Abstract: Tumor is an uncontrolled growth of tissues in any part
of the body. Tumors are of different types and they have different
characteristics and treatments. Brain tumor is inherently serious and
life-threatening because of its character in the limited space of the
intracranial cavity (space formed inside the skull). Locating the tumor
within MR (magnetic resonance) image of brain is integral part of the
treatment of brain tumor. This segmentation task requires
classification of each voxel as either tumor or non-tumor, based on
the description of the voxel under consideration. Many studies are
going on in the medical field using Markov Random Fields (MRF) in
segmentation of MR images. Even though the segmentation process
is better, computing the probability and estimation of parameters is
difficult. In order to overcome the aforementioned issues, Conditional
Random Field (CRF) is used in this paper for segmentation, along
with the modified artificial bee colony optimization and modified
fuzzy possibility c-means (MFPCM) algorithm. This work is mainly
focused to reduce the computational complexities, which are found in
existing methods and aimed at getting higher accuracy. The
efficiency of this work is evaluated using the parameters such as
region non-uniformity, correlation and computation time. The
experimental results are compared with the existing methods such as
MRF with improved Genetic Algorithm (GA) and MRF-Artificial
Bee Colony (MRF-ABC) algorithm.
Abstract: Skin detection is an important task for computer
vision systems. A good method of skin detection means a good and
successful result of the system.
The colour is a good descriptor for image segmentation and
classification; it allows detecting skin colour in the images. The
lighting changes and the objects that have a colour similar than skin
colour make the operation of skin detection difficult.
In this paper, we proposed a method using the YCbCr colour space
for skin detection and lighting effects elimination, then we use the
information of texture to eliminate the false regions detected by the
YCbCr skin model.
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: In this paper, we propose a new packing strategy to
find a free resource for run-time mapping of application tasks to
NoC-based Heterogeneous MPSoC. The proposed strategy minimizes
the task mapping time in addition to placing the communicating tasks
close to each other. To evaluate our approach, a comparative study is
carried out for a platform containing single task supported PEs.
Experiments show that our strategy provides better results when
compared to latest dynamic mapping strategies reported in the
literature.
Abstract: One of the most important tasks in the risk
management is the correct determination of probability of default
(PD) of particular financial subjects. In this paper a possibility of
determination of financial institution’s PD according to the creditscoring
models is discussed. The paper is divided into the two parts.
The first part is devoted to the estimation of the three different
models (based on the linear discriminant analysis, logit regression
and probit regression) from the sample of almost three hundred US
commercial banks. Afterwards these models are compared and
verified on the control sample with the view to choose the best one.
The second part of the paper is aimed at the application of the chosen
model on the portfolio of three key Czech banks to estimate their
present financial stability. However, it is not less important to be able
to estimate the evolution of PD in the future. For this reason, the
second task in this paper is to estimate the probability distribution of
the future PD for the Czech banks. So, there are sampled randomly
the values of particular indicators and estimated the PDs’ distribution,
while it’s assumed that the indicators are distributed according to the
multidimensional subordinated Lévy model (Variance Gamma model
and Normal Inverse Gaussian model, particularly). Although the
obtained results show that all banks are relatively healthy, there is
still high chance that “a financial crisis” will occur, at least in terms
of probability. This is indicated by estimation of the various quantiles
in the estimated distributions. Finally, it should be noted that the
applicability of the estimated model (with respect to the used data) is
limited to the recessionary phase of the financial market.
Abstract: Due to the large amount of information in the World
Wide Web (WWW, web) and the lengthy and usually linearly
ordered result lists of web search engines that do not indicate
semantic relationships between their entries, the search for topically
similar and related documents can become a tedious task. Especially,
the process of formulating queries with proper terms representing
specific information needs requires much effort from the user. This
problem gets even bigger when the user's knowledge on a subject and
its technical terms is not sufficient enough to do so. This article
presents the new and interactive search application DocAnalyser that
addresses this problem by enabling users to find similar and related
web documents based on automatic query formulation and state-ofthe-
art search word extraction. Additionally, this tool can be used to
track topics across semantically connected web documents.
Abstract: The sub-task pattern in terms of deviations and defects
should be identified and understood in order to improve the quality of
practices in construction projects. Therefore, sub-task susceptibility
to exposure to deviations and defects has been evaluated and
classified via six classifications proposed in this study. Thirty-four
case studies of specific sub-tasks (from compression members in
constructed concrete structures) were collected from seven
construction projects in order to examine the study’s proposed
classifications. The study revealed that the sub-task has a high
sensitivity to deviation, where 91% of the cases were recorded as
deviations; however, only 19% of cases were recorded as defects.
Other findings were that the actual work during the execution process
is a high source of deviation for this sub-task (74%), while only 26%
of the source of deviation was due to both design documentation and
the actual work. These findings significantly imply that the study’s
proposed classifications could be used to determine the pattern of
each sub-task and develop proactive actions to overcome issues of
sub-task deviations and defects.
