Abstract: Mammography has been one of the most reliable
methods for early detection of breast cancer. There are different
lesions which are breast cancer characteristic such as
microcalcifications, masses, architectural distortions and bilateral
asymmetry. One of the major challenges of analysing digital
mammogram is how to extract efficient features from it for accurate
cancer classification. In this paper we proposed a hybrid feature
extraction method to detect and classify all four signs of breast
cancer. The proposed method is based on multiscale surrounding
region dependence method, Gabor filters, multi fractal analysis,
directional and morphological analysis. The extracted features are
input to self adaptive resource allocation network (SRAN) classifier
for classification. The validity of our approach is extensively
demonstrated using the two benchmark data sets Mammographic
Image Analysis Society (MIAS) and Digital Database for Screening
Mammograph (DDSM) and the results have been proved to be
progressive.
Abstract: Predicting earthquakes is an important issue in the
study of geography. Accurate prediction of earthquakes can help
people to take effective measures to minimize the loss of personal
and economic damage, such as large casualties, destruction of
buildings and broken of traffic, occurred within a few seconds.
United States Geological Survey (USGS) science organization
provides reliable scientific information about Earthquake Existed
throughout history & the Preliminary database from the National
Center Earthquake Information (NEIC) show some useful factors to
predict an earthquake in a seismic area like Aleutian Arc in the U.S.
state of Alaska. The main advantage of this prediction method that it
does not require any assumption, it makes prediction according to the
future evolution of the object's time series. The article compares
between simulation data result from trained BP and RBF neural
network versus actual output result from the system calculations.
Therefore, this article focuses on analysis of data relating to real
earthquakes. Evaluation results show better accuracy and higher
speed by using radial basis functions (RBF) neural network.
Abstract: The purpose of this work is examining the multiproduct
multi-stage in a battery production line. To improve the
performances of an assembly production line by determine the
efficiency of each workstation. Data collected from every
workstation. The data are throughput rate, number of operator, and
number of parts that arrive and leaves during part processing. Data
for the number of parts that arrives and leaves are collected at least at
the amount of ten samples to make the data is possible to be analyzed
by Chi-Squared Goodness Test and queuing theory. Measures of this
model served as the comparison with the standard data available in
the company. Validation of the task time value resulted by comparing
it with the task time value based on the company database. Some
performance factors for the multi-product multi-stage in a battery
production line in this work are shown.
The efficiency in each workstation was also shown. Total
production time to produce each part can be determined by adding
the total task time in each workstation. To reduce the queuing time
and increase the efficiency based on the analysis any probably
improvement should be done. One probably action is by increasing
the number of operators how manually operate this workstation.
Abstract: The knowledge of biodiesel density over large ranges
of temperature and pressure is important for predicting the behavior
of fuel injection and combustion systems in diesel engines, and for
the optimization of such systems. In this study, cottonseed oil was
transesterified into biodiesel and its density was measured at
temperatures between 288 K and 358 K and pressures between 0.1
MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg⋅m-
3. Experimental pressure-volume-temperature (pVT) cottonseed data
was used along with literature data relative to other 18 biodiesels, in
order to build a database used to test the correlation of density with
temperarure and pressure using the Goharshadi–Morsali–Abbaspour
equation of state (GMA EoS). To our knowledge, this is the first that
density measurements are presented for cottonseed biodiesel under
such high pressures, and the GMA EoS used to model biodiesel
density. The new tested EoS allowed correlations within 0.2 kg·m-3
corresponding to average relative deviations within 0.02%. The built
database was used to develop and test a new full predictive model
derived from the observed linear relation between density and degree
of unsaturation (DU), which depended from biodiesel FAMEs
profile. The average density deviation of this method was only about
3 kg.m-3 within the temperature and pressure limits of application.
These results represent appreciable improvements in the context of
density prediction at high pressure when compared with other
equations of state.
Abstract: Different strategies and tools are available at the oil
and gas industry for detecting and analyzing tension and possible
fractures in borehole walls. Most of these techniques are based on
manual observation of the captured borehole images. While this
strategy may be possible and convenient with small images and few
data, it may become difficult and suitable to errors when big
databases of images must be treated. While the patterns may differ
among the image area, depending on many characteristics (drilling
strategy, rock components, rock strength, etc.). In this work we
propose the inclusion of data-mining classification strategies in order
to create a knowledge database of the segmented curves. These
classifiers allow that, after some time using and manually pointing
parts of borehole images that correspond to tension regions and
breakout areas, the system will indicate and suggest automatically
new candidate regions, with higher accuracy. We suggest the use of
different classifiers methods, in order to achieve different knowledge
dataset configurations.
