167 resultados para GPU computing


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A soft computing framework to classify and optimize text-based information extracted from customers' product reviews is proposed in this paper. The soft computing framework performs classification and optimization in two stages. Given a set of keywords extracted from unstructured text-based product reviews, a Support Vector Machine (SVM) is used to classify the reviews into two categories (positive and negative reviews) in the first stage. An ensemble of evolutionary algorithms is deployed to perform optimization in the second stage. Specifically, the Modified micro Genetic Algorithm (MmGA) optimizer is applied to maximize classification accuracy and minimize the number of keywords used in classification. Two Amazon product reviews databases are employed to evaluate the effectiveness of the SVM classifier and the ensemble of MmGA optimizers in classification and optimization of product related keywords. The results are analyzed and compared with those published in the literature. The outputs potentially serve as a list of impression words that contains useful information from the customers' viewpoints. These impression words can be further leveraged for product design and improvement activities in accordance with the Kansei engineering methodology.

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 The endless transformation of technological innovation requires greater collaboration of Information Communication and Technology (ICT) in various areas especially in public sectors. Many attempts have been made in improving the quality of E-Government services; one of it is adopting the cloud computing technology. Successful implementation of cloud computing technology can benefit the public sector in many ways one of it is cost reduction. Most government organizations especially in the developing countries are committed in adopting the cloud technology based on the increased demands in cloud adoption in E Government services. Unfortunately, despite all the benefits, the cloud computing technology raises some major risks. The success of implementation of cloud computing technology is determined by how well the government tackles the challenges. Therefore, this paper specifically surveyed the associated challenges of adopting Cloud Technology for E-Government by choosing Malaysia as the case study.

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Trust problem in Software as a Service Cloud Computing is a broad range of a Data Owner’s concerns about the data in the Cloud. The Data Owner’s concerns about the data arise from the way the data is handled in locations and machines that are unknown to the Data Owner.

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 This thesis presents a number of applications of symbolic computing to the study of differential equations. In particular, three packages have been produced for the computer algebra system MAPLE and used to find a variety of symmetries (and corresponding invariant solutions) for a range of differential systems.

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 This research focused on building Software as a Service clouds to support mammalian genomic applications such as personalized medicine. Outcomes of this research included a Software as a Service cloud framework, the Uncinus research cloud and novel genomic analysis software. Results have been published in high ranking peer-reviewed international journals.

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This paper focuses on an investigation to explore architectural design potentials with a responsive material system and physical computing. Contemporary architects and designers are seeking to integrate physical computing in responsive architectural designs; however, they have largely borrowed from engineering technology's mechanical devices and components. There is the opportunity to investigate an unexplored design approach to exploit the responsive capacity of material properties as alternatives to the current focus on mechanical components and discrete sensing devices. This opportunity creates a different design paradigm for responsive architecture that investigates the potential to integrate physical computing with responsive materials as one integrated material system. Instead of adopting highly intricate and expensive materials, this approach is explored through accessible and off-the-shelf materials to form a responsive material system, called Lumina. Lumina is implemented as an architectural installation called Cloud that serves as a morphing architectural skin. Cloud is a proof of concept to embody a responsive material system with physical computing to create a reciprocal and luminous architectural intervention for a selected dark corridor. It represents a different design paradigm for responsive architecture through alternative exploitation of contemporary materials and parametric design tools. © 2014, The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong.

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The primary purpose of this book is to capture the state-of-the-art in Cloud Computing technologies and applications. The book will also aim to identify potential research directions and technologies that will facilitate creation a global market-place of cloud computing services supporting scientific, industrial, business, and consumer applications. We expect the book to serve as a reference for larger audience such as systems architects, practitioners, developers, new researchers and graduate level students. This area of research is relatively recent, and as such has no existing reference book that addresses it. This book will be a timely contribution to a field that is gaining considerable research interest, momentum, and is expected to be of increasing interest to commercial developers. The book is targeted for professional computer science developers and graduate students especially at Masters level. As Cloud Computing is recognized as one of the top five emerging technologies that will have a major impact on the quality of science and society over the next 20 years, its knowledge will help position our readers at the forefront of the field. © 2011 John Wiley & Sons, Inc.