Abstract: The cooling channels of injection mould play a crucial
role in determining the productivity of moulding process and the
product quality. It’s not a simple task to design high quality cooling
channels. In this paper, an intelligent cooling channels design system
including automatic layout of cooling channels, interference checking
and assembly of accessories is studied. Automatic layout of cooling
channels using genetic algorithm is analyzed. Through integrating
experience criteria of designing cooling channels, considering the
factors such as the mould temperature and interference checking, the
automatic layout of cooling channels is implemented. The method of
checking interference based on distance constraint algorithm and the
function of automatic and continuous assembly of accessories are
developed and integrated into the system. Case studies demonstrate the
feasibility and practicality of the intelligent design system.
Abstract: Fuzzy systems have been successfully used for
exchange rate forecasting. However, fuzzy system is very confusing
and complex to be designed by an expert, as there is a large set of
parameters (fuzzy knowledge base) that must be selected, it is not a
simple task to select the appropriate fuzzy knowledge base for an
exchange rate forecasting. The researchers often look the effect of
fuzzy knowledge base on the performances of fuzzy system
forecasting. This paper proposes a genetic fuzzy predictor to forecast
the future value of daily US Dollar/Euro exchange rate time’s series.
A range of methodologies based on a set of fuzzy predictor’s which
allow the forecasting of the same time series, but with a different
fuzzy partition. Each fuzzy predictor is built from two stages, where
each stage is performed by a real genetic algorithm.
Abstract: Identification and selection of appropriate product and
manufacturing technologies are key factors for competitiveness and
market success of technology-based companies. Therefore, many
companies perform technology intelligence (TI) activities to ensure
the identification of evolving technologies at the right time.
Technology monitoring is one of the three base activities of TI,
besides scanning and scouting.
As the technological progress is accelerating, more and more
technologies are being developed. Against the background of limited
resources it is therefore necessary to focus TI activities. In this paper
we propose a concept for defining appropriate search fields for
technology monitoring. This limitation of search space leads to more
concentrated monitoring activities. The concept will be introduced
and demonstrated through an anonymized case study conducted
within an industry project at the Fraunhofer Institute for Production
Technology IPT.
The described concept provides a customized monitoring
approach, which is suitable for use in technology-oriented companies.
It is shown in this paper that the definition of search fields and search
tasks are suitable methods to define topics of interest and thus to
align monitoring activities. Current as well as planned product,
production and material technologies and existing skills, capabilities
and resources form the basis for derivation of relevant search areas.
To further improve the concept of technology monitoring the
proposed concept should be extended during future research e.g. by
the definition of relevant monitoring parameters.
Abstract: Innovations not only contribute to competitiveness of
the company but have also positive effects on revenues. On average,
product innovations account to 14 percent of companies’ sales.
Innovation management has substantially changed during the last
decade, because of growing reliance on external partners. As a
consequence, a new task for purchasing arises, as firms need to
understand which suppliers actually do have high potential
contributing to the innovativeness of the firm and which do not.
Proper organization of the purchasing function is important since
for the majority of manufacturing companies deal with substantial
material costs which pass through the purchasing function. In the past
the purchasing function was largely seen as a transaction-oriented,
clerical function but today purchasing is the intermediate with supply
chain partners contributing to innovations, be it product or process
innovations. Therefore, purchasing function has to be organized
differently to enable firm innovation potential.
However, innovations are inherently risky. There are behavioral
risk (that some partner will take advantage of the other party),
technological risk in terms of complexity of products and processes
of manufacturing and incoming materials and finally market risks,
which in fact judge the value of the innovation. These risks are
investigated in this work. Specifically, technological risks which deal
with complexity of the products, and processes will be investigated
more thoroughly. Buying components or such high edge technologies
necessities careful investigation of technical features and therefore is
usually conducted by a team of experts. Therefore it is hypothesized
that higher the technological risk, higher will be the centralization of
the purchasing function as an interface with other supply chain
members.
Main contribution of this research lies is in the fact that analysis
was performed on a large data set of 1493 companies, from 25
countries collected in the GMRG 4 survey. Most analyses of
purchasing function are done by case study analysis of innovative
firms. Therefore this study contributes with empirical evaluations that
can be generalized.
Abstract: The use of IT equipment has become a part of every
day. However, each device that is part of cyberspace should be
secured against unauthorized use. It is very important to know the
basics of these security devices, but also the basics of safe conduct
their owners. This information should be part of every curriculum
computer science education in primary and secondary schools.
Therefore, the work focuses on the education of pupils in primary and
secondary schools on the Internet. Analysis of the current state
describes approaches to the education of pupils in security issues on
the Internet. The paper presents a questionnaire-based survey which
was carried out in the Czech Republic, whose task was to ascertain
the level of opinion pupils in primary and secondary schools on the
issue of communication in social networks. The research showed that
awareness of socio-pathological phenomena on the Internet
environment is very low. Based on the results it was proposed
appropriate ways of teaching to this issue and its inclusion a proposal
of curriculum for primary and secondary schools.
