Abstract: Generalization is one of the most challenging issues
of Learning Classifier Systems. This feature depends on the
representation method which the system used. Considering the
proposed representation schemes for Learning Classifier System, it
can be concluded that many of them are designed to describe the
shape of the region which the environmental states belong and the
other relations of the environmental state with that region was
ignored. In this paper, we propose a new representation scheme
which is designed to show various relationships between the
environmental state and the region that is specified with a particular
classifier.
Abstract: An effective approach for extracting document images from a noisy background is introduced. The entire scheme is divided into three sub- stechniques – the initial preprocessing operations for noise cluster tightening, introduction of a new thresholding method by maximizing the ratio of stan- dard deviations of the combined effect on the image to the sum of weighted classes and finally the image restoration phase by image binarization utiliz- ing the proposed optimum threshold level. The proposed method is found to be efficient compared to the existing schemes in terms of computational complexity as well as speed with better noise rejection.
Abstract: In this paper we introduce some subspaces of fuzzy entire sequence space. Some general properties of these sequence spaces are discussed. Also some inclusion relation involving the spaces are obtained. Mathematics Subject Classification: 40A05, 40D25.
Abstract: In this paper, we have presented a new multivariate fuzzy time series forecasting method. This method assumes mfactors with one main factor of interest. History of past three years is used for making new forecasts. This new method is applied in forecasting total number of car accidents in Belgium using four secondary factors. We also make comparison of our proposed method with existing methods of fuzzy time series forecasting. Experimentally, it is shown that our proposed method perform better than existing fuzzy time series forecasting methods. Practically, actuaries are interested in analysis of the patterns of causalities in road accidents. Thus using fuzzy time series, actuaries can define fuzzy premium and fuzzy underwriting of car insurance and life insurance for car insurance. National Institute of Statistics, Belgium provides region of risk classification for each road. Thus using this risk classification, we can predict premium rate and underwriting of insurance policy holders.
Abstract: Paleoclimate was reconstructed by the clay mineral
assemblages of shale units of Pabdeh (Paleocene- Oligocene), Gurpi
(Upper Cretaceous), Kazhdumi (Albian-Cenomanian) and Gadvan
(Aptian-Neocomian) formations in the Bangestan anticline. To
compare with clay minerals assemblages in these formations,
selected samples also taken from available formations in drilled wells
in Ahvaz, Marun, Karanj, and Parsi oil fields. Collected samples
prepared using standard clay mineral methodology. They were
treated as normal, glycolated and heated oriented glass slides. Their
identification was made on X-Ray diffractographs. Illite % varies
from 8 to 36. Illite quantity increased from Pabdeh to Gurpi
Formation. This may be due to dominant dry climate. Kaolinite is in
range of 12-49%. Its variation style in different formations could be a
marker of climate changes from wet to dry which is supported by the
lithological changes. Chlorite (4-28%) can also be detected in those
samples without any kaolinite. Mixed layer minerals as the mixture
of illite-chlorite and illite-vermiculite-montmorillonite are varied
from 6 to 36%, decreased during Kazhdumi deposition from the base
to the top. This result may be according to decreasing of illite
leaching process. Vermiculite was also determined in very less
quantity and found in those units without kaolinite. Montmorillonite
varies from 8 to 43%, and its presence is due to terrestrial
depositional condition. Stratigraphical documents is also supported
this idea that clay mineral distribution is a function of the climate
changes. It seems, thus, the present results can be indicated a possible
procedure for ancient climate changes evaluation.
Abstract: Urban problems are problems of organized complexity. Thus, many models and scientific methods to resolve urban problems are failed. This study is concerned with proposing of a fuzzy system driven approach for classification and solving urban problems. The proposed study investigated mainly the selection of the inputs and outputs of urban systems for classification of urban problems. In this research, five categories of urban problems, respect to fuzzy system approach had been recognized: control, polytely, optimizing, open and decision making problems. Grounded Theory techniques were then applied to analyze the data and develop new solving method for each category. The findings indicate that the fuzzy system methods are powerful processes and analytic tools for helping planners to resolve urban complex problems. These tools can be successful where as others have failed because both incorporate or address uncertainty and risk; complexity and systems interacting with other systems.
