Dear Colleague:

We are pleased to announce the release of a new issue of Journal of
Computing Science and Engineering (JCSE), published by the Korean Institute
of Information Scientists and Engineers (KIISE). KIISE is the largest
organization for computer scientists in Korea with over 4000 active members.

Journal of Computing Science and Engineering (JCSE) is a peer-reviewed
quarterly journal that publishes high-quality papers on all aspects of
computing science and engineering. JCSE aims to foster communication between
academia and industry within the rapidly evolving field of Computing Science
and Engineering. The journal is intended to promote problem-oriented
research that fuses academic and industrial expertise. The journal focuses
on emerging computer and information technologies including, but not limited
to, embedded computing, ubiquitous computing, convergence computing, green
computing, smart and intelligent computing, and human computing. JCSE
publishes original research contributions, surveys, and experimental studies
with scientific advances.

Please take a look at our new issue posted at http://jcse.kiise.org
<http://jcse.kiise.org/> . All the papers can be downloaded from the Web
page.

The contents of the latest issue of Journal of Computing Science and
Engineering (JCSE)

Official Publication of the Korean Institute of Information Scientists and
Engineers

Volume 11, Number 1, March 2017

pISSN: 1976-4677

eISSN: 2093-8020

* JCSE web page: http://jcse.kiise.org 

* e-submission: http://mc.manuscriptcentral.com/jcse 

Editor in Chief: Insup Lee (University of Pennsylvania)

Il-Yeol Song (Drexel University) 

Jong C. Park (KAIST)

Taewhan Kim (Seoul National University)

JCSE, vol. 11, no. 1, March 2017

[Paper One]

- Title: Memory-Efficient NBNN Image Classification

- Authors: YoonSeok Lee and Sung-Eui Yoon

- Keyword: Image classification; NBNN; Hashing; Memory efficiency; Indexing

- Abstract

Naive Bayes nearest neighbor (NBNN) is a simple image classifier based on
identifying nearest neighbors. NBNN uses original image descriptors (e.g.,
SIFTs) without vector quantization for preserving the discriminative power
of descriptors and has a powerful generalization characteristic. However, it
has a distinct disadvantage. Its memory requirement can be prohibitively
high while processing a large amount of data. To deal with this problem, we
apply a spherical hashing binary code embedding technique, to compactly
encode data without significantly losing classification accuracy. We also
propose using an inverted index to identify nearest neighbors among
binarized image descriptors. To demonstrate the benefits of our method, we
apply our method to two existing NBNN techniques with an image dataset. By
using 64 bit length, we are able to reduce memory 16 times with higher
runtime performance and no significant loss of classification accuracy. This
result is achieved by our compact encoding scheme for image descriptors
without losing much information from original image descriptors.

To obtain a copy of the entire article, click on the link below.
JCSE, vol. 11, no. 1, pp.1-8
<http://jcse.kiise.org/PublishedPaper/topic_abstract.asp?idx=276> 

[Paper Two]

- Title: NuDE 2.0: A Formal Method-based Software Development, Verification
and Safety Analysis Environment for Digital I&Cs in NPPs

- Authors: Eui-Sub Kim, Dong-Ah Lee, Sejin Jung, Junbeom Yoo, Jong-Gyun Choi
and Jang-Soo Lee

- Keyword: MBD; Formal methods; Safety analysis; PLC; FPGA; Digital I&C

- Abstract

NuDE 2.0 (Nuclear Development Environment 2.0) is a formal-method-based
software development, verification and safety analysis environment for
safety-critical digital I&Cs implemented with programmable logic controller
(PLC) and field-programmable gate array (FPGA). It simultaneously develops
PLC/FPGA software implementations from one requirement/design specification
and also helps most of the development, verification, and safety analysis to
be performed mechanically and in sequence. The NuDE 2.0 now consists of 25
CASE tools and also includes an in-depth solution for indirect commercial
off-the-shelf (COTS) software dedication of new FPGA-based digital I&Cs. We
expect that the NuDE 2.0 will be widely used as a means of diversifying
software design/implementation and model-based software development
methodology.