Abstract: The paper is focused on the methods to solutions of
the crisis situation in the Czech Republic associated with the mass
methanol poisoning. The emphasis is put on tasks of individual state
bodies and of Integrated Rescue System during the handling of the
crisis.
The theoretical part describes poisonings, ways of intoxication,
types of intoxicants and cases of mass poisoning by dangerous
substances in the world.
The practical part describes the development, causes and solutions
of extraordinary event, mass methanol poisoning in the Czech
Republic. The main emphasis was put on the crisis management of
the Czech Republic in solving this situation.
Abstract: Segmentation is one of the essential tasks in image
processing. Thresholding is one of the simplest techniques for
performing image segmentation. Multilevel thresholding is a simple
and effective technique. The primary objective of bi-level or
multilevel thresholding for image segmentation is to determine a best
thresholding value. To achieve multilevel thresholding various
techniques has been proposed. A study of some nature inspired
metaheuristic algorithms for multilevel thresholding for image
segmentation is conducted. Here, we study about Particle swarm
optimization (PSO) algorithm, artificial bee colony optimization
(ABC), Ant colony optimization (ACO) algorithm and Cuckoo
search (CS) algorithm.
Abstract: This paper presents general results on the Java source
code snippet detection problem. We propose the tool which uses
graph and subgraph isomorphism detection. A number of solutions
for all of these tasks have been proposed in the literature. However,
although that all these solutions are really fast, they compare just the
constant static trees. Our solution offers to enter an input sample
dynamically with the Scripthon language while preserving an
acceptable speed. We used several optimizations to achieve very low
number of comparisons during the matching algorithm.
Abstract: This paper deals with a simulation programs and
technologies using in the educational process for members of the crisis
management. Risk analysis, simulation, preparation and planning are
among the main activities of workers of crisis management. Made
correctly simulation of emergency defines the extent of the danger. On
this basis, it is possible to effectively prepare and plan measures to
minimize damage. The paper is focused on simulation programs that
are trained at the University of Defence. Implementation of the outputs
from simulation programs in decision-making processes of crisis staffs
is one of the main tasks of the research project.
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: In healthy humans, the cortical brain rhythm shows
specific mu (~6-14 Hz) and beta (~18-24 Hz) band patterns in the
cases of both real and imaginary motor movements. As cerebellar
ataxia is associated with impairment of precise motor movement
control as well as motor imagery, ataxia is an ideal model system in
which to study the role of the cerebellocortical circuit in rhythm
control. We hypothesize that the EEG characteristics of ataxic patients
differ from those of controls during the performance of a
Brain-Computer Interface (BCI) task. Ataxia and control subjects
showed a similar distribution of mu power during cued relaxation.
During cued motor imagery, however, the ataxia group showed
significant spatial distribution of the response, while the control group
showed the expected decrease in mu-band power (localized to the
motor cortex).
Abstract: This research paper aims to identify, analyze and rank
factors affecting labor productivity in Spain with respect to their
relative importance. Using a selected set of 35 factors, a structured
questionnaire survey was utilized as the method to collect data from
companies. Target population is comprised by a random
representative sample of practitioners related with the Spanish
construction industry. Findings reveal the top five ranked factors are
as follows: (1) shortage or late supply of materials; (2) clarity of the
drawings and project documents; (3) clear and daily task assignment;
(4) tools or equipment shortages; (5) level of skill and experience of
laborers. Additionally, this research also pretends to provide simple
and comprehensive recommendations so that they could be
implemented by construction managers for an effective management
of construction labor forces.
Abstract: Color Histogram is considered as the oldest method
used by CBIR systems for indexing images. In turn, the global
histograms do not include the spatial information; this is why the
other techniques coming later have attempted to encounter this
limitation by involving the segmentation task as a preprocessing step.
The weak segmentation is employed by the local histograms while
other methods as CCV (Color Coherent Vector) are based on strong
segmentation. The indexation based on local histograms consists of
splitting the image into N overlapping blocks or sub-regions, and
then the histogram of each block is computed. The dissimilarity
between two images is reduced, as consequence, to compute the
distance between the N local histograms of the both images resulting
then in N*N values; generally, the lowest value is taken into account
to rank images, that means that the lowest value is that which helps to
designate which sub-region utilized to index images of the collection
being asked. In this paper, we make under light the local histogram
indexation method in the hope to compare the results obtained against
those given by the global histogram. We address also another
noteworthy issue when Relying on local histograms namely which
value, among N*N values, to trust on when comparing images, in
other words, which sub-region among the N*N sub-regions on which
we base to index images. Based on the results achieved here, it seems
that relying on the local histograms, which needs to pose an extra
overhead on the system by involving another preprocessing step
naming segmentation, does not necessary mean that it produces better
results. In addition to that, we have proposed here some ideas to
select the local histogram on which we rely on to encode the image
rather than relying on the local histogram having lowest distance with
the query histograms.