<p>Disertacija se bavi problematikom adaptivnih web-baziranih sistema u oblasti e-učenja. Definisan je model sistema čije su osnovne komponente: učenik, učitelj i obučavajući materijali. Model je pro&scaron;iriv i domenski nezavistan. Istražena je interakcija između komponenti modela, pre svega između učenika i obučavajućih materijala. Razvijen je modul za procenu usagla&scaron;enosti potreba učenika sa jedne strane i sadržaja obučavajućih materijala sa druge strane. Kori&scaron;ćene su mere udaljenosti odnosno sličnosti, na taj način postignuta je delimična adaptibilnost modela. Adaptibilnost modela pro&scaron;irena je modulom koji koristi Ako Onda pravila generisana od strane sistema baziranog na Teoriji grubih skupova. Pravila u Ako Onda formi procenjuju uticaj obučavajućih materijala na učenika i shodno proceni vr&scaron;e adaptaciju. Model je implementiran, testiran i kori&scaron;ćen za vr&scaron;enje eksperimenata na test skupu obučavajućih materijala i učenika. Pokazano je na koji način se vr&scaron;i adaptacija u okviru kori&scaron;ćenog sistema.</p> / <p>The dissertation deals with the problem of adaptive Web-based systems in the field of e-learning. The model whose basic components are: the student, the teacher and the learning materials is defined. The model is extensible and domain independent. The interaction between the components of the model is examined, especially among students and learning materials. Module for the conformity assessment between needs of students and the content of the learning materials is developed. The distance measures or similarity measures are used, thus is achieved a partial adaptability of the model. Adaptability of the model was extended by module that uses If Then rules generated by the system based on the Rough sets theory. If Then rules are used to estimate the impact of learning materials to students and after that, is performed the adaptation. The model was implemented, tested and used to carry out experiments on the test set of learning materials and students. It is shown how the adjustments are done.</p>

The ever-increasing need for more computing and data processing power demands for a continuous and rapid growth of power-hungry data center capacities all over the world. As a first study in 2008 revealed, energy consumption of such data centers is becoming a critical problem, since their power consumption is about to double every 5 years. However, a recently (2016) released follow-up study points out that this threatening trend was dramatically throttled within the past years, due to the increased energy efficiency actions taken by data center operators. Furthermore, the authors of the study emphasize that making and keeping data centers energy-efficient is a continuous task, because more and more computing power is demanded from the same or an even lower energy budget, and that this threatening energy consumption trend will resume as soon as energy efficiency research efforts and its market adoption are reduced. An important class of applications running in data centers are data management systems, which are a fundamental component of nearly every application stack. While those systems were traditionally designed as disk-based databases that are optimized for keeping disk accesses as low a possible, modern state-of-the-art database systems are main memory-centric and store the entire data pool in the main memory, which replaces the disk as main bottleneck. To scale up such in-memory database systems, non-uniform memory access (NUMA) hardware architectures are employed that face a decreased bandwidth and an increased latency when accessing remote memory compared to the local memory. In this thesis, we investigate energy awareness aspects of large scale-up NUMA systems in the context of in-memory data management systems. To do so, we pick up the idea of a fine-grained data-oriented architecture and improve the concept in a way that it keeps pace with increased absolute performance numbers of a pure in-memory DBMS and scales up on NUMA systems in the large scale. To achieve this goal, we design and build ERIS, the first scale-up in-memory data management system that is designed from scratch to implement a data-oriented architecture. With the help of the ERIS platform, we explore our novel core concept for energy awareness, which is Energy Awareness by Adaptivity. The concept describes that software and especially database systems have to quickly respond to environmental changes (i.e., workload changes) by adapting themselves to enter a state of low energy consumption. We present the hierarchically organized Energy-Control Loop (ECL), which is a reactive control loop and provides two concrete implementations of our Energy Awareness by Adaptivity concept, namely the hardware-centric Resource Adaptivity and the software-centric Storage Adaptivity. Finally, we will give an exhaustive evaluation regarding the scalability of ERIS as well as our adaptivity facilities.

