio
(CBR) values of the OPC/BA stabilized soil increased with higher
energy level from 2, 4 and 10% for the natural soil to Peak values of
55, 18 and 8% were recorded at 8% OPC/4% BA 8% OPC/2% BA
and 8% OPC/4% BA, treatments when SP, WAS and MP compactive
effort were used, respectively. The durability of specimens was
determined by immersion in water. Soils treatment at 8% OPC/ 4%
BA blend gave a value of 50% resistance to loss in strength value
which is acceptable because of the harsh test condition of 7 days
soaking period specimens were subjected instead of the 4 days
soaking period that specified a minimum resistance to loss in strength
of 80%. Finally An optimal blend of is 8% OPC/ 4% BA is
recommended for treatment of expansive black cotton soil for use as
a sub-base material.
Abstract: The growing interest in the issue of intangible assets not only in the scientific community but also in some professional bodies internationally can be explained by several points of view. From the business perspective, enterprises are increasingly motivated by external and internal forces to measure and proactively manage their intangibles. With respect to the issue of intangibles, goodwill has been debated in many countries throughout the world. Despite the numerous efforts and the existence of international accounting standards there is not yet a common accepted accounting treatment for goodwill. This study attempts on the one hand to impress the accounting treatment of goodwill internationally, on the other hand analyses the major subjects in relation to the accounting treatment of goodwill in Greece, since 2005, year where the international accounting standards have been in use for the Greek listed companies. The results indicate that the accounting treatment for the goodwill in Greece, despite the effort for accounting harmonization in Europe from 2005, sustains many differences especially for the no listed companies.
Abstract: A low bit rate still image compression scheme by
compressing the indices of Vector Quantization (VQ) and generating
residual codebook is proposed. The indices of VQ are compressed by
exploiting correlation among image blocks, which reduces the bit per
index. A residual codebook similar to VQ codebook is generated that
represents the distortion produced in VQ. Using this residual
codebook the distortion in the reconstructed image is removed,
thereby increasing the image quality. Our scheme combines these two
methods. Experimental results on standard image Lena show that our
scheme can give a reconstructed image with a PSNR value of 31.6 db
at 0.396 bits per pixel. Our scheme is also faster than the existing VQ
variants.
Abstract: The aim of this paper is to rank the impact of Object
Oriented(OO) metrics in fault prediction modeling using Artificial
Neural Networks(ANNs). Past studies on empirical validation of
object oriented metrics as fault predictors using ANNs have focused
on the predictive quality of neural networks versus standard
statistical techniques. In this empirical study we turn our attention to
the capability of ANNs in ranking the impact of these explanatory
metrics on fault proneness. In ANNs data analysis approach, there is
no clear method of ranking the impact of individual metrics. Five
ANN based techniques are studied which rank object oriented
metrics in predicting fault proneness of classes. These techniques are
i) overall connection weights method ii) Garson-s method iii) The
partial derivatives methods iv) The Input Perturb method v) the
classical stepwise methods. We develop and evaluate different
prediction models based on the ranking of the metrics by the
individual techniques. The models based on overall connection
weights and partial derivatives methods have been found to be most
accurate.
Abstract: The class of geometric deformable models, so-called
level sets, has brought tremendous impact to medical imagery. In
this paper we present yet another application of level sets to medical
imaging. The method we give here will in a way modify the speed
term in the standard level sets equation of motion. To do so we
build a potential based on the distance and the gradient of the
image we study. In turn the potential gives rise to the force field:
F~F(x, y) = P
∀(p,q)∈I
((x, y) - (p, q)) |ÔêçI(p,q)|
|(x,y)-(p,q)|
2 . The direction
and intensity of the force field at each point will determine the
direction of the contour-s evolution. The images we used to test
our method were produced by the Univesit'e de Sherbrooke-s PET
scanners.
