896 resultados para computation- and data-intensive applications


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The Thesis is dedicated to development of an operative tool to support decision making of battery energy storages implementation in distribution networks. The basics of various battery technologies, their perspectives and challenges are represented in the Thesis. Mathematical equations that describe economic effect from battery energy storage installation are offered. The main factors that influence profitability of battery settings have been explored and mathematically defined. Mathematical model and principal trends of battery storage profitability under an impact of the major factors are determined. The meaning of annual net value was introduced to show the difference between savings and required costs. The model gives a clear vision for dependencies between annual net value and main factors. Proposals for optimal network and battery characteristics are suggested.

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Digitalization has been predicted to change the future as a growing range of non-routine tasks will be automated, offering new kinds of business models for enterprises. Serviceoriented architecture (SOA) provides a basis for designing and implementing welldefined problems as reusable services, allowing computers to execute them. Serviceoriented design has potential to act as a mediator between IT and human resources, but enterprises struggle with their SOA adoption and lack a linkage between the benefits and costs of services. This thesis studies the phenomenon of service reuse in enterprises, proposing an ontology to link different kinds of services with their role conceptually as a part of the business model. The proposed ontology has been created on the basis of qualitative research conducted in three large enterprises. Service reuse has two roles in enterprises: it enables automated data sharing among human and IT resources, and it may provide cost savings in service development and operations. From a technical viewpoint, the ability to define a business problem as a service is one of the key enablers for achieving service reuse. The research proposes two service identification methods, first to identify prospective services in the existing documentation of the enterprise and secondly to model the services from a functional viewpoint, supporting service identification sessions with business stakeholders.

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Rare-earth based upconverting nanoparticles (UCNPs) have attracted much attention due to their unique luminescent properties. The ability to convert multiple photons of lower energy to ones with higher energy through an upconversion (UC) process offers a wide range of applications for UCNPs. The emission intensities and wavelengths of UCNPs are important performance characteristics, which determine the appropriate applications. However, insufficient intensities still limit the use of UCNPs; especially the efficient emission of blue and ultraviolet (UV) light via upconversion remains challenging, as these events require three or more near-infrared (NIR) photons. The aim of the study was to enhance the blue and UV upconversion emission intensities of Tm3+ doped NaYF4 nanoparticles and to demonstrate their utility in in vitro diagnostics. As the distance between the sensitizer and the activator significantly affect the energy transfer efficiency, different strategies were explored to change the local symmetry around the doped lanthanides. One important strategy is the intentional co-doping of active (participate in energy transfer) or passive (do not participate in energy transfer) impurities into the host matrix. The roles of doped passive impurities (K+ and Sc3+) in enhancing the blue and UV upconversions, as well as in influencing the intense UV upconversion emission through excess sensitization (active impurity) were studied. Additionally, the effects of both active and passive impurity doping on the morphological and optical performance of UCNPs were investigated. The applicability of UV emitting UCNPs as an internal light source for glucose sensing in a dry chemistry test strip was demonstrated. The measurements were in agreement with the traditional method based on reflectance measurements using an external UV light source. The use of UCNPs in the glucose test strip offers an alternative detection method with advantages such as control signals for minimizing errors and high penetration of the NIR excitation through the blood sample, which gives more freedom for designing the optical setup. In bioimaging, the excitation of the UCNPs in the transparent IR region of the tissue permits measurements, which are free of background fluorescence and have a high signal-to-background ratio. In addition, the narrow emission bandwidth of the UCNPs enables multiplexed detections. An array-in-well immunoassay was developed using two different UC emission colours. The differentiation between different viral infections and the classification of antibody responses were achieved based on both the position and colour of the signal. The study demonstrates the potential of spectral and spatial multiplexing in the imaging based array-in-well assays.

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Advancements in information technology have made it possible for organizations to gather and store vast amounts of data of their customers. Information stored in databases can be highly valuable for organizations. However, analyzing large databases has proven to be difficult in practice. For companies in the retail industry, customer intelligence can be used to identify profitable customers, their characteristics, and behavior. By clustering customers into homogeneous groups, companies can more effectively manage their customer base and target profitable customer segments. This thesis will study the use of the self-organizing map (SOM) as a method for analyzing large customer datasets, clustering customers, and discovering information about customer behavior. Aim of the thesis is to find out whether the SOM could be a practical tool for retail companies to analyze their customer data.

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The MgAl2O4 ceramics were prepared by the conventional solid-state ceramic route and the dielectric properties studied in the microwave frequency region (3–13 GHz). The phase purity and crystal structure were identified using the X-ray diffraction technique. The MgAl2O4 spinel ceramics show interesting microwave dielectric properties (εr = 8.75, Qux f = 68 900 GHz (loss tangent = 0.00017 at 12.3 GHz), τf =−75 ppm/◦C). The MgAl2O4 has high negative τf, which precludes its immediate use in practical applications. Hence the microwave dielectric properties of MgAl2O4 spinels were tailored by adding different mole fractions of TiO2. The εr and Q factor of the mixed phases were increased with the molar addition of TiO2 into the spinel to form mixtures based on (1−x)MgAl2O4-xTiO2 (x = 0.0−1.0). For x = 0.25 in (1−x)MgAl2O4-xTiO2, the microwave quality factor reaches a maximum value of Qux f = 105 400 GHz (loss tangent = 0.00007 at 7.5 GHz) where εr and τf are 11.035 and −12 ppm/◦C, respectively. The microwave dielectric properties of the newly developed 0.75MgAl2O4-0.25TiO2 dielectric is superior to several commercially available low loss dielectric substrates.

