Abstract: Frequent pattern mining is the process of finding a
pattern (a set of items, subsequences, substructures, etc.) that occurs
frequently in a data set. It was proposed in the context of frequent
itemsets and association rule mining. Frequent pattern mining is used
to find inherent regularities in data. What products were often
purchased together? Its applications include basket data analysis,
cross-marketing, catalog design, sale campaign analysis, Web log
(click stream) analysis, and DNA sequence analysis. However, one of
the bottlenecks of frequent itemset mining is that as the data increase
the amount of time and resources required to mining the data
increases at an exponential rate. In this investigation a new algorithm
is proposed which can be uses as a pre-processor for frequent itemset
mining. FASTER (FeAture SelecTion using Entropy and Rough sets)
is a hybrid pre-processor algorithm which utilizes entropy and roughsets
to carry out record reduction and feature (attribute) selection
respectively. FASTER for frequent itemset mining can produce a
speed up of 3.1 times when compared to original algorithm while
maintaining an accuracy of 71%.
Abstract: Two types of commercial cylindrical lithium ion
batteries (Panasonic 3.4 Ah NCR-18650B and Samsung 2.9 Ah
INR-18650), were investigated experimentally. The capacities of these
samples were individually measured using constant current-constant
voltage (CC-CV) method at different ambient temperatures (-10°C,
0°C, 25°C). Their internal resistance was determined by
electrochemical impedance spectroscopy (EIS) and pulse discharge
methods. The cells with different configurations of parallel connection
NCR-NCR, INR-INR and NCR-INR were charged/discharged at the
aforementioned ambient temperatures. The results showed that the
difference of internal resistance between cells much more evident at
low temperatures. Furthermore, the parallel connection of NCR-NCR
exhibits the most uniform temperature distribution in cells at -10°C,
this feature is quite favorable for the safety of the battery pack.
Abstract: The importance of the formal specification in the
software life cycle is barely concealing to anyone. Formal
specifications use mathematical notation to describe the properties of
information system precisely, without unduly constraining the way in
how these properties are achieved. Having a correct and quality
software specification is not easy task. This study concerns with how
a group of rectifiers can communicate with each other and work to
prepare and produce a correct formal software specification. WBCS
has been implemented based mainly in the proposed supported
cooperative work model and a survey conducted on the existing Webbased
collaborative writing tools. This paper aims to assess the
feasibility of executing the web-based collaboration process using
WBCS. The purpose of conducting this test is to test the system as a
whole for functionality and fitness for use based on the evaluation
test plan.
Abstract: The generalized wave equation models various
problems in sciences and engineering. In this paper, a new three-time
level implicit approach based on cubic trigonometric B-spline for the
approximate solution of wave equation is developed. The usual finite
difference approach is used to discretize the time derivative while
cubic trigonometric B-spline is applied as an interpolating function in
the space dimension. Von Neumann stability analysis is used to
analyze the proposed method. Two problems are discussed to exhibit
the feasibility and capability of the method. The absolute errors and
maximum error are computed to assess the performance of the
proposed method. The results were found to be in good agreement
with known solutions and with existing schemes in literature.
Abstract: Concerns on corrosion and effective coating
protection of double hull tankers and bulk carriers in service have
been raised especially in water ballast tanks (WBTs). Test
protocols/methodologies specifically that which is incorporated in the
International Maritime Organisation (IMO), Performance Standard
for Protective Coatings for Dedicated Sea Water ballast tanks (PSPC)
are being used to assess and evaluate the performance of the coatings
for type approval prior to their application in WBTs. However, some
of the type approved coatings may be applied as very thick films to
less than ideally prepared steel substrates in the WBT. As such films
experience hygrothermal cycling from operating and environmental
conditions, they become embrittled which may ultimately result in
cracking. This embrittlement of the coatings is identified as an
undesirable feature in the PSPC but is not mentioned in the test
protocols within it. There is therefore renewed industrial research
aimed at understanding this issue in order to eliminate cracking and
achieve the intended coating lifespan of 15 years in good condition.
This paper will critically review test protocols currently used for
assessing and evaluating coating performance, particularly the IMO
PSPC.
Abstract: Consumer-to-Consumer (C2C) E-commerce has been
growing at a very high speed in recent years. Since identical or
nearly-same kinds of products compete one another by relying on
keyword search in C2C E-commerce, some sellers describe their
products with spam keywords that are popular but are not related to
their products. Though such products get more chances to be retrieved
and selected by consumers than those without spam keywords,
the spam keywords mislead the consumers and waste their time.
This problem has been reported in many commercial services like
ebay and taobao, but there have been little research to solve this
problem. As a solution to this problem, this paper proposes a method
to classify whether keywords of a product are spam or not. The
proposed method assumes that a keyword for a given product is
more reliable if the keyword is observed commonly in specifications
of products which are the same or the same kind as the given
product. This is because that a hierarchical category of a product
in general determined precisely by a seller of the product and so is
the specification of the product. Since higher layers of the hierarchical
category represent more general kinds of products, a reliable degree
is differently determined according to the layers. Hence, reliable
degrees from different layers of a hierarchical category become
features for keywords and they are used together with features only
from specifications for classification of the keywords. Support Vector
Machines are adopted as a basic classifier using the features, since
it is powerful, and widely used in many classification tasks. In
the experiments, the proposed method is evaluated with a golden
standard dataset from Yi-han-wang, a Chinese C2C E-commerce,
and is compared with a baseline method that does not consider
the hierarchical category. The experimental results show that the
proposed method outperforms the baseline in F1-measure, which
proves that spam keywords are effectively identified by a hierarchical
category in C2C E-commerce.
