Abstract: Text Mining is around applying knowledge discovery
techniques to unstructured text is termed knowledge discovery in text
(KDT), or Text data mining or Text Mining. In decision tree
approach is most useful in classification problem. With this
technique, tree is constructed to model the classification process.
There are two basic steps in the technique: building the tree and
applying the tree to the database. This paper describes a proposed
C5.0 classifier that performs rulesets, cross validation and boosting
for original C5.0 in order to reduce the optimization of error ratio.
The feasibility and the benefits of the proposed approach are
demonstrated by means of medial data set like hypothyroid. It is
shown that, the performance of a classifier on the training cases from
which it was constructed gives a poor estimate by sampling or using a
separate test file, either way, the classifier is evaluated on cases that
were not used to build and evaluate the classifier are both are large. If
the cases in hypothyroid.data and hypothyroid.test were to be
shuffled and divided into a new 2772 case training set and a 1000
case test set, C5.0 might construct a different classifier with a lower
or higher error rate on the test cases. An important feature of see5 is
its ability to classifiers called rulesets. The ruleset has an error rate
0.5 % on the test cases. The standard errors of the means provide an
estimate of the variability of results. One way to get a more reliable
estimate of predictive is by f-fold –cross- validation. The error rate of
a classifier produced from all the cases is estimated as the ratio of the
total number of errors on the hold-out cases to the total number of
cases. The Boost option with x trials instructs See5 to construct up to
x classifiers in this manner. Trials over numerous datasets, large and
small, show that on average 10-classifier boosting reduces the error
rate for test cases by about 25%.
Abstract: Chloride induced corrosion of steel reinforcement is
the main cause of deterioration of reinforced concrete marine
structures. This paper investigates the relative performance of
alternative repair options with respect to the deterioration of
reinforced concrete bridge elements in marine environments. Focus is
placed on the initiation phase of reinforcement corrosion. A
laboratory study is described which involved exposing concrete
samples to accelerated chloride-ion ingress. The study examined the
relative efficiencies of two repair methods, namely Ordinary Portland
Cement (OPC) concrete and a concrete which utilised Ground
Granulated Blastfurnace Cement (GGBS) as a partial cement
replacement. The mix designs and materials utilised were identical to
those implemented in the repair of a marine bridge on the South East
coast of Ireland in 2007. The results of this testing regime serve to
inform input variables employed in probabilistic modelling of
deterioration for subsequent reliability based analysis to compare the
relative performance of the studied repair options.
Abstract: In the recent past, there has been an increasing interest
in applying evolutionary methods to Knowledge Discovery in
Databases (KDD) and a number of successful applications of Genetic
Algorithms (GA) and Genetic Programming (GP) to KDD have been
demonstrated. The most predominant representation of the
discovered knowledge is the standard Production Rules (PRs) in the
form If P Then D. The PRs, however, are unable to handle
exceptions and do not exhibit variable precision. The Censored
Production Rules (CPRs), an extension of PRs, were proposed by
Michalski & Winston that exhibit variable precision and supports an
efficient mechanism for handling exceptions. A CPR is an
augmented production rule of the form:
If P Then D Unless C, where C (Censor) is an exception to the rule.
Such rules are employed in situations, in which the conditional
statement 'If P Then D' holds frequently and the assertion C holds
rarely. By using a rule of this type we are free to ignore the exception
conditions, when the resources needed to establish its presence are
tight or there is simply no information available as to whether it
holds or not. Thus, the 'If P Then D' part of the CPR expresses
important information, while the Unless C part acts only as a switch
and changes the polarity of D to ~D.
This paper presents a classification algorithm based on evolutionary
approach that discovers comprehensible rules with exceptions in the
form of CPRs.
The proposed approach has flexible chromosome encoding, where
each chromosome corresponds to a CPR. Appropriate genetic
operators are suggested and a fitness function is proposed that
incorporates the basic constraints on CPRs. Experimental results are
presented to demonstrate the performance of the proposed algorithm.
Abstract: Principle component analysis is often combined with
the state-of-art classification algorithms to recognize human faces.