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The objective of the preset work is to develop optical fiber sensors for various physical and chemical parameters. As a part of this we initially investigated trace analysis of silica, ammonia, iron and phosphate in water. For this purpose the author has implemented a dual wavelength probing scheme which has many advantages over conventional evanescent wave sensors. Dual wavelength probing makes the design more reliable and repeatable and this design makes the sensor employable for concentration, chemical content, adulteration level, monitoring and control in industries or any such needy environments. Use of low cost components makes the system cost effective and simple. The Dual wavelength probing scheme is employed for the trace analysis of silica, iron, phosphate, and ammonia in water. Such sensors can be employed for the steam and water quality analysers in power plants. Few samples from a power plant are collected and checked the performance of developed system for practical applications.

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Light emitting polymers (LEPs) are considered as the second generation of conducting polymers. A Prototype LEP device based on electroluminescence emission of poly(p-phenylenevinylene) (PPV) was first assembled in 1990. LEPs have progressed tremendously over the past 20 years. The development of new LEP derivatives are important because polymer light emitting diodes (PLEDs) can be used for the manufacture of next-generation displays and other optoelectronic applications such as lasers, photovoltaic cells and sensors. Under this circumstance, it is important to understand thermal, structural, morphological, electrochemical and photophysical characteristics of luminescent polymers. In this thesis the author synthesizes a series of light emitting polymers that can emit three primary colors (RGB) with high efficiency

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Fluorescence is a powerful tool in biological research, the relevance of which relies greatly on the availability of sensitive and selective fluorescent probes. Nanometer sized fluorescent semiconductor materials have attracted considerable attention in recent years due to the high luminescence intensity, low photobleaching, large Stokes’ shift and high photochemical stability. The optical and spectroscopic features of nanoparticles make them very convincing alternatives to traditional fluorophores in a range of applications. Efficient surface capping agents make these nanocrystals bio-compatible. They can provide a novel platform on which many biomolecules such as DNA, RNA and proteins can be covalently linked. In the second phase of the present work, bio-compatible, fluorescent, manganese doped ZnS (ZnS:Mn) nanocrystals suitable for bioimaging applications have been developed and their cytocompatibility has been assessed. Functionalization of ZnS:Mn nanocrystals by safe materials results in considerable reduction of toxicity and allows conjugation with specific biomolecules. The highly fluorescent, bio-compatible and water- dispersible ZnS:Mn nanocrystals are found to be ideal fluorescent probes for biological labeling

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Flexible and thin single layer microwave absorbers based on strontium ferrite–carbon black–nitrile rubber composites have been fabricated employing a specific recipe and their reflection loss characteristics were studied in the S (2–4 GHz) and X-bands (8–12 GHz). The incorporation of carbon black not only reinforces the rubber by improving the mechanical properties of the composite but also modifies the dielectric permittivity of the composite. Strontium ferrite when impregnated into a rubber matrix imparts the required magnetic permeability to the composite. The combination of strontium ferrite and carbon black can then be employed to tune the microwave absorption characteristics of the resulting composite. The complex dielectric permittivity and permeability were measured by employing a cavity perturbation technique. The microwave absorption characteristics of composites were modelled in that an electromagnetic wave incident normally on the metal terminated single layer absorber. The influence of filler volume fraction, frequency, absorber thickness on the bandwidth of absorption are discussed and correlated

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In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin.

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The furious pace of Moore's Law is driving computer architecture into a realm where the the speed of light is the dominant factor in system latencies. The number of clock cycles to span a chip are increasing, while the number of bits that can be accessed within a clock cycle is decreasing. Hence, it is becoming more difficult to hide latency. One alternative solution is to reduce latency by migrating threads and data, but the overhead of existing implementations has previously made migration an unserviceable solution so far. I present an architecture, implementation, and mechanisms that reduces the overhead of migration to the point where migration is a viable supplement to other latency hiding mechanisms, such as multithreading. The architecture is abstract, and presents programmers with a simple, uniform fine-grained multithreaded parallel programming model with implicit memory management. In other words, the spatial nature and implementation details (such as the number of processors) of a parallel machine are entirely hidden from the programmer. Compiler writers are encouraged to devise programming languages for the machine that guide a programmer to express their ideas in terms of objects, since objects exhibit an inherent physical locality of data and code. The machine implementation can then leverage this locality to automatically distribute data and threads across the physical machine by using a set of high performance migration mechanisms. An implementation of this architecture could migrate a null thread in 66 cycles -- over a factor of 1000 improvement over previous work. Performance also scales well; the time required to move a typical thread is only 4 to 5 times that of a null thread. Data migration performance is similar, and scales linearly with data block size. Since the performance of the migration mechanism is on par with that of an L2 cache, the implementation simulated in my work has no data caches and relies instead on multithreading and the migration mechanism to hide and reduce access latencies.

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The COntext INterchange (COIN) strategy is an approach to solving the problem of interoperability of semantically heterogeneous data sources through context mediation. COIN has used its own notation and syntax for representing ontologies. More recently, the OWL Web Ontology Language is becoming established as the W3C recommended ontology language. We propose the use of the COIN strategy to solve context disparity and ontology interoperability problems in the emerging Semantic Web – both at the ontology level and at the data level. In conjunction with this, we propose a version of the COIN ontology model that uses OWL and the emerging rules interchange language, RuleML.