This is a master’s thesis project of 30 credits written with guidance from the Swedish research institute ICT Viktoria and Industrial Ecology at KTH. This thesis is conducted by two students at KTH, one with a background in Mechanical Engineering and Industrial Ecology and the other with a background in Energy and Environmental Technology. This study focuses on circular economy linked to the furniture industry in Sweden and how the transition from theoretical to practical concepts can be improved. The methods of this thesis consist of three semi-structured interviews, a survey and an analytical comparative literature review. The interviews, survey and literature review is analyzed with the purpose of finding important criteria relevant for office chairs in circular business models. The interviews are performed face-to-face with three different key persons; an office supply manager, a CEO at a refurbishing company and a product manager. The study focuses on product design within the Swedish furniture industry although some aspects regarding circular business models, logistics and psychological values are included. The results are design criteria for office chairs in circular business models and a design evaluation program for the industry built on these. The program, based on multi criteria analysis, can help reduce the gap between theory and practice of how circular economy should be implemented in the industry. By giving early feedback during the design phase on how well an office chair and a company’s structure meet circular economy criteria the authors hope to ease and speed up this transition. The main characteristics of an office chair designed for circular business models are: Durable Easy to service Adaptable Modular Homogeneous material composition in modules Although the transition to circular business models can be a comprehensive process the authors believe that if furniture manufacturers would integrate circular business models for office chairs into their business structure this would be both economically viable and highly beneficial for their environmental profile which can strengthen their position on the market.

The thesis is concerned with theoretical and practical aspects of the hp- adaptive finite element method for solving elliptic and electromagnetic prob- lems described by partial differential equations in three spatial dimensions. Besides the standard element refinements, the hp-adaptivity allows indepen- dent adaptation of degrees of the polynomial approximation as well. This leads to exponentially fast convergence even for problems with singularities. The efficiency of the hp-adaptivity is enhanced even more by the ability of the algorithm to work with meshes with arbitrary-level hanging nodes. This generality, however, leads to great complexity of the implementation. There- fore, the thesis concentrates on the mathematical analysis of algorithms that have led to successful implementation of the method. In addition, the the- sis discusses the numerical integration in 3D and the implementation of the method itself. Finally, numerical results obtained by this new implemen- tation are presented. They confirm advantages of hp-adaptivity on meshes with arbitrary-level hanging nodes. 1

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[pt] Este trabalho consiste no desenvolvimento e implementação de um sistema computacional integrado para Modelagem Geo- étrica, Geração de Malhas, Análise Numérica, Auto- Adaptação do tipo h e Otimização de Forma e Espessura em Cascas. O Modelo Geométrico adotado consiste em representar a superfície por meio de B-Splines Racionais Recortadas, admitindo variação de espessura segundo as mesmas funções que descrevem a superfície. Para a utilização nos módulos de Auto-Adaptação e Otimização, Geradores de Malhas Não-Estruturadas sobre superfícies paramétricas foram empregados. Com base em um gerador de malhas triangulares que utiliza a técnica de avanço de Fronteira, dois geradores de malhas quadrilaterais foram desenvolvidos. Os elementos finitos empregados são baseados nas hipóteses de Reissner-Mindlin e no conceito de degeneração de sólidos. São considerados os elementos tradicionais, baseados puramente em deslocamentos, bem como elementos de formulação mais robusta, com base em campos assumidos de deformação. Um procedimento para Auto-Adaptação de Malhas do tipo foi desenvolvido para o Modelo Geométrico e para os elementos considerados. As malhas obtidas a partir de níveis de erro prescritos permitem aos modelos a obtenção de suas taxas de convergência mesmo em problemas com singularidades e efeitos de fronteira. A Análise de Sensibilidade, ferramenta essencial nos procedimentos de Otimização, é feita com a utilização do Método Semi-Analítico, considerando as características especiais dos elementos de casca. Foi desenvolvida para elementos degenerados de casca uma versão do Método Semi- Analítico que elimina sua imprecisão eventual, através da diferenciação exata das componentes de deslocamento de corpo rígido. Para os elementos baseados puramente em deslocamentos, o Método Analítico também foi desenvolvido. Os módulos de Otimização de Forma e Espessura trabalham sobre diversas possibilidades de definição das variáveis de projeto e com diferentes algoritmos de Programação Matemá tica. Permitem também a Otimização de Forma com consideração de Auto-Adaptatividade para obter as malhas durante o processo de mudança de forma. Devido à interconexão entre os diversos módulos e com o objetivo de facilitar a comunicação e a implementação dos mesmos, o sistema computacional foi completamente desenvolvido utilizando técnicas de Programação Orientada para Objetos. / [en] The purpose of this thesis is the development of an integrated computational system for Geometric Modelling, Unstructured Mesh Generation, Numerical Analysis, Adaptivity and Shape Optimization of Shells.The Geometric Model is composed of Non-Uniform Rational B-Spline Surfaces (NURBS), further modified by trimming loops described in the parametric plane. Smooth thickness variations may be modelled by means of the same functions that describe the surface geometry.For Unstructured Mesh Generation, two algorithms were implemented for quadrilateral elements and one for triangles. The triangular Mesh Generator is based on the Advancing Front Technique applied to parametric surfaces. The quadrilateral Mesh Generators employ the indirect approach for converting the triangular meshes to pure quadrilateral ones. The Finite Element formulation is based on the degenerated isoparametric approach. Pure displacement based elements, as well as assumed strain robust shell elements, are employed in the Analysis, Adaptivity and Optimization modules. A procedure for h-Adaptive Mesh Refinement was developed for the shell models. For this purpose an Error Estimator scheme, based upon a Zienkiewicz-Zhu Patch Recovery Technique, adapted to handle curved shell surfaces, was employed. The adaptive procedure allows the convergence rates of the Finite Element Model to be maintained even in the presence of singularities and boundary layers.For the Sensitivity Evaluation, the well- known Semi-Analytical Method is employed and adapted for the degenerated solid shell element approach. In order to solve the inaccuracy problems inherent to the application of the method for certain types of structures, the recent Refined Semi- Analytical Method, is extended for degenerated shell elements. For the pure displacement-based elements, the Analytical Method is also developed. The Shape and Thickness Optimization modules work with a wide variety of design variable descriptions, different mathematical Programming algorithms, Sensitivity schemes and Finite Element Models. The possibility of h-Adaptive Mesh refinement in conjunction with Shape Optimization is also considered in this stage. In order to ease up code expansion, communication and data exchange between the modules,the computational system was fully developed employing Object-Oriented Programming techniques.

