Abstract: The Partitioned Global Address Space (PGAS) programming
paradigm offers ease-of-use in expressing parallelism
through a global shared address space while emphasizing performance
by providing locality awareness through the partitioning of
this address space. Therefore, the interest in PGAS programming
languages is growing and many new languages have emerged and
are becoming ubiquitously available on nearly all modern parallel
architectures. Recently, new parallel machines with multiple cores
are designed for targeting high performance applications. Most of the
efforts have gone into benchmarking but there are a few examples of
real high performance applications running on multicore machines.
In this paper, we present and evaluate a parallelization technique
for implementing a local DNA sequence alignment algorithm using
a PGAS based language, UPC (Unified Parallel C) on a chip
multithreading architecture, the UltraSPARC T1.
Abstract: The purpose of this paper is to explore the role of
cognitive decision effort in recommendation system, combined with
indicators "information quality" and "service quality" from IS success
model to exam the awareness of the user for the "recommended system
performance". A total of 411 internet user answered a questionnaire
assessing their attention of use and satisfaction of recommendation
system in internet book store. Quantitative result indicates following
research results. First, information quality of recommended system
has obvious influence in consumer shopping decision-making process,
and the attitude to use the system. Second, in the process of consumer's
shopping decision-making, the recommendation system has no
significant influence for consumers to pay lower cognitive
decision-making effort. Third, e-commerce platform provides
recommendations and information is necessary, but the quality of
information on user needs must be considered, or they will be other
competitors offer homogeneous services replaced.
Abstract: This survey highlights a number of important issues
which relate to the needs to counseling for distance learners studying
at the School of Distance Education in University science Malaysia
(DEUSM) according to their gender. Data were obtained by selfreport
questionnaire that had been developed by the researchers in
counseling and educational psychology and interviews were take
place. 116 voluntary respondents complete the Questionnaire and
returned it back during new student-s registration week.64% of the
respondents were female and 52% were males that means
55%ofthem were females and 45% were males. The data was
analyzed to find out the frequencies of respondents agreements of the
items. The average of the female was 18 and the average of the male
was 19.6 by using t- test there is no significant values between the
genders. The findings show that respondents have needs for
counseling. (22) Significant needs for mails (DEUSM) the highest
was their families complain about the amount of time they spend at
work. (11) Significant needs for females the highest was they
convinced themselves that they only need 4 to 5 hours of sleep per
night.
Abstract: This paper presents an architecture to assist in the
development of tools to perform experimental analysis. Existing
implementations of tools based on this architecture are also described
in this paper. These tools are applied to the real world problem of
fault attack emulation and detection in cryptographic algorithms.
Abstract: Ti-6Al-4V alloy has demonstrated a high strength to
weight ratio as well as good properties at high temperature. The
successful application of the alloy in some important areas depends
on suitable joining techniques. Friction welding has many
advantageous features to be chosen for joining Titanium alloys. The
present work investigates the feasibility of producing similar metal
joints of this Titanium alloy by rotary friction welding method. The
joints are produced at three different speeds and the performances of
the welded joints are evaluated by conducting microstructure studies,
Vickers Hardness and tensile tests at the joints. It is found that the
weld joints produced are sound and the ductile fractures in the tensile
weld specimens occur at locations away from the welded joints. It is
also found that a rotational speed of 1500 RPM can produce a very
good weld, with other parameters kept constant.
Abstract: Artificial Neural Networks (ANNs) have been used successfully in many scientific, industrial and business domains as a method for extracting knowledge from vast amounts of data. However the use of ANN techniques in the sporting domain has been limited. In professional sport, data is stored on many aspects of teams, games, training and players. Sporting organisations have begun to realise that there is a wealth of untapped knowledge contained in the data and there is great interest in techniques to utilise this data. This study will use player data from the elite Australian Football League (AFL) competition to train and test ANNs with the aim to predict the onset of injuries. The results demonstrate that an accuracy of 82.9% was achieved by the ANNs’ predictions across all examples with 94.5% of all injuries correctly predicted. These initial findings suggest that ANNs may have the potential to assist sporting clubs in the prediction of injuries.