Abstract: In this paper the issue of dimensionality reduction is
investigated in finger vein recognition systems using kernel Principal
Component Analysis (KPCA). One aspect of KPCA is to find the
most appropriate kernel function on finger vein recognition as there
are several kernel functions which can be used within PCA-based
algorithms. In this paper, however, another side of PCA-based
algorithms -particularly KPCA- is investigated. The aspect of
dimension of feature vector in PCA-based algorithms is of
importance especially when it comes to the real-world applications
and usage of such algorithms. It means that a fixed dimension of
feature vector has to be set to reduce the dimension of the input and
output data and extract the features from them. Then a classifier is
performed to classify the data and make the final decision. We
analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in
this paper and investigate the optimal feature extraction dimension in
finger vein recognition using KPCA.
Abstract: The construction of a new airport or the extension of
an existing one requires massive investments and many times public
private partnerships were considered in order to make feasible such
projects. One characteristic of these projects is uncertainty with
respect to financial and environmental impacts on the medium to long
term. Another one is the multistage nature of these types of projects.
While many airport development projects have been a success, some
others have turned into a nightmare for their promoters.
This communication puts forward a new approach for airport
investment risk assessment. The approach takes explicitly into
account the degree of uncertainty in activity levels prediction and
proposes milestones for the different stages of the project for
minimizing risk. Uncertainty is represented through fuzzy dual theory
and risk management is performed using dynamic programming. An
illustration of the proposed approach is provided.
Abstract: Analysis of real life problems often results in linear
systems of equations for which solutions are sought. The method to
employ depends, to some extent, on the properties of the coefficient
matrix. It is not always feasible to solve linear systems of equations
by direct methods, as such the need to use an iterative method
becomes imperative. Before an iterative method can be employed
to solve a linear system of equations there must be a guaranty that
the process of solution will converge. This guaranty, which must
be determined apriori, involve the use of some criterion expressible
in terms of the entries of the coefficient matrix. It is, therefore,
logical that the convergence criterion should depend implicitly on the
algebraic structure of such a method. However, in deference to this
view is the practice of conducting convergence analysis for Gauss-
Seidel iteration on a criterion formulated based on the algebraic
structure of Jacobi iteration. To remedy this anomaly, the Gauss-
Seidel iteration was studied for its algebraic structure and contrary
to the usual assumption, it was discovered that some property of the
iteration matrix of Gauss-Seidel method is only diagonally dominant
in its first row while the other rows do not satisfy diagonal dominance.
With the aid of this structure we herein fashion out an improved
version of Gauss-Seidel iteration with the prospect of enhancing
convergence and robustness of the method. A numerical section is
included to demonstrate the validity of the theoretical results obtained
for the improved Gauss-Seidel method.
Abstract: Roof top rainwater harvesting (RWH) has been
carried out worldwide to provide an inexpensive source of water for
many people. This research aims at evaluating the potential of roof
top rain water harvesting as a resource in Jordan. For the purpose of
this work, two case studies at Al-Jubiha and Shafa-Badran districts in
Amman city were selected. All existing rooftops in both districts
were identified by digitizing 2012 satellite images of the two districts
using Google earth and ArcGIS tools. Rational method was used to
estimate the potential volume of rainwater that can be harvested from
the digitized rooftops. Results indicated that 1.17 and 0.526 MCM/yr
can be harvested in Al-Jubiha and Shafa-Badran districts,
respectively. This study should increase the attention to the
importance of implementing RWH technique in Jordanian residences
as a viable alternative for ensuring a continued source of non-potable
water.
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: We present our approach on using continuous delivery
pattern for release management. One of the key practices of agile and
lean teams is the continuous delivery of new features to stakeholders.
The main benefits of this approach lie in the ability to release new
applications rapidly which has real strategic impact on the
competitive advantage of an organization. Organizations that
successfully implement Continuous Delivery have the ability to
evolve rapidly to support innovation, provide stable and reliable
software in more efficient ways, decrease the amount of resources
need for maintenance, and lower the software delivery time and costs.
One of the objectives of this paper is to elaborate a case study where
IT division of Central Securities Depository Institution (MKK) of
Turkey apply Continuous Delivery pattern to improve release
management process.