Energy awareness of database systems has emerged as a critical research topic, since energy consumption is becoming a major limiter for their scalability. Recent energy-related hardware developments trend towards offering more and more configuration opportunities for the software to control its own energy consumption. Existing research so far mainly focused on leveraging this configuration spectrum to find the most energy-efficient configuration for specific operators or entire queries. In this demo, we introduce the concept of energy elasticity and propose the energy-control loop as an implementation of this concept. Energy elasticity refers to the ability of software to behave energy-proportional and energy-efficient at the same time while maintaining a certain quality of service. Thus, our system does not draw the least energy possible but the least energy necessary to still perform reasonably. We demonstrate our overall approach using a rich interactive GUI to give attendees the opportunity to learn more about our concept.

The development of adaptive mesh refinement capabilities in the field of computational fluid dynamics is an essential tool for enabling the simulation of larger and more complex physical problems. While such techniques have been known for a long time, most simulations do not make use of them because of the lack of a robust implementation. In this work, we present recent progresses that have been made to develop adaptive mesh refinement features in Nek5000, a code based on the spectral element method. These developments are driven by the algorithmic challenges posed by future exascale supercomputers. First, we perform the study of the strong scaling of Nek5000 on three petascale machines in order to assess the scalability of the code and identify the current bottlenecks. It is found that strong scaling limit ranges between 5, 000 and 220, 000 degrees of freedom per core depending on the machine and the case. The need for synchronized and low latency communication for efficient computational fluid dynamics simulation is also confirmed. Additionally, we present how Hypre, a library for linear algebra, is used to develop a new and efficient code for performing the setup step required prior to the use of an algebraic multigrid solver for preconditioning the pressure equation in Nek5000. Finally, the main objective of this work is to develop new methods for estimating the error on a numerical solution of the Navier–Stokes equations via the resolution of an adjoint problem. These new estimators are compared to existing ones, which are based on the decay of the spectral coefficients. Then, the estimators are combined with newly implemented capabilities in Nek5000 for automatic grid refinement and adaptive mesh adaptation is carried out. The applications considered so far are steady and two-dimensional, namely the lid-driven cavity at Re = 7, 500 and the flow past a cylinder at Re = 40. The use of adaptive mesh refinement techniques makes mesh generation easier and it is shown that a similar accuracy as with a static mesh can be reached with a significant reduction in the number of degrees of freedom. / <p>QC 20171114</p>

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The ever-increasing demand for scalable database systems is limited by their energy consumption, which is one of the major challenges in research today. While existing approaches mainly focused on transaction-oriented disk-based database systems, we are investigating and optimizing the energy consumption and performance of data-oriented scale-up in-memory database systems that make heavy use of the main power consumers, which are processors and main memory. In this demo, we present energy-utility functions as an approach for enabling the operating system to improve the energy efficiency of scalable in-memory database systems. Our highly interactive demo setup mainly allows attendees to switch between multiple DBMS workloads and watch in detail how the system responds by adapting the hardware configuration appropriately.