[AISWorld] Newly published papers of JCSE (Sep. 2016)

Fri Sep 30 05:19:33 EDT 2016

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 10, Number 3, September 2016

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. 10, no. 3, September 2016

[Paper One]

- Title: Data-driven Adaptive Safety Monitoring Using Virtual Subjects in
Medical Cyber-Physical Systems: A Glucose Control Case Study

- Authors: Sanjian Chen, Oleg Sokolsky, James Weimer, and Insup Lee

- Keyword: Medical cyber-physical systems; Data-driven approach;
Computational Virtual Subjects; Safety

monitoring; Glucose control

- Abstract

Medical cyber-physical systems (MCPS) integrate sensors, actuators, and
software to improve patient safety and quality

of healthcare. These systems introduce major challenges to safety analysis
because the patient's physiology is complex,

nonlinear, unobservable, and uncertain. To cope with the challenge that
unidentified physiological parameters may

exhibit short-term variances in certain clinical scenarios, we propose a
novel run-time predictive safety monitoring technique

that leverages a maximal model coupled with online training of a
computational virtual subject (CVS) set. The proposed

monitor predicts safety-critical events at run-time using only clinically
available measurements. We apply the

technique to a surgical glucose control case study. Evaluation on
retrospective real clinical data shows that the algorithm

achieves 96% sensitivity with a low average false alarm rate of 0.5 false
alarm per surgery.

To obtain a copy of the entire article, click on the link below.
JCSE, vol. 10, no. 3, pp.75-84
<http://jcse.kiise.org/PublishedPaper/year_abstract.asp?idx=265&page_url=Cur
rent_Issues> 

[Paper Two]

- Title: A Model-Based Method for Information Alignment: A Case Study on
Educational Standards

- Authors: Namyoun Choi, Il-Yeol Song and Yongjun Zhu

- Keyword: Information alignment; Model-based method; Educational standards
alignment; Materialization

- Abstract

We propose a model-based method for information alignment using educational
standards as a case study. Discrepancies and inconsistencies in educational
standards across different states/cities hinder the retrieval and sharing of
educational resources. Unlike existing educational standards alignment
systems that only give binary judgments (either "aligned" or "not-aligned"),
our proposed system classifies each pair of educational standard statements
in one of seven levels of alignments: Strongly Fully-aligned, Weakly
Fully-aligned, Partially-aligned***, Partially-aligned**,
Partially-aligned*, Poorly-aligned, and Not-aligned. Such a 7-level
categorization extends the notion of binary alignment and provides a
finer-grained system for comparing educational standards that can broaden
categories of resource discovery and retrieval. This study continues our
previous use of mathematics education as a domain, because of its generally
unambiguous concepts. We adopt a materialization pattern (MP) model
developed in our earlier work to represent each standard statement as a
verb-phrase graph and a noun-phrase graph; we align a pair of statements
using graph matching based on Bloom's Taxonomy, WordNet, and taxonomy of
mathematics concepts. Our experiments on data sets of mathematics
educational standards show that our proposed system can provide alignment
results with a high degree of agreement with domain expert's judgments.

To obtain a copy of the entire article, click on the link below.
JCSE, vol. 10, no. 3, pp.85-94
<http://jcse.kiise.org/PublishedPaper/year_abstract.asp?idx=266&page_url=Cur
rent_Issues> 

[Paper Three]

- Title: Enhanced Sign Language Transcription System via Hand Tracking and
Pose Estimation

- Authors: Jung-Ho Kim, Najoung Kim, Hancheol Park, and Jong C. Park

- Keyword: Sign language recognition; Hand tracking; Depth prediction; Pose
estimation; Transcription

- Abstract

In this study, we propose a new system for constructing parallel corpora for
sign languages, which are generally underresourced in comparison to spoken
languages. In order to achieve scalability and accessibility regarding data
collection and corpus construction, our system utilizes deep learning-based
techniques and predicts depth information to perform pose estimation on hand
information obtainable from video recordings by a single RGB camera. These
estimated poses are then transcribed into expressions in SignWriting. We
evaluate the accuracy of hand tracking and hand pose estimation modules of
our system quantitatively, using the American Sign Language Image Dataset
and the American Sign Language Lexicon Video Dataset. The evaluation results
show that our transcription system has a high potential to be successfully
employed in constructing a sizable sign language corpus using various types
of video resources.

To obtain a copy of the entire article, click on the link below.
JCSE, vol. 10, no. 3, pp.95-101
<http://jcse.kiise.org/PublishedPaper/year_abstract.asp?idx=267&page_url=Cur
rent_Issues> 

[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 at kiise.org>
office at kiise.org (phone: +82-2-588-9240; FAX: +82-2-521-1352).