Abstract: As the Internet technology has developed rapidly, the
number of identities (IDs) managed by each individual person has
increased and various ID management technologies have been
developed to assist users. However, most of these technologies are
vulnerable to the existing hacking methods such as phishing attacks
and key-logging. If the administrator-s password is exposed, an
attacker can access the entire contents of the stolen user-s data files in
other devices. To solve these problems, we propose here a new ID
management scheme based on a Single Password Protocol. The paper
presents the details of the new scheme as well as a formal analysis of
the method using BAN Logic.
Abstract: The aim of this study was to establish the feasibility of a minute incremental exercise testing protocol in young asthma children. Twenty-two children with clinically diagnosed mild to moderate asthma volunteered to participate. The maximum incremental exercise test was performed using a cycle ergometer with an electromagnetic braking. A warm-up unloaded for 2 minutes then the workload was started at 40 watts for 2 minutes, and then stepwise increments of 8 watts per 2 minutes were applied. The pedaling frequency was set at 50 rpm. Ventilation and gas exchange were measured with a breath-by-breath automatic metabolic measurement system. Results showed that this test was well tolerated by all asthmatic children. Most of the children reached the VO2 plateau and satisfied the criteria for maximal respiratory exchange ratio of ≥ 1. This Study demonstrated that this testing protocol was suitable for young asthmatic children.
Abstract: Purpose: To explore the use of Curvelet transform to
extract texture features of pulmonary nodules in CT image and support
vector machine to establish prediction model of small solitary
pulmonary nodules in order to promote the ratio of detection and
diagnosis of early-stage lung cancer. Methods: 2461 benign or
malignant small solitary pulmonary nodules in CT image from 129
patients were collected. Fourteen Curvelet transform textural features
were as parameters to establish support vector machine prediction
model. Results: Compared with other methods, using 252 texture
features as parameters to establish prediction model is more proper.
And the classification consistency, sensitivity and specificity for the
model are 81.5%, 93.8% and 38.0% respectively. Conclusion: Based
on texture features extracted from Curvelet transform, support vector
machine prediction model is sensitive to lung cancer, which can
promote the rate of diagnosis for early-stage lung cancer to some
extent.
Abstract: In this paper, a method to detect multiple ellipses is presented. The technique is efficient and robust against incomplete ellipses due to partial occlusion, noise or missing edges and outliers. It is an iterative technique that finds and removes the best ellipse until no reasonable ellipse is found. At each run, the best ellipse is extracted from randomly selected edge patches, its fitness calculated and compared to a fitness threshold. RANSAC algorithm is applied as a sampling process together with the Direct Least Square fitting of ellipses (DLS) as the fitting algorithm. In our experiment, the method performs very well and is robust against noise and spurious edges on both synthetic and real-world image data.
Abstract: The efficient knowledge management system (KMS)
is one of the important strategies to help firms to achieve sustainable
competitive advantages, but little research has been conducted to
understand what contributes to the KMS success. This study thus set
to investigate the determinants of KMS success in the context of Thai
banking industry. A questionnaire survey was conducted in four
major Thai Banks to test the proposed KMS Success model.
The result of this study shows that KMS use and user satisfaction
relate significantly to the success of KMS, and knowledge quality,
service quality and trust lead to system use, and knowledge quality,
system quality and trust lead to user satisfaction. However, this
research focuses only on system and user-related factors. Future
research thus can extend to study factors such as management support
and organization readiness.
Abstract: This paper describes a 3D modeling system in
Augmented Reality environment, named 3DARModeler. It can be
considered a simple version of 3D Studio Max with necessary
functions for a modeling system such as creating objects, applying
texture, adding animation, estimating real light sources and casting
shadows. The 3DARModeler introduces convenient, and effective
human-computer interaction to build 3D models by combining both
the traditional input method (mouse/keyboard) and the tangible input
method (markers). It has the ability to align a new virtual object with
the existing parts of a model. The 3DARModeler targets nontechnical
users. As such, they do not need much knowledge of
computer graphics and modeling techniques. All they have to do is
select basic objects, customize their attributes, and put them together
to build a 3D model in a simple and intuitive way as if they were
doing in the real world. Using the hierarchical modeling technique,
the users are able to group several basic objects to manage them as a
unified, complex object. The system can also connect with other 3D
systems by importing and exporting VRML/3Ds Max files. A
module of speech recognition is included in the system to provide
flexible user interfaces.
