Abstract: True integration of multimedia services over wired or
wireless networks increase the productivity and effectiveness in
today-s networks. IP Multimedia Subsystems are Next Generation
Network architecture to provide the multimedia services over fixed
or mobile networks. This paper proposes an extended SIP-based QoS
Management architecture for IMS services over underlying IP access
networks. To guarantee the end-to-end QoS for IMS services in
interconnection backbone, SIP based proxy Modules are introduced
to support the QoS provisioning and to reduce the handoff disruption
time over IP access networks. In our approach these SIP Modules
implement the combination of Diffserv and MPLS QoS mechanisms
to assure the guaranteed QoS for real-time multimedia services. To
guarantee QoS over access networks, SIP Modules make QoS
resource reservations in advance to provide best QoS to IMS users
over heterogeneous networks. To obtain more reliable multimedia
services, our approach allows the use of SCTP protocol over SIP
instead of UDP due to its multi-streaming feature. This architecture
enables QoS provisioning for IMS roaming users to differentiate IMS
network from other common IP networks for transmission of realtime
multimedia services. To validate our approach simulation
models are developed on short scale basis. The results show that our
approach yields comparable performance for efficient delivery of
IMS services over heterogeneous IP access networks.
Abstract: Rapid advancement in computing technology brings
computers and humans to be seamlessly integrated in future. The
emergence of smartphone has driven computing era towards
ubiquitous and pervasive computing. Recognizing human activity has
garnered a lot of interest and has raised significant researches-
concerns in identifying contextual information useful to human
activity recognition. Not only unobtrusive to users in daily life,
smartphone has embedded built-in sensors that capable to sense
contextual information of its users supported with wide range
capability of network connections. In this paper, we will discuss the
classification algorithms used in smartphone-based human activity.
Existing technologies pertaining to smartphone-based researches in
human activity recognition will be highlighted and discussed. Our
paper will also present our findings and opinions to formulate
improvement ideas in current researches- trends. Understanding
research trends will enable researchers to have clearer research
direction and common vision on latest smartphone-based human
activity recognition area.
Abstract: Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved.
Abstract: Although backpropagation ANNs generally predict
better than decision trees do for pattern classification problems, they
are often regarded as black boxes, i.e., their predictions cannot be
explained as those of decision trees. In many applications, it is
desirable to extract knowledge from trained ANNs for the users to
gain a better understanding of how the networks solve the problems.
A new rule extraction algorithm, called rule extraction from artificial
neural networks (REANN) is proposed and implemented to extract
symbolic rules from ANNs. A standard three-layer feedforward ANN
is the basis of the algorithm. A four-phase training algorithm is
proposed for backpropagation learning. Explicitness of the extracted
rules is supported by comparing them to the symbolic rules generated
by other methods. Extracted rules are comparable with other methods
in terms of number of rules, average number of conditions for a rule,
and predictive accuracy. Extensive experimental studies on several
benchmarks classification problems, such as breast cancer, iris,
diabetes, and season classification problems, demonstrate the
effectiveness of the proposed approach with good generalization
ability.
Abstract: Fair share is one of the scheduling objectives supported on many production systems. However, fair share has been shown to cause performance problems for some users, especially the users with difficult jobs. This work is focusing on extending goaloriented parallel computer job scheduling policies to cover the fair share objective. Goal-oriented parallel computer job scheduling policies have been shown to achieve good scheduling performances when conflicting objectives are required. Goal-oriented policies achieve such good performance by using anytime combinatorial search techniques to find a good compromised schedule within a time limit. The experimental results show that the proposed goal-oriented parallel computer job scheduling policy (namely Tradeofffs( Tw:avgX)) achieves good scheduling performances and also provides good fair share performance.
Abstract: Traffic Density provides an indication of the level of
service being provided to the road users. Hence, there is a need to
study the traffic flow characteristics with specific reference to
density in detail. When the length and speed of the vehicles in a
traffic stream vary significantly, the concept of occupancy, rather
than density, is more appropriate to describe traffic concentration.
When the concept of occupancy is applied to heterogeneous traffic
condition, it is necessary to consider the area of the road space and
the area of the vehicles as the bases. Hence, a new concept named,
'area-occupancy' is proposed here. It has been found that the
estimated area-occupancy gives consistent values irrespective of
change in traffic composition.
