Dear all,
We apologize if you received multiple copies of this message.
Please be informed that the Vol.32 No.1 of the VNU Journal of Science:
Computer Science and Communication Engineering has been
published. This issue is also available online in the website of the
journal, http://www.jcsce.vnu.edu.vn. We are sending you the title and
abstract of the articles published in this issue in case you may be
interested in.
By the way, we would like to let you know that the journal has been
considered as one of the most influential journals in the IT field in
Vietnam by many organizations. We look forward to your new contribution
to the journal.
Thank you for your attention!
Best regards,
Prof. Nguyen Thanh Thuy
Editor Head of JCSCE
VNU Journal of Science: Computer Science and Communication Engineering
http://www.jcsce.vnu.edu.vn
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[1] Efficient Region-of-Interest Based Adaptive Bit Allocation for 3D-TV Video Transmission over Networks,
Nam Thanh Pham, Khuong Duy Vu, Duong Trieu Dinh, and Ha Thanh Le,
pages 1-9
Abstract:
Due to characteristics of human visual system (HVS), people usually
focus more on a specific region named region-of-interest (ROI) of a
video frame, rather than watch the whole frame. In addition, ROI-based
video coding can also help to effectively reduce the number of
encoding bitrates required for video transmission over networks,
especially for the 3D-TV transmissions. Therefore, in this work, we
propose a novel ROI-based bit allocation (BA) method which can
adaptively extract and increase the visual quality of ROI while saving
a huge number of encoding bitrates for video data. In the proposed
method, we first detect and extract ROI based on the depth information
obtained from 3D-TV video coding sequences. Then, based on the
extracted ROI, a novel BA scheme is performed to solve the
rate-distortion (R-D) optimization problem, in which the higher
priority bitrates are adaptively assigned to ROI while the total
encoding bitrates of video frames are kept satisfying all constraints
required by the R-D optimization. Experimental results show that the
proposed method provides much better higher peak signal-to-noise ratio
(PSNR) as compared to other conventional BA methods.
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[2] Hyper-volume Evolutionary Algorithm,
Khoi Nguyen Le and Dario Landa-Silva,
pages 10-32
Abstract:
We propose a multi-objective evolutionary algorithm (MOEA), named the
Hyper-volume Evolutionary Algorithm (HVEA). The algorithm is
characterised by three components. First, individual fitness
evaluation depends on the current Pareto front, specifically on the
ratio of its dominated hyper-volume to the current Pareto front
hyper-volume, hence giving an indication of how close the individual
is to the current Pareto front. Second, a ranking strategy classifies
individuals based on their fitness instead of Pareto dominance,
individuals within the same rank are non guaranteed to be mutually
non-dominated. Third, a crowding assignment mechanism that adapts
according to the individual’s neighbouring area, controlled by the
neighbouring area radius parameter, and the archive of non-dominated
solutions. We perform extensive experiments on the multiple 0/1
knapsack problem using different greedy repair methods to compare the
performance of HVEA to other MOEAs including NSGA2, SEAMO2, SPEA2,
IBEA and MOEA/D. This paper shows that by tuning the neighbouring area
radius parameter, the performance of the proposed HVEA can be pushed
towards better convergence, diversity or coverage and this could be
beneficial to different types of problems.
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[3] Reducing Startup Time in MP4 On-demand Video Streaming Services with Movie Atom Caching,
Xuan Tung Hoang and Tien Thanh Nguyen,
pages 33-41
Abstract:
This paper points out negative effects on startup time of video
streaming sessions caused by atom metadata in MP4 movie files. Based
on experiments, it is shown that the duration for downloading metadata
atom could be relatively large for high-quality full-length movie
videos. This leads to noticeable and disturbing startup delay to users
when watching MP4 movies online. In order to reduce the startup delay,
we present a mechanism, called Movie Atom Caching, that reuses
previously downloaded metadata atoms or proactively downloads and
caches movie metadata atoms at video players before users actually
play the video. The mechanism is implemented in our video streaming
prototype system. Experiments on the system show that user experience
is improved as startup delay is cut down significantly in typical
cases.
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[4] An OCL-Based Framework for Model Transformations
Duc-Hanh Dang and Martin Gogolla
pages 42-57
Abstract:
Model transformation is an important building block for model-driven
approaches. It puts forward a necessity and a challenge to specify and
realize model transformation as well as to ensure the correctness of
transformations. This paper proposes an OCL-based framework for model
transformations. The formal foundation of the framework is the
integration of Triple Graph Grammars and the Object Constraint
Language (OCL). The OCL-based transformation framework offers an
on-the-fly verification of model transformations and means for
transformation quality assurance.
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[5] Towards Model-Checking Probabilistic Timed Automata against Probabilistic Duration Properties,
Hung Van Dang, Miaomiao Zhang, and Chinh Dinh Pham,
pages 58-73
Abstract:
In this paper, we consider a subclass of Probabilistic Duration
Calculus formula called Simple Probabilistic Duration Calculus (SPDC)
as a language for specifying dependability requirements for real-time
systems, and address the two problems: to decide if a probabilistic
timed automaton satisfies a SPDC formula, and to decide if there
exists a strategy of a probabilistic timed automaton satisfies a SPDC
formula. We prove that the both problems are decidable for a class of
SPDC called probabilistic linear duration invariants, and provide
model checking algorithms for solving these problems.
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