Abstract: This paper presents the new results of energy plant –
rye and triticale at yellow ripeness and ripe, pre-treatment in high
pressure steam reactor and monosaccharide extraction. There were
investigated the influence of steam pressure (20 to 22 bar), retention
duration (180 to 240 s) and catalytic sulphuric acid concentration
strength (0 to 0.5 %) on the pre-treatment process, contents of
monosaccharides (glucose, arabinose, xylose, mannose) and
undesirable by-compounds (furfural and HMF) in the reactor. The
study has determined that the largest amount of monosaccharides
(37.2 % of glucose, 2.7 % of arabinose, 8.4 % of xylose, and 1.3 %
of mannose) was received in the rye at ripe, the samples of which
were mixed with 0.5 % concentration of catalytic sulphuric acid, and
hydrolysed in the reactor, where the pressure was 20 bar, whereas the
reaction time – 240 s.
Abstract: Competing risks survival data that comprises of more
than one type of event has been used in many applications, and one
of these is in clinical study (e.g. in breast cancer study). The
decision tree method can be extended to competing risks survival
data by modifying the split function so as to accommodate two or
more risks which might be dependent on each other. Recently,
researchers have constructed some decision trees for recurrent
survival time data using frailty and marginal modelling. We further
extended the method for the case of competing risks. In this paper,
we developed the decision tree method for competing risks survival
time data based on proportional hazards for subdistribution of
competing risks. In particular, we grow a tree by using deviance
statistic. The application of breast cancer data is presented. Finally,
to investigate the performance of the proposed method, simulation
studies on identification of true group of observations were executed.
Abstract: The consumption capability of people in China has
been a big issue to tourism business. Due to the increasing of China
tourists, Taiwan-s government rescinded the category of people in
China and opened up the non-stopped airline from China to Taiwan.
The “one-day traveling style between China and Taiwan" has formed,
hoping to bring business to Taiwan. Night market, which shows
foreigners the very local character of Taiwan, contains various
merchandise for consumers to purchase. With the increasing numbers
of non-stopped airline, visiting Taiwan-s night markets has also been
one of major activities to China-s tourists. The purpose of the present
study is to understand the consumer behavior of China tourists in
tourist night markets in Taipei and analyze that if their shopping
motives cause the different shopping behaviors and post-purchase
satisfaction and revisiting intention. The results reveled that for the
China tourists, the motives of significant influence to the shopping
behaviors. Also, the shopping behaviors significant influence to the
whole satisfaction and the whole satisfaction significant influence to
post-purchase behavior.
Abstract: This paper describes a paradigmatic approach to develop architecture of secure systems by describing the requirements from four different points of view: that of the owner, the administrator, the user, and the network. Deriving requirements and developing architecture implies the joint elicitation and describing the problem and the structure of the solution. The view points proposed in this paper are those we consider as requirements towards their contributions as major parties in the design, implementation, usage and maintenance of secure systems. The dramatic growth of the technology of Internet and the applications deployed in World Wide Web have lead to the situation where the security has become a very important concern in the development of secure systems. Many security approaches are currently being used in organizations. In spite of the widespread use of many different security solutions, the security remains a problem. It is argued that the approach that is described in this paper for the development of secure architecture is practical by all means. The models representing these multiple points of view are termed the requirements model (views of owner and administrator) and the operations model (views of user and network). In this paper, this multiple view paradigm is explained by first describing the specific requirements and or characteristics of secure systems (particularly in the domain of networks) and the secure architecture / system development methodology.
Abstract: In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web-pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.
Abstract: This paper illustrates why existing technology
acceptance models are only of limited use for predicting and
explaining the adoption of future information and communication
technologies. It starts with a general overview over technology
adoption processes, and presents several theories for the acceptance
as well as adoption of traditional information technologies. This is
followed by an overview over the recent developments in the area of
information and communication technologies. Based on the
arguments elaborated in these sections, it is shown why the factors
used to predict adoption in existing systems, will not be sufficient for
explaining the adoption of future information and communication
technologies.
Abstract: In this paper a one-dimension Self Organizing Map
algorithm (SOM) to perform feature selection is presented. The
algorithm is based on a first classification of the input dataset on a
similarity space. From this classification for each class a set of
positive and negative features is computed. This set of features is
selected as result of the procedure. The procedure is evaluated on an
in-house dataset from a Knowledge Discovery from Text (KDT)
application and on a set of publicly available datasets used in
international feature selection competitions. These datasets come
from KDT applications, drug discovery as well as other applications.
The knowledge of the correct classification available for the training
and validation datasets is used to optimize the parameters for positive
and negative feature extractions. The process becomes feasible for
large and sparse datasets, as the ones obtained in KDT applications,
by using both compression techniques to store the similarity matrix
and speed up techniques of the Kohonen algorithm that take
advantage of the sparsity of the input matrix. These improvements
make it feasible, by using the grid, the application of the
methodology to massive datasets.