Abstract: This paper presents an algorithm based on the
wavelet decomposition, for feature extraction from the ECG signal
and recognition of three types of Ventricular Arrhythmias using
neural networks. A set of Discrete Wavelet Transform (DWT)
coefficients, which contain the maximum information about the
arrhythmias, is selected from the wavelet decomposition. After that a
novel clustering algorithm based on nature inspired algorithm (Ant
Colony Optimization) is developed for classifying arrhythmia types.
The algorithm is applied on the ECG registrations from the MIT-BIH
arrhythmia and malignant ventricular arrhythmia databases. We
applied Daubechies 4 wavelet in our algorithm. The wavelet
decomposition enabled us to perform the task efficiently and
produced reliable results.
Abstract: Integrins are a large family of multidomain α/β cell
signaling receptors. Some integrins contain an additional inserted I
domain, whose earliest expression appears to be with the chordates,
since they are observed in the urochordates Ciona intestinalis (vase
tunicate) and Halocynthia roretzi (sea pineapple), but not in integrins
of earlier diverging species. The domain-s presence is viewed as a
hallmark of integrins of higher metazoans, however in vertebrates,
there are clearly three structurally-different classes: integrins without
I domains, and two groups of integrins with I domains but separable
by the presence or absence of an additional αC helix. For example,
the αI domains in collagen-binding integrins from Osteichthyes
(bony fish) and all higher vertebrates contain the specific αC helix,
whereas the αI domains in non-collagen binding integrins from
vertebrates and the αI domains from earlier diverging urochordate
integrins, i.e. tunicates, do not. Unfortunately, within the early
chordates, there is an evolutionary gap due to extinctions between the
tunicates and cartilaginous fish. This, coupled with a knowledge gap
due to the lack of complete genomic data from surviving species,
means that the origin of collagen-binding αC-containing αI domains
remains unknown. Here, we analyzed two available genomes from
Callorhinchus milii (ghost shark/elephant shark; Chondrichthyes –
cartilaginous fish) and Petromyzon marinus (sea lamprey;
Agnathostomata), and several available Expression Sequence Tags
from two Chondrichthyes species: Raja erinacea (little skate) and
Squalus acanthias (dogfish shark); and Eptatretus burgeri (inshore
hagfish; Agnathostomata), which evolutionary reside between the
urochordates and osteichthyes. In P. marinus, we observed several
fragments coding for the αC-containing αI domain, allowing us to
shed more light on the evolution of the collagen-binding integrins.
Abstract: Continuously variable transmission (CVT) is a type of
automatic transmission that can change the gear ratio to any arbitrary
setting within the limits. The most common type of CVT operates on
a pulley system that allows an infinite variability between highest and
lowest gears with no discrete steps. However, the current CVT
system with hydraulic actuation method suffers from the power loss.
It needs continuous force for the pulley to clamp the belt and hold the
torque resulting in large amount of energy consumption. This study
focused on the development of an electromechanical actuated control
CVT to eliminate the problem that faced by the existing CVT. It is
conducted with several steps; computing and selecting the
appropriate sizing for stroke length, lead screw system and etc. From
the visual observation it was found that the CVT system of this
research is satisfactory.
Abstract: Fishing has always been an essential component of
the Polynesians- life. Fishhooks, mostly in pearl shell, found during
archaeological excavations are the artifacts related to this activity the
most numerous. Thanks to them, we try to reconstruct the ancient
techniques of resources exploitation, inside the lagoons and offshore.