However, principle component analysis can only capture these
features contributing to the global characteristics of data because it is a
global feature selection algorithm. It misses those features
contributing to the local characteristics of data because each principal
component only contains some levels of global characteristics of data.
In this study, we present a novel face recognition approach using
non-negative principal component analysis which is added with the
constraint of non-negative to improve data locality and contribute to
elucidating latent data structures. Experiments are performed on the
Cambridge ORL face database. We demonstrate the strong
performances of the algorithm in recognizing human faces in
comparison with PCA and NREMF approaches.
Abstract: Internet is nowadays included to all National Curriculums of the elementary school. A comparative study of their
goals leads to the conclusion that a complete curriculum should aim to student-s acquisition of the abilities to navigate and search for
information and additionally to emphasize on the evaluation of the information provided by the World Wide Web. In a constructivistic knowledge framework the design of a course has to take under
consideration the conceptual representations of students. The following paper presents the conceptual representation of students of eleven years old, attending the Sixth Grade of Greek Elementary School about World Wide Web and their use in the design and
implementation of an innovative course.
Abstract: Human amniotic membrane (HAM) is a useful
biological material for the reconstruction of damaged ocular surface.
The processing and preservation of HAM is critical to prevent the
patients undergoing amniotic membrane transplant (AMT) from cross
infections. For HAM preparation human placenta is obtained after an
elective cesarean delivery. Before collection, the donor is screened
for seronegativity of HCV, Hbs Ag, HIV and Syphilis. After
collection, placenta is washed in balanced salt solution (BSS) in
sterile environment. Amniotic membrane is then separated from the
placenta as well as chorion while keeping the preparation in BSS.
Scrapping of HAM is then carried out manually until all the debris is
removed and clear transparent membrane is acquired. Nitrocellulose
membrane filters are then placed on the stromal side of HAM, cut
around the edges with little membrane folded towards other side
making it easy to separate during surgery. HAM is finally stored in
solution of glycerine and Dulbecco-s Modified Eagle Medium
(DMEM) in 1:1 ratio containing antibiotics. The capped borosil vials
containing HAM are kept at -80°C until use. This vial is thawed to
room temperature and opened under sterile operation theatre
conditions at the time of surgery.
Abstract: In the present paper, the three-dimensional
temperature field of tool is determined during the machining and
compared with experimental work on C45 workpiece using carbide
cutting tool inserts. During the metal cutting operations, high
temperature is generated in the tool cutting edge which influence on
the rate of tool wear. Temperature is most important characteristic of
machining processes; since many parameters such as cutting speed,
surface quality and cutting forces depend on the temperature and high
temperatures can cause high mechanical stresses which lead to early
tool wear and reduce tool life. Therefore, considerable attention is
paid to determine tool temperatures. The experiments are carried out
for dry and orthogonal machining condition. The results show that
the increase of tool temperature depends on depth of cut and
especially cutting speed in high range of cutting conditions.
Abstract: Many factors affect the success of Machine Learning
(ML) on a given task. The representation and quality of the instance
data is first and foremost. If there is much irrelevant and redundant
information present or noisy and unreliable data, then knowledge
discovery during the training phase is more difficult. It is well known
that data preparation and filtering steps take considerable amount of
processing time in ML problems. Data pre-processing includes data
cleaning, normalization, transformation, feature extraction and
selection, etc. The product of data pre-processing is the final training
set. It would be nice if a single sequence of data pre-processing
algorithms had the best performance for each data set but this is not
happened. Thus, we present the most well know algorithms for each
step of data pre-processing so that one achieves the best performance
for their data set.
