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The title of the annual report 2013 "Shaping change: The University Addresses Society‘s Probing Challenges" reveals the great importance placed on social, economic and technological changes at the university.
This key aspect thus runs through the contents of the 90-page annual report like a common thread, without losing track of the enormous variety of research and teaching at Bonn-Rhein-Sieg University. Whether the exploration of gaps in robot safety during a European Intensive Programme, a report about the Philipines crisis region from a graduate who has worked as an organizer for Care International, or the chapter "What does change look like?" – The annual report provides the full spectrum of opportunities, activities and findings of university members.
A principal step towards solving diverse perception problems is segmentation. Many algorithms benefit from initially partitioning input point clouds into objects and their parts. In accordance with cognitive sciences, segmentation goal may be formulated as to split point clouds into locally smooth convex areas, enclosed by sharp concave boundaries. This goal is based on purely geometrical considerations and does not incorporate any constraints, or semantics, of the scene and objects being segmented, which makes it very general and widely applicable. In this work we perform geometrical segmentation of point cloud data according to the stated goal. The data is mapped onto a graph and the task of graph partitioning is considered. We formulate an objective function and derive a discrete optimization problem based on it. Finding the globally optimal solution is an NP-complete problem; in order to circumvent this, spectral methods are applied. Two algorithms that implement the divisive hierarchical clustering scheme are proposed. They derive graph partition by analyzing the eigenvectors obtained through spectral relaxation. The specifics of our application domain are used to automatically introduce cannot-link constraints in the clustering problem. The algorithms function in completely unsupervised manner and make no assumptions about shapes of objects and structures that they segment. Three publicly available datasets with cluttered real-world scenes and an abundance of box-like, cylindrical, and free-form objects are used to demonstrate convincing performance. Preliminary results of this thesis have been contributed to the International Conference on Autonomous Intelligent Systems (IAS-13).
Business process infrastructures like BPMS (Business Process Management Systems) and WfMS (Workflow Management Systems) traditionally focus on the automation of processes predefined at design time. This approach is well suited for routine tasks which are processed repeatedly and which are described by a predefined control flow. In contrast, knowledge-intensive work is more goal and data-driven and less control-flow oriented. Knowledge workers need the flexibility to decide dynamically at run-time and based on current context information on the best next process step to achieve a given goal. Obviously, in most practical scenarios, these decisions are complex and cannot be anticipated and modeled completely in a predefined process model. Therefore, adaptive and dynamic process management techniques are necessary to augment the control-flow oriented part of process management (which is still a need also for knowledge workers) with flexible, context-dependent, goaloriented support.
The contribution of the most common reciprocal translocation in childhood B-cell precursor leukemia t(12;21)(p13;q22) to leukemia development is still under debate. Direct as well as secondary indirect effects of the TEL-AML1 fusion protein are commonly recorded by using cell lines and patient samples, often bearing the TEL-AML1 fusion protein for decades. To identify direct targets of the fusion protein a short-term induction of TEL-AML1 is needed. We here describe in detail the experimental procedure, quality controls and contents of the ChIP, mRNA expression and SILAC datasets associated with the study published by Linka and colleagues in the Blood Cancer Journal [1] utilizing a short term induction of TEL-AML1 in an inducible precursor B-cell line model.
We investigated graphene structures grafted with fullerenes. The size of the graphene sheets ranges from 6400 to 640,000 atoms. The fullerenes (C60 and C240) are placed on top of the graphene sheets, using different impact velocities we could distinguish three types of impact. Furthermore, we investigated the changes of the vibrational properties. The modified graphene planes show additional features in the vibronic density of states.
We are happy to present you the special issue on Best Practice in Robot Software Development of the Journal on Software Engineering for Robotics! The spark for this special issue came during the eighth workshop on Software Development and Integration in Robotics (SDIR) at the 2013 IEEE International Conference on Robotics and Automation. The workshop focused on Robot Software Architectures, and the fruitful discussions made it clear that the design, development, and deployment of robot software is always an interplay between competing aspects. These are often couched in antagonistic pairs, such as dependability versus performance, and prominently include quality attributes as well as functional, nonfunctional, and application requirements.
The Fifth International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob'14) was held in conjunction with the 2014 International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR 2014), October 2014 in Bergamo, Italy. The main topics of the workshop were Domain-Specific Languages (DSLs) and Model-driven Software Development (MDSD) for robotics. A domain-specific language is a programming language dedicated to a particular problem domain that offers specific notations and abstractions that increase programmer productivity within that domain. Model-driven software development offers a high-level way for domain users to specify the functionality of their system at the right level of abstraction. DSLs and models have historically been used for programming complex systems. However recently they have garnered interest as a separate field of study. Robotic systems blend hardware and software in a holistic way that intrinsically raises many crosscutting concerns (concurrency, uncertainty, time constraints, ...), for which reason, traditional general-purpose languages often lead to a poor fit between the language features and the implementation requirements. DSLs and models offer a powerful, systematic way to overcome this problem, enabling the programmer to quickly and precisely implement novel software solutions to complex problems within the robotics domain.
