Abstract: The similarity comparison of RNA secondary
structures is important in studying the functions of RNAs. In recent
years, most existing tools represent the secondary structures by
tree-based presentation and calculate the similarity by tree alignment
distance. Different to previous approaches, we propose a new method
based on maximum clique detection algorithm to extract the maximum
common structural elements in compared RNA secondary structures.
A new graph-based similarity measurement and maximum common
subgraph detection procedures for comparing purely RNA secondary
structures is introduced. Given two RNA secondary structures, the
proposed algorithm consists of a process to determine the score of the
structural similarity, followed by comparing vertices labelling, the
labelled edges and the exact degree of each vertex. The proposed
algorithm also consists of a process to extract the common structural
elements between compared secondary structures based on a proposed
maximum clique detection of the problem. This graph-based model
also can work with NC-IUB code to perform the pattern-based
searching. Therefore, it can be used to identify functional RNA motifs
from database or to extract common substructures between complex
RNA secondary structures. We have proved the performance of this
proposed algorithm by experimental results. It provides a new idea of
comparing RNA secondary structures. This tool is helpful to those
who are interested in structural bioinformatics.
Abstract: On-board Error Detection and Correction (EDAC)
devices aim to secure data transmitted between the central
processing unit (CPU) of a satellite onboard computer and its local
memory. This paper presents a comparison of the performance of
four low complexity EDAC techniques for application in Random
Access Memories (RAMs) on-board small satellites. The
performance of a newly proposed EDAC architecture is measured
and compared with three different EDAC strategies, using the same
FPGA technology. A statistical analysis of single-event upset (SEU)
and multiple-bit upset (MBU) activity in commercial memories
onboard Alsat-1 is given for a period of 8 years
Abstract: Flat double-layer grid is from category of space structures that are formed from two flat layers connected together with diagonal members. Increased stiffness and better seismic resistance in relation to other space structures are advantages of flat double layer space structures. The objective of this study is assessment and calculation of Behavior factor of flat double layer space structures. With regarding that these structures are used widely but Behavior factor used to design these structures against seismic force is not determined and exact, the necessity of study is obvious. This study is theoretical. In this study we used structures with span length of 16m and 20 m. All connections are pivotal. ANSYS software is used to non-linear analysis of structures.
Abstract: The purpose of this study was to measure the maximal
isometric strength and to investigate the effects of different handleheights
and elbow angles with respect to Mid. sagittal plane on the
pushing and pulling strength in vertical direction. Eight male subjects
performed a series of static strength measurement for each subject.
The highest isometric strength was found in pulling at shoulder
height (S.H.) (Mean = 60.29 lb., SD = 16.78 lb.) and the lowest
isometric strength was found also in pulling at elbow height (E.H.)
(Mean = 33.06 lb., SD = 6.56 lb.). Although the isometric strengths
were higher at S.H than at E.H. for both activities, the maximal
isometric strengths were compared statistically. ANOVA was
performed. The results of the experiment revealed that there was a
significant different between handle heights. However, there were no
significant different between angles and activities, also no correlation
between grip strength and activities.
Abstract: In the recent years, high dynamic range imaging has
gain popularity with the advancement in digital photography. In this
contribution we present a subjective evaluation of various tone
production and tone mapping techniques by a number of participants.
Firstly, standard HDR images were used and the participants were
asked to rate them based on a given rating scheme. After that, the
participant was asked to rate HDR image generated using linear and
nonlinear combination approach of multiple exposure images. The
experimental results showed that linearly generated HDR images
have better visualization than the nonlinear combined ones. In
addition, Reinhard et al. and the exponential tone mapping operators
have shown better results compared to logarithmic and the Garrett et
al. tone mapping operators.