Abstract: The seismic rehabilitation designs of two reinforced
concrete school buildings, representative of a wide stock of similar
edifices designed under earlier editions of the Italian Technical
Standards, are presented in this paper. The mutual retrofit solution
elaborated for the two buildings consists in the incorporation of a
dissipative bracing system including pressurized fluid viscous springdampers
as passive protective devices. The mechanical parameters,
layouts and locations selected for the constituting elements of the
system; the architectural renovation projects developed to properly
incorporate the structural interventions and improve the appearance
of the buildings; highlights of the installation works already
completed in one of the two structures; and a synthesis of the
performance assessment analyses carried out in original and
rehabilitated conditions, are illustrated. The results of the analyses
show a remarkable enhancement of the seismic response capacities of
both structures. This allows reaching the high performance objectives
postulated in the retrofit designs with much lower costs and
architectural intrusion as compared to traditional rehabilitation
interventions designed for the same objectives.
Abstract: In the recent years, high dynamic range imaging has
gain popularity with the advancement in digital photography. In this
contribution we present a subjective evaluation of various tone
production and tone mapping techniques by a number of participants.
Firstly, standard HDR images were used and the participants were
asked to rate them based on a given rating scheme. After that, the
participant was asked to rate HDR image generated using linear and
nonlinear combination approach of multiple exposure images. The
experimental results showed that linearly generated HDR images
have better visualization than the nonlinear combined ones. In
addition, Reinhard et al. and the exponential tone mapping operators
have shown better results compared to logarithmic and the Garrett et
al. tone mapping operators.
Abstract: Effectiveness of Artificial Neural Networks (ANN)
and Support Vector Machines (SVM) classifiers for fault diagnosis of
rolling element bearings are presented in this paper. The
characteristic features of vibration signals of rotating driveline that
was run in its normal condition and with faults introduced were used
as input to ANN and SVM classifiers. Simple statistical features such
as standard deviation, skewness, kurtosis etc. of the time-domain
vibration signal segments along with peaks of the signal and peak of
power spectral density (PSD) are used as features to input the ANN
and SVM classifier. The effect of preprocessing of the vibration
signal by Discreet Wavelet Transform (DWT) prior to feature
extraction is also studied. It is shown from the experimental results
that the performance of SVM classifier in identification of bearing
condition is better then ANN and pre-processing of vibration signal
by DWT enhances the effectiveness of both ANN and SVM classifier
Abstract: Antiseismic property of telecommunication equipment
is very important for the grasp of the damage and the restoration after
earthquake. Telecommunication business operators are regulating
seismic standard for their equipments. These standards are organized
to simulate the real seismic situations and usually define the minimum
value of first natural frequency of the equipments or the allowable
maximum displacement of top of the equipments relative to bottom.
Using the finite element analysis, natural frequency can be obtained
with high accuracy but the relative displacement of top of the
equipments is difficult to predict accurately using the analysis.
Furthermore, in the case of simulating the equipments with access
floor, predicting the relative displacement of top of the equipments
become more difficult.
In this study, using enormous experimental datum, an empirical
formula is suggested to forecast the relative displacement of top of the
equipments. Also it can be known that which physical quantities are
related with the relative displacement.
Abstract: The aim of this study was to investigate the pregnancy
outcomes of teenage mothers at DanKhunThot hospital, Nakhon
Ratchasima, Thailand. A retrospective descriptive study was
conducted in 573 of teenage pregnant from charts reviewed from 1st
October 2010-31st March, 2012. Data were analyzed by frequency
distribution, mean and Standard Deviation.
The results shown several problems and negatives outcomes of
pregnancy in teenager such as not attended prenatal care, Low birth
weight infants, death fetus in utero and other complications. The
results of this study can be utilized in the development of prenatal,
perinatal and post natal care services, especially in DanKhunthot
Hospital contexts. Moreover, the results were present to the District
Health Care committees in order to enhance health care service
system for teenage pregnancy of DanKhunthot District in further.