Abstract: The edges of low contrast images are not clearly
distinguishable to human eye. It is difficult to find the edges and
boundaries in it. The present work encompasses a new approach for
low contrast images. The Chebyshev polynomial based fractional
order filter has been used for filtering operation on an image. The
preprocessing has been performed by this filter on the input image.
Laplacian of Gaussian method has been applied on preprocessed
image for edge detection. The algorithm has been tested on two test
images.
Abstract: Standard processes, similar and limited production
lines, the production of high direct costs will be more accurate than
the use of parts of the traditional cost systems in the literature.
However, direct costs, overhead expenses, in turn, decrease the
burden of increasingly sophisticated production facilities, a situation
that led the researchers to look for the cost of traditional systems of
alternative techniques. Variety cost management approaches for
example Total quality management (TQM), just-in-time (JIT),
benchmarking, kaizen costing, targeting cost, life cycle costs (LLC),
activity-based costing (ABC) value engineering have been
introduced. Management and cost applications have changed over the
past decade and will continue to change. Modern cost systems can
provide relevant and accurate cost information. These methods
provide the decisions about customer, product and process
improvement. The aim of study is to describe and explain the
adoption and application of costing systems in SME. This purpose
reports on a survey conducted during 2014 small and medium sized
enterprises (SME) in Ankara. The survey results were evaluated
using SPSS18 package program.
Abstract: This study aims to investigate the possibility of crime
prevention through CCTV by analyzing the appropriateness of the
CCTV location, whether it is installed in the hotspot of crime-prone
areas, and exploring the crime prevention effect and transition effect.
The real crime and CCTV locations of case city were converted into
the spatial data by using GIS. The data was analyzed by hotspot
analysis and weighted displacement quotient (WDQ). As study
methods, it analyzed existing relevant studies for identifying the trends
of CCTV and crime studies based on big data from 1800 to 2014 and
understanding the relation between CCTV and crime. Second, it
investigated the current situation of nationwide CCTVs and analyzed
the guidelines of CCTV installation and operation to draw attention to
the problems and indicating points of CCTV use. Third, it investigated
the crime occurrence in case areas and the current situation of CCTV
installation in the spatial aspects, and analyzed the appropriateness and
effectiveness of CCTV installation to suggest a rational installation of
CCTV and the strategic direction of crime prevention. The results
demonstrate that there was no significant effect in the installation of
CCTV on crime prevention in the case area. This indicates that CCTV
should be installed and managed in a more scientific way reflecting
local crime situations. In terms of CCTV, the methods of spatial
analysis such as GIS, which can evaluate the installation effect, and the
methods of economic analysis like cost-benefit analysis should be
developed. In addition, these methods should be distributed to local
governments across the nation for the appropriate installation of
CCTV and operation. This study intended to find a design guideline of
the optimum CCTV installation. In this regard, this study is
meaningful in that it will contribute to the creation of a safe city.
Abstract: Development of a method to estimate gene functions is
an important task in bioinformatics. One of the approaches for the
annotation is the identification of the metabolic pathway that genes are
involved in. Since gene expression data reflect various intracellular
phenomena, those data are considered to be related with genes’
functions. However, it has been difficult to estimate the gene function
with high accuracy. It is considered that the low accuracy of the
estimation is caused by the difficulty of accurately measuring a gene
expression. Even though they are measured under the same condition,
the gene expressions will vary usually. In this study, we proposed a
feature extraction method focusing on the variability of gene
expressions to estimate the genes' metabolic pathway accurately. First,
we estimated the distribution of each gene expression from replicate
data. Next, we calculated the similarity between all gene pairs by KL
divergence, which is a method for calculating the similarity between
distributions. Finally, we utilized the similarity vectors as feature
vectors and trained the multiclass SVM for identifying the genes'
metabolic pathway. To evaluate our developed method, we applied the
method to budding yeast and trained the multiclass SVM for
identifying the seven metabolic pathways. As a result, the accuracy
that calculated by our developed method was higher than the one that
calculated from the raw gene expression data. Thus, our developed
method combined with KL divergence is useful for identifying the
genes' metabolic pathway.
Abstract: This paper consider the solution of the matrix
differential models using quadratic, cubic, quartic, and quintic
splines. Also using the Taylor’s and Picard’s matrix methods, one
illustrative example is included.
Abstract: Experimental & numeral study of temperature
distribution during milling process, is important in milling quality
and tools life aspects. In the present study the milling cross-section
temperature is determined by using Artificial Neural Networks
(ANN) according to the temperature of certain points of the work
piece and the point specifications and the milling rotational speed of
the blade. In the present work, at first three-dimensional model of the
work piece is provided and then by using the Computational Heat
Transfer (CHT) simulations, temperature in different nods of the
work piece are specified in steady-state conditions. Results obtained
from CHT are used for training and testing the ANN approach. Using
reverse engineering and setting the desired x, y, z and the milling
rotational speed of the blade as input data to the network, the milling
surface temperature determined by neural network is presented as
output data. The desired points temperature for different milling
blade rotational speed are obtained experimentally and by
extrapolation method for the milling surface temperature is obtained
and a comparison is performed among the soft programming ANN,
CHT results and experimental data and it is observed that ANN soft
programming code can be used more efficiently to determine the
temperature in a milling process.