Abstract: Effectiveness of Artificial Neural Networks (ANN)
and Support Vector Machines (SVM) classifiers for fault diagnosis of
rolling element bearings are presented in this paper. The
characteristic features of vibration signals of rotating driveline that
was run in its normal condition and with faults introduced were used
as input to ANN and SVM classifiers. Simple statistical features such
as standard deviation, skewness, kurtosis etc. of the time-domain
vibration signal segments along with peaks of the signal and peak of
power spectral density (PSD) are used as features to input the ANN
and SVM classifier. The effect of preprocessing of the vibration
signal by Discreet Wavelet Transform (DWT) prior to feature
extraction is also studied. It is shown from the experimental results
that the performance of SVM classifier in identification of bearing
condition is better then ANN and pre-processing of vibration signal
by DWT enhances the effectiveness of both ANN and SVM classifier
Abstract: The electromagnetic spectrum is a natural resource
and hence well-organized usage of the limited natural resources is the
necessities for better communication. The present static frequency
allocation schemes cannot accommodate demands of the rapidly
increasing number of higher data rate services. Therefore, dynamic
usage of the spectrum must be distinguished from the static usage to
increase the availability of frequency spectrum. Cognitive radio is not
a single piece of apparatus but it is a technology that can incorporate
components spread across a network. It offers great promise for
improving system efficiency, spectrum utilization, more effective
applications, reduction in interference and reduced complexity of
usage for users. Cognitive radio is aware of its environmental,
internal state, and location, and autonomously adjusts its operations
to achieve designed objectives. It first senses its spectral environment
over a wide frequency band, and then adapts the parameters to
maximize spectrum efficiency with high performance. This paper
only focuses on the analysis of Bit-Error-Rate in cognitive radio by
using Particle Swarm Optimization Algorithm. It is theoretically as
well as practically analyzed and interpreted in the sense of
advantages and drawbacks and how BER affects the efficiency and
performance of the communication system.
Abstract: Although considerable amount of research has attested to the link between work-to-family conflict (WFC) and family-to-work conflict (FWC) and psychological strain and wellbeing, there is a paucity of research investigating the phenomenon in the context of social workers. Moreover, very little is known about the impact of WFC and FWC in developing countries. The present study investigated the mediating effect of psychological strain on the relationship between WFC and FWC with wellbeing of social workers in India. Our findings show that WFC and FWC are influential antecedents of wellbeing; their influence is both direct on psychological strain, and indirect on wellbeing transmitted through psychological strain. Implications of the findings are discussed.
Abstract: Vehicular Ad-Hoc Networks (VANET) can provide
communications between vehicles or infrastructures. It provides the
convenience of driving and the secure driving to reduce accidents. In
VANET, the security is more important because it is closely related to
accidents. Additionally, VANET raises a privacy issue because it can
track the location of vehicles and users- identity when a security
mechanism is provided. In this paper, we analyze the problem of an
existing solution for security requirements required in VANET, and
resolve the problem of the existing method when a key management
mechanism is provided for the security operation in VANET.
Therefore, we show suitability of the Long Term Evolution (LTE) in
VANET for the solution of this problem.
Abstract: Prospective readers can quickly determine whether a document is relevant to their information need if the significant phrases (or keyphrases) in this document are provided. Although keyphrases are useful, not many documents have keyphrases assigned to them, and manually assigning keyphrases to existing documents is costly. Therefore, there is a need for automatic keyphrase extraction. This paper introduces a new domain independent keyphrase extraction algorithm. The algorithm approaches the problem of keyphrase extraction as a classification task, and uses a combination of statistical and computational linguistics techniques, a new set of attributes, and a new machine learning method to distinguish keyphrases from non-keyphrases. The experiments indicate that this algorithm performs better than other keyphrase extraction tools and that it significantly outperforms Microsoft Word 2000-s AutoSummarize feature. The domain independence of this algorithm has also been confirmed in our experiments.
Abstract: The aim of the present paper is to investigate the
interdependency among ego-identity status, autobiographical memory
and cultural life story schema. The study shows considerable
differences between autobiographical memory characteristics and
“family script", which is typical for participants (adolescents, M age
years = 17.84, SD = 1.18, N = 58), with different ego-identity
statuses. Participants with diffused ego-identity status recalled fewer
autobiographical memories. Additionally, this group of participants
recalled fewer events from their parents- life. Participants with
moratorium ego-identity status dated their first recollections to a later
age than others, and recalled fewer memories relating to their
childhood. Participants with achieved identity status recalled more
self-defining memories and events from their parents- life. They used
more functions from the autobiographical memory. There weren-t
any significant differences between the foreclosed identity status
group and the others. These findings support the idea of a
bidirectional relation between culture, memory and self.
