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PatTrieSort - External String Sorting based on Patricia Tries
Get PDFExternal merge sort belongs to the most efficient and widely used algorithms to sort big data: As much data as fits inside is sorted in main memory and afterwards swapped to external storage as so called initial run. After sorting all the data in this way block-wise, the initial runs are merged in a merging phase in order to retrieve the final sorted run containing the completely sorted original data. Patricia tries are one of the most space-efficient ways to store strings especially those with common prefixes. Hence, we propose to use patricia tries for initial run generation in an external merge sort variant, such that initial runs can become large compared to traditional external merge sort using the same main memory size. Furthermore, we store the initial runs as patricia tries instead of lists of sorted strings. As we will show in this paper, patricia tries can be efficiently merged having a superior performance in comparison to merging runs of sorted strings. We complete our discussion with a complexity analysis as well as a comprehensive performance evaluation, where our new approach outperforms traditional external merge sort by a factor of 4 for sorting over 4 billion strings of real world data
Eventual Consistent Databases: State of the Art
Get PDFOne of the challenges of cloud programming is to achieve the right balance between the availability and consistency in a distributed database. Cloud computing environments, particularly cloud databases, are rapidly increasing in importance, acceptance and usage in major applications, which need the partition-tolerance and availability for scalability purposes, but sacrifice the consistency side (CAP theorem). In these environments, the data accessed by users is stored in a highly available storage system, thus the use of paradigms such as eventual consistency became more widespread. In this paper, we review the state-of-the-art database systems using eventual consistency from both industry and research. Based on this review, we discuss the advantages and disadvantages of eventual consistency, and identify the future research challenges on the databases using eventual consistency
Data Transfers in Hadoop: A Comparative Study
Get PDFHadoop is an open source framework for processing large amounts of data in distributed computing environment. It plays an important role in processing and analyzing the Big Data. This framework is used for storing data on large clusters of commodity hardware. Data input and output to and from Hadoop is an indispensable action for any data processing job. At present, many tools have been evolved for importing and exporting Data in Hadoop. In this article, some commonly used tools for importing and exporting data have been emphasized. Moreover, a state-of-the-art comparative study among the various tools has been made. With this study, it has been decided that where to use one tool over the other with emphasis on the data transfer to and from Hadoop system. This article also discusses about how Hadoop handles backup and disaster recovery along with some open research questions in terms of Big Data transfer when dealing with cloud-based services
Ontology Evolution Using Ontology Templates
Get PDFEvolving ontologies by domain experts is difficult and typically cannot be performed without the assistance of an ontology engineer. This process takes long time and often recurrent modeling errors have to be resolved. This paper proposes a technique for creating controlled ontology evolution scenarios that ensure consistency of the possible ontology evolution and give guarrantees to the domain expert that his/her updates do not cause inconsistency. We introduce ontology templates that formalize the notion of controlled evolution and define ontology template consistency checking service together with a consistency checking algorithm. We prove correctness and demonstate the practical use of the techniques in two scenarios
BEAUFORD: A Benchmark for Evaluation of Formalisation of Definitions in OWL
Get PDFIn this paper we present BEAUFORD, a benchmark for methods which aim to provide formal expressions of concepts using the natural language (NL) definition of these concepts. Adding formal expressions of concepts to a given ontology allows reasoners to infer more useful pieces of information or to detect inconsistencies in this given ontology. To the best of our knowledge, BEAUFORD is the first benchmark to tackle this ontology enrichment problem. BEAUFORD allows the breaking down of a given formalisation approach by identifying its key features. In addition, BEAUFORD provides strong mechanisms to evaluate efficiently an approach even in case of ambiguity which is a major challenge in formalisation of NL resources. Indeed, BEAUFORD takes into account the fact that a given NL phrase can be formalised in many ways. Hence, it proposes a suitable specification to represent these multiple formalisations. Taking advantage of this specification, BEAUFORD redefines classical precision and recall and introduces other metrics to take into account the fact that there is not only one unique way to formalise a definition. Finally, BEAUFORD comprises a well-suited dataset to concretely judge of the efficiency of methods of formalisation. Using BEAUFORD, current approaches of formalisation of definitions can be compared accurately using a suitable gold standard
Model of Creative Thinking Process on Analysis of Handwriting by Digital Pen