They can also be used as chronological and cultural indicators. The
shapes and dimensions of these artifacts allow comparisons and
classifications used in both functional approach and chrono-cultural
perspective. Hence it is very important for the ethno-archaeologists
to dispose of reliable methods and standardized measurement of
these artifacts. Such a reliable objective and standardized method
have been previously proposed. But this method cannot be envisaged
manually because of the very important time required to measure
each fishhook manually and the quantity of fishhooks to measure
(many hundreds). We propose in this paper a detailed acquisition
protocol of fishhooks and an automation of every step of this method.
We also provide some experimental results obtained on the fishhooks
coming from three archaeological excavations sites.
Abstract: This paper regards the phenomena of intensive suburbanization and urbanization in Olomouc city and in Olomouc region in general for the period of 1986–2009. A Remote Sensing approach that involves tracking of changes in Land Cover units is proposed to quantify the urbanization state and trends in temporal and spatial aspects. It actually consisted of two approaches, Experiment 1 and Experiment 2 which implied two different image classification solutions in order to provide Land Cover maps for each 1986–2009 time split available in the Landsat image set. Experiment 1 dealt with the unsupervised classification, while Experiment 2 involved semi- supervised classification, using a combination of object-based and pixel-based classifiers. The resulting Land Cover maps were subsequently quantified for the proportion of urban area unit and its trend through time, and also for the urban area unit stability, yielding the relation of spatial and temporal development of the urban area unit. Some outcomes seem promising but there is indisputably room for improvements of source data and also processing and filtering.
Abstract: The medical data statistical analysis often requires the
using of some special techniques, because of the particularities of
these data. The principal components analysis and the data clustering
are two statistical methods for data mining very useful in the medical
field, the first one as a method to decrease the number of studied
parameters, and the second one as a method to analyze the
connections between diagnosis and the data about the patient-s
condition. In this paper we investigate the implications obtained from
a specific data analysis technique: the data clustering preceded by a
selection of the most relevant parameters, made using the principal
components analysis. Our assumption was that, using the principal
components analysis before data clustering - in order to select and to
classify only the most relevant parameters – the accuracy of
clustering is improved, but the practical results showed the opposite
fact: the clustering accuracy decreases, with a percentage
approximately equal with the percentage of information loss reported
by the principal components analysis.
Abstract: This paper proposed classification models that would
be used as a proxy for hard disk drive (HDD) functional test equitant
which required approximately more than two weeks to perform the
HDD status classification in either “Pass" or “Fail". These models
were constructed by using committee network which consisted of a
number of single neural networks. This paper also included the
method to solve the problem of sparseness data in failed part, which
was called “enforce learning method". Our results reveal that the
constructed classification models with the proposed method could
perform well in the sparse data conditions and thus the models,
which used a few seconds for HDD classification, could be used to
substitute the HDD functional tests.
Abstract: A trustworthy voting process in democratic is
important that each vote is recorded with accuracy and impartiality.
The accuracy and impartiality are tallied in high rate with biometric
system. One of the sign is a fingerprint. Fingerprint recognition is
still a challenging problem, because of the distortions among the
different impression of the same finger. Because of the trustworthy of
biometric voting technologies, it may give a great effect on numbers
of voter-s participation and outcomes of the democratic process.
Hence in this study, the authors are interested in designing and
analyzing the Electronic Voting System and the participation of the
users. The system is based on the fingerprint minutiae with the
addition of person ID number. This is in order to enhance the
accuracy and speed of the voting process. The new design is analyzed
by conducting pilot election among a class of students for selecting
their representative.