Over the past two decades social protection has gained importance at the international and the national level of many low and middle income countries. Despite reforms in this sector being a global phenomenon, they differ from country to country. Traditional efforts to explain these dif- ferences focus on domestic factors. Yet it remains unclear how international influences and interdependencies contrib- ute to policy change. The study ‘International Policy Learn- ing and Policy Change’ aims at providing an answer to this question, by focusing on ‘soft governance’ via horizontal processes, meaning processes between equal actors. The studie was carried out in two parts. While in Part I the cur- rent state of the art in relevant research fields was assessed, in Part II the findings from Part I were used to conduct a survey which analyses the role of policy networks.
The latest advances in the field of smart card technologies allow modern cards to be more than just simple security tokens. Recent developments facilitate the use of interactive components like buttons, displays or even touch-sensors within the cards body thus conquering whole new areas of application. With interactive functionalities the usability aspect becomes the most important one for designing secure and popularly accepted products. Unfortunately the usability can only be tested fully with completely integrated hence expensive smart card prototypes. This restricts application specific research, case studies of new smart card user interfaces, concerning applications and the performance of useability tests in smart card development. Rapid development and simulation of smart card interfaces and applications can help to avoid this restriction. This paper presents SCUIDtextsuperscript{Sim} a tool for rapid user-centric development of new smart card interfaces and applications based on common smartphone technology.
The work being described in this paper is the result of a cooperation project between the Institute of Visual Computing at the Bonn-Rhein-Sieg University of Applied Sciences, Germany and the Laboratory of Biomedical Engineering at the Federal University of Uberlândia, Brazil. The aim of the project is the development of a virtual environment based training simulator which enables for better and faster learning the control of upper limb prostheses. The focus of the paper is the description of the technical setup since learning tutorials still need to be developed as well as a comprehensive evaluation still needs to be carried out.
Gas chromatography with flame-ionization detection (FID) and gas chromatography-mass spectrometry (GC/MS) with electron impact ionization (EI) and chemical ionization (PCI and NCI) were successfully used for separation and identification of commercially available longchain primary alkyl amines. The investigated compounds were used as corrosion inhibiting and antifouling agents in a water-steam circuit of energy systems in the power industry. Solidphase extraction (SPE) with octadecyl bonded silica (C18) sorbents followed by gas chromatography were used for quantification of the investigated Primene JM-T™ alkyl amines in boiler water, condensate and superheated steam samples from the power plant. Amine formulations from Kotamina group favor formation of protective layers on internal surfaces and keep them free from corrosion and scale. Alkyl amines contained in those formulations both render the environment alkaline and limit the corrosion impact of ionic and gaseous impurities by formation of protective layers. Moreover, alkyl amines limit scaling on heating surfaces of boilers and in turbine, ensuring failure-free operation. Application of alkyl amine formulation enhances heat exchange during boiling and condensation processes. Alkyl amines with branched structure are more thermally stable than linear alkyl amines, exhibit better adsorption and effectiveness of surface shielding. As a result, application of thermostable long-chain branched alkyl amines increases the efficiency of anti-corrosive protection. Moreover, the concentration of ammonia content in water and in steam was also considerably decreased.
Purpose – The aim of the study is to investigate the implementation of corporate sustainability (CS) in the German real estate sector.
Design/methodology/approach – The authors begin by outlining the framework set by the European Union and the German Federal Government for companies wanting to be classified as sustainable. After this, the relevance of sustainability for German real estate companies is discussed. Their empirical section contains an international comparison. Finally, they present an analysis checking the implementation of CS for the main 135 German real estate companies.
Findings – The present analysis shows that German real estate companies compare well with their international counterparts, in 2012 representing 15 per cent of all real estate firms reporting on the basis of the Global Reporting Initiative. However, of the 135 companies in Germany surveyed, only a small proportion classify themselves as CS and CSR (corporate social responsibility) enterprises. This number could be rapidly increased by better documentation of companies’ commitment to sustainability.
Practical implications – The study’s importance lies in the overview it provides of CS activities in the German real estate industry. In addition, it provides hints on how companies can improve their documentation to classify as CSR enterprises. Although the analysis concentrates on Germany, the results are also relevant for companies in other European countries.
The ability to track moving people is a key aspect of autonomous robot systems in real-world environments. Whilst for many tasks knowing the approximate positions of people may be sufficient, the ability to identify unique people is needed to accurately count people in the real world. To accomplish the people counting task, a robust system for people detection, tracking and identification is needed.
Adapting plans to changes in the environment by finding alternatives and taking advantage of opportunities is a common human behavior. The need for such behavior is often rooted in the uncertainty produced by our incomplete knowledge of the environment. While several existing planning approaches deal with such issues, artificial agents still lack the robustness that humans display in accomplishing their tasks. In this work, we address this brittleness by combining Hierarchical Task Network planning, Description Logics, and the notions of affordances and conceptual similarity. The approach allows a domestic service robot to find ways to get a job done by making substitutions. We show how knowledge is modeled, how the reasoning process is used to create a constrained planning problem, and how the system handles cases where plan generation fails due to missing/unavailable objects. The results of the evaluation for two tasks in a domestic service domain show the viability of the approach in finding and making the appropriate goal transformations.