Jisc: Building a Cohesive Repository Shared Services Infrastructure for the UK

Panel at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Virtual Cellar of the Estonian Literary Museum: the Challenges of the Open Access in the Digital Era

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

The Purdue University Research Repository (PURR): An institutional data management service with a virtual research environment, data publication, and archiving

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Fedora 4 as a Shared Linked Data repository for the Art Institute of Chicago Collections

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Promoting Interoperability and Services Through Shared Identifiers

Panel at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Interoperability and Services Through Shared Identifiers

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

The Human Communication Science Virtual Lab (HCS vLab): A repository microclimate in a rapidly evolving research-ecosystem

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Cost-efficient virtual machine management : provisioning, admission control, and consolidation

One of the main challenges in Software Engineering is to cope with the transition from an industry based on software as a product to software as a service. The field of Software Engineering should provide the necessary methods and tools to develop and deploy new cost-efficient and scalable digital services. In this thesis, we focus on deployment platforms to ensure cost-efficient scalability of multi-tier web applications and on-demand video transcoding service for different types of load conditions. Infrastructure as a Service (IaaS) clouds provide Virtual Machines (VMs) under the pay-per-use business model. Dynamically provisioning VMs on demand allows service providers to cope with fluctuations on the number of service users. However, VM provisioning must be done carefully, because over-provisioning results in an increased operational cost, while underprovisioning leads to a subpar service. Therefore, our main focus in this thesis is on cost-efficient VM provisioning for multi-tier web applications and on-demand video transcoding. Moreover, to prevent provisioned VMs from becoming overloaded, we augment VM provisioning with an admission control mechanism. Similarly, to ensure efficient use of provisioned VMs, web applications on the under-utilized VMs are consolidated periodically. Thus, the main problem that we address is cost-efficient VM provisioning augmented with server consolidation and admission control on the provisioned VMs. We seek solutions for two types of applications: multi-tier web applications that follow the request-response paradigm and on-demand video transcoding that is based on video streams with soft realtime constraints. Our first contribution is a cost-efficient VM provisioning approach for multi-tier web applications. The proposed approach comprises two subapproaches: a reactive VM provisioning approach called ARVUE and a hybrid reactive-proactive VM provisioning approach called Cost-efficient Resource Allocation for Multiple web applications with Proactive scaling. Our second contribution is a prediction-based VM provisioning approach for on-demand video transcoding in the cloud. Moreover, to prevent virtualized servers from becoming overloaded, the proposed VM provisioning approaches are augmented with admission control approaches. Therefore, our third contribution is a session-based admission control approach for multi-tier web applications called adaptive Admission Control for Virtualized Application Servers. Similarly, the fourth contribution in this thesis is a stream-based admission control and scheduling approach for on-demand video transcoding called Stream-Based Admission Control and Scheduling. Our fifth contribution is a computation and storage trade-o strategy for cost-efficient video transcoding in cloud computing. Finally, the sixth and the last contribution is a web application consolidation approach, which uses Ant Colony System to minimize the under-utilization of the virtualized application servers.

Virtual Testing of Active Magnetic Bearing Systems based on Design Guidelines given by the Standards

Active Magnetic Bearings offer many advantages that have brought new applications to the industry. However, similarly to all new technology, active magnetic bearings also have downsides and one of those is the low standardization level. This thesis is studying mainly the ISO 14839 standard and more specifically the system verification methods. These verifying methods are conducted using a practical test with an existing active magnetic bearing system. The system is simulated with Matlab using rotor-bearing dynamics toolbox, but this study does not include the exact simulation code or a direct algebra calculation. However, this study provides the proof that standardized simulation methods can be applied in practical problems.

Lebesgue and Sobolev spaces with variable exponents

Kirjallisuusarvostelu

pp-Blast: a "pseudo-parallel" Blast

We have developed a software called pp-Blast that uses the publicly available Blast package and PVM (parallel virtual machine) to partition a multi-sequence query across a set of nodes with replicated or shared databases. Benchmark tests show that pp-Blast running in a cluster of 14 PCs outperformed conventional Blast running in large servers. In addition, using pp-Blast and the cluster we were able to map all human cDNAs onto the draft of the human genome in less than 6 days. We propose here that the cost/benefit ratio of pp-Blast makes it appropriate for large-scale sequence analysis. The source code and configuration files for pp-Blast are available at http://www.ludwig.org.br/biocomp/tools/pp-blast.

Shared control of maltose and trehalose utilization in Candida utilis

Trehalose biosynthesis and its hydrolysis have been extensively studied in yeast, but few reports have addressed the catabolism of exogenously supplied trehalose. Here we report the catabolism of exogenous trehalose by Candida utilis. In contrast to the biphasic growth in glucose, the growth of C. utilis in a mineral medium with trehalose as the sole carbon and energy source is aerobic and exhibits the Kluyver effect. Trehalose is transported into the cell by an inducible trehalose transporter (K M of 8 mM and V MAX of 1.8 µmol trehalose min-1 mg cell (dry weight)-1. The activity of the trehalose transporter is high in cells growing in media containing trehalose or maltose and very low or absent during the growth in glucose or glycerol. Similarly, total trehalase activity was increased from about 1.0 mU/mg protein in cells growing in glucose to 39.0 and 56.2 mU/mg protein in cells growing in maltose and trehalose, respectively. Acidic and neutral trehalase activities increased during the growth in trehalose, with neutral trehalase contributing to about 70% of the total activity. In addition to the increased activities of the trehalose transporter and trehalases, growth in trehalose promoted the increase in the activity of alpha-glucosidase and the maltose transporter. These results clearly indicate that maltose and trehalose promote the increase of the enzymatic activities necessary to their catabolism but are also able to stimulate each other's catabolism, as reported to occur in Escherichia coli. We show here for the first time that trehalose induces the catabolism of maltose in yeast.

Virtual Runtime Application Partitions for Resource Management in Massively Parallel Architectures

This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.