Vol.11 No.1&2
April 2, 2015
A Mobile Omnidirectional Wheelchair: Its
Implementation and Experimental Evaluation
(1-9)
Keita Matsuo, Donald Elmazi, Yi Liu, and Leonard Barolli
In recent years, more and more convenient facilities and equipments have
been developed in order to satisfy the requirements of elderly people
and disabled people. Among them, wheelchair is a common one which is
widely used and can provide the user with many benefits, such as
maintaining mobility, continuing or broadening community and social
activities, conserving strength and energy, and enhancing quality of
life. The wheelchair body must be compact enough to go through narrow
doorways. The wheelchair must be wide enough to prevent the patient from
falling on the floor. A large footprint is therefore desirable for
stability and safety, while wheelchairs must conform to dimensional
constraints. In this paper, we present the implementation and evaluation
of an omnidirectional wheelchair, which has a small size and can move
easily in narrow spaces. In order to evaluate the implemented
wheelchair, we carried out some experiments and discussed some
implementation and application issues. The experimental results show
that the implemented wheelchair in general works properly.
Implementation and Evaluation of A Fuzzy-based
Cluster-Head Selection System for Wireless Sensor Networks Considering
Network Traffic
(10-20)
Donald Elmazi, Keita Matsuo, Tetsuya Oda, Makoto Ikeda, and
Leonard Barolli
There are many fundamental problems that Wireless Sensor Networks (WSNs)
research will have to address in order to ensure a reasonable degree of
cost and system quality. Some of these problems include sensor node
clustering, Cluster Head (CH) selection and energy dissipation. Cluster
formation and CH selection are important problems in WSNs applications
and can drastically affect the WSNs energy. However, selecting of the CH
is not easy in different environments which may have different
characteristics. In order to deal with this problem, in our previous
work, we have proposed a power reduction algorithm for WNSs based on
fuzzy logic and number of neighbor nodes. In this paper, we propose a
new fuzzy-based CH selection system considering network traffic to
improve the performance of the previous system. We evaluate the proposed
system by simulations and show that it has a good CH selection.
Evaluation of a RFID-Based System of a Table Type
Rfid Reader (21-33)
Kiyotaka Fujisaki
RFID system is one of the key technology to bring efficiency to library
services such as the automatic rental of book and return. In this paper,
we evaluate the performance of table type RFID reader. Furthermore, when
RFID reader is on the metallic plate (which affected the performance of
RFID), we investigate the relation between the reading rate and the
distance between metallic plate and RFID reader. From the experiments,
it is clearly shown that communication area decreases and becomes near
the center of reader's antenna as the distance between the tag and the
reader increases. The influence of the metallic plate to the reader
depends on the gap between the metallic plate and the reader.
Improving Reliability of JXTA-Overlay Platform:
Evaluation for e-Learning and Trustworthiness
(34-49)
Yi Liu, Shinji Sakamoto, Keita Matsuo, Makoto Ikeda, and Leonard
Barolli
We have implemented JXTA-Overlay platform, which is a middleware built
on top of the JXTA specification. The JXTA-Overlay defines a set of
protocols that standardize how different devices may communicate and
collaborate among them. Also, it provides a set of basic
functionalities, primitives, intended to be as complete as possible to
satisfy the needs of most JXTA-based applications. In P2P systems, each
peer has to obtain information of peers and propagate it to other peers.
The trustworthiness of peers is very important for safe communication in
P2P systems. In this paper, we propose and evaluate a fuzzy-based system
to improve the reliability of JXTA-Overlay platform. The JXTA-Overlay is
integrated with Internet of Things (IoT) by using RFID technology and
SmartBox. We evaluate JXTA-Overlay platform for e-learning and
trustworthiness. The experimental results show that by using JXTA-Overlay
is possible to decide the situation of learners. The simulation results
have shown that the proposed system has a good performance and can
select trusted peers to connect to JXTA-Overlay platform.
Performance Evaluation of Sightseeing Contents
Considering Different Computer Skill and Devices (50-65)
Kaoru Sugita, Ken Nishimur,_ and Masao Yokota
In our previous work, we already
proposed a user interface switching function as a new concept of
‘universal multimedia access’ to narrow the digital divide by providing
appropriate multimedia expressions according to users’ (mental and
physical) abilities, computer facilities, and network environments. The
user interface switching provides a User Interface (UI) with appropriate
operations and media according to their computer skill and computer
facilities. In order to evaluate our approach for user interface
switching, we have constructed sightseeing contents and introduce 28
spots in 6 prefectures of Japan providing 9 types of user interfaces in
HTML5 and Java Script. In this paper, we discuss
the performance evaluation for the sightseeing contents.
