912 resultados para fundamental principles and applications


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Mathematics Subject Classification: 44A15, 33D15, 81Q99

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Mathematics Subject Classification: 26A33, 34A60, 34K40, 93B05

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Editorial

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Whether distance learning spells the end of traditional campuses, as some maintain, or whether distance learning instead represents a powerful addition to a growing array of delivery options for higher education, its impact on higher education is great and growing. Distance learning is creating alternative models of teaching and learning, new job descriptions for faculty, and new types of higher education providers. The advent of Distance and Distributed Learning has raised numerous questions about quality and quality assurance: ² How do established distance learning institutions ensure quality? ² What more needs to be done? ² How do quality assurance agencies view the distinction between on- and off-campus teaching and learning? This talk discusses these issues from the viewpoints of funding organisa- tion, quality assurance agencies and the learners.

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Кремена В. Стефанова - В тази статия са разрешени някои нелинейни интегрални неравенства, които включват максимума на неизвестната функция на две променливи. Разгледаните неравенства представляват обобщения на класическото неравенство на Гронуол-Белман. Значението на тези интегрални неравенства се определя от широките им приложения в качествените изследвания на частните диференциални уравнения с “максимуми” и е илюстрирано чрез някои директни приложения.

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We present some recent trends in the field of digital cultural heritage management and applications including digital cultural data curation, interoperability, open linked data publishing, crowd sourcing, visualization, platforms for digital cultural heritage, and applications. We present some examples from research and development projects of MUSIC/TUC in those areas.

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2000 Mathematics Subject Classification: Primary 40C99, 46B99.

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2000 Mathematics Subject Classification: 35Q55,42B10.

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2000 Mathematics Subject Classification: 35B40, 35L15.

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We review our recent progress on the realisation of pulse shaping in passively-mode-locked fibre lasers by inclusion of an amplitude and/or phase spectral filter into the laser cavity. We numerically show that depending on the amplitude transfer function of the in-cavity filter, various regimes of advanced waveform generation can be achieved, including ones featuring parabolic-, flat-top- and triangular-profiled pulses. An application of this approach using a flat-top spectral filter is shown to achieve the direct generation of high-quality sinc-shaped optical Nyquist pulses with a widely tunable bandwidth from the laser oscillator. We also present the operation of an ultrafast fibre laser in which conventional soliton, dispersion-managed soliton (stretched-pulse) and dissipative soliton mode-locking regimes can be selectively and reliably targeted by adaptively changing the dispersion profile and bandwidth programmed on an in-cavity programmable filter. The results demonstrate the strong potential of an in-cavity spectral pulse shaper for achieving a high degree of control over the dynamics and output of mode-locked fibre lasers.

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Random fiber lasers blend together attractive features of traditional random lasers, such as low cost and simplicity of fabrication, with high-performance characteristics of conventional fiber lasers, such as good directionality and high efficiency. Low coherence of random lasers is important for speckle-free imaging applications. The random fiber laser with distributed feedback proposed in 2010 led to a quickly developing class of light sources that utilize inherent optical fiber disorder in the form of the Rayleigh scattering and distributed Raman gain. The random fiber laser is an interesting and practically important example of a photonic device based on exploitation of optical medium disorder. We provide an overview of recent advances in this field, including high-power and high-efficiency generation, spectral and statistical properties of random fiber lasers, nonlinear kinetic theory of such systems, and emerging applications in telecommunications and distributed sensing.