Abstract: Fractional Fourier Transform is a generalization of the
classical Fourier Transform. The Fractional Fourier span in general
depends on the amplitude and phase functions of the signal and varies
with the transform order. However, with the development of the
Fractional Fourier filter banks, it is advantageous in some cases to
have different transform orders for different filter banks to achieve
better decorrelation of the windowed and overlapped time signal. We
present an expression that is useful for finding the perturbation in the
Fractional Fourier span due to the erroneous transform order and the
possible variation in the window shape and length. The expression is
based on the dependency of the time-Fractional Fourier span
Uncertainty on the amplitude and phase function of the signal. We
also show with the help of the developed expression that the
perturbation of span has a varying degree of sensitivity for varying
degree of transform order and the window coefficients.
Abstract: Data mining uses a variety of techniques each of which
is useful for some particular task. It is important to have a deep
understanding of each technique and be able to perform sophisticated
analysis. In this article we describe a tool built to simulate a variation
of the Kohonen network to perform unsupervised clustering and
support the entire data mining process up to results visualization. A
graphical representation helps the user to find out a strategy to
optimize classification by adding, moving or delete a neuron in order
to change the number of classes. The tool is able to automatically
suggest a strategy to optimize the number of classes optimization, but
also support both tree classifications and semi-lattice organizations of
the classes to give to the users the possibility of passing from one
class to the ones with which it has some aspects in common.
Examples of using tree and semi-lattice classifications are given to
illustrate advantages and problems. The tool is applied to classify
macroeconomic data that report the most developed countries- import
and export. It is possible to classify the countries based on their
economic behaviour and use the tool to characterize the commercial
behaviour of a country in a selected class from the analysis of
positive and negative features that contribute to classes formation.
Possible interrelationships between the classes and their meaning are
also discussed.
Abstract: In this paper, we propose a practical digital music matching system that is robust to variation in sound qualities. The proposed system is subdivided into two parts: client and server. The client part consists of the input, preprocessing and feature extraction modules. The preprocessing module, including the music onset module, revises the value gap occurring on the time axis between identical songs of different formats. The proposed method uses delta-grouped Mel frequency cepstral coefficients (MFCCs) to extract music features that are robust to changes in sound quality. According to the number of sound quality formats (SQFs) used, a music server is constructed with a feature database (FD) that contains different sub feature databases (SFDs). When the proposed system receives a music file, the selection module selects an appropriate SFD from a feature database; the selected SFD is subsequently used by the matching module. In this study, we used 3,000 queries for matching experiments in three cases with different FDs. In each case, we used 1,000 queries constructed by mixing 8 SQFs and 125 songs. The success rate of music matching improved from 88.6% when using single a single SFD to 93.2% when using quadruple SFDs. By this experiment, we proved that the proposed method is robust to various sound qualities.
Abstract: A variable structure model reference adaptive control
(VS-MRAC) strategy for active steering assistance of a two wheel
steering car is proposed. An ideal steering system with fixed
properties and moving on an ideal road is used as the reference
model, and the active steering assistance system is forced to attain
the same behavior as the reference model. The proposed system can
treat the nonlinear relationships between the side slip angles and
lateral forces on tire, and the uncertainties on friction of the road
surface, whose compensation are very important under critical
situations. Simulation results show improvements on yaw rate and
side slip.
Abstract: Sustainability and sustainable development have been
the main theme of many international conferences, such the UN Rio
de Janeiro 1992 Earth Summit This was followed by the appearance
of the global conferences at the late of the nineties and the early of
2000 to confirm the importance of the sustainable development .it
was focused on the importance of the economic development as it is
considered an effective tool in the operations of the sustainable
development. Industry plays a critical role in technological
innovations and research and development activities, which are
crucial for the economic and social development of any country.