Abstract: The objective of this study was to investigate hydrogen production from alcohol wastewater by anaerobic sequencing batch reactor (ASBR) under thermophillic operation. The ASBR unit used in this study had a liquid holding volume of 4 L and was operated at 6 cycles per day. The seed sludge taken from an upflow anaerobic sludge blanket unit treating the same wastewater was boiled at 95 °C for 15 min before being fed to the ASBR unit. The ASBR system was operated at different COD loading rates at a thermophillic temperature (55 °C), and controlled pH of 5.5. When the system was operated under optimum conditions (providing maximum hydrogen production performance) at a feed COD of 60 000 mg/l, and a COD loading rate of 68 kg/m3 d, the produced gas contained 43 % H2 content in the produced gas. Moreover, the hydrogen yield and the specific hydrogen production rate (SHPR) were 130 ml H2/g COD removed and 2100 ml H2/l d, respectively.
Abstract: Rule Discovery is an important technique for mining
knowledge from large databases. Use of objective measures for
discovering interesting rules leads to another data mining problem,
although of reduced complexity. Data mining researchers have
studied subjective measures of interestingness to reduce the volume
of discovered rules to ultimately improve the overall efficiency of
KDD process.
In this paper we study novelty of the discovered rules as a
subjective measure of interestingness. We propose a hybrid approach
based on both objective and subjective measures to quantify novelty
of the discovered rules in terms of their deviations from the known
rules (knowledge). We analyze the types of deviation that can arise
between two rules and categorize the discovered rules according to
the user specified threshold. We implement the proposed framework
and experiment with some public datasets. The experimental results
are promising.
Abstract: This research focuses on the effect of weight
percentage variation and size variation of MgFeSi added,
gating system design and reaction chamber design on inmold
process. By using inmold process, well-known problem of
fading is avoided because the liquid iron reacts with
magnesium in the mold and not, as usual, in the ladle. During
the pouring operation, liquid metal passes through the
chamber containing the magnesium, where the reaction of the
metal with magnesium proceeds in the absence of atmospheric
oxygen [1].In this paper, the results of microstructural
characteristic of ductile iron on this parameters are mentioned.
The mechanisms of the inmold process are also described [2].
The data obtained from this research will assist in producing
the vehicle parts and other machinery parts for different
industrial zones and government industries and in transferring
the technology to all industrial zones in Myanmar. Therefore,
the inmold technology offers many advantages over traditional
treatment methods both from a technical and environmental,
as well as an economical point of view. The main objective of
this research is to produce ductile iron castings in all industrial
sectors in Myanmar more easily with lower costs. It will also
assist the sharing of knowledge and experience related to the
ductile iron production.
Abstract: To offer a large variety of products while maintaining
low costs, high speed, and high quality in a mass customization
product development environment, platform based product
development has much benefit and usefulness in many industry fields.
This paper proposes a product configuration strategy by similarity
measure, incorporating the knowledge engineering principles such as
product information model, ontology engineering, and formal concept
analysis.
Abstract: A large number of semantic web service composition
approaches are developed by the research community and one is
more efficient than the other one depending on the particular
situation of use. So a close look at the requirements of ones particular
situation is necessary to find a suitable approach to use. In this paper,
we present a Technique Recommendation System (TRS) which using
a classification of state-of-art semantic web service composition
approaches, can provide the user of the system with the
recommendations regarding the use of service composition approach
based on some parameters regarding situation of use. TRS has
modular architecture and uses the production-rules for knowledge
representation.
Abstract: Knowledge about the magnetic quantities in a magnetic circuit is always of great interest. On the one hand, this information is needed for the simulation of a transformer. On the other hand, parameter studies are more reliable, if the magnetic quantities are derived from a well established model. One possibility to model the 3-phase transformer is by using a magnetic equivalent circuit (MEC). Though this is a well known system, it is often not an easy task to set up such a model for a large number of lumped elements which additionally includes the nonlinear characteristic of the magnetic material. Here we show the setup of a solver for a MEC and the results of the calculation in comparison to measurements taken. The equations of the MEC are based on a rearranged system of the nodal analysis. Thus it is possible to achieve a minimum number of equations, and a clear and simple structure. Hence, it is uncomplicated in its handling and it supports the iteration process. Additional helpful tasks are implemented within the solver to enhance the performance. The electric circuit is described by an electric equivalent circuit (EEC). Our results for the 3-phase transformer demonstrate the computational efficiency of the solver, and show the benefit of the application of a MEC.
