Abstract: Psoriasis is a widespread skin disease affecting up to 2% population with plaque psoriasis accounting to about 80%. It can be identified as a red lesion and for the higher severity the lesion is usually covered with rough scale. Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. Surface roughness of lesion can be used as a scaliness feature, since existing scale on lesion surface makes the lesion rougher. The dermatologist usually assesses the severity through their tactile sense, therefore direct contact between doctor and patient is required. The problem is the doctor may not assess the lesion objectively. In this paper, a digital image analysis technique is developed to objectively determine the scaliness of the psoriasis lesion and provide the PASI scaliness score. Psoriasis lesion is modelled by a rough surface. The rough surface is created by superimposing a smooth average (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate average surface followed by a subtraction between rough and average surface to give elevation surface (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 444 lesion models. From roughness validation result, only 6 models can not be accepted (percentage error is greater than 10%). These errors occur due the scanned image quality. Roughness algorithm is validated for roughness measurement on abrasive papers at flat surface. The Pearson-s correlation coefficient of grade value (G) of abrasive paper and Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.
Abstract: The proper selection of the AC-side passive filter
interconnecting the voltage source converter to the power supply is
essential to obtain satisfactory performances of an active power filter
system. The use of the LCL-type filter has the advantage of
eliminating the high frequency switching harmonics in the current
injected into the power supply. This paper is mainly focused on
analyzing the influence of the interface filter parameters on the active
filtering performances. Some design aspects are pointed out. Thus,
the design of the AC interface filter starts from transfer functions by
imposing the filter performance which refers to the significant current
attenuation of the switching harmonics without affecting the
harmonics to be compensated. A Matlab/Simulink model of the entire
active filtering system including a concrete nonlinear load has been
developed to examine the system performances. It is shown that a
gamma LC filter could accomplish the attenuation requirement of the
current provided by converter. Moreover, the existence of an optimal
value of the grid-side inductance which minimizes the total harmonic
distortion factor of the power supply current is pointed out.
Nevertheless, a small converter-side inductance and a damping
resistance in series with the filter capacitance are absolutely needed
in order to keep the ripple and oscillations of the current at the
converter side within acceptable limits. The effect of change in the
LCL-filter parameters is evaluated. It is concluded that good active
filtering performances can be achieved with small values of the
capacitance and converter-side inductance.
Abstract: Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge financial and other losses. It is therefore necessary that critical loads be supplied with electricity of acceptable quality. Recognition of the presence of any disturbance and classifying any existing disturbance into a particular type is the first step in combating the problem. In this work two classes of AI methods for Power quality data mining are studied: Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs). We show that SVMs are superior to ANNs in two critical respects: SVMs train and run an order of magnitude faster; and SVMs give higher classification accuracy.
Abstract: Many studies have been conducted for derivation of
attenuation relationships worldwide, however few relationships have
been developed to use for the seismic region of Iranian plateau and
only few of these studies have been conducted for derivation of
attenuation relationships for parameters such as uniform duration.
Uniform duration is the total time during which the acceleration is
larger than a given threshold value (default is 5% of PGA). In this
study, the database was same as that used previously by Ghodrati
Amiri et al. (2007) with same correction methods for earthquake
records in Iran. However in this study, records from earthquakes with
MS< 4.0 were excluded from this database, each record has
individually filtered afterward, and therefore the dataset has been
expanded. These new set of attenuation relationships for Iran are
derived based on tectonic conditions with soil classification into rock
and soil. Earthquake parameters were chosen to be
hypocentral distance and magnitude in order to make it easier to use
the relationships for seismic hazard analysis. Tehran is the capital
city of Iran wit ha large number of important structures. In this study,
a probabilistic approach has been utilized for seismic hazard
assessment of this city. The resulting uniform duration against return
period diagrams are suggested to be used in any projects in the area.
Abstract: Understanding road features such as lanes, the color
of lanes, and sidewalks in a live video captured from a moving
vehicle is essential to build video-based navigation systems. In this
paper, we present a novel idea to understand the road features using
support vector machines. Various feature vectors including color
components of road markings and the difference between two
regions, i.e., chosen AOIs, and so on are fed into SVM, deciding
colors of lanes and sidewalks robustly. Experimental results are
provided to show the robustness of the proposed idea.