Abstract: An anthropometric study applied to 1,115 students of
the Faculty of Chemical Sciences and Engineering of the
Autonomous University of California. Thirteen individual
measurements were taken in a sitting position. The results obtained
allow forming a reliable anthropometric database for statistical
studies and analysis and inferences of specific distributions, so the
opinion of experts in occupational medicine recommendations may
emit to reduce risks resulting in an alteration of the vital signs during
the execution of their school activities. Another use of these analyses
is to use them as a reliable reference for future deeper research, to the
design of spaces, tools, utensils, workstations, with anthropometric
dimensions and ergonomic characteristics suitable to use.
Abstract: This research is aimed to develop the online-class
scheduling management system and improve as a complex problem
solution, this must take into consideration in various conditions and
factors. In addition to the number of courses, the number of students
and a timetable to study, the physical characteristics of each class
room and regulations used in the class scheduling must also be taken
into consideration. This system is developed to assist management in
the class scheduling for convenience and efficiency. It can provide
several instructors to schedule simultaneously. Both lecturers and
students can check and publish a timetable and other documents
associated with the system online immediately. It is developed in a
web-based application. PHP is used as a developing tool. The
database management system was MySQL. The tool that is used for
efficiency testing of the system is questionnaire. The system was
evaluated by using a Black-Box testing. The sample was composed
of 2 groups: 5 experts and 100 general users. The average and the
standard deviation of results from the experts were 3.50 and 0.67.
The average and the standard deviation of results from the general
users were 3.54 and 0.54. In summary, the results from the research
indicated that the satisfaction of users were in a good level.
Therefore, this system could be implemented in an actual workplace
and satisfy the users’ requirement effectively.
Abstract: Over the past era, there have been a lot of efforts and
studies are carried out in growing proficient tools for performing
various tasks in big data. Recently big data have gotten a lot of
publicity for their good reasons. Due to the large and complex
collection of datasets it is difficult to process on traditional data
processing applications. This concern turns to be further mandatory
for producing various tools in big data. Moreover, the main aim of
big data analytics is to utilize the advanced analytic techniques
besides very huge, different datasets which contain diverse sizes from
terabytes to zettabytes and diverse types such as structured or
unstructured and batch or streaming. Big data is useful for data sets
where their size or type is away from the capability of traditional
relational databases for capturing, managing and processing the data
with low-latency. Thus the out coming challenges tend to the
occurrence of powerful big data tools. In this survey, a various
collection of big data tools are illustrated and also compared with the
salient features.
Abstract: Frequent, continuous speech training has proven to be
a necessary part of a successful speech therapy process, but
constraints of traveling time and employment dispensation become
key obstacles especially for individuals living in remote areas or for
dependent children who have working parents. In order to ameliorate
speech difficulties with ample guidance from speech therapists, a
website has been developed that supports speech therapy and training
for people with articulation disorders in the standard Thai language.
This web-based program has the ability to record speech training
exercises for each speech trainee. The records will be stored in a
database for the speech therapist to investigate, evaluate, compare
and keep track of all trainees’ progress in detail. Speech trainees can
request live discussions via video conference call when needed.
Communication through this web-based program facilitates and
reduces training time in comparison to walk-in training or
appointments. This type of training also allows people with
articulation disorders to practice speech lessons whenever or
wherever is convenient for them, which can lead to a more regular
training processes.
Abstract: Web search engines are designed to retrieve and
extract the information in the web databases and to return dynamic
web pages. The Semantic Web is an extension of the current web in
which it includes semantic content in web pages. The main goal of
semantic web is to promote the quality of the current web by
changing its contents into machine understandable form. Therefore,
the milestone of semantic web is to have semantic level information
in the web. Nowadays, people use different keyword- based search
engines to find the relevant information they need from the web.
But many of the words are polysemous. When these words are
used to query a search engine, it displays the Search Result Records
(SRRs) with different meanings. The SRRs with similar meanings are
grouped together based on Word Sense Disambiguation (WSD). In
addition to that semantic annotation is also performed to improve the
efficiency of search result records. Semantic Annotation is the
process of adding the semantic metadata to web resources. Thus the
grouped SRRs are annotated and generate a summary which
describes the information in SRRs. But the automatic semantic
annotation is a significant challenge in the semantic web. Here
ontology and knowledge based representation are used to annotate
the web pages.
