[AISWorld] Newly published papers of JCSE (Mar. 2018)

Fri Mar 30 03:15:13 EDT 2018

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 4,000 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 12, Number 1, March 2018

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. 12, no. 1, March 2018

[Paper One]

- Title: Human Activities Recognition Based on Skeleton Information via
Sparse Representation

- Authors: Suolan Liu, Lizhi Kong, and Hongyuan Wang

- Keyword: Activity recognition; Skeleton feature; Temporal feature; Sparse
representation

- Abstract

Human activities recognition is a challenging task due to its complexity of
human movements and the variety performed by different subjects for the same
action. This paper presents a recognition algorithm by using skeleton
information generated from depth maps. Concatenating motion features and
temporal constraint feature produces feature vector. Reducing dictionary
scale proposes an improved fast classifier based on sparse representation.
The developed method is shown to be effective by recognizing different
activities on the UTD-MHAD dataset. Comparison results indicate superior
performance of our method over some existing methods.

To obtain a copy of the entire article, click on the link below.
JCSE, vol. 12, no. 1, pp.1-11
<http://jcse.kiise.org/PublishedPaper/year_abstract.asp?idx=301&page_url=Cur
rent_Issues> 

[Paper Two]

- Title: Why Dynamic Security for the Internet of Things?

- Authors: Seyyed Yasser Hashemi and Fereidoon Shams Aliee

- Keyword: Dynamic Security; Internet of Things; IoT architectures

- Abstract

The Internet of Things (IoT) ecosystem potentially includes heterogeneous
devices with different processing mechanisms as well as very complicated
network and communication models. Thus, analysis of data associated with
adverse conditions is much more complicated. Moreover, mobile things in the
IoT lead to dynamic alteration of environments and developments of a dynamic
and ultra-large-scale (ULS) environment. Also, IoT and the services provided
by that are mostly based on devices with limited resources or things that
may not be capable of hosting conventional controls.

Finally, the dynamic and heterogeneous and ULS environment of the IoT will
lead to the emergence of new security requirements. The conventional
preventive and diagnostic security controls cannot sufficiently protect it
against increasing complication of threats. The counteractions provided by
these methods are mostly dependent on insufficient static data that cannot
sufficiently protect systems against sophisticated and dynamically evolved
attacks. Accordingly, this paper investigates the current security
approaches employed in the IoT architectures. Moreover, we define the
dynamic security based on dynamic event analysis, dynamic engineering of new
security requirements, context awareness and adaptability, clarify the need
for employment of new security mechanism, and delineate further works that
need to be conducted to achieve a secure IoT.

To obtain a copy of the entire article, click on the link below.
JCSE, vol. 12, no. 1, pp.12-23
<http://jcse.kiise.org/PublishedPaper/year_abstract.asp?idx=302&page_url=Cur
rent_Issues> 

[Paper Three]

- Title: Toward Optimal FPGA Implementation of Deep Convolutional Neural
Networks for Handwritten Hangul Character Recognition

- Authors: Hanwool Park, Yechan Yoo, Yoonjin Park, Changdae Lee, Hakkyung
Lee, Injung Kim, and Kang Yi

- Keyword: Deep convolutional neural networks; Deep learning accelerator;
FPGA optimal design; Hangul character recognition

- Abstract

Deep convolutional neural network (DCNN) is an advanced technology in image
recognition. Because of extreme computing resource requirements, DCNN
implementation with software alone cannot achieve real-time requirement.
Therefore, the need to implement DCNN accelerator hardware is increasing. In
this paper, we present a field programmable gate array (FPGA)-based hardware
accelerator design of DCNN targeting handwritten Hangul character
recognition application. Also, we present design optimization techniques in
SDAccel environments for searching the optimal FPGA design space. The
techniques we used include memory access optimization and computing unit
parallelism, and data conversion. We achieved about 11.19 ms recognition
time per character with Xilinx FPGA accelerator. Our design optimization was
performed with Xilinx HLS and SDAccel environment targeting Kintex XCKU115
FPGA from Xilinx.

Our design outperforms CPU in terms of energy efficiency (the number of
samples per unit energy) by 5.88 times, and GPGPU in terms of energy
efficiency by 5 times. We expect the research results will be an alternative
to GPGPU solution for real-time applications, especially in data centers or
server farms where energy consumption is a critical problem.

To obtain a copy of the entire article, click on the link below.
JCSE, vol. 12, no. 1, pp.24-35
<http://jcse.kiise.org/PublishedPaper/year_abstract.asp?idx=303&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).