Abstract: The aim of this study was to build ‘Ubi-Net’, a
decision-making support system for systematic establishment in
U-City planning. We have experienced various urban problems caused
by high-density development and population concentrations in
established urban areas. To address these problems, a U-Service
contributes to the alleviation of urban problems by providing real-time
information to citizens through network connections and related
information. However, technology, devices, and information for
consumers are required for systematic U-Service planning in towns
and cities where there are many difficulties in this regard, and a lack of
reference systems.
Thus, this study suggests methods to support the establishment of
sustainable planning by providing comprehensive information
including IT technology, devices, news, and social networking
services (SNS) to U-City planners through intelligent searches. In this
study, we targeted Smart U-Parking Planning to solve parking
problems in an ‘old’ city. Through this study, we sought to contribute
to supporting advances in U-Space and the alleviation of urban
problems.
Abstract: The goal of image segmentation is to cluster pixels
into salient image regions. Segmentation could be used for object
recognition, occlusion boundary estimation within motion or stereo
systems, image compression, image editing, or image database lookup.
In this paper, we present a color image segmentation using
support vector machine (SVM) pixel classification. Firstly, the pixel
level color and texture features of the image are extracted and they
are used as input to the SVM classifier. These features are extracted
using the homogeneity model and Gabor Filter. With the extracted
pixel level features, the SVM Classifier is trained by using FCM
(Fuzzy C-Means).The image segmentation takes the advantage of
both the pixel level information of the image and also the ability of
the SVM Classifier. The Experiments show that the proposed method
has a very good segmentation result and a better efficiency, increases
the quality of the image segmentation compared with the other
segmentation methods proposed in the literature.
Abstract: A quartz crystal microbalance (QCM) nanosensor was developed to detect lysozyme enzyme by functionalizing its gold surface with the attachment of poly(methacroyl-L-phenylalanine) (PMAPA) nanoparticles. PMAPA was chosen as a hydrophobic matrix. The hydrophobic nanoparticles were synthesized by micro-emulsion polymerization method. Hydrophobic QCM nanosensor was tested for real time detection of lysozyme enzyme from aqueous solution. The kinetic and affinity studies were determined by using lysozyme solutions with different concentrations. The responses related with mass (Δm) and frequency (Δf) shifts were used to evaluate adsorption properties.
Abstract: Operations, maintenance and reliability of wind
turbines have received much attention over the years due to the rapid
expansion of wind farms. This paper explores early fault diagnosis
technique for a 5MW wind turbine system subjected to multiple
faults, where genetic optimization algorithm is employed to make the
residual sensitive to the faults, but robust against disturbances. The
proposed technique has a potential to reduce the downtime mostly
caused by the breakdown of components and exploit the productivity
consistency by providing timely fault alarms. Simulation results show
the effectiveness of the robust fault detection methods used under
Matlab/Simulink/Gatool environment.
Abstract: In this paper, we consider the vehicle routing problem
with mixed fleet of conventional and heterogenous electric vehicles
and time dependent charging costs, denoted VRP-HFCC, in which
a set of geographically scattered customers have to be served by a
mixed fleet of vehicles composed of a heterogenous fleet of Electric
Vehicles (EVs), having different battery capacities and operating
costs, and Conventional Vehicles (CVs). We include the possibility
of charging EVs in the available charging stations during the routes
in order to serve all customers. Each charging station offers charging
service with a known technology of chargers and time dependent
charging costs. Charging stations are also subject to operating time
windows constraints. EVs are not necessarily compatible with all
available charging technologies and a partial charging is allowed.
Intermittent charging at the depot is also allowed provided that
constraints related to the electricity grid are satisfied.
The objective is to minimize the number of employed vehicles and
then minimize the total travel and charging costs.
In this study, we present a Mixed Integer Programming Model and
develop a Charging Routing Heuristic and a Local Search Heuristic
based on the Inject-Eject routine with different insertion methods. All
heuristics are tested on real data instances.
Abstract: In urban area, several landmarks may affect housing
price and rents, and hedonic analysis should employ distance variables
corresponding to each landmarks. Unfortunately, the effects of
distances to landmarks on housing prices are generally not consistent
with the true price. These distance variables may cause magnitude
error in regression, pointing a problem of spatial multicollinearity. In
this paper, we provided some approaches for getting the samples with
less bias and method on locating the specific sampling area to avoid
the multicollinerity problem in two specific landmarks case.
Abstract: ESPRIT-TLS method appears a good choice for high
resolution fault detection in induction machines. It has a very high
effectiveness in the frequency and amplitude identification.