To obtain a copy of the entire article, click on the link below.
JCSE, vol. 11, no. 1, pp.9-23
<http://jcse.kiise.org/PublishedPaper/topic_abstract.asp?idx=277> 

[Paper Three]

- Title: A Comparative Study of Local Features in Face-based Video Retrieval

- Authors: Juan Zhou and Lan Huang

- Keyword: Video retrieval; Face matching; Harris operators; SIFT; SURF;
Eigenfaces

- Abstract

Face-based video retrieval has become an active and important branch of
intelligent video analysis. Face profiling and matching is a fundamental
step and is crucial to the effectiveness of video retrieval. Although many
algorithms have been developed for processing static face images, their
effectiveness in face-based video retrieval is still unknown, simply because
videos have different resolutions, faces vary in scale, and different
lighting conditions and angles are used. In this paper, we combined
content-based and semantic-based image analysis techniques, and
systematically evaluated four mainstream local features to represent face
images in the video retrieval task: Harris operators, SIFT and SURF
descriptors, and eigenfaces. Results of ten independent runs of 10-fold
cross-validation on datasets consisting of TED (Technology Entertainment
Design) talk videos showed the effectiveness of our approach, where the SIFT
descriptors achieved an average F-score of 0.725 in video retrieval and thus
were the most effective, while the SURF descriptors were computed in 0.3
seconds per image on average and were the most efficient in most cases.

To obtain a copy of the entire article, click on the link below.
JCSE, vol. 11, no. 1, pp.24-31
<http://jcse.kiise.org/PublishedPaper/topic_abstract.asp?idx=278> 

[Paper Four]

- Title: Word Sense Disambiguation Using Embedded Word Space

- Authors: Myung Yun Kang, Bogyum Kim and Jae Sung Lee

- Keyword: Word sense disambiguation; Word embedding; Word space; Semantic
analysis

- Abstract

Determining the correct word sense among ambiguous senses is essential for
semantic analysis. One of the models for word sense disambiguation is the
word space model which is very simple in the structure and effective.
However, when the context word vectors in the word space model are merged
into sense vectors in a sense inventory, they become typically very large
but still suffer from the lexical scarcity. In this paper, we propose a word
sense disambiguation method using word embedding that makes the sense
inventory vectors compact and efficient due to its additive
compositionality. Results of experiments with a Korean sense-tagged corpus
show that our method is very effective.

To obtain a copy of the entire article, click on the link below.
JCSE, vol. 11, no. 1, pp.32-38
<http://jcse.kiise.org/PublishedPaper/topic_abstract.asp?idx=279> 

[Call For Papers]

Journal of Computing Science and Engineering (JCSE), published by the Korean
Institute of Information Scientists and Engineers (KIISE) is devoted to the
timely dissemination of novel results and discussions on all aspects of
computing science and engineering, divided into Foundations, Software &
Applications, and Systems & Architecture. Papers are solicited in all areas
of computing science and engineering. See JCSE home page at
http://jcse.kiise.org <http://jcse.kiise.org/>  for the subareas.

The journal publishes regularly submitted papers, invited papers, selected
best papers from reputable conferences and workshops, and thematic issues
that address hot research topics. Potential authors are invited to submit
their manuscripts electronically, prepared in PDF files, through
<http://mc.manuscriptcentral.com/jcse> http://mc.manuscriptcentral.com/jcse,
where ScholarOne is used for on-line submission and review. Authors are
especially encouraged to submit papers of around 10 but not more than 30
double-spaced pages in twelve point type. The corresponding author's full
postal and e-mail addresses, telephone and FAX numbers as well as current
affiliation information must be given on the manuscript. Further inquiries
are welcome at JCSE Editorial Office,  <mailto:office@kiise.org>
office@kiise.org (phone: +82-2-588-9240; FAX: +82-2-521-1352).

_______________________________________________
AISWorld mailing list
AISWorld@lists.aisnet.org

Betreff:	[AISWorld] Newly published papers of JCSE (Mar. 2017)
Datum:	Thu, 30 Mar 2017 19:55:41 +0900
Von:	office@kiise.org
An:	aisworld@lists.aisnet.org