Abstract: With the rapid progress of modern cities, the railway
construction must be developing quickly in China.As a typical
high-density country, shopping center on the subway should be one
important factor during the process of urban development. The paper
discusses the influence of the layout of shopping center on the subway,
and put it in the time and space’s axis of Shanghai urban development.
We usethe digital technology to establish the database of relevant
information. And then get the change role about shopping center on
subway in Shanghaiby the Kernel density estimate.The result shows
the development of shopping center on subway has a relationship with
local economic strength, population size, policysupport, and city
construction. And the suburbanization trend of shopping center would
be increasingly significant.By this case research, we could see the
Kernel density estimate is an efficient analysis method on the spatial
layout. It could reveal the characters of layout form of shopping center
on subway in essence. And it can also be applied to the other research
of space form.
Abstract: Phase equilibria of AZ91D Mg alloys for
nonflammable use, containing Ca and Y, were carried out by using
FactSage® and FTLite database, which revealed that solid solution
treatment could be performed at temperatures from 400 to 450oC.
Solid solution treatment of AZ91D Mg alloy without Ca and Y was
successfully conducted at 420oC and supersaturated microstructure
with all beta phase resolved into matrix was obtained. In the case of
AZ91D Mg alloy with some Ca and Y; however, a little amount of
intermetallic particles were observed after solid solution treatment.
After solid solution treatment, each alloy was annealed at temperatures
of 180 and 200oC for time intervals from 1 min to 48 hrs and hardness
of each condition was measured by micro-Vickers method. Peak aging
conditions were deduced as at the temperature of 200oC for 10 hrs.
Abstract: The purposes of this study were to design and find
users’ satisfaction after using the decision support system for tourism
northern part of Thailand, which can provide tourists touristic
information and plan their personal voyage. Such information can be
retrieved systematically based on personal budget and provinces. The
samples of this study were five experts and users 30 persons white
collars in Bangkok. This decision support system was designed via
ASP.NET. Its database was developed by using MySQL, for
administrators are able to effectively manage the database. The
application outcome revealed that the innovation works properly as
sought in objectives. Specialists and white collars in Bangkok have
evaluated the decision support system; the result was satisfactorily
positive.
Abstract: High temperature deformation behavior of cast
Fe-20Cr-5Al alloy has been investigated in this study by performing
tensile and compression tests at temperatures from 1100 to 1200oC.
Rectangular ingots of which the dimensions were 300×300×100 in
millimeter were cast using vacuum induction melting. Phase
equilibrium was calculated using the FactSage®, thermodynamic
software and database. Tensile strength of cast Fe-20Cr-5Al alloy was
4 MPa at 1200oC. With temperature decreased, tensile strength
increased rapidly and reached up to 13 MPa at 1100oC. Elongation
also increased from 18 to 80% with temperature decreased from
1200oC to 1100oC. Microstructure observation revealed that M23C6
carbide was precipitated along the grain boundary and within the
matrix.
Abstract: ‘Steganalysis’ is one of the challenging and attractive interests for the researchers with the development of information hiding techniques. It is the procedure to detect the hidden information from the stego created by known steganographic algorithm. In this paper, a novel feature based image steganalysis technique is proposed. Various statistical moments have been used along with some similarity metric. The proposed steganalysis technique has been designed based on transformation in four wavelet domains, which include Haar, Daubechies, Symlets and Biorthogonal. Each domain is being subjected to various classifiers, namely K-nearest-neighbor, K* Classifier, Locally weighted learning, Naive Bayes classifier, Neural networks, Decision trees and Support vector machines. The experiments are performed on a large set of pictures which are available freely in image database. The system also predicts the different message length definitions.
Abstract: Advances in the field of image processing envision a
new era of evaluation techniques and application of procedures in
various different fields. One such field being considered is the
biomedical field for prognosis as well as diagnosis of diseases. This
plethora of methods though provides a wide range of options to select
from, it also proves confusion in selecting the apt process and also in
finding which one is more suitable. Our objective is to use a series of
techniques on bone scans, so as to detect the occurrence of
rheumatoid arthritis (RA) as accurately as possible. Amongst other
techniques existing in the field our proposed system tends to be more
effective as it depends on new methodologies that have been proved
to be better and more consistent than others. Computer aided
diagnosis will provide more accurate and infallible rate of
consistency that will help to improve the efficiency of the system.
