922 resultados para data storage concept
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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We describe a low-cost, high quality device capable of monitoring indirect activity by detecting touch-release events on a conducting surface, i.e., the animal's cage cover. In addition to the detecting sensor itself, the system includes an IBM PC interface for prompt data storage. The hardware/software design, while serving for other purposes, is used to record the circadian activity rhythm pattern of rats with time in an automated computerized fashion using minimal cost computer equipment (IBM PC XT). Once the sensor detects a touch-release action of the rat in the upper portion of the cage, the interface sends a command to the PC which records the time (hours-minutes-seconds) when the activity occurred. As a result, the computer builds up several files (one per detector/sensor) containing a time list of all recorded events. Data can be visualized in terms of actograms, indicating the number of detections per hour, and analyzed by mathematical tools such as Fast Fourier Transform (FFT) or cosinor. In order to demonstrate method validation, an experiment was conducted on 8 Wistar rats under 12/12-h light/dark cycle conditions (lights on at 7:00 a.m.). Results show a biological validation of the method since it detected the presence of circadian activity rhythm patterns in the behavior of the rats
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The global interest towards renewable energy production such as wind and solar energy is increasing, which in turn calls for new energy storage concepts due to the larger share of intermittent energy production. Power-to-gas solutions can be utilized to convert surplus electricity to chemical energy which can be stored for extended periods of time. The energy storage concept explored in this thesis is an integrated energy storage tank connected to an oxy-fuel combustion plant. Using this approach, flue gases from the plant could be fed directly into the storage tank and later converted into synthetic natural gas by utilizing electrolysis-methanation route. This work utilizes computational fluid dynamics to model the desublimation of carbon dioxide inside a storage tank containing cryogenic liquid, such as liquefied natural gas. Numerical modelling enables the evaluation of the transient flow patterns caused by the desublimation, as well as general fluid behaviour inside the tank. Based on simulations the stability of the cryogenic storage and the magnitude of the key parameters can be evaluated.
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After sales business is an effective way to create profit and increase customer satisfaction in manufacturing companies. Despite this, some special business characteristics that are linked to these functions, make it exceptionally challenging in its own way. This Master’s Thesis examines the current situation of the data and inventory management in the case company regarding possibilities and challenges related to the consolidation of current business operations. The research examines process steps, procedures, data requirements, data mining practices and data storage management of spare part sales process, whereas the part focusing on inventory management is reviewing the current stock value and examining current practices and operational principles. There are two global after sales units which supply spare parts and issues reviewed in this study are examined from both units’ perspective. The analysis is focused on the operations of that unit where functions would be centralized by default, if change decisions are carried out. It was discovered that both data and inventory management include clear shortcomings, which result from lack of internal instructions and established processes as well as lack of cooperation with other stakeholders related to product’s lifecycle. The main product of data management was a guideline for consolidating the functions, tailored for the company’s needs. Additionally, potentially scrapped spare part were listed and a proposal of inventory management instructions was drafted. If the suggested spare part materials will be scrapped, stock value will decrease 46 percent. A guideline which was reviewed and commented in this thesis was chosen as the basis of the inventory management instructions.
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Remote Data acquisition and analysing systems developed for fisheries and related environmental studies have been reported. It consists of three units. The first one namely multichannel remote data acquisition system is installed at the remote place powered by a rechargeable battery. It acquires and stores the 16 channel environmental data on a battery backed up RAM. The second unit called the Field data analyser is used for insitue display and analysis of the data stored in the backed up RAM. The third unit namely Laboratory data analyser is an IBM compatible PC based unit for detailed analysis and interpretation of the data after bringing the RAM unit to the laboratory. The data collected using the system has been analysed and presented in the form of a graph. The system timer operated at negligibly low current, switches on the power to the entire remote operated system at prefixed time interval of 2 hours.Data storage at remote site on low power battery backedupRAM and retrieval and analysis of data using PC are the special i ty of the system. The remote operated system takes about 7 seconds including the 5 second stabilization time to acquire and store data and is very ideal for remote operation on rechargeable bat tery. The system can store 16 channel data scanned at 2 hour interval for 10 days on 2K backed up RAM with memory expansion facility for 8K RAM.