Abstract: This work attempts to improve the permselectivity of poly-ortho-phenylenediamine (PPD) coating for glutamate biosensor applications on Pt microelectrode, using constant potential amperometry and cyclic voltammetry. Percentage permeability of the modified PPD microelectrode was carried out towards hydrogen peroxide (H2O2) and ascorbic acid (AA) whereas permselectivity represents the percentage interference by AA in H2O2 detection. The 50-μm diameter Pt disk microelectrode showed a good permeability value toward H2O2 (95%) and selectivity against AA (0.01%) compared to other sizes of electrode studied here. The electrode was further modified with glutamate oxidase (GluOx) that was immobilized and cross linked with glutaraldehyde (GA, 0.125%), resulting in Pt/PPD/GluOx-GA electrode design. The maximum current density Jmax and apparent Michaelis constant, KM, obtained on Pt/PPD/GluOx-GA electrodes were 48 μA cm-2 and 50 μM, respectively. The linear region slope (LRS) was 0.96 μA cm-2 mM-1. The detection limit (LOD) for glutamate was 3.0 ± 0.6 μM. This study shows a promising glutamate microbiosensor for brain glutamate detection.
Abstract: This paper investigates the problem of absolute stability and robust stability of a class of Lur-e systems with neutral type and time-varying delays. By using Lyapunov direct method and linear matrix inequality technique, new delay-dependent stability criteria are obtained and formulated in terms of linear matrix inequalities (LMIs) which are easy to check the stability of the considered systems. To obtain less conservative stability conditions, an operator is defined to construct the Lyapunov functional. Also, the free weighting matrices approach combining a matrix inequality technique is used to reduce the entailed conservativeness. Numerical examples are given to indicate significant improvements over some existing results.
Abstract: The actual grow of the infrastructure in develop country require sophisticate ways manage the operation and control the quality served. This research wants to concentrate in the operation of this infrastructure beyond the construction. The infrastructure-s operation involves an uncertain environment, where unexpected variables are present every day and everywhere. Decision makers need to make right decisions with right information/data analyzed most in real time. To adequately support their decisions and decrease any negative impact and collateral effect, they need to use computational tools called decision support systems (DSS), but now the main source of information came from common users thought an extensive crowdsourcing
Abstract: During signal transmission, the combined effect of the
transmitter filter, the transmission medium, and additive white
Gaussian noise (AWGN) are included in the channel which distort
and add noise to the signal. This causes the well defined signal
constellation to spread causing errors in bit detection. A compact pi
neural network with minimum number of nodes is proposed. The
replacement of summation at each node by multiplication results in
more powerful mapping. The resultant pi network is tested on six
different channels.
Abstract: In this study, a network quality of service (QoS)
evaluation system was proposed. The system used a combination of
fuzzy C-means (FCM) and regression model to analyse and assess the
QoS in a simulated network. Network QoS parameters of multimedia
applications were intelligently analysed by FCM clustering
algorithm. The QoS parameters for each FCM cluster centre were
then inputted to a regression model in order to quantify the overall
QoS. The proposed QoS evaluation system provided valuable
information about the network-s QoS patterns and based on this
information, the overall network-s QoS was effectively quantified.
Abstract: Identifying protein coding regions in DNA sequences is a basic step in the location of genes. Several approaches based on signal processing tools have been applied to solve this problem, trying to achieve more accurate predictions. This paper presents a new predictor that improves the efficacy of three techniques that use the Fourier Transform to predict coding regions, and that could be computed using an algorithm that reduces the computation load. Some ideas about the combination of the predictor with other methods are discussed. ROC curves are used to demonstrate the efficacy of the proposed predictor, based on the computation of 25 DNA sequences from three different organisms.
Abstract: This paper focuses on a critical component of the situational awareness (SA), the neural control of autonomous constant depth flight of an autonomous underwater vehicle (AUV). Autonomous constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. The fundamental requirement for constant depth flight is the knowledge of the depth, and a properly designed controller to govern the process. The AUV, named VORAM, is used as a model for the verification of the proposed hybrid control algorithm. Three neural network controllers, named NARMA-L2 controllers, are designed for fast and stable diving maneuvers of chosen AUV model. This hybrid control strategy for chosen AUV model has been verified by simulation of diving maneuvers using software package Simulink and demonstrated good performance for fast SA in real-time searchand- rescue operations.