An Interactive e-Learning System for Improving
Students Motivation and Self-learning by Using Smartphones
(66-74)
Noriyasu Yamamoto
In this paper, we present an
interactive learning system, which uses a method of acquiring /
utilizing the study records for improving the students learning
motivation for learning. During the lecture, the students use the
smartphone for learning. The results showed that the proposed study
record system has a good effect for improving students’ motivation for
learning. For the professors of the university, it is difficult to offer
all necessary information to the students. In addition, they cannot
provide the information to satisfy all students because the quantity of
knowledge of each student attending a lecture is different. Therefore,
for higher level lectures than intermediate level, the students should
study by themselves the learning materials. In this study, we show that
our method of acquiring / utilizing the study record promotes the
self-learning of the student. In this research, we carried experiments
during real lectures at the intermediate level. The results showed that
the proposed study record system can improve the degree of self-learning
after the lecture.
Adaptive Remeshing for Edge Length Interval
Constraining (75-89)
João Vitor de Sá Hauck, Ramon Nogueira Da Silva, Marcelo
Bernardes Vieira,
and Rodrigo Luis de Souza da Silva
This paper presents a method for explicitly remesh an arbitrary input
surface into a mesh with all edge lengths within a fixed interval. The
process starts with an arbitrary triangular 2-manifold mesh. The
proposed method is iterative and uses stellar operations to achieve the
necessary amount of vertices and triangles. It also applies a technique
to uniformly distribute the vertices of the model over the surface. At
earlier stages of the algorithm, this technique is an approximation of
the Laplacian filter. In order to preserve the geometry of the model,
some constraints are added to the filter. At later stages, we replace
the global uniformization strategy with a nonlinear optimizer, that
performs only locally. A projection step is also applied at each
iteration, to prevent the geometric distortions caused by the method. We
also apply a post processing step to correct the final edges, if the
standard iterations do not converge. Our method results in a very
regular mesh, with uniform distribution of vertices. The dual trivalent
mesh obtained by this mesh can be useful for several applications. The
main contribution of this work is a new approach for edge length
equalization, with explicit constraints definition, higher computational
performance and lower global geometry losses if compared to previous
works.
A Video Tensor Self-descriptor Based on Block
Matching
(90-102)
Helena Almeida Maia, Ana Mara De Oliveira Figueiredo, Fabio Luiz
Marinho De Oliveira,
Virginia Fernandes Mota, and Marcelo
Bernardes Vieira
This paper presents a different and simple approach for video
description using only block matching vectors, considering that most
works on the field are based on the gradient of image intensities. We
first divide the image into blocks of different sizes. The block
matching method returns a displacement vector for each block, which we
use as motion information to obtain orientation tensors and to generate
the final self-descriptor, since it depends only on the input video. The
resulting descriptor is evaluated by a classification of KTH, UCF11 and
Hollywood2 video datasets with a non-linear SVM classifier. Our results
indicate that the method runs fast and has fairly competitive results
compared to similar approaches. It is suitable when the time response is
a major application issue. It also generates compact descriptors which
are desirable to describe large datasets.
Tracing Fast-Changing Landscape of Study on Big
Data
(103-118)
Weiguang Wang, Xi Zhang, Patricia Ordonez de Pablos, and Jinghuai
She
This study traced the
fast-changing landscape of study on big data. Three hottest aspects of
big data study are: technologies, application to academic study and real
value in big data. With the rising of mobile multimedia and social
media, more and more data were produced in our daily life. Traditional
methods and technologies are inefficient or even powerless facing such
large scales of data. Also, academics gained greater abilities to
produce much more data than before, but had few good methods of
analysing big data. Therefore, new technologies targeting efficient
utilization of big data are being proposed, like MapReduce, Hadoop and
so on. Methods of applying big data to academic study are also being
discussed intensively. Furthermore, the political and business value
hidden in big data is very attractive. People believe that although some
profits have been made, much more are hidden in big data to be dug out.