Abstract: This paper presents a watermarking protocol able to
solve the well-known “customer-s right problem" and “unbinding
problem". In particular, the protocol has been purposely designed
to be adopted in a web context, where users wanting to buy digital
contents are usually neither provided with digital certificates issued
by certification authorities (CAs) nor able to autonomously perform
specific security actions. Furthermore, the protocol enables users to
keep their identities unexposed during web transactions as well as
allows guilty buyers, i.e. who are responsible distributors of illegal
replicas, to be unambiguously identified. Finally, the protocol has
been designed so that web content providers (CPs) can exploit
copyright protection services supplied by web service providers (SPs)
in a security context. Thus, CPs can take advantage of complex
services without having to directly implement them.
Abstract: This research is a collaborative narrative research, which is mixed with issues of selected papers and researcher's experience as an anonymous user on social networking sites. The objective of this research is to understand the reasons of the regular users who reject to contact with anonymous users, and to study the communication traditions used in the selected studies. Anonymous users are rejected by regular users, because of the fear of cyber bully, the fear of unpleasant behaviors, and unwillingness of changing communication norm. The suggestion for future research design is to use longitudinal design or quantitative design; and the theory in rhetorical tradition should be able to help develop a strong trust message.
Abstract: The policies governing the business of any
organization are well reflected in her business rules. The business
rules are implemented by data validation techniques, coded during
the software development process. Any change in business
policies results in change in the code written for data validation
used to enforce the business policies. Implementing the change in
business rules without changing the code is the objective of this
paper. The proposed approach enables users to create rule sets at
run time once the software has been developed. The newly defined
rule sets by end users are associated with the data variables for
which the validation is required. The proposed approach facilitates
the users to define business rules using all the comparison
operators and Boolean operators. Multithreading is used to
validate the data entered by end user against the business rules
applied. The evaluation of the data is performed by a newly
created thread using an enhanced form of the RPN (Reverse Polish
Notation) algorithm.
Abstract: This paper presents the result of three senior capstone
projects at the Department of Computer Engineering, Prince of
Songkla University, Thailand. These projects focus on developing an
examination management system for the Faculty of Engineering in
order to manage the examination both the examination room
assignments and the examination proctor assignments in each room.
The current version of the software is a web-based application. The
developed software allows the examination proctors to select their
scheduled time online while each subject is assigned to each available
examination room according to its type and the room capacity. The
developed system is evaluated using real data by prospective users of
the system. Several suggestions for further improvements are given
by the testers. Even though the features of the developed software are
not superior, the developing process can be a case study for a projectbased
teaching style. Furthermore, the process of developing this
software can show several issues in developing an educational
support application.
Abstract: This study proposes a novel recommender system to
provide the advertisements of context-aware services. Our proposed
model is designed to apply a modified collaborative filtering (CF)
algorithm with regard to the several dimensions for the personalization
of mobile devices – location, time and the user-s needs type. In
particular, we employ a classification rule to understand user-s needs
type using a decision tree algorithm. In addition, we collect primary
data from the mobile phone users and apply them to the proposed
model to validate its effectiveness. Experimental results show that the
proposed system makes more accurate and satisfactory advertisements
than comparative systems.
Abstract: This paper proposes a new of cloud computing for individual computer users to share applications in distributed communities, called community-based personal cloud computing (CPCC). The paper also presents a prototype design and implementation of CPCC. The users of CPCC are able to share their computing applications with other users of the community. Any member of the community is able to execute remote applications shared by other members. The remote applications behave in the same way as their local counterparts, allowing the user to enter input, receive output as well as providing the access to the local data of the user. CPCC provides a peer-to-peer (P2P) environment where each peer provides applications which can be used by the other peers that are connected CPCC.
Abstract: We present the results of a case study aiming to assess the reflection of the tourism community in the Web and its usability to propose new ways to communicate visually. The wealth of information contained in the Web and the clear facilities to communicate personals points of view makes of the social web a new space of exploration. In this way, social web allow the sharing of information between communities with similar interests. However, the tourism community remains unexplored as is the case of the information covered in travel stories. Along the Web, we find multiples sites allowing the users to communicate their experiences and personal points of view of a particular place of the world. This cultural heritage is found in multiple documents, usually very little supplemented with photos, so they are difficult to explore due to the lack of visual information. This paper explores the possibility of analyzing travel stories to display them visually on maps and generate new knowledge such as patterns of travel routes. This way, travel narratives published in electronic formats can be very important especially to the tourism community because of the great amount of knowledge that can be extracted. Our approach is based on the use of a Geoparsing Web Service to extract geographic coordinates from travel narratives in order to draw the geo-positions and link the documents into a map image.
Abstract: Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders.
