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Bayesian statistical algorithm plays a significant role in the quality of the images produced by Emission Tomography like PET/SPECT, since they can provide an accurate system model. The major drawbacks associated with this algorithm include the problem of slow convergence, choice of optimum initial point and ill-posedness. To address these issues, in this paper a hybrid-cascaded framework for Median...
Replication is a strategy in which multiple copies of same data are stored at multiple sites. Replication has been used in cloud storage systems as a way to increase data availability, reliability and fault tolerance and to increase the performance. Number of replicas to be created for a file and placement of the replicas are the two important factors which determine the storage requirement and performance...
Searching for solutions that optimize a continuous function can be difficult due to the infinite search space, and can be further complicated by the high dimensionality in the number of variables and complexity in the structure of constraints. Both deterministic and stochastic methods have been presented in the literature with a purpose of exploiting the search space and avoiding local optima as much...
In this paper, the effect of low, middle and high frequency DCT coefficients are investigated onto gray scale image watermarking in terms of imperceptibility and robustness. The performance of Lagrangian twin support vector regression (LTSVR), which was successfully applied on synthetic datasets obtained from UCI repository for various kinds of regression problems by Balasundaram et al. [9], onto...
A novel and intuitive way of scheduling entities on a heterogeneous multiprocessing system is presented. The key idea is to understand the behavioral characteristics (foreground/background, IO-bound/CPU-bound) of a scheduling entity to predict the need for its processing bandwidth. This is then used by the scheduler to influence the selection of the big cluster (high-performance) or the LITTLE cluster...
Anomaly detection is an important task in many real world applications such as fraud detection, suspicious activity detection, health care monitoring etc. In this paper, we tackle this problem from supervised learning perspective in online learning setting. We maximize well known Gmean metric for class-imbalance learning in online learning framework. Specifically, we show that maximizing Gmean is...
The era of cloud based multimedia applications has lead to a huge increase in the no. of requests on cloud. The increased no. of requests on cloud leads to an increased workload, making workload balancing an important QoS Parameter. Workload Balancing also leads to a judicious use of resources like electricity etc. and thus promotes the concept of Green IT. The paper presents a new Load Balanced Resource...
Academics establish relations among them in multitude ways, co-authorship being one of them. In fact co-authorship has the advantage of being the best recorded among all forms of academic collaborations. Co-authored publications appear in the form of research articles, conference and workshop proceedings, technical reports, etc. As per DBLP, one of the major digital libraries, around 55 percent of...
This article focuses on the writer verification using safe handwritten passwords on smartphones. We extract and select 25 static and dynamic biometric features from a handwritten character password sequence on an android touch-screen device. For the writer verification we use the classification algorithms of WEKA framework. Our 32 test persons wrote generated safe passwords with a length of 8 characters...
In a time when personal data circulates constantly between devices and within the cloud, biometric security systems represents one of the most viable security solutions. A relatively new biometric modality based on the individual's Electroencephalogram (EEG) is starting now to gain popularity among researchers. Its relevance relay mainly on its prospects of high security and robustness against intruders...
This paper presents a new approach for the acoustic classification of frogs' calls using a novel fusion of features: Mel Frequency Cepstral Coefficients (MFCCs), Shannon entropy and syllable duration. First, the audio recordings of different frogs' species are segmented in syllables. For each syllable, each feature is extracted and the cepstral features (MFCC) are computed and evaluated separately...
With rapid technological development and growth of sequencing data, an umpteen gamut of biological data has been generated. As an alternative, Data Compression is employed to reduce the size of data. In this direction, this paper proposes a new reference-based compression approach, which is employed as a solution. Firstly, a reference has been constructed from the common sub strings of randomly selected...
The chances of copyright violation and piracy have been increased due to growth of networking and technology. Digital watermark is useful to verify the integrity of the content and for authenticity of an owner. The digital watermark must be robust against various attacks in order to protect the copyright information which is embedded in the original content. The proposed algorithm is useful for protecting...
For a cloud datacenter the biggest issue is how to tackle billions of requests coming dynamically from the end users. To handle such requests efficiently and effectively, there is a need to distribute the load evenly among the cloud nodes. To achieve this goal, various load balancing approaches have been proposed in the past years. Load balancing strategies aim at achieving high user satisfaction...
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