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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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