The image first undergoes histogram smoothing and specification,
morphing operation, boundary detection by edge following algorithm
and finally image subtraction to determine the presence of
rheumatoid arthritis in a more efficient and effective way. Using preprocessing
noises are removed from images and using segmentation,
region of interest is found and Histogram smoothing is applied for a
specific portion of the images. Gray level co-occurrence matrix
(GLCM) features like Mean, Median, Energy, Correlation, Bone
Mineral Density (BMD) and etc. After finding all the features it
stores in the database. This dataset is trained with inflamed and noninflamed
values and with the help of neural network all the new
images are checked properly for their status and Rough set is
implemented for further reduction.
Abstract: This research aims to create a knowledge-based system as a database for self-healthcare analysis, diagnosis of simple illnesses, and the use of Thai herbs instead of modern medicine by using principles of Thai traditional medication theory. These were disseminated by website network programs within Suan Sunandha Rajabhat University. The population used in this study was divided into two groups: the first group consisted of four experts of Thai traditional medication and the second group was 300 website users. The methods used for collecting data were paper questionnaires and poll questionnaires on the website. The statistics used for analyzing data was at an average level. The results were divided into three parts: the first part was the development of a knowledge-based system and the second part was applied programs on website. Both parts could be fulfilled and achieved according to the set goal. The third part was the evaluation of the study: The evaluation of the viewpoints of the experts towards website designs were evaluated at a good level of 4.20. The satisfaction evaluation of the users was found at a good level of average satisfactory level at 4.24. It was found that the young population of those under the age of 16 had less cares about their health than the population of other teenagers, working age adults and those of older age. The research findings should be extended in order to encourage the lifestyle modifications to people of all ages by using the self-healthcare principles.
Abstract: By running transactions under the SNAPSHOT isolation
we can achieve a good level of concurrency, specially in databases
with high-intensive read workloads. However, SNAPSHOT is not
immune to all the problems that arise from competing transactions
and therefore no serialization warranty exists. We propose in this
paper a technique to obtain data consistency with SNAPSHOT by using
some special triggers that we named DAEMON TRIGGERS. Besides
keeping the benefits of the SNAPSHOT isolation, the technique is
specially useful for those database systems that do not have an
isolation level that ensures serializability, like Firebird and Oracle. We
describe all the anomalies that might arise when using the SNAPSHOT
isolation and show how to preclude them with DAEMON TRIGGERS.
Based on the methodology presented here, it is also proposed the
creation of a new isolation level: DAEMON SNAPSHOT.
Abstract: The inhibition of SH2 domain regulated protein-protein interactions is an attractive target for developing an effective chemotherapeutic approach in the treatment of disease. Molecular simulation is a useful tool for developing new drugs and for studying molecular recognition. In this study, we searched potential drug compounds for the inhibition of SH2 domain by performing structural similarity search in PubChem Compound Database. A total of 37 compounds were screened from the database, and then we used the LibDock docking program to evaluate the inhibition effect. The best three compounds (AP22408, CID 71463546 and CID 9917321) were chosen for MD simulations after the LibDock docking. Our results show that the compound CID 9917321 can produce a more stable protein-ligand complex compared to other two currently known inhibitors of Src SH2 domain. The compound CID 9917321 may be useful for the inhibition of SH2 domain based on these computational results. Subsequently experiments are needed to verify the effect of compound CID 9917321 on the SH2 domain in the future studies.
Abstract: The objective of the paper is to measure and compare market orientation of Swiss and Czech banks, as well as examine statistically the degree of influence it has on competitiveness of the institutions. The analysis of market orientation is based on the collecting, analysis and correct interpretation of the data. Descriptive analysis of market orientation describe current situation. Research of relation of competitiveness and market orientation in the sector of big international banks is suggested with the expectation of existence of a strong relationship. Partially, the work served as reconfirmation of suitability of classic methodologies to measurement of banks’ market orientation.
Two types of data were gathered. Firstly, by measuring subjectively perceived market orientation of a company and secondly, by quantifying its competitiveness. All data were collected from a sample of small, mid-sized and large banks. We used numerical secondary character data from the international statistical financial Bureau Van Dijk’s BANKSCOPE database.
Statistical analysis led to the following results. Assuming classical market orientation measures to be scientifically justified, Czech banks are statistically less market-oriented than Swiss banks. Secondly, among small Swiss banks, which are not broadly internationally active, small relationship exist between market orientation measures and market share based competitiveness measures. Thirdly, among all Swiss banks, a strong relationship exists between market orientation measures and market share based competitiveness measures. Above results imply existence of a strong relation of this measure in sector of big international banks. A strong statistical relationship has been proven to exist between market orientation measures and equity/total assets ratio in Switzerland.