Abstract: As Malaysia aims to be a developed country by year 2020; the construction industry has since been identified as a major catalyst for the country to attain the status. It is one of the sectors that contribute to most environmental pollutions. It is, therefore, important for the industry to implement sustainable construction practices to reduce the negative impacts that it has on the environment. However, most Malaysian developers have placed much focus on market demand and economic factors; neglecting the need for attention on environmental issues. The practice of sustainable construction is deemed to be an obstacle to achieve short-term economic goals due to the higher cost incurred in the operations. Hence, choices need to be made and a balance needs to be struck in weighing the long-term environmental benefits against immediate economic factors. This paper discusses the challenges faced by Malaysian developers in adopting sustainable practices in the construction industry and the cause of these challenges. It also looks into the achievements and breakthroughs that developers in Malaysia have achieved so far. The paper aims explores the long-term benefits of sustainable practices that would potentially raise awareness on the feasibility and economic potential of sustainable construction.
Abstract: An extensive amount of work has been done in data
clustering research under the unsupervised learning technique in Data
Mining during the past two decades. Moreover, several approaches
and methods have been emerged focusing on clustering diverse data
types, features of cluster models and similarity rates of clusters.
However, none of the single clustering algorithm exemplifies its best
nature in extracting efficient clusters. Consequently, in order to
rectify this issue, a new challenging technique called Cluster
Ensemble method was bloomed. This new approach tends to be the
alternative method for the cluster analysis problem. The main
objective of the Cluster Ensemble is to aggregate the diverse
clustering solutions in such a way to attain accuracy and also to
improve the eminence the individual clustering algorithms. Due to
the massive and rapid development of new methods in the globe of
data mining, it is highly mandatory to scrutinize a vital analysis of
existing techniques and the future novelty. This paper shows the
comparative analysis of different cluster ensemble methods along
with their methodologies and salient features. Henceforth this
unambiguous analysis will be very useful for the society of clustering
experts and also helps in deciding the most appropriate one to resolve
the problem in hand.
Abstract: When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.
Abstract: Vertical slotted walls can be used as permeable
breakwaters to provide economical and environmental protection
from undesirable waves and currents inside the port. The permeable
breakwaters are partially protection and have been suggested to
overcome the environmental disadvantages of fully protection
breakwaters. For regular waves a semi-analytical model is based on
an eigenfunction expansion method and utilizes a boundary condition
at the surface of each wall are developed to detect the energy
dissipation through the slots. Extensive laboratory tests are carried
out to validate the semi-analytic models. The structure of the physical
model contains two walls and it consists of impermeable upper and
lower part, where the draft is based a decimal multiple of the total
depth. The middle part is permeable with a porosity of 50%. The
second barrier is located at a distant of 0.5, 1, 1.5 and 2 times of the
water depth from the first one. A comparison of the theoretical results
with previous studies and experimental measurements of the present
study show a good agreement and that, the semi-analytical model is
able to adequately reproduce most the important features of the
experiment.
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: The process of thermoforming a carbon fiber reinforced thermoplastic (CFRTP) has increased its presence in the automotive industry for its wide applicability to the mass production car. A non-isothermal forming for CFRTP can shorten its cycle time to less than 1 minute. In this paper, the textile reinforcement FE model which the authors proposed in a previous work is extended to the CFRTP model for non-isothermal forming simulation. The effect of thermoplastic is given by adding shell elements which consider thermal effect to the textile reinforcement model. By applying Reuss model to the stress calculation of thermoplastic, the proposed model can accurately predict in-plane shear behavior, which is the key deformation mode during forming, in the range of the process temperature. Using the proposed model, thermoforming simulation was conducted and the results are in good agreement with the experimental results.
Abstract: The impact deformation and fracture behaviour of cobalt-based Haynes 188 superalloy are investigated by means of a split Hopkinson pressure bar. Impact tests are performed at strain rates ranging from 1×103 s-1 to 5×103 s-1 and temperatures between 25°C and 800°C. The experimental results indicate that the flow response and fracture characteristics of cobalt-based Haynes 188 superalloy are significantly dependent on the strain rate and temperature. The flow stress, work hardening rate and strain rate sensitivity all increase with increasing strain rate or decreasing temperature. It is shown that the impact response of the Haynes 188 specimens is adequately described by the Zerilli-Armstrong fcc model. The fracture analysis results indicate that the Haynes 188 specimens fail predominantly as the result of intensive localised shearing. Furthermore, it is shown that the flow localisation effect leads to the formation of adiabatic shear bands. The fracture surfaces of the deformed Haynes 188 specimens are characterised by dimple- and / or cleavage-like structure with knobby features. The knobby features are thought to be the result of a rise in the local temperature to a value greater than the melting point.
Abstract: Time base maintenance (TBM) is conventionally applied by the power utilities to maintain circuit breakers (CBs), transformers, bus bars and cables, which may result in under maintenance or over maintenance. As information and communication technology (ICT) industry develops, the maintenance policies of many power utilities have gradually changed from TBM to condition base maintenance (CBM) to improve system operating efficiency, operation cost and power supply reliability. This paper discusses the feasibility of using intelligent electronic devices (IEDs) to construct a CB CBM management platform. CBs in power substations can be monitored using IEDs with additional logic configuration and wire connections. The CB monitoring data can be sent through intranet to a control center and be analyzed and integrated by the Elipse Power Studio software. Finally, a human-machine interface (HMI) of supervisory control and data acquisition (SCADA) system can be designed to construct a CBM management platform to provide maintenance decision information for the maintenance personnel, management personnel and CB manufacturers.