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In some applications with case-based system, the attributes available for indexing are better described as linguistic variables instead of receiving numerical treatment. In these applications, the concept of fuzzy hypercube can be applied to give a geometrical interpretation of similarities among cases. This paper presents an approach that uses geometrical properties of fuzzy hypercube space to make indexing and retrieval processes of cases.
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Background: Statistical shape models are widely used in biomedical research. They are routinely implemented for automatic image segmentation or object identification in medical images. In these fields, however, the acquisition of the large training datasets, required to develop these models, is usually a time-consuming process. Even after this effort, the collections of datasets are often lost or mishandled resulting in replication of work. Objective: To solve these problems, the Virtual Skeleton Database (VSD) is proposed as a centralized storage system where the data necessary to build statistical shape models can be stored and shared. Methods: The VSD provides an online repository system tailored to the needs of the medical research community. The processing of the most common image file types, a statistical shape model framework, and an ontology-based search provide the generic tools to store, exchange, and retrieve digital medical datasets. The hosted data are accessible to the community, and collaborative research catalyzes their productivity. Results: To illustrate the need for an online repository for medical research, three exemplary projects of the VSD are presented: (1) an international collaboration to achieve improvement in cochlear surgery and implant optimization, (2) a population-based analysis of femoral fracture risk between genders, and (3) an online application developed for the evaluation and comparison of the segmentation of brain tumors. Conclusions: The VSD is a novel system for scientific collaboration for the medical image community with a data-centric concept and semantically driven search option for anatomical structures. The repository has been proven to be a useful tool for collaborative model building, as a resource for biomechanical population studies, or to enhance segmentation algorithms.
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Due to the advancement of both, information technology in general, and databases in particular; data storage devices are becoming cheaper and data processing speed is increasing. As result of this, organizations tend to store large volumes of data holding great potential information. Decision Support Systems, DSS try to use the stored data to obtain valuable information for organizations. In this paper, we use both data models and use cases to represent the functionality of data processing in DSS following Software Engineering processes. We propose a methodology to develop DSS in the Analysis phase, respective of data processing modeling. We have used, as a starting point, a data model adapted to the semantics involved in multidimensional databases or data warehouses, DW. Also, we have taken an algorithm that provides us with all the possible ways to automatically cross check multidimensional model data. Using the aforementioned, we propose diagrams and descriptions of use cases, which can be considered as patterns representing the DSS functionality, in regard to DW data processing, DW on which DSS are based. We highlight the reusability and automation benefits that this can be achieved, and we think this study can serve as a guide in the development of DSS.
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In this paper we describe Fénix, a data model for exchanging information between Natural Language Processing applications. The format proposed is intended to be flexible enough to cover both current and future data structures employed in the field of Computational Linguistics. The Fénix architecture is divided into four separate layers: conceptual, logical, persistence and physical. This division provides a simple interface to abstract the users from low-level implementation details, such as programming languages and data storage employed, allowing them to focus in the concepts and processes to be modelled. The Fénix architecture is accompanied by a set of programming libraries to facilitate the access and manipulation of the structures created in this framework. We will also show how this architecture has been already successfully applied in different research projects.