Abstract: This paper studies, maps and explains the interactions between downloaders and uploaders pertaining to the Internet film piracy. This study also covers several motivational factors that influence users to upload or download movies, and thus to engage in film piracy over the Internet. The essay also proposes a model that describes user behavior including their relationships and influences. Moreover, proposed theoretical interactions and motivational factors are applied to the real world scenario, using examples of a data storage webpage server Ulozto.net and webpage Piratebay.org gathering information about downloadable BitTorrents. Moreover, the theory is further supported by description of behavior of real Internet uploaders.
Abstract: A nonlinear optimal controller with a fuzzy gain
scheduler has been designed and applied to a Line-Of-Sight (LOS)
stabilization system. Use of Linear Quadratic Regulator (LQR)
theory is an optimal and simple manner of solving many control
engineering problems. However, this method cannot be utilized
directly for multigimbal LOS systems since they are nonlinear in
nature. To adapt LQ controllers to nonlinear systems at least a
linearization of the model plant is required. When the linearized
model is only valid within the vicinity of an operating point a gain
scheduler is required. Therefore, a Takagi-Sugeno Fuzzy Inference
System gain scheduler has been implemented, which keeps the
asymptotic stability performance provided by the optimal feedback
gain approach. The simulation results illustrate that the proposed
controller is capable of overcoming disturbances and maintaining a
satisfactory tracking performance.
Abstract: A portable sensor for the analysis of phosphate in
aqueous samples has been developed. The sensor incorporates
microfluidic technology, colorimetric detection, and wireless
communications into a compact and rugged portable device. The
detection method used is the molybdenum yellow method, in which a
phosphate-containing sample is mixed with a reagent containing
ammonium metavanadate and ammonium molybdate in an acidic
medium. A yellow-coloured compound is generated and the
absorption of this compound is measured using a light emitting diode
(LED) light source and a photodiode detector. The absorption is
directly proportional to the phosphate concentration in the original
sample. In this paper we describe the application of this phosphate
sensor to the analysis of wastewater at a municipal wastewater
treatment plant in Co. Kildare, Ireland.
Abstract: Based on a long-term vegetation index dataset of NDVI and meteorological data from 68 meteorological stations in the Qinghai-Tibet plateau and their relations with major climate factors were analyzed. The results show the following: 1) The linear trends of temperature in the Qinghai-Tibet plateau indicate that the temperature in the plateau generally increased, but it rose faster in the last 20 years. 2) The most significant NDVI increase occurred in the eastern and southern plateau. However, the western and northern plateau demonstrate a decreasing trend. 3) There is a significant positive linear correlation between NDVI and temperature and a negative correlation between NDVI and mean wind speed. However, no significant statistical relationship was found between NDVI and relative humidity, precipitation or sunshine duration.4) The changes in NDVI for the plateau are driven by temperature-precipitation, but for the desert and forest areas, the relation changes to precipitation-temperature-wind velocity and wind velocity-temperature-precipitation.
Abstract: The rate of production of main products of the Fischer-Tropsch reactions over Fe/HZSM5 bifunctional catalyst in a fixed bed reactor is investigated at a broad range of temperature, pressure, space velocity, H2/CO feed molar ratio and CO2, CH4 and water flow rates. Model discrimination and parameter estimation were performed according to the integral method of kinetic analysis. Due to lack of mechanism development for Fisher – Tropsch Synthesis on bifunctional catalysts, 26 different models were tested and the best model is selected. Comprehensive one and two dimensional heterogeneous reactor models are developed to simulate the performance of fixed-bed Fischer – Tropsch reactors. To reduce computational time for optimization purposes, an Artificial Feed Forward Neural Network (AFFNN) has been used to describe intra particle mass and heat transfer diffusion in the catalyst pellet. It is seen that products' reaction rates have direct relation with H2 partial pressure and reverse relation with CO partial pressure. The results show that the hybrid model has good agreement with rigorous mechanistic model, favoring that the hybrid model is about 25-30 times faster.