Abstract: FAQ system can make user find answer to the problem that puzzles them. But now the research on Chinese FAQ system is still on the theoretical stage. This paper presents an approach to semantic inference for FAQ mining. To enhance the efficiency, a small pool of the candidate question-answering pairs retrieved from the system for the follow-up work according to the concept of the agriculture domain extracted from user input .Input queries or questions are converted into four parts, the question word segment (QWS), the verb segment (VS), the concept of agricultural areas segment (CS), the auxiliary segment (AS). A semantic matching method is presented to estimate the similarity between the semantic segments of the query and the questions in the pool of the candidate. A thesaurus constructed from the HowNet, a Chinese knowledge base, is adopted for word similarity measure in the matcher. The questions are classified into eleven intension categories using predefined question stemming keywords. For FAQ mining, given a query, the question part and answer part in an FAQ question-answer pair is matched with the input query, respectively. Finally, the probabilities estimated from these two parts are integrated and used to choose the most likely answer for the input query. These approaches are experimented on an agriculture FAQ system. Experimental results indicate that the proposed approach outperformed the FAQ-Finder system in agriculture FAQ retrieval.
Abstract: A robust still image face localization algorithm
capable of operating in an unconstrained visual environment is
proposed. First, construction of a robust skin classifier within a
shifted HSV color space is described. Then various filtering
operations are performed to better isolate face candidates and
mitigate the effect of substantial non-skin regions. Finally, a novel
Bhattacharyya-based face detection algorithm is used to compare
candidate regions of interest with a unique illumination-dependent
face model probability distribution function approximation.
Experimental results show a 90% face detection success rate despite
the demands of the visually noisy environment.
Abstract: Due to the constant increase in the volume of information available to applications in fields varying from medical diagnosis to web search engines, accurate support of similarity becomes an important task. This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision. We present a novel approach to filtering based solely on layout, whose goal is not only to correctly identify spam, but also warn about major emerging threats. We propose a mathematical formulation of the email message layout and based on it we elaborate an algorithm to separate different types of emails and find the new, numerically relevant spam types.
Abstract: When dealing with safety in structures, the connections between structural components play an important role. Robustness of a structure as a whole depends both on the load- bearing capacity of the structural component and on the structures capacity to resist total failure, even though a local failure occurs in a component or a connection between components. To avoid progressive collapse it is necessary to be able to carry out a design for connections. A connection may be executed with anchors to withstand local failure of the connection in structures built with prefabricated components. For the design of these anchors, a model is developed for connections in structures performed in prefabricated autoclaved aerated concrete components. The design model takes into account the effect of anchors placed close to the edge, which may result in splitting failure. Further the model is developed to consider the effect of reinforcement diameter and anchor depth. The model is analytical and theoretically derived assuming a static equilibrium stress distribution along the anchor. The theory is compared to laboratory test, including the relevant parameters and the model is refined and theoretically argued analyzing the observed test results. The method presented can be used to improve safety in structures or even optimize the design of the connections
Abstract: Learning using labeled and unlabelled data has
received considerable amount of attention in the machine learning
community due its potential in reducing the need for expensive
labeled data. In this work we present a new method for combining
labeled and unlabeled data based on classifier ensembles. The model
we propose assumes each classifier in the ensemble observes the
input using different set of features. Classifiers are initially trained
using some labeled samples. The trained classifiers learn further
through labeling the unknown patterns using a teaching signals that is
generated using the decision of the classifier ensemble, i.e. the
classifiers self-supervise each other. Experiments on a set of object
images are presented. Our experiments investigate different classifier
models, different fusing techniques, different training sizes and
different input features. Experimental results reveal that the proposed
self-supervised ensemble learning approach reduces classification
error over the single classifier and the traditional ensemble classifier
approachs.
Abstract: To coop with urbanization issues and the economic need for expansion, the city of Jakarta is planning to reclaim more land in the Jakarta Bay. However, the reclamation activities of some islands have barely started and already the developers are facing difficulties in finding sufficient quantities of sand as fill material. When addressing the problem of sand scarcity in the case of Jakarta where, an excess of waste production, an inadequate solid waste management system and a lack of dumping ground pose a major problem, it is hard not to think of the use of waste as alternative fill material. This paper analyses the possibilities of using waste in the land reclamation projects, considering the governmental, social, environmental and economic context of the city. The results identify types of waste that could be used, ways of using those types of waste and implementation conditions for the city of Jakarta.