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The increasing demand for high capacity data storage requires decreasing the head-to-tape gap and reducing the track width. A problem very often encountered is the development of adhesive debris on the heads at low humidity and high temperatures that can lead to an increase of space between the head and media, and thus a decrease in the playback signal. The influence of stains on the playback signal of reading heads is studied using RAW (Read After Write) tests and their influence on the wear of the heads by using indentation technique. The playback signal has been found to vary and the errors to increase as stains form a patchy pattern and grow in size to form a continuous layer. The indentation technique shows that stains reduce the wear rate of the heads. In addition, the wear tends to be more pronounced at the leading edge of the head compared to the trailing one. Chemical analysis of the stains using ferrite samples in conjunction with MP (metal particulate) tapes shows that stains contain iron particles and polymeric binder transferred from the MP tape. The chemical anchors in the binder used to grip the iron particles now react with the ferrite surface to create strong chemical bonds. At high humidity, a thin layer of iron oxyhydroxide forms on the surface of the ferrite. This soft material increases the wear rate and so reduces the amount of stain present on the heads. The stability of the binder under high humidity and under high temperature as well as the chemical reactions that might occur on the ferrite poles of the heads influences the dynamic behaviour of stains. A model of stain formation taking into account the channels of binder degradation and evolution upon different environmental conditions is proposed.
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The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model's parsing mechanism. The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents.
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In order to become better prepared to support Research Data Management (RDM) practices in sciences and engineering, Queen’s University Library, together with the University Research Services, conducted a research study of all ranks of faculty members, as well as postdoctoral fellows and graduate students at the Faculty of Engineering & Applied Science, Departments of Chemistry, Computer Science, Geological Sciences and Geological Engineering, Mathematics and Statistics, Physics, Engineering Physics & Astronomy, School of Environmental Studies, and Geography & Planning in the Faculty of Arts and Science.
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The large upfront investments required for game development pose a severe barrier for the wider uptake of serious games in education and training. Also, there is a lack of well-established methods and tools that support game developers at preserving and enhancing the games’ pedagogical effectiveness. The RAGE project, which is a Horizon 2020 funded research project on serious games, addresses these issues by making available reusable software components that aim to support the pedagogical qualities of serious games. In order to easily deploy and integrate these game components in a multitude of game engines, platforms and programming languages, RAGE has developed and validated a hybrid component-based software architecture that preserves component portability and interoperability. While a first set of software components is being developed, this paper presents selected examples to explain the overall system’s concept and its practical benefits. First, the Emotion Detection component uses the learners’ webcams for capturing their emotional states from facial expressions. Second, the Performance Statistics component is an add-on for learning analytics data processing, which allows instructors to track and inspect learners’ progress without bothering about the required statistics computations. Third, a set of language processing components accommodate the analysis of textual inputs of learners, facilitating comprehension assessment and prediction. Fourth, the Shared Data Storage component provides a technical solution for data storage - e.g. for player data or game world data - across multiple software components. The presented components are exemplary for the anticipated RAGE library, which will include up to forty reusable software components for serious gaming, addressing diverse pedagogical dimensions.
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After years of deliberation, the EU commission sped up the reform process of a common EU digital policy considerably in 2015 by launching the EU digital single market strategy. In particular, two core initiatives of the strategy were agreed upon: General Data Protection Regulation and the Network and Information Security (NIS) Directive law texts. A new initiative was additionally launched addressing the role of online platforms. This paper focuses on the platform privacy rationale behind the data protection legislation, primarily based on the proposal for a new EU wide General Data Protection Regulation. We analyse the legislation rationale from an Information System perspective to understand the role user data plays in creating platforms that we identify as “processing silos”. Generative digital infrastructure theories are used to explain the innovative mechanisms that are thought to govern the notion of digitalization and successful business models that are affected by digitalization. We foresee continued judicial data protection challenges with the now proposed Regulation as the adoption of the “Internet of Things” continues. The findings of this paper illustrate that many of the existing issues can be addressed through legislation from a platform perspective. We conclude by proposing three modifications to the governing rationale, which would not only improve platform privacy for the data subject, but also entrepreneurial efforts in developing intelligent service platforms. The first modification is aimed at improving service differentiation on platforms by lessening the ability of incumbent global actors to lock-in the user base to their service/platform. The second modification posits limiting the current unwanted tracking ability of syndicates, by separation of authentication and data store services from any processing entity. Thirdly, we propose a change in terms of how security and data protection policies are reviewed, suggesting a third party auditing procedure.