Abstract: This study attempts to validate the consumer-oriented
criteria list, developed by Wang et al. (2010), for selecting online
travel shopping sites. Based on a sample of 985 respondents,
confirmatory factor analysis was employed to test the factor structure
and assess the reliability and validity of the list. The results support the
list developed by Wang et al. (2010) and claim the list can be further
used to analyze, explain, and understand consumer behaviors about
online travel shopping.
Abstract: Business Process Management (BPM) helps in optimizing the business processes inside an enterprise. But BPM architecture does not provide any help for extending the enterprise. Modern business environments and rapidly changing technologies are asking for brisk changes in the business processes. Service Oriented Architecture (SOA) can help in enabling the success of enterprise-wide BPM. SOA supports agility in software development that is directly related to achieve loose coupling of interacting software agents. Agility is a premium concern of the current software designing architectures. Together, BPM and SOA provide a perfect combination for enterprise computing. SOA provides the capabilities for services to be combined together and to support and create an agile, flexible enterprise. But there are still many questions to answer; BPM is better or SOA? and what is the future track of BPM and SOA? This paper tries to answer some of these important questions.
Abstract: This article discusses the problem of estimating the
orientation of inclined ground on which a human subject stands based
on information provided by the vestibular system consisting of the
otolith and semicircular canals. It is assumed that body segments are
not necessarily aligned and thus forming an open kinematic chain.
The semicircular canals analogues to a technical gyrometer provide a
measure of the angular velocity whereas the otolith analogues to a
technical accelerometer provide a measure of the translational
acceleration. Two solutions are proposed and discussed. The first is
based on a stand-alone Kalman filter that optimally fuses the two
measurements based on their dynamic characteristics and their noise
properties. In this case, no body dynamic model is needed. In the
second solution, a central extended disturbance observer that
incorporates a body dynamic model (internal model) is employed.
The merits of both solutions are discussed and demonstrated by
experimental and simulation results.
Abstract: A simple network model is developed in OPNET to
study the performance of the Wi-Fi protocol. The model is simulated
in OPNET and performance factors such as load, throughput and delay
are analysed from the model. Four applications such as oracle, http, ftp
and voice are applied over the Wireless LAN network to determine the
throughput. The voice application utilises a considerable amount of
bandwidth of up to 5Mbps, as a result the 802.11g standard of the
Wi-Fi protocol was chosen which can support a data rate of up to
54Mbps. Results indicate that when the load in the Wi-Fi network is
increased the queuing delay on the point-to-point links in the Wi-Fi
network significantly reduces until it is comparable to that of WiMAX.
In conclusion, the queuing delay of the Wi-Fi protocol for the network
model simulated was about 0.00001secs comparable to WiMAX
network values.
Abstract: In this paper we describes the authentication for DHCP
(Dynamic Host Configuration Protocol) message which provides the
efficient key management and reduces the danger replay attack without
an additional packet for a replay attack. And the authentication for
DHCP message supports mutual authentication and provides both
entity authentication and message authentication. We applied the
authentication for DHCP message to the home network environments
and tested through a home gateway.
Abstract: The paper describes ergonomics problems trend of
student at B5101 classroom building 2, Suranaree University of
Technology. The objective to survey ergonomics problems and effect
from use chairs for sitting in class room. The result from survey
method 100 student they use lecture chair for sitting in classroom
more than 2 hours/ day by RULA[1]. and Body discomfort survey[2].
The result from Body discomfort survey contribute fatigue problems
at neck, lower back, upper back and right shoulder 2.93, 2.91, 2.33,
1.75 respectively and result from RULA contribute fatigue problems
at neck, body and right upper arm 4.00, 3.75 and 3.00 respectively
are consistent. After that the researcher provide improvement plan
for design new chair support student fatigue reduction by prepare
data of sample anthropometry and design ergonomics chair prototype
3 unit. Then sample 100 student trial to use new chair and evaluate
again by RULA, Body discomfort and satisfaction. The result from
trial new chair after improvement by RULA present fatigue reduction
average of head and neck from 4.00 to 2.25 , body and trunk from
3.75 to 2.00 and arm force from 1.00 to 0.25 respectively. The result
from trial new chair after improvement by Body discomfort present
fatigue reduction average of lower back from 2.91 to 0.87, neck from
2.93 to 1.24, upper back 2.33 to 0.84 and right upper arm from 1.75
to 0.74. That statistical of RULA and Body discomfort survey
present fatigue reduction after improvement significance with a
confidence level of 95% (p-value 0.05). When analyzing the
relationship of fatigue as part of the body by Chi – square test during
RULA and Body discomfort that before and after improvements were
consistent with the significant level of confidence 95% (p-value 0.05)
. Moreover the students satisfaction result from trial with a new chair
for 30 minutes [3]. 72 percent very satisfied of the folding of the
secondary writing simple 66% the width of the writing plate, 64% the
suitability of the writing plate, 62% of soft seat cushion and 61%
easy to seat the chair.
