COMPUTE

In this paper we present a comparison study of two widely used parallelizing frameworks on the CPU, namely, OpenMP and Intel Threading Building Blocks (TBB). The particular problem domain we apply to is a grid-based fluid simulation solver. The standard ...

Software Quality is generally characterized by several factors which reveal the degree of success of the software developed and its future maintainability. Although many existing models provide frameworks of huge potential pertaining to quality analysis,...

A scalable, packet address driven strategy that tests an open fault on network-on-chip (NoC) interconnects and maximal connectivity between neighbor routers in presence of a short fault is proposed. The open faults and maximal connectivity are tested ...

The objective of the paper is to propose trust aware routing method for cooperative and resilient geographic routing in Wireless Ad-hoc and Sensor Networks (WASNs). The proposed method calculates the trust value on the basis of node behavior in routing ...

A new recommendation framework that addresses the correct and quick resolution of incidents that occur within the complex systems of an enterprise is introduced here. It uses statistical learning to mediate problem solving by large-scale Resolution ...

Maintaining the desired coverage level and reliability is a major challenge in the field of wireless sensor networks (WSNs). WSN consists of number of resource constrained and unreliable sensors. In this paper we have proposed a node scheduling protocol ...

Stemming is an operation that reduces morphological variants of words to its stem. Stemming is a pre-processing tool which is used in various natural language processing applications such as text summarization, information retrieval, word sense ...

Handling and processing of larger volume of data requires efficient data mining algorithms. k-means is a very popular clustering algorithm for data mining, but its performance suffers because of initial seeding problem. The computation time of k-means ...

Data Mining Technique, namely Classification, is used to predict group membership for data samples. Ensemble learning, combining multiple classifiers using bagging, boosting or stacking, are proven data-mining methods, we have used boosting in this ...

Over the decades, researchers are trying to find an effective methodology for smooth uninterrupted multimedia data streaming through the broad band network in video on demand system. The problem is directly related to the efficiently use of methodology ...

As the digital data continues to grow unbounded, users expect intelligent processing and accurate coverage of all its domains. Advances in display technology have led to a variety of viewing devices, each with its own characteristic sizes and ...

Exponentiation is computing ge, where g is an element of a group G and e is a positive integer. In modular exponentiation the underlying group is Zn or Z*n. This paper describe the methods to compute exponentiation where a fixed-exponent e is raised to ...

In this paper we describe techniques to use SPDY and HTTP network resources optimally for testing purposes with limited resources such as RAM. We demonstrate how to overcome the system limitations of network analysis tools such as the 64K limit on ...

The feature extraction-coding-pooling framework improves the performance of image classification because it generates robust and discriminative image representation. The proposed system uses saliency driven multi-scale nonlinear diffusion filtering with ...

Cloud Computing provides an easy access to the end users i.e. users can access the services from wherever they want to without concerning about the storage, management, and cost and so on. With an increase in its number of users per day, threat for ...

The modern enterprise is becoming larger and geographically distributed. The structure of companies is also becoming more complicated. Oraganizations are depending on knowledge within the enterprise and outside the enterprise. More and more individuals ...

Capturing, modeling, and querying data provenance in databases has gained considerable importance in the last decade. All kinds of applications developed on top of databases, now a days collect provenance for various purposes like trustworthiness of ...

k-nearest neighbor (k-NN) search is one of the commonly used query in database systems. It has its application in various domains like data mining, decision support systems, information retrieval, multimedia and spatial databases, etc. When k-NN search ...

Classification is one of the most interesting problems in the fast evolving fields such as e-commerce and web-based businesses where the data is growing exponentially. Existing classification techniques over e-commerce data are mainly based on the users'...