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Cloud computing is becoming popular as the next infrastructure of computing platform. However, with data and business applications outsourced to a third party, how to protect cloud data centers from numerous attacks has become a critical concern. In this paper, we propose a clusterized framework of cloud firewall, which characters performance and cost evaluation. To provide quantitative performance analysis of the cloud firewall, a novel M/Geo/1 analytical model is established. The model allows cloud defenders to extract key system measures such as request response time, and determine how many resources are needed to guarantee quality of service (QoS). Moreover, we give an insight into financial cost of the proposed cloud firewall. Finally, our analytical results are verified by simulation experiments.

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Cloud-based service computing has started to change the way how research in science, in particular biology, medicine, and engineering, is being carried out. Researchers in the area of mammalian genomics have taken advantage of cloud computing technology to cost-effectively process large amounts of data and speed up discovery. Mammalian genomics is limited by the cost and complexity of analysis, which require large amounts of computational resources to analyse huge amount of data and biology specialists to interpret results. On the other hand the application of this technology requires computing knowledge, in particular programming and operations management skills to develop high performance computing (HPC) applications and deploy them on HPC clouds. We carried out a survey of cloud-based service computing solutions, as the most recent and promising instantiations of distributed computing systems, in the context their use in research of mammalian genomic analysis. We describe our most recent research and development effort which focuses on building Software as a Service (SaaS) clouds to simplify the use of HPC clouds for carrying out mammalian genomic analysis.

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There is a growing awareness of the importance of including computing education in the curriculum of secondary schools in countries like the United States of America, the United Kingdom, New Zealand, and South Korea. Consequently, we have seen serious efforts to introduce computing education to the core curriculum and/or to improve it. Recent reports (such as Wilson et al. 2010; Hubwieser et al. 2011) reveal that computing education faces problems regarding its lack of exposure as well as a lack of motivators for students to follow this line of study. Although students use computers for many tasks both at home and at school, many of them never quite understand what computer science is and how it relates to algorithmic thinking and problem solving. This panel will bring together leaders in computing education from Australia, Germany, Greece, Israel and Norway to describe the state of computing education in each of their countries. Issues raised will include how high school computer education is conducted in that country, how teachers are skilled /accredited, the challenges that are being faced today and how these challenges are being addressed. Panellists will suggest lessons other countries may find of value from their way of doing things. An important issue is how to recruit female students in to computer education at high school level and how to encourage them to continue in the discipline to university. The problem is exacerbated because computer education is still not included as a compulsory subject in the regular curriculum of high schools in all of these countries.

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This paper is devoted to a case study of a new construction of classifiers. These classifiers are called automatically generated multi-level meta classifiers, AGMLMC. The construction combines diverse meta classifiers in a new way to create a unified system. This original construction can be generated automatically producing classifiers with large levels. Different meta classifiers are incorporated as low-level integral parts of another meta classifier at the top level. It is intended for the distributed computing and networking. The AGMLMC classifiers are unified classifiers with many parts that can operate in parallel. This make it easy to adopt them in distributed applications. This paper introduces new construction of classifiers and undertakes an experimental study of their performance. We look at a case study of their effectiveness in the special case of the detection and filtering of phishing emails. This is a possible important application area for such large and distributed classification systems. Our experiments investigate the effectiveness of combining diverse meta classifiers into one AGMLMC classifier in the case study of detection and filtering of phishing emails. The results show that new classifiers with large levels achieved better performance compared to the base classifiers and simple meta classifiers classifiers. This demonstrates that the new technique can be applied to increase the performance if diverse meta classifiers are included in the system.