Abstract: Propagation of solitons in single-mode birefringent fibers is considered under the presence of third-order dispersion (TOD). The behavior of two neighboring solitons and their interaction is investigated under the presence of third-order dispersion with different group velocity dispersion (GVD) parameters. It is found that third-order dispersion makes the resultant soliton to deviate from its ideal position and increases the interaction between adjacent soliton pulses. It is also observed that this deviation due to third-order dispersion is considerably small when the optical pulse propagates at wavelengths relatively far from the zerodispersion. Modified coupled nonlinear Schrödinger-s equations (CNLSE) representing the propagation of optical pulse in single mode fiber with TOD are solved using split-step Fourier algorithm. The results presented in this paper reveal that the third-order dispersion can substantially increase the interaction between the solitons, but large group velocity dispersion reduces the interaction between neighboring solitons.
Abstract: Pearson-s correlation coefficient and sequential path
analysis has been used for determining the interrelationship among
yield, yield components, soil minerals and aroma of Khao Dawk Mali
(KDML) 105 rice grown in the area of Tungkularonghai in Roi-Et
province, located in the northeast of Thailand. Pearson-s correlation
coefficient in this study showed that the number of panicles was the
only factor that had positive significant (0.790**) effect on grain
yield. Sequential path analysis revealed that the number of panicles
followed by the number of fertile spikelets and 100-grain weight
were the first-order factors which had positive direct effects on grain
yield. Whereas, other factors analyzed had indirect effects
influencing grain yield. This study also indicated that no significant
relationship was found between the aroma level and any of the
factors analyzed.
Abstract: Company mergers and acquisitions reached their peak
in the twenty-first century. Mergers and acquisitions have become one
of the competitive strategies for external growth. In general, it is
believed that mergers and acquisitions can create synergies. However,
they require complete information technology system and service
integration, especially in the banking industry. Much of the research
has focused on performance evaluation, shareholder equity allocation,
or even the increase of company market value after the merger and
acquisition, whereas few scholars have focused on information system
integration post merger and acquisition. This study indicates the role
of information systems after a merger and acquisition, explaining the
benefits of information system integration using a merger and
acquisition case in the banking industry as an example. In addition, we
discuss factors that affect the performance of information system
integration, and utilize system dynamics to interpret the relationship
among factors that affect information system integration performance
in the banking industry after a merger and acquisition.
Abstract: Frequently a group of people jointly decide and authorize
a specific person as a representative in some business/poitical
occasions, e.g., the board of a company authorizes the chief executive
officer to close a multi-billion acquisition deal. In this paper, an
integrated proxy multi-signature scheme that allows anonymously
vetoable delegation is proposed. This protocol integrates mechanisms
of private veto, distributed proxy key generation, secure transmission
of proxy key, and existentially unforgeable proxy multi-signature
scheme. First, a provably secure Guillou-Quisquater proxy signature
scheme is presented, then the “zero-sharing" protocol is extended
over a composite modulus multiplicative group, and finally the above
two are combined to realize the GQ proxy multi-signature with
anonymously vetoable delegation. As a proxy signature scheme, this
protocol protects both the original signers and the proxy signer.
The modular design allows simplified implementation with less
communication overheads and better computation performance than
a general secure multi-party protocol.
Abstract: Most fingerprint recognition techniques are based on minutiae matching and have been well studied. However, this technology still suffers from problems associated with the handling of poor quality impressions. One problem besetting fingerprint matching is distortion. Distortion changes both geometric position and orientation, and leads to difficulties in establishing a match among multiple impressions acquired from the same finger tip. Marking all the minutiae accurately as well as rejecting false minutiae is another issue still under research. Our work has combined many methods to build a minutia extractor and a minutia matcher. The combination of multiple methods comes from a wide investigation into research papers. Also some novel changes like segmentation using Morphological operations, improved thinning, false minutiae removal methods, minutia marking with special considering the triple branch counting, minutia unification by decomposing a branch into three terminations, and matching in the unified x-y coordinate system after a two-step transformation are used in the work.
Abstract: A feature weighting and selection method is proposed
which uses the structure of a weightless neuron and exploits the
principles that govern the operation of Genetic Algorithms and
Evolution. Features are coded onto chromosomes in a novel way
which allows weighting information regarding the features to be
directly inferred from the gene values. The proposed method is
significant in that it addresses several problems concerned with
algorithms for feature selection and weighting as well as providing
significant advantages such as speed, simplicity and suitability for
real-time systems.
Abstract: Methods of contemporary mathematical physics such
as chaos theory are useful for analyzing and understanding the
behavior of complex biological and physiological systems. The three
dimensional model of HIV/AIDS is the basis of active research since
it provides a complete characterization of disease dynamics and the
interaction of HIV-1 with the immune system. In this work, the
behavior of the HIV system is analyzed using the three dimensional
HIV model and a chaotic measure known as the Hurst exponent.