Transportation and mobility are an important part or urban
economics and the quality of life. To analyze urban transportation
and its environmental impacts, a comprehensive approach is needed.
So this research aims to apply new approach for the development of
the urban communities that insure the continuity and facing the
deterioration. This approach aims to integrate sustainable transport
solutions with economic development and community development.
For that purpose we will concentrate on one of the most sustainable
cities in the world (Curitiba in Brazil) which provides the world with
a model in how to integrate sustainable transport considerations into
business development, road infrastructure development, and local
community development.
Abstract: Industrial design engineering is an information and
knowledge intensive job. Although Wikipedia offers a lot of this
information, design engineers are better served with a wiki tailored to
their job, offering information in a compact manner and functioning
as a design tool. For that reason WikID has been developed.
However for the viability of a wiki, an active user community is
essential. The main subject of this paper is a study to the influence of
the communication and the contents of WikID on the user-s
willingness to contribute.
At first the theory about a website-s first impression, general
usability guidelines and user motivation in an online community is
studied. Using this theory, the aspects of the current site are analyzed
on their suitability. These results have been verified with a
questionnaire amongst 66 industrial design engineers (or students
industrial design engineering).
The main conclusion is that design engineers are enchanted with
the existence of WikID and its knowledge structure (taxonomy) but
this structure has not become clear without any guidance. In other
words, the knowledge structure is very helpful for inspiring and
guiding design engineers through their tailored knowledge domain in
WikID but this taxonomy has to be better communicated on the main
page. Thereby the main page needs to be fitted more to the target
group preferences.
Abstract: A number of automated shot-change detection
methods for indexing a video sequence to facilitate browsing and
retrieval have been proposed in recent years. This paper emphasizes
on the simulation of video shot boundary detection using one of the
methods of the color histogram wherein scaling of the histogram
metrics is an added feature. The difference between the histograms of
two consecutive frames is evaluated resulting in the metrics. Further
scaling of the metrics is performed to avoid ambiguity and to enable
the choice of apt threshold for any type of videos which involves
minor error due to flashlight, camera motion, etc. Two sample videos
are used here with resolution of 352 X 240 pixels using color
histogram approach in the uncompressed media. An attempt is made
for the retrieval of color video. The simulation is performed for the
abrupt change in video which yields 90% recall and precision value.
Abstract: One of the approaches enabling people with amputated
limbs to establish some sort of interface with the real world includes
the utilization of the myoelectric signal (MES) from the remaining
muscles of those limbs. The MES can be used as a control input to a
multifunction prosthetic device. In this control scheme, known as the
myoelectric control, a pattern recognition approach is usually utilized
to discriminate between the MES signals that belong to different
classes of the forearm movements. Since the MES is recorded using
multiple channels, the feature vector size can become very large. In
order to reduce the computational cost and enhance the generalization
capability of the classifier, a dimensionality reduction method is
needed to identify an informative yet moderate size feature set. This
paper proposes a new fuzzy version of the well known Fisher-s
Linear Discriminant Analysis (LDA) feature projection technique.
Furthermore, based on the fact that certain muscles might contribute
more to the discrimination process, a novel feature weighting scheme
is also presented by employing Particle Swarm Optimization (PSO)
for estimating the weight of each feature. The new method, called
PSOFLDA, is tested on real MES datasets and compared with other
techniques to prove its superiority.
Abstract: This paper introduces a measure of similarity between
two clusterings of the same dataset produced by two different
algorithms, or even the same algorithm (K-means, for instance, with
different initializations usually produce different results in clustering
the same dataset). We then apply the measure to calculate the
similarity between pairs of clusterings, with special interest directed
at comparing the similarity between various machine clusterings and
human clustering of datasets. The similarity measure thus can be used
to identify the best (in terms of most similar to human) clustering
algorithm for a specific problem at hand. Experimental results
pertaining to the text categorization problem of a Portuguese corpus
(wherein a translation-into-English approach is used) are presented, as well as results on the well-known benchmark IRIS dataset. The
significance and other potential applications of the proposed measure
are discussed.