In this paper, current stage, influential references, outstanding
authors, important institutions, top-tier journals and evolution of hot
topics are all analysed with help of CiteSpace to map big data study.
Finally, forecasting on development of big data study was made to
provide help for future study.
Mobile and Multimedia Learning in Preschool
Education
(119-133)
Athanasios Drigas, Georgia Kokkalia, and Miltiadis D. Lytras
The growing use of mobile and
multimedia learning in our day lives has affected different domains of
education. Nowadays, recent development in the role of kindergarten
–preschool education in children’s progress includes the use of
Information and Communication Technologies (ICTs) and especially the
support of mobile and multimedia tools. Mobile and multimedia are
recognized as the tools that can foster the knowledge and the
experiences for this crucial age and the support of specific areas in
kindergarten according to the educational perspective is thought
significant. In this paper we present an overview of the most
representative studies of the last decade (2003-2014) which concentrates
on the skills that are examined in kindergarten (early literacy, early
mathematics, cognitive, social-emotional, motor) and are supported by
mobile and multimedia educational tools. The effectiveness of them in
special education is also examined.
The TPACK Model to Prepare and Evaluate Lesson
Plans: An Experience with Pre-service Teachers Using Social Networks and
Digital Resources (134-146)
Maria Graciela Badilla Quintana and Diana Sabillón Zelaya
It is essential to understand and manage
technology for pre-service teachers in order to propose methodological,
educational and assessment strategies that allow them to innovate and
respond adequately to the demands of the educational system. The
objective is to identify the elements that pre-service teachers use in
learning situations for the production of digital educational resources
created to teach using social networks through the TPACK rubric.
This research was developed focused
on a quantitative methodology and a descriptive design.
The sample was formed by 32
pre-service teachers who attend an Information and Communication
Technology Course in 2014, at the Faculty of Education, Universidad
Católica de la Santísima Concepción. Main results obtained from the
analysis of three educational resources (blog, Prezi and cartoons)
indicate that they possess a low level of integration of curricular
objectives and technologies; however, results show that students have a
high level to select the technological resources in the design of
didactic activities. It can be concluded that incorporation of the TPACK
model, positively helps pre-service students to know how to integrate
the teaching resources in an innovative way. It enables the achievement
of an adequate articulation of technology in teaching and learning.
Mobile Learning and Higher Education: A
Theoretical Overview
(147-156)
Monica Aresta, Luis Pedro, and Carlos Santos
Nowadays, mobile technologies play an
important role in Higher Education students’ academic and social lives.
When the digital and "always-connected" dimension of the students’ lives
becomes an issue of crescent importance, Higher Education Institutions
face the need to develop approaches focused on the integration of mobile
devices in learning processes. When the adoption of mobile technology
for teaching and learning is recognized as an important area of
educational research, this paper reviews recent literature on mobile
learning in Higher Education settings and summarizes the findings of
empirical investigations. Reviewed literature uncovered some benefits
and limitations of the adoption of mobile devices in education, showing
that Higher Education students’ value the opportunities and improvements
brought by mobile learning as well as reveal some frustration and
concerns. In the centre of everything and as one of the mains reason for
either adopting of rejecting mobile learning, lies the perception of
students regarding the added value of mobile devices in their learning
processes.
Fuzzy, Neural Network and
Expert Systems Methodologies and Applications: A Review (157-176)
Ul Amin Rooh, AiJun Li, and Malik M. Ali
The rapid growth in the field of
artificial intelligence from past one decade has a significant impact on
various application areas i.e. health, security, home appliances among
many. In this paper we aim to review artificial intelligence
methodologies and their potential applications intended for variable
purposes i.e. Agriculture, applied sciences, business, engineering,
finance, management etc. For this purpose articles from past one decade
(from 2004 to 2013) are reviewed in order to explore the most recent
research advancements in this domain. The review includes 172 articles
gathered from related sources including conference proceedings and
academic journals. We have categorized the selected articles into four
main categories i.e. fuzzy systems, neural network based systems, neuro
fuzzy systems and expert systems. Furthermore, expert systems are
further classified into three categories: (i) rule based expert systems,
(ii) knowledge based expert systems and (iii) intelligent agents. This
review presents research implications for practitioners regarding
integration of artificial intelligence techniques with classical
approaches and suggestions for exploration of AI techniques in variable
applications.
Back
to JMM Online Front Page |