Abstract: In the crack growth analysis, the Stress Intensity
Factor (SIF) is a fundamental prerequisite. In the present study, the
mode I stress intensity factor (SIF) of three-dimensional penny-
Shaped crack is obtained in an isotropic elastic cylindrical medium
with arbitrary dimensions under arbitrary loading at the top of the
cylinder, by the semi-analytical method based on the Rayleigh-Ritz
method. This method that is based on minimizing the potential
energy amount of the whole of the system, gives a very close results
to the previous studies. Defining the displacements (elastic fields) by
hypothetical functions in a defined coordinate system is the base of
this research. So for creating the singularity conditions at the tip of
the crack the appropriate terms should be found.
Abstract: all of religions free towards society in Kazakhstan. Considering that Islam is more widespread religion in the region, Islamic industry is developing sector of Economy. There are some new sectors of Halal (Islamic) industry, which have importance for state developing on the whole. One of the youngest sectors of Halal industry is Islamic tourism, which became an object of disputes and led to dilemma, such as Islamic tourism is a result of a Religious revival and Islamic tourism is a new trend of Tourism. The paper was written under the research project “Islam in modern Kazakhstan: the nature and outcome of the religious revival".
Abstract: The daily increase of organic waste materials resulting
from different activities in the country is one of the main factors for
the pollution of environment. Today, with regard to the low level of
the output of using traditional methods, the high cost of disposal
waste materials and environmental pollutions, the use of modern
methods such as anaerobic digestion for the production of biogas has
been prevailing. The collected biogas from the process of anaerobic
digestion, as a renewable energy source similar to natural gas but
with a less methane and heating value is usable. Today, with the help
of technologies of filtration and proper preparation, access to biogas
with features fully similar to natural gas has become possible. At
present biogas is one of the main sources of supplying electrical and
thermal energy and also an appropriate option to be used in four
stroke engine, diesel engine, sterling engine, gas turbine, gas micro
turbine and fuel cell to produce electricity. The use of biogas for
different reasons which returns to socio-economic and environmental
advantages has been noticed in CHP for the production of energy in
the world. The production of biogas from the technology of anaerobic
digestion and its application in CHP power plants in Iran can not only
supply part of the energy demands in the country, but it can
materialize moving in line with the sustainable development. In this
article, the necessity of the development of CHP plants with biogas
fuels in the country will be dealt based on studies performed from the
economic, environmental and social aspects. Also to prove the
importance of the establishment of these kinds of power plants from
the economic point of view, necessary calculations has been done as
a case study for a CHP power plant with a biogas fuel.
Abstract: In recent years, a new numerical method has been
developed, the extended finite element method (X-FEM). The
objective of this work is to exploit the (X-FEM) for the treatment of
the fracture mechanics problems on 3D geometries, where we
showed the ability of this method to simulate the fatigue crack
growth into two cases: edge and central crack. In the results we
compared the six first natural frequencies of mode shapes uncracking
with the cracking initiation in the structure, and showed the stress
intensity factor (SIF) evolution function as crack size propagation
into structure, the analytical validation of (SIF) is presented. For to
evidence the aspects of this method, all result is compared between
FEA and X-FEM.
Abstract: In this paper, we propose a texture feature-based
language identification using wavelet-domain BDIP (block difference
of inverse probabilities) and BVLC (block variance of local
correlation coefficients) features and FFT (fast Fourier transform)
feature. In the proposed method, wavelet subbands are first obtained
by wavelet transform from a test image and denoised by Donoho-s
soft-thresholding. BDIP and BVLC operators are next applied to the
wavelet subbands. FFT blocks are also obtained by 2D (twodimensional)
FFT from the blocks into which the test image is
partitioned. Some significant FFT coefficients in each block are
selected and magnitude operator is applied to them. Moments for each
subband of BDIP and BVLC and for each magnitude of significant
FFT coefficients are then computed and fused into a feature vector. In
classification, a stabilized Bayesian classifier, which adopts variance
thresholding, searches the training feature vector most similar to the
test feature vector. Experimental results show that the proposed
method with the three operations yields excellent language
identification even with rather low feature dimension.