Results demonstrate that Hurst exponents of CD4, CD8 cells and
viral load vary nonlinearly with respect to variations in system
parameters. Further, it was observed that the three dimensional HIV
model can accommodate both persistent (H>0.5) and anti-persistent
(H
Abstract: Acoustical properties of speech have been shown to
be related to mental states of speaker with symptoms: depression
and remission. This paper describes way to address the issue of
distinguishing depressed patients from remitted subjects based on
measureable acoustics change of their spoken sound. The vocal-tract
related frequency characteristics of speech samples from female
remitted and depressed patients were analyzed via speech
processing techniques and consequently, evaluated statistically by
cross-validation with Support Vector Machine. Our results
comparatively show the classifier's performance with effectively
correct separation of 93% determined from testing with the subjectbased
feature model and 88% from the frame-based model based on
the same speech samples collected from hospital visiting interview
sessions between patients and psychiatrists.
Abstract: The evolutionary tree is an important topic in bioinformation. In 2006, Chen and Lindsay proposed a new method to build the mixture tree from DNA sequences. Mixture tree is a new type evolutionary tree, and it has two additional information besides the information of ordinary evolutionary tree. One of the information is time parameter, and the other is the set of mutated sites. In 2008, Lin and Juan proposed an algorithm to compute the distance between two mixture trees. Their algorithm computes the distance with only considering the time parameter between two mixture trees. In this paper, we proposes a method to measure the similarity of two mixture trees with considering the set of mutated sites and develops two algorithm to compute the distance between two mixture trees. The time complexity of these two proposed algorithms are O(n2 × max{h(T1), h(T2)}) and O(n2), respectively
Abstract: Association rules are an important problem in data
mining. Massively increasing volume of data in real life databases
has motivated researchers to design novel and incremental algorithms
for association rules mining. In this paper, we propose an incremental
association rules mining algorithm that integrates shocking
interestingness criterion during the process of building the model. A
new interesting measure called shocking measure is introduced. One
of the main features of the proposed approach is to capture the user
background knowledge, which is monotonically augmented. The
incremental model that reflects the changing data and the user beliefs
is attractive in order to make the over all KDD process more
effective and efficient. We implemented the proposed approach and
experiment it with some public datasets and found the results quite
promising.
Abstract: Vitamin A deficiency is a public health problem in
Zimbabwe. Addressing vitamin A deficiency has the potential of
enhancing resistance to disease and reducing mortality especially in
children less than 5 years. We implemented and adapted vitamin A
outreach supplementation strategy within the National Immunization
Days and Extended Programme of Immunization in a rural district in
Zimbabwe. Despite usual operational challenges faced this approach
enabled the district to increase delivery of supplementation coverage.
This paper describes the outreach strategy that was implemented in
the remote rural district. The strategy covered 63 outreach sites with
2 sites being covered per day and visited once per month for the
whole year. Coverage reached 71% in an area of previous coverage
rates of around less than 50%. We recommend further exploration of
this strategy by others working in similar circumstances. This
strategy can be a potential way for use by Scaling-Up-Nutrition
member states.
Abstract: An automated wood recognition system is designed to
classify tropical wood species.The wood features are extracted based
on two feature extractors: Basic Grey Level Aura Matrix (BGLAM)
technique and statistical properties of pores distribution (SPPD)
technique. Due to the nonlinearity of the tropical wood species
separation boundaries, a pre classification stage is proposed which
consists ofKmeans clusteringand kernel discriminant analysis (KDA).
Finally, Linear Discriminant Analysis (LDA) classifier and KNearest
Neighbour (KNN) are implemented for comparison purposes.
The study involves comparison of the system with and without pre
classification using KNN classifier and LDA classifier.The results
show that the inclusion of the pre classification stage has improved
the accuracy of both the LDA and KNN classifiers by more than
12%.
Abstract: This paper presents an evaluation for a wavelet-based
digital watermarking technique used in estimating the quality of
video sequences transmitted over Additive White Gaussian Noise
(AWGN) channel in terms of a classical objective metric, such as
Peak Signal-to-Noise Ratio (PSNR) without the need of the original
video. In this method, a watermark is embedded into the Discrete
Wavelet Transform (DWT) domain of the original video frames
using a quantization method. The degradation of the extracted
watermark can be used to estimate the video quality in terms of
PSNR with good accuracy. We calculated PSNR for video frames
contaminated with AWGN and compared the values with those
estimated using the Watermarking-DWT based approach. It is found
that the calculated and estimated quality measures of the video
frames are highly correlated, suggesting that this method can provide
a good quality measure for video frames transmitted over AWGN
channel without the need of the original video.