Abstract: The main focus of this paper is on the human induced
forces. Almost all existing force models for this type of load (defined
either in the time or frequency domain) are developed from the
assumption of perfect periodicity of the force and are based on force
measurements conducted on rigid (i.e. high frequency) surfaces. To
verify the different authors conclusions the vertical pressure
measurements invoked during the walking was performed, using
pressure gauges in various configurations. The obtained forces are
analyzed using Fourier transformation. This load is often decisive in
the design of footbridges. Design criteria and load models proposed
by widely used standards and other researchers were introduced and a
comparison was made.
Abstract: Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.
Abstract: Today the intangible assets are the capital of knowledge and are the most important and the most valuable resource for organizations. All employees have knowledge independently of the kind of jobs they do. Knowledge is thus an asset, which influences business operations. The objective of this article is to identify knowledge continuity as an objective of business continuity management. The article has been prepared based on the analysis of secondary sources and the evaluation of primary sources of data by means of a quantitative survey conducted in the Czech Republic. The conclusion of the article is that organizations that apply business continuity management do not focus on the preservation of the knowledge of key employees. Organizations ensure knowledge continuity only intuitively, on a random basis, non-systematically and discontinuously. The non-ensuring of knowledge continuity represents a threat of loss of key knowledge for organizations and can also negatively affect business continuity.
Abstract: Globalization, supported by information and
communication technologies, changes the rules of competitiveness
and increases the significance of information, knowledge and
network cooperation. In line with this trend, the need for efficient
trust-building tools has emerged. The absence of trust building
mechanisms and strategies was identified within several studies.
Through trust development, participation on e-business network and
usage of network services will increase and provide to SMEs new
economic benefits. This work is focused on effective trust building
strategies development for electronic business network platforms.
Based on trust building mechanism identification, the questionnairebased
analysis of its significance and minimum level of requirements
was conducted. In the paper, we are confirming the trust dependency
on e-Skills which play crucial role in higher level of trust into the
more sophisticated and complex trust building ICT solutions.
Abstract: This research contribution propels the idea of collaborating environment for the execution of student satellite projects in the backdrop of project management principles. The recent past has witnessed a technological shift in the aerospace industry from the big satellite projects to the small spacecrafts especially for the earth observation and communication purposes. This vibrant shift has vitalized the academia and industry to share their resources and to create a win-win paradigm of mutual success and technological development along with the human resource development in the field of aerospace. Small student satellites are the latest jargon of academia and more than 100 CUBESAT projects have been executed successfully all over the globe and many new student satellite projects are in the development phase. The small satellite project management requires the application of specific knowledge, skills, tools and techniques to achieve the defined mission requirements. The Authors have presented the detailed outline for the project management of student satellites and presented the role of industry to collaborate with the academia to get the optimized results in academic environment.
Abstract: The purpose of this paper is to guide the effort in
improving the economic added value of Indonesian fisheries product
through post fishing program, which is cold storage program.
Indonesia's fisheries potential has been acknowledged by the world.
FAO (2009) stated that Indonesia is one of the tenth highest
producers of fishery products in the world. Based on BPS (Statistics
Indonesia data), the national fisheries production in 2011 reached
5.714 million tons, which 93.55% came from marine fisheries and
6.45% from open waters. Indonesian territory consist of 2/3 of
Indonesian waters, has given enormous benefits for Indonesia,
especially fishermen. To improve the economic level of fishermen
requires efforts to develop fisheries business unit. On of the efforts is
by improving the quality of products which are marketed in the
regional and international levels. It is certainly need the support of
the existence of various fishery facilities (infrastructure to
superstructure), one of which is cold storage. Given the many
benefits of cold storage as a means of processing of fishery resources,
Indonesia Maritime Security Coordinating Board (IMSCB) as one of
the maritime institutions for maritime security and safety, has a
program to empower the coastal community through encourages the
development of cold storage in the middle and lower fishery business
unit. The development of cold storage facilities which able to run its
maximum role requires synergistic efforts of various parties.