Abstract: In the end of the day, meteorological data and environmental data becomes widely used such as plant varieties selection system. Variety plant selection for planted area is of almost importance for all crops, including varieties of sugarcane. Since sugarcane have many varieties. Variety plant non selection for planting may not be adapted to the climate or soil conditions for planted area. Poor growth, bloom drop, poor fruit, and low price are to be from varieties which were not recommended for those planted area. This paper presents plant varieties selection system for planted areas in Thailand from meteorological data and environmental data by the use of decision tree techniques. With this software developed as an environmental data analysis tool, it can analyze resulting easier and faster. Our software is a front end of WEKA that provides fundamental data mining functions such as classify, clustering, and analysis functions. It also supports pre-processing, analysis, and decision tree output with exporting result. After that, our software can export and display data result to Google maps API in order to display result and plot plant icons effectively.
Abstract: Leprosy is an infectious disease caused by
Mycobacterium Leprae, this disease, generally, compromises
the neural fibers, leading to the development of disability.
Disabilities are changes that limit daily activities or social life
of a normal individual. When comes to leprosy, the study of
disability considered the functional limitation (physical
disabilities), the limitation of activity and social participation,
which are measured respectively by the scales: EHF, SALSA
and PARTICIPATION SCALE. The objective of this work is
to propose an on-line monitoring of leprosy patients, which is
based on information scales EHF, SALSA and
PARTICIPATION SCALE. It is expected that the proposed
system is applied in monitoring the patient during treatment
and after healing therapy of the disease. The correlations that
the system is between the scales create a variety of
information, presented the state of the patient and full of
changes or reductions in disability. The system provides
reports with information from each of the scales and the
relationships that exist between them. This way, health
professionals, with access to patient information, can
intervene with techniques for the Prevention of Disability.
Through the automated scale, the system shows the level of
the patient and allows the patient, or the responsible, to take a
preventive measure. With an online system, it is possible take
the assessments and monitor patients from anywhere.
Abstract: In this paper we are interested in classification problems
with a performance constraint on error probability. In such
problems if the constraint cannot be satisfied, then a rejection option
is introduced. For binary labelled classification, a number of SVM
based methods with rejection option have been proposed over the
past few years. All of these methods use two thresholds on the SVM
output. However, in previous works, we have shown on synthetic data
that using thresholds on the output of the optimal SVM may lead to
poor results for classification tasks with performance constraint. In
this paper a new method for supervised classification with rejection
option is proposed. It consists in two different classifiers jointly
optimized to minimize the rejection probability subject to a given
constraint on error rate. This method uses a new kernel based linear
learning machine that we have recently presented. This learning
machine is characterized by its simplicity and high training speed
which makes the simultaneous optimization of the two classifiers
computationally reasonable. The proposed classification method with
rejection option is compared to a SVM based rejection method
proposed in recent literature. Experiments show the superiority of
the proposed method.
Abstract: With the popularity of the multi-core and many-core architectures there is a great requirement for software frameworks which can support parallel programming methodologies. In this paper we introduce an Eclipse toolkit, JConqurr which is easy to use and provides robust support for flexible parallel progrmaming. JConqurr is a multi-core and many-core programming toolkit for Java which is capable of providing support for common parallel programming patterns which include task, data, divide and conquer and pipeline parallelism. The toolkit uses an annotation and a directive mechanism to convert the sequential code into parallel code. In addition to that we have proposed a novel mechanism to achieve the parallelism using graphical processing units (GPU). Experiments with common parallelizable algorithms have shown that our toolkit can be easily and efficiently used to convert sequential code to parallel code and significant performance gains can be achieved.