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Clusters are aggregations of atoms or molecules, generally intermediate in size between individual atoms and aggregates that are large enough to be called bulk matter. Clusters can also be called nanoparticles, because their size is on the order of nanometers or tens of nanometers. A new field has begun to take shape called nanostructured materials which takes advantage of these atom clusters. The ultra-small size of building blocks leads to dramatically different properties and it is anticipated that such atomically engineered materials will be able to be tailored to perform as no previous material could.^ The idea of ionized cluster beam (ICB) thin film deposition technique was first proposed by Takagi in 1972. It was based upon using a supersonic jet source to produce, ionize and accelerate beams of atomic clusters onto substrates in a vacuum environment. Conditions for formation of cluster beams suitable for thin film deposition have only recently been established following twenty years of effort. Zinc clusters over 1,000 atoms in average size have been synthesized both in our lab and that of Gspann. More recently, other methods of synthesizing clusters and nanoparticles, using different types of cluster sources, have come under development.^ In this work, we studied different aspects of nanoparticle beams. The work includes refinement of a model of the cluster formation mechanism, development of a new real-time, in situ cluster size measurement method, and study of the use of ICB in the fabrication of semiconductor devices.^ The formation process of the vaporized-metal cluster beam was simulated and investigated using classical nucleation theory and one dimensional gas flow equations. Zinc cluster sizes predicted at the nozzle exit are in good quantitative agreement with experimental results in our laboratory.^ A novel in situ real-time mass, energy and velocity measurement apparatus has been designed, built and tested. This small size time-of-flight mass spectrometer is suitable to be used in our cluster deposition systems and does not suffer from problems related to other methods of cluster size measurement like: requirement for specialized ionizing lasers, inductive electrical or electromagnetic coupling, dependency on the assumption of homogeneous nucleation, limits on the size measurement and non real-time capability. Measured ion energies using the electrostatic energy analyzer are in good accordance with values obtained from computer simulation. The velocity (v) is measured by pulsing the cluster beam and measuring the time of delay between the pulse and analyzer output current. The mass of a particle is calculated from m = (2E/v$\sp2).$ The error in the measured value of background gas mass is on the order of 28% of the mass of one N$\sb2$ molecule which is negligible for the measurement of large size clusters. This resolution in cluster size measurement is very acceptable for our purposes.^ Selective area deposition onto conducting patterns overlying insulating substrates was demonstrated using intense, fully-ionized cluster beams. Parameters influencing the selectivity are ion energy, repelling voltage, the ratio of the conductor to insulator dimension, and substrate thickness. ^

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Strategic planning is the key to producing a realistic, attractive rate of growth and a respectable return on investment. The author analyzes the steps in the planning process and looks at the environmental and cultural values which influence the strategic planner in his/her work.

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Personalized recommender systems aim to assist users in retrieving and accessing interesting items by automatically acquiring user preferences from the historical data and matching items with the preferences. In the last decade, recommendation services have gained great attention due to the problem of information overload. However, despite recent advances of personalization techniques, several critical issues in modern recommender systems have not been well studied. These issues include: (1) understanding the accessing patterns of users (i.e., how to effectively model users' accessing behaviors); (2) understanding the relations between users and other objects (i.e., how to comprehensively assess the complex correlations between users and entities in recommender systems); and (3) understanding the interest change of users (i.e., how to adaptively capture users' preference drift over time). To meet the needs of users in modern recommender systems, it is imperative to provide solutions to address the aforementioned issues and apply the solutions to real-world applications. ^ The major goal of this dissertation is to provide integrated recommendation approaches to tackle the challenges of the current generation of recommender systems. In particular, three user-oriented aspects of recommendation techniques were studied, including understanding accessing patterns, understanding complex relations and understanding temporal dynamics. To this end, we made three research contributions. First, we presented various personalized user profiling algorithms to capture click behaviors of users from both coarse- and fine-grained granularities; second, we proposed graph-based recommendation models to describe the complex correlations in a recommender system; third, we studied temporal recommendation approaches in order to capture the preference changes of users, by considering both long-term and short-term user profiles. In addition, a versatile recommendation framework was proposed, in which the proposed recommendation techniques were seamlessly integrated. Different evaluation criteria were implemented in this framework for evaluating recommendation techniques in real-world recommendation applications. ^ In summary, the frequent changes of user interests and item repository lead to a series of user-centric challenges that are not well addressed in the current generation of recommender systems. My work proposed reasonable solutions to these challenges and provided insights on how to address these challenges using a simple yet effective recommendation framework.^