Abstract: The majority of existing predictors for time series are
model-dependent and therefore require some prior knowledge for the
identification of complex systems, usually involving system
identification, extensive training, or online adaptation in the case of
time-varying systems. Additionally, since a time series is usually
generated by complex processes such as the stock market or other
chaotic systems, identification, modeling or the online updating of
parameters can be problematic. In this paper a model-free predictor
(MFP) for a time series produced by an unknown nonlinear system or
process is derived using tracking theory. An identical derivation of the
MFP using the property of the Newton form of the interpolating
polynomial is also presented. The MFP is able to accurately predict
future values of a time series, is stable, has few tuning parameters and
is desirable for engineering applications due to its simplicity, fast
prediction speed and extremely low computational load. The
performance of the proposed MFP is demonstrated using the
prediction of the Dow Jones Industrial Average stock index.
Abstract: The purpose of this investigation is to relate the rain
power and the overland flow power to soil erodibility to assess the
effects of both parameters on soil erosion using variable rainfall
intensity on remoulded agricultural soil. Six rainfall intensities were
used to simulate the natural rainfall and are as follows: 12.4mm/h,
20.3mm/h, 28.6mm/h, 52mm/h, 73.5mm/h and 103mm/h. The results
have shown that the relationship between overland flow power and
rain power is best represented by a linear function (R2=0.99). As
regards the relationships between soil erodibility factor and rain and
overland flow powers, the evolution of both parameters with the
erodibility factor follow a polynomial function with high coefficient
of determination. From their coefficients of determination (R2=0.95)
for rain power and (R2=0.96) for overland flow power, we can
conclude that the flow has more power to detach particles than rain.
This could be explained by the fact that the presence of particles,
already detached by rain and transported by the flow, give the flow
more weight and then contribute to the detachment of particles by
collision.
Abstract: Knowledge capabilities are increasingly important for
the innovative technology enterprises to enhance the business
performance in terms of product competitiveness, innovation and
sales. Recognition of the company capability by auditing allows them
to further pursue advancement, strategic planning and hence gain
competitive advantages. This paper attempts to develop an
Organizations- Knowledge Capabilities Assessment (OKCA) method
to assess the knowledge capabilities of technology companies. The
OKCA is a questionnaire-based assessment tool which has been
developed to uncover the impact of various knowledge capabilities on
different organizational performance. The collected data is then
analyzed to find out the crucial elements for different technological
companies. Based on the results, innovative technology enterprises are
able to recognize the direction for further improvement on business
performance and future development plan. External environmental
factors affecting organization performance can be found through the
further analysis of some selected reference companies.
Abstract: 20 years of dentistry was a period of transition from
communist to market economy but Romanian doctors have
insufficient management knowledge. Recently, the need for modern
management has increased due to technologies and superior materials
appearance, as patient-s demands.
Research goal is to increase efficiency by evaluating dental
medical office cost categories in real pricing procedures.
Empirical research is based on guided study that includes
information about the association between categories of cost
perception and therapeutic procedures commonly used in dental
offices.
Due to the obtained results to identify all the labours that make up
a settled procedure costs were determined for each procedure.
Financial evaluation software was created with the main functions:
introducing and maintaining patient records, treatment and
appointments made, procedures cost and monitoring office
productivity.
We believe that the study results can significantly improve the
financial management of dental offices, increasing the effectiveness
and quality of services.
Abstract: The innovative intelligent fuzzy weighted input
estimation method (FWIEM) can be applied to the inverse heat
transfer conduction problem (IHCP) to estimate the unknown
time-varying heat flux of the multilayer materials as presented in this
paper. The feasibility of this method can be verified by adopting the
temperature measurement experiment. The experiment modular may
be designed by using the copper sample which is stacked up 4
aluminum samples with different thicknesses. Furthermore, the
bottoms of copper samples are heated by applying the standard heat
source, and the temperatures on the tops of aluminum are measured by
using the thermocouples. The temperature measurements are then
regarded as the inputs into the presented method to estimate the heat
flux in the bottoms of copper samples. The influence on the estimation
caused by the temperature measurement of the sample with different
thickness, the processing noise covariance Q, the weighting factor γ ,
the sampling time interval Δt , and the space discrete interval Δx ,
will be investigated by utilizing the experiment verification. The
results show that this method is efficient and robust to estimate the
unknown time-varying heat input of the multilayer materials.