Abstract: This paper proposes a novel hybrid algorithm for feature selection based on a binary ant colony and SVM. The final subset selection is attained through the elimination of the features that produce noise or, are strictly correlated with other already selected features. Our algorithm can improve classification accuracy with a small and appropriate feature subset. Proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low. The performance of the proposed algorithm is evaluated through a real Rotary Cement kiln dataset. The results show that our algorithm outperforms existing algorithms.
Abstract: Until recently, researchers have developed various
tools and methodologies for effective clinical decision-making.
Among those decisions, chest pain diseases have been one of
important diagnostic issues especially in an emergency department. To
improve the ability of physicians in diagnosis, many researchers have
developed diagnosis intelligence by using machine learning and data
mining. However, most of the conventional methodologies have been
generally based on a single classifier for disease classification and
prediction, which shows moderate performance. This study utilizes an
ensemble strategy to combine multiple different classifiers to help
physicians diagnose chest pain diseases more accurately than ever.
Specifically the ensemble strategy is applied by using the integration
of decision trees, neural networks, and support vector machines. The
ensemble models are applied to real-world emergency data. This study
shows that the performance of the ensemble models is superior to each
of single classifiers.
Abstract: This paper presented a collaborative education model,
which consists four parts: collaborative teaching, collaborative
working, collaborative training and interaction. Supported by an
e-learning platform, collaborative education was practiced in a data
structure e-learning course. Data collected shows that most of students
accept collaborative education. This paper goes one step attempting to
determine which aspects appear to be most important or helpful in
collaborative education.
Abstract: The availability of broadband internet and increased
access to computers has been instrumental in the rise of internet
literacy in Malaysia. This development has led to the adoption of
online shopping by many Malaysians. On another note, the
Government has supported the development and production of local
herbal products. This has resulted in an increase in the production and
diversity of products by SMEs. The purpose of this study is to
evaluate the influence of the Malaysian demographic factors and
selected attitudinal characteristics in relation to the online purchasing
of herbal products. In total, 1054 internet users were interviewed
online and Chi-square analysis was used to determine the relationship
between demographic variables and different aspects of online
shopping for herbal products. The overall results show that the
demographic variables such as age, gender, education level, income
and ethnicity were significant when considering the online shopping
antecedents of trust, quality of herbal products, perceived risks and
perceived benefits.
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: 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: The number of users supported in a DS-CDMA
cellular system is typically less than spreading factor (N), and the
system is said to be underloaded. Overloading is a technique to
accommodate more number of users than the spreading factor N. In
O/O overloading scheme, the first set is assigned to the N
synchronous users and the second set is assigned to the additional
synchronous users. An iterative multistage soft decision interference
cancellation (SDIC) receiver is used to remove high level of
interference between the two sets. Performance is evaluated in terms
of the maximum number acceptable users so that the system
performance is degraded slightly compared to the single user
performance at a specified BER. In this paper, the capacity of CDMA
based O/O overloading scheme is evaluated with SDIC receiver. It is
observed that O/O scheme using orthogonal Gold codes provides
25% channel overloading (N=64) for synchronous DS-CDMA
system on an AWGN channel in the uplink at a BER of 1e-5.For a
Rayleigh faded channel, the critical capacity is 40% at a BER of 5e-5
assuming synchronous users. But in practical systems, perfect chip
timing is very difficult to maintain in the uplink.. We have shown that
the overloading performance reduces to 11% for a timing
synchronization error of 0.02Tc for a BER of 1e-5.
Abstract: In the globalized e-learning environment, students coming from different cultures and countries have different characteristics and require different support designed for their approaches to study and learning styles. This paper explores the ways in which cultural background influences students- approaches to study and learning styles. Participants in the study consisted of 131 eastern students and 54 western students from an Australian university. The students were tested using the Study Process Questionnaire (SPQ) for assessing their approaches to study and the Index of Learning Styles Questionnaire (ILS) for assessing their learning styles. The results of the study led to a set of principles being proposed to guide personalization of e-learning system design on the basis of cultural differences.
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: Selective oxidation of H2S to elemental sulfur in a
fixed bed reactor over newly synthesized alumina nanocatalysts was
physio-chemically investigated and results compared with a
commercial Claus catalyst. Amongst these new materials, Al2O3-
supported sodium oxide prepared with wet chemical technique and
Al2O3 nanocatalyst prepared with spray pyrolysis method were the
most active catalysts for selective oxidation of H2S to elemental
sulfur. Other prepared nanocatalysts were quickly deactivated,
mainly due to the interaction with H2S and conversion into sulfides.