TY - CHAP A1 - Kiy, Alexander A1 - Grünwald, Franka A1 - Weise, Matthias A1 - Lucke, Ulrike T1 - Facilitating portfolio-driven learning in a personal learning environment T2 - 3rd Workshop on Technology-Enhanced Formative Assessment, TEFA 2016; CEUR Workshop Proceedings N2 - In universities, diverse tools and software systems exist that each facilitates a different teaching and learning scenario. A deviating approach is taken by Personal Learning Environments (PLE) that aim to provide a common platform. Considering e-portfolios as an integral part of PLEs, especially portfolio-based learning and assessment have to be supported. Therefore, the concept of a PLE is developed further by enabling the products of different software systems to be integrated in portfolio pages and finally submitted for feedback and assessment. It is further elaborated how the PLE approach is used to support the continuous formative assessment within portfolio-based learning scenarios. Y1 - 2016 UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85021883746&partnerID=MN8TOARS SN - 1613-0073 VL - 1850 SP - 45 EP - 52 ER - TY - CHAP A1 - Kiy, Alexander A1 - Lucke, Ulrike T1 - Technical Approaches for Personal Learning Environments BT - Identifying Archetypes from a Literature Review T2 - 2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT) N2 - The term Personal Learning Environment (PLE) is associated with the desire to put the learner in control of his own learning process, so that he is able to set and accomplish the desired learning goals at the right time with the learning environment chosen by him. Gradually, such a learning environment includes several digital content, services and tools. It is thus summarized as the Virtual Learning Environment (VLE). Even though the construction of an individual PLE is a complex task, several approaches to support this process already exist. They mostly occur under the umbrella term PLE or with little accentuations like iPLE, which especially live within the context of institutions. This paper sums up the variety of attempts and technical approaches to establish a PLE and suggests a categorization for them. Y1 - 2016 U6 - https://doi.org/10.1109/icalt.2016.122 ER - TY - JOUR A1 - Lagriffoul, Fabien A1 - Andres, Benjamin T1 - Combining task and motion planning BT - A culprit detection problem JF - The international journal of robotics research N2 - Solving problems combining task and motion planning requires searching across a symbolic search space and a geometric search space. Because of the semantic gap between symbolic and geometric representations, symbolic sequences of actions are not guaranteed to be geometrically feasible. This compels us to search in the combined search space, in which frequent backtracks between symbolic and geometric levels make the search inefficient.We address this problem by guiding symbolic search with rich information extracted from the geometric level through culprit detection mechanisms. KW - combined task and motion planning KW - manipulation planning Y1 - 2016 U6 - https://doi.org/10.1177/0278364915619022 SN - 1741-3176 SN - 0278-3649 VL - 35 IS - 8 SP - 890 EP - 927 PB - Sage Science Press CY - Thousand Oaks ER - TY - THES A1 - Müller, Stephan Heinz T1 - Aggregates Caching for Enterprise Applications N2 - The introduction of columnar in-memory databases, along with hardware evolution, has made the execution of transactional and analytical enterprise application workloads on a single system both feasible and viable. Yet, we argue that executing analytical aggregate queries directly on the transactional data can decrease the overall system performance. Despite the aggregation capabilities of columnar in-memory databases, the direct access to records of a materialized aggregate is always more efficient than aggregating on the fly. The traditional approach to materialized aggregates, however, introduces significant overhead in terms of materialized view selection, maintenance, and exploitation. When this overhead is handled by the application, it increases the application complexity, and can slow down the transactional throughput of inserts, updates, and deletes. In this thesis, we motivate, propose, and evaluate the aggregate cache, a materialized aggregate engine in the main-delta architecture of a columnar in-memory database that provides efficient means to handle costly aggregate queries of enterprise applications. For our design, we leverage the specifics of the main-delta architecture that separates a table into a main and delta partition. The central concept is to only cache the partial aggregate query result as defined on the main partition of a table, because the main partition is relatively stable as records are only inserted into the delta partition. We contribute by proposing incremental aggregate maintenance and query compensation techniques for mixed workloads of enterprise applications. In