Abstract: The Taiwan government has invested approximately
21 billion NT dollars in the construction of bicycle paths since
bicycling has gained huge popularity as a healthy leisure and
recreational activity. This study focuses on the behavior of
recreational bicyclists in Danshuei and Bali, northern Taiwan. Data
were collected from a field investigation carried out along the
Danshuei bicycle path and Bali left-bank bicycle path. A total of 578
questionnaires were gathered for data analysis. Descriptive statistics
and Chi-Square tests were used to assess bicyclists- behaviors. The
frequency shows that, in these areas, Danshuei and Bali, most
bicyclists rented bicycles, rode the bicycle path in the afternoon for
about 2 hours. The used the bicycle path one time per week. For most,
it was the first time to ride these bicycle paths. There were significant
differences in distribution of bicycle ownership, time of day, duration
of ride, ride frequency, and whether riding occurred on weekdays or
weekends. Results indicated that most bicyclists in Danshuei and Bali
were infrequent users.
Abstract: Decision Support System (DSS) are interactive
software systems that are built to assist the management of an
organization in the decision making process when faced with nonroutine
problems in a specific application domain. Non-functional
requirements (NFRs) for a DSS deal with the desirable qualities and
restrictions that the DSS functionalities must satisfy. Unlike the
functional requirements, which are tangible functionalities provided
by the DSS, NFRs are often hidden and transparent to DSS users but
affect the quality of the provided functionalities. NFRs are often
overlooked or added later to the system in an ad hoc manner, leading
to a poor overall quality of the system. In this paper, we discuss the
development of NFRs as part of the requirements engineering phase
of the system development life cycle of DSSs. To help eliciting
NFRs, we provide a comprehensive taxonomy of NFRs for DSSs.
Abstract: The survey and classification of the different security
attacks in structured peer-to-peer (P2P) overlay networks can be
useful to computer system designers, programmers, administrators,
and users. In this paper, we attempt to provide a taxonomy of
structured P2P overlay networks security attacks. We have specially
focused on the way these attacks can arise at each level of the
network. Moreover, we observed that most of the existing systems
such as Content Addressable Network (CAN), Chord, Pastry,
Tapestry, Kademlia, and Viceroy suffer from threats and vulnerability
which lead to disrupt and corrupt their functioning. We hope that our
survey constitutes a good help for who-s working on this area of
research.
Abstract: Lately there has been a significant boost of interest in
music digital libraries, which constitute an attractive area of research
and development due to their inherent interesting issues and
challenging technical problems, solutions to which will be highly
appreciated by enthusiastic end-users. We present here a DL that we
have developed to support users in their quest for classical music
pieces within a particular collection of 18,000+ audio recordings.
To cope with the early DL model limitations, we have used a refined
socio-semantic and contextual model that allows rich bibliographic
content description, along with semantic annotations, reviewing,
rating, knowledge sharing etc. The multi-layered service model
allows incorporation of local and distributed information,
construction of rich hypermedia documents, expressing the complex
relationships between various objects and multi-dimensional spaces,
agents, actors, services, communities, scenarios etc., and facilitates
collaborative activities to offer to individual users the needed
collections and services.
Abstract: In line with changes of consumers modern lifestyle has call for the advertising strategy to change. This research is to find out how game with telepresence and product experience embedded in the computer game to affect users- intention to purchase. Game content developers are urging to consider of placing product message as part of game design strategy that can influence the game player-s intention to purchase. Experiment was carried out on two hundred and fifty undergraduate students who volunteered to participate in the Internet game playing activities. A factor analysis and correlation analysis was performed on items designed to measure telepresence, attitudes toward telepresence, and game player intention to purchase the product advertise in the game that respondents experienced. The results indicated that telepresence consist of interactive experience and product experience. The study also found that product experience is positively related to the game players- intention to purchase. The significance of product experience implies the usefulness of an interactive advertising in the game playing to attract players- intention to purchase the advertised product placed in the creative game design.
Abstract: The Virtual Reality (VR) is becoming increasingly
important for business, education, and entertainment, therefore VR
technology have been applied for training purposes in the areas of
military, safety training and flying simulators. In particular, the
superior and high reliability VR training system is very important in
immersion. Manipulation training in immersive virtual environments
is difficult partly because users must do without the hap contact with
real objects they rely on in the real world to orient themselves and
their manipulated.
In this paper, we create a convincing questionnaire of immersion
and an experiment to assess the influence of immersion on
performance in VR training system. The Immersion Questionnaire
(IQ) included spatial immersion, Psychological immersion, and
Sensory immersion. We show that users with a training system
complete visual attention and detection of signals. Twenty subjects
were allocated to a factorial design consisting of two different VR
systems (Desktop VR and Projector VR). The results indicated that
different VR representation methods significantly affected the
participants- Immersion dimensions.