Get PDFIn order to perceive infrequent events as hints for new ideas, it is desired to know and model the process of creating and refining ideas. In this paper, we address this modeling problem experimentally. Firstly, we focus on the relation between thinking time and writing time in handwriting. We observe two types of patterns; one group takes longer time in thinking and shorter in writing, the other takes longer in writing and shorter in thinking. The group having spends longer in writing has shorter time span from one sentence to another than the other group. Backtracking, i.e., the event that participants return back to their former sheet and modify opinions, is observed more often in the group of longer writing than the other group. In addition, participants in this backtracking group gets higher scores for their ideas on sheets than those in the no-backtracking group. We propose a model of creative thinking by applying Operations of Structure of Intellect. It is inferred that the group of longer writing conducts a series of thinking flow, including divergent thinking, convergent thinking and evaluation. In contrast, the group of longer thinking tends to conduct the two different thinking flow: divergent thinking and evaluation; convergent thinking and evaluation. For making creative ideas, we conduct divergent thinking without evaluation and created a large number of ideas. We conclude that the rotations of divergent thinking, convergent thinking and evaluation increase the frequency of "backtracking" and make the ideas more logical ones
Evidential Sensor Data Fusion in a Smart City Environment
Get PDFWireless sensor networks have increasingly become contributors of very large amounts of data. The recent deployment of wireless sensor networks in Smart City infrastructures have led to very large amounts of data being generated each day across a variety of domains, with applications including environmental monitoring, healthcare monitoring and transport monitoring. The information generated through the wireless sensor nodes has made possible the visualization of a Smart City environment for better living. The Smart City offers intelligent infrastructure and cogitative environment for the elderly and other people living in the Smart society. Different types of sensors are present that help in monitoring inhabitants' behaviour and their interaction with real world objects. To take advantage of the increasing amounts of data, there is a need for new methods and techniques for effective data management and analysis, to generate information that can assist in managing the resources intelligently and dynamically. Through this research a Smart City ontology model is proposed, which addresses the fusion process related to uncertain sensor data using semantic web technologies and Dempster-Shafer uncertainty theory. Based on the information handling methods, such as Dempster-Shafer theory (DST), an equally weighted sum operator and maximization operation, a higher level of contextual information is inferred from the low-level sensor data fusion process. In addition, the proposed ontology model helps in learning new rules that can be used in defining new knowledge in the Smart City system
A Comparative Evaluation of Current HTML5 Web Video Implementations
Get PDFHTML5 video is the upcoming standard for playing videos on the World Wide Web. Although its specification has not been fully adopted yet, all major browsers provide the HTML5 video element and web developers already rely on its functionality. But there are differences between implementations and inaccuracies that trouble the web developer community. To help to improve the current situation we draw a comparison between the most important web browsers. We focus on the event mechanism, since it is essential for interacting with the video element. Furthermore, we compare the seeking accuracy, which is relevant for more specialized applications. Our tests reveal varieties of differences between browser interfaces and show that even simple software solutions may still need third-party plugins in today's browsers
Fuzzy Color Space for Apparel Coordination
Get PDFHuman perception of colors constitutes an important part in color theory. The applications of color science are truly omnipresent, and what impression colors make on human plays a vital role in them. In this paper, we offer the novel approach for color information representation and processing using fuzzy sets and logic theory, which is extremely useful in modeling human impressions. Specifically, we use fuzzy mathematics to partition the gamut of feasible colors in HSI color space based on standard linguistic tags. The proposed method can be useful in various image processing applications involving query processing. We demonstrate its effectivity in the implementation of a framework for the apparel online shopping coordination based on a color scheme. It deserves attention, since there is always some uncertainty inherent in the description of apparels
An Introductory Approach to Risk Visualization as a Service
Get PDFThis paper introduces the Risk Visualization as a Service (RVaaS) and presents the motivation, rationale, methodology, Cloud APIs used, operations and examples of using RVaaS. Risks can be calculated within seconds and presented in the form of Visualization to ensure that unexploited areas are ex-posed. RVaaS operates in two phases. The first phase includes the risk modeling in Black Scholes Model (BSM), creating 3D Visualization and Analysis. The second phase consists of calculating key derivatives such as Delta and Theta for financial modeling. Risks presented in visualization allow the potential investors and stakeholders to keep track of the status of risk with regard to time, prices and volatility. Our approach can improve accuracy and performance. Results in experiments show that RVaaS can perform up to 500,000 simulations and complete all simulations within 24 seconds for time steps of up to 50. We also introduce financial stock market analysis (FSMA) that can fully blend with RVaaS and demonstrate two examples that can help investors make better decision based on the pricing and market volatility information. RVaaS provides a structured way to deploy low cost, high quality risk assessment and support real-time calculations