addition, we introduce aggregate profit metrics that increase the likelihood of persisting the most profitable aggregates in the aggregate cache. Query compensation and maintenance of materialized aggregates based on joins of multiple tables is expensive due to the partitioned tables in the main-delta architecture. Our analysis of enterprise applications has revealed several data schema and workload patterns. This includes the observation that transactional data is persisted in header and item tables, whereas in many cases, the insertion of related header and item records is executed in a single database transaction. We contribute by proposing an approach to transport these application object semantics to the database system and optimize the query processing using the aggregate cache by applying partition pruning and predicate pushdown techniques. For the experimental evaluation, we propose the FICO benchmark that is based on data from a productive ERP system with extracted mixed workloads. Our evaluation reveals that the aggregate cache can accelerate the execution of aggregate queries up to a factor of 60 whereas the speedup highly depends on the number of aggregated records in the main and delta partitions. In mixed workloads, the proposed aggregate maintenance and query compensation techniques perform up to an order of magnitude better than traditional materialized aggregate maintenance approaches. The introduced aggregate profit metrics outperform existing costbased metrics by up to 20%. Lastly, the join pruning and predicate pushdown techniques can accelerate query execution in the aggregate cache in the presence of multiple partitioned tables by up to an order of magnitude. Y1 - 2016 ER - TY - THES A1 - Schindler, Sven T1 - Honeypot Architectures for IPv6 Networks Y1 - 2016 ER - TY - THES A1 - Al-Saffar, Loay Talib Ahmed T1 - Analysing prerequisites, expectations, apprehensions, and attitudes of University students studying computer science Y1 - 2016 ER - TY - THES A1 - Saleh, Eyad T1 - Securing Multi-tenant SaaS Environments N2 - Software-as-a-Service (SaaS) offers several advantages to both service providers and users. Service providers can benefit from the reduction of Total Cost of Ownership (TCO), better scalability, and better resource utilization. On the other hand, users can use the service anywhere and anytime, and minimize upfront investment by following the pay-as-you-go model. Despite the benefits of SaaS, users still have concerns about the security and privacy of their data. Due to the nature of SaaS and the Cloud in general, the data and the computation are beyond the users' control, and hence data security becomes a vital factor in this new paradigm. Furthermore, in multi-tenant SaaS applications, the tenants become more concerned about the confidentiality of their data since several tenants are co-located onto a shared infrastructure. To address those concerns, we start protecting the data from the provisioning process by controlling how tenants are being placed in the infrastructure. We present a resource allocation algorithm designed to minimize the risk of co-resident tenants called SecPlace. It enables the SaaS provider to control the resource (i.e., database instance) allocation process while taking into account the security of tenants as a requirement. Due to the design principles of the multi-tenancy model, tenants follow some degree of sharing on both application and infrastructure levels. Thus, strong security-isolation should be present. Therefore, we develop SignedQuery, a technique that prevents one tenant from accessing others' data. We use the Signing Concept to create a signature that is used to sign the tenant's request, then the server can verifies the signature and recognizes the requesting tenant, and hence ensures that the data to be accessed is belonging to the legitimate tenant. Finally, Data confidentiality remains a critical concern due to the fact that data in the Cloud is out of users' premises, and hence beyond their control. Cryptography is increasingly proposed as a potential approach to address such a challenge. Therefore, we present SecureDB, a system designed to run SQL-based applications over an encrypted database. SecureDB captures the schema design and analyzes it to understand the internal structure of the data (i.e., relationships between the tables and their attributes). Moreover, we determine the appropriate partialhomomorphic encryption scheme for each attribute where computation is possible even when the data is encrypted. To evaluate our work, we conduct extensive experiments with di↵erent settings. The main use case in our work is a popular open source HRM application, called OrangeHRM. The results show that our multi-layered approach is practical, provides enhanced security and isolation among tenants, and have a moderate complexity in terms of processing encrypted data. Y1 - 2016 ER -