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Idle Time Estimation for Bandwidth-Efficient
Synchronization in Replicated Distributed File System
Fidan Kaya Gülağız, Süleyman
Eken, Adnan Kavak, and Ahmet Sayar
Department of Computer Engineering, Kocaeli University,
Turkey
Abstract: Synchronization is a promising approach to solve
the consistency problems in replicated distributed file systems. The
synchronization can be repeated periodically, with fixed time interval or a
time interval which can be adjusted adaptively. In this paper, we propose a
policy-based performance efficient distributed file synchronization approach,
in which synchronization processes occur in varying time intervals and adjusted
adaptively. The study is based on tracing network idle times by means of
measuring and clustering Round Trip Time (RTT) values. K-means clustering is
used to cluster RTT values as idle, normal, and busy. To estimate the most
suitable synchronization time intervals, the measured RTT values are included
into these classes with an algorithm similar to Transmission Control Protocol (TCP)
Additive-Increase/Multiplicative-Decrease (AIMD) feedback control. The
efficiency and feasibility of the proposed technique is examined on a
distributed file synchronization application within the scope of Fatih project,
which is one of the most important educational projects in Turkey.
Keywords: Idle time detection algorithm, cloud
traffic, round trip time, K-means clustering, distributed file synchronization,
policy-based synchronization.
Received October 4, 2015; accepted January 3, 2016
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Image Processing in
Differential Digital
Holography (DDH)
Kresimir Nenadic, Tomislav Galba, and
Irena Galic
Faculty of Electrical Engineering, Computer Science and Information Technology in
University of Osijek, Croatia
Abstract: Accumulating dust on Charge-Coupled
Device/Complementary Metal-oxide-Semiconductor (CCD/CMOS) sensors can cause problems in detecting
defects on observed object in some industrial production. This paper describes
Differential Digital Holography (DDH) and observed effect of cancelling the
negative impact of dust on optical sensor. The laboratory setup for recording
digital holograms is described and shown graphically later in paper. Differential
digital holography method is presented step by step. Furthermore, negative
effect of accumulating dust on CCD/CMOS sensor and cancelling effect due to DDH
method is explained. DDH method comprises of both hardware and software parts.
Digital hologram recording process takes place on hardware and all image, i.e.,
digital hologram, while processing is performed by intensive calculations on
processor. Experiments were conducted and graphical results are shown.
Keywords: CCD/CMOS image sensors, digital
holography, dust, holographic optical components, Image processing.
Received April 15, 2015; accepted November 29, 2016
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An Optimized Model for Visual Speech Recognition Using
HMM
Sujatha Paramasivam1
and Radhakrishnan Murugesanadar2
1Department of
Computer Science and Engineering, Sudharsan Engineering College, India
2Department of
Civil Engineering, Sethu Institute of Technology, India
Abstract: Visual Speech Recognition (VSR) is to identify spoken
words from visual data only without the corresponding acoustic signals. It is
useful in situations in which conventional audio processing is ineffective like
very noisy environments or impossible like unavailability of audio signals. In
this paper, an optimized model for VSR is introduced which proposes simple
geometric projection method for mouth localization that reduces the computation
time.16-point distance method and chain code method are used to extract the
visual features and its recognition performance is compared using the
classifier Hidden Markov Model (HMM). To optimize the model, more prominent features
are selected from a large set of extracted visual attributes using Discrete
Cosine Transform (DCT). The experiments were conducted on an in-house database
of 10 digits [1 to 10] taken from 10 subjects and tested with 10-fold cross
validation technique. Also, the model is evaluated based on the metrics
specificity, sensitivity and accuracy. Unlike other models in the literature,
the proposed method is more robust to subject variations with high sensitivity
and specificity for the digits 1 to 10. The result shows that the combination
of 16-point distance method and DCT gives better results than only 16-point
distance method and chain code method.
Keywords: Visual speech recognition, feature extraction,
discrete cosine transform, chain code, hidden markov model.
Received March
20, 2015; accepted August 31, 2015
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A Fuzzy Based Matrix Methodology for Evaluation
and Ranking of Data Warehouse Conceptual Models Metrics
Naveen Dahiya1,
Vishal Bhatnagar2, and Manjeet Singh3
1Maharaja
Surajmal Institute of Technology, C-4, Janakpuri, India
2Ambedkar
Institute of Advanced Communication Technology and Research, India
3YMCA
University of Science and Technology, Sector-6, India
Abstract: The authors present a methodology for ranking data
warehouse conceptual models metrics based on opinion of experts using fuzzy
inference technique. The fuzzy based approach gives a precise ranking
methodology due to its ability to handle imprecise data involved in ranking of
metrics and ambiguity involved in expert decision making process. The proposed
work aims towards ranking of quality metrics already proposed and validated by
Manuel Serrano along certain identified parameters based on expert opinion and
evaluation of criteria matrix using permanent function. The results obtained
are also compared with the actual experts ranking. The achieved results are
better as the imprecise human thinking is taken into consideration during
calculation of results to give realistic results.
Keywords: Fuzzy, data warehouse, conceptual models, quality
metrics, criteria matrix.
Received October
23, 2014; accepted July 7, 2015
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