Contrariwise, it presents a high computation complexity which
affects its implementation in real time fault diagnosis. To avoid this
problem, a Fast-ESPRIT algorithm that combined the IIR band-pass
filtering technique, the decimation technique and the original
ESPRIT-TLS method was employed to enhance extracting accurately
frequencies and their magnitudes from the wind stator current with
less computation cost. The proposed algorithm has been applied to
verify the wind turbine machine need in the implementation of an online,
fast, and proactive condition monitoring. This type of remote
and periodic maintenance provides an acceptable machine lifetime,
minimize its downtimes and maximize its productivity. The
developed technique has evaluated by computer simulations under
many fault scenarios. Study results prove the performance of Fast-
ESPRIT offering rapid and high resolution harmonics recognizing
with minimum computation time and less memory cost.
Abstract: In review the generalized data about different methods
of synthesis of biological activity aminated hydroxyanthraquinones is
presented. The basic regularity of a synthesis is analyzed. Action of
temperature, pH, solubility, catalysts and other factors on a reaction
product yield is revealed.
Abstract: Organic Rankine Cycle (ORC) is the most commonly used method for recovering energy from small sources of heat. The investigation of the ORC in supercritical condition is a new research area as it has a potential to generate high power and thermal efficiency in a waste heat recovery system. This paper presents a steady state ORC model in supercritical condition and its simulations with a real engine’s exhaust data. The key component of ORC, evaporator, is modelled using finite volume method, modelling of all other components of the waste heat recovery system such as pump, expander and condenser are also presented. The aim of this paper is to investigate the effects of mass flow rate and evaporator outlet temperature on the efficiency of the waste heat recovery process. Additionally, the necessity of maintaining an optimum evaporator outlet temperature is also investigated. Simulation results show that modification of mass flow rate is the key to changing the operating temperature at the evaporator outlet.
Abstract: This article discusses issues related to the System of
Innovation: Comparing economies of Brazil and South Africa.
Having as this study aimed at comparing the Innovation System of
the countries mentioned. Then briefly describe the process of Venture
Capital and present the industry innovation in Brazil and South
Africa. The methodological approach described in this article is
descriptive and the approach is qualitative, taking as a basis
secondary data relating to research articles. The main results are
related to the different forms of financing of Venture Capital used by
countries compared, in addition to the training and economic policy.
And finally, it was highlighted the importance of implementation of
policy reforms for the Brazil and Africa in the innovation process.
Abstract: Remote sensing plays a vital role in mapping of
resources and monitoring of environments of the earth. In the present
research study, mapping and monitoring of clay siltations occurred in
the Alkhod Dam of Muscat, Sultanate of Oman are carried out using
low-cost multispectral Landsat and ASTER data. The dam is
constructed across the Wadi Samail catchment for ground water
recharge. The occurrence and spatial distribution of siltations in the
dam are studied with five years of interval from the year 1987 of
construction to 2014. The deposits are mainly due to the clay, sand
and silt occurrences derived from the weathering rocks of ophiolite
sequences occurred in the Wadi Samail catchment. The occurrences
of clays are confirmed by minerals identification using ASTER
VNIR-SWIR spectral bands and Spectral Angle Mapper supervised
image processing method. The presence of clays and their spatial
distribution are verified in the field. The study recommends the
technique and the low-cost satellite data to similar region of the
world.
Abstract: In this article a comparison was made between Cu and
TiO2 supported catalysts on activated carbon for ozone
decomposition reaction. The activated carbon support in the case of
TiO2/AC sample was prepared by physicochemical pyrolysis and for
Cu/AC samples the supports are chemically modified carbons. The
prepared catalysts were synthesized by impregnation method. The
samples were annealed in two different regimes- in air and under
vacuum. To examine adsorption efficiency of the samples BET
method was used. All investigated catalysts supported on chemically
modified carbons have higher specific surface area compared to the
specific surface area of TiO2 supported catalysts, varying in the range
590÷620 m2/g. The method of synthesis of the precursors had
influenced catalytic activity.
Abstract: Based on the experimental data, the impact of
resistance and reactance of the winding, as well as the magnetic
permeability of the magnetic circuit steel material on the value of the
electromotive force of the induction converter is investigated. The
obtained results allow estimating the main technological spreads and
determining the maximum level of the electromotive force change.
By the method of experiment planning, the expression of a
polynomial for the electromotive force which can be used to estimate
the adequacy of mathematical models to be used at the investigation
and design of induction converters is obtained.
Abstract: This study investigates the cleaning performance of
high intensity 360 kHz frequency on removal of nano-dimensional
and sub-micron particles from various surfaces, uniformity of the
cleaning tank and run to run variation of cleaning process. The
uniformity of the cleaning tank was measured by two different
methods i.e. 1. ppbTM meter and 2. Liquid Particle Counting (LPC)
technique. The result indicates that the energy was distributed more
uniformly throughout the entire cleaning vessel even at the corners
and edges of the tank when megasonic sweeping technology is
applied. The result also shows that rinsing the parts with 360 kHz
frequency at final rinse gives lower particle counts, hence higher
cleaning efficiency as compared to other frequencies. When
megasonic sweeping technology is applied each piezoelectric
transducers will operate at their optimum resonant frequency and
generates stronger acoustic cavitational force and higher acoustic
streaming velocity. These combined forces are helping to enhance the
particle removal and at the same time improve the overall cleaning
performance. The multiple extractions study was also carried out for
various frequencies to measure the cleaning potential and asymptote
value.