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Time-of-flight (ToF) sensors have become an alternative to conventional distance sensing techniques like laser scanners or image based stereo. ToF sensors provide full range distance information at high frame-rates and thus have a significant impact onto current research in areas like online object recognition, collision prevention or scene reconstruction. However, ToF cameras like the photonic mixer device (PMD) still exhibit a number of challenges regarding static and dynamic effects, e.g. systematic distance errors and motion artefacts, respectively. Sensor calibration techniques reducing static system errors have been proposed and show promising results. However, current calibration techniques in general need a large set of reference data in order to determine the corresponding parameters for the calibration model. This paper introduces a new calibration approach which combines different demodulation techniques for the ToF- camera 's reference signal. Examples show, that the resulting combined demodulation technique yields improved distance values based on only two required reference data sets.
The Volatility Framework is a collection of tools for the analysis of computer RAM. The framework offers a multitude of analysis options and is used by many investigators worldwide. Volatility currently comes with a command line interface only, which might be a hinderer for some investigators to use the tool. In this paper we present a GUI and extensions for the Volatility Framework, which on the one hand simplify the usage of the tool and on the other hand offer additional functionality like storage of results in a database, shortcuts for long Volatility Framework command sequences, and entirely new commands based on correlation of data stored in the database.
Der CMS-Guide : Content-Management-Systeme: Erfolgsfaktoren, Geschäftsmodelle, Produktübersicht
(2001)
Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of water distribution systems (WDS), i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, graph-theoretical metrics have been proposed. In this study, a promising approach is first physically derived analytically and then applied to assess the resilience of the WDS for a district in a major German City. The topology based resilience index computed for every consumer node takes into consideration the resistance of the best supply path as well as alternative supply paths. This resistance of a supply path is derived to be the dimensionless pressure loss in the pipes making up the path. The conducted analysis of a present WDS provides insight into the process of actively influencing the resilience of WDS locally and globally by adding pipes. The study shows that especially pipes added close to the reservoirs and main branching points in the WDS result in a high resilience enhancement of the overall WDS.
Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience.
Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. In practice, the focus is set on the most beneficial maintenance measures and/or capacity adaptations of existing water distribution systems (WDS). Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of WDS, i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, metrics based on graph theory have been proposed. In this study, a promising approach is applied to assess the resilience of the WDS for a district in a major German City. The conducted analysis provides insight into the process of actively influencing the
resilience of WDS
Open Data impliziert die freie Zugänglichkeit, Verfügbarkeit und Wiederverwendbarkeit von Datensätzen. Obwohl hochwertige Datensätze öffentlich verfügbar sind, ist der Zugang zu diesen und die Transparenz über die Formate nicht immer gegeben. Dies mindert die optimale Nutzung des Potenzials zur Wertschöpfung, trotz der vorherrschenden Einigkeit über ihre Chancen. Denn Open Data ermöglicht das Vorantreiben von Compliance-Themen wie Transparenz und Rechenschaftspflicht bis hin zur Förderung von Innovationen. Die Nutzung von Open Data erfordert Mut und eine gemeinsame Anstrengung verschiedener Akteure und Branchen. Im Rahmen des vorliegenden Beitrags werden auf Grundlage des Design Science-Ansatzes eine Open Data Capability Map sowie darauf aufbauend eine Datenarchitektur für Open Data in der Luftfahrtindustrie an einem Beispiel entwickelt.
Arbeitswissenschaft
(2001)
Unter Arbeit wird das Tätigsein des Menschen verstanden, bei dem dieser mit anderen Menschen und (technischen) Hilfsmitteln in Interaktion tritt, um unter wirtschaftlichen Zielsetzungen Güter und Dienstleistungen zu erstellen (Luczak, 1998a). Arbeit dient direkt oder indirekt der Erhaltung der eigenen Existenz und der Existenz der Gesellschaft. Arbeit ist deshalb eine besondere Form des Tätigseins neben anderen wie Spiel, Sport, Lemen usw.
Purpose
To demonstrate that high quality T₂-weighted (T2w) turbo spin-echo (TSE) imaging of the complete prostate can be achieved routinely and within safety limits at 7 T, using an external transceive body array coil only.
Methods
Nine healthy volunteers and 12 prostate cancer patients were scanned on a 7 T whole-body system. Preparation consisted of B₀ and radiofrequency shimming and localized flip angle calibration. T₁ and T₂ relaxation times were measured and used to define the T2w-TSE protocol. T2w imaging was performed using a TSE sequence (pulse repetition time/echo time 3000–3640/71 ms) with prolonged excitation and refocusing pulses to reduce specific absorption rate.
Results
High quality T2w TSE imaging was performed in less than 2 min in all subjects. Tumors of patients with gold-standard tumor localization (MR-guided biopsy or prostatectomy) were well visualized on 7 T imaging (n = 3). The number of consecutive slices achievable within a 10-g averaged specific absorption rate limit of 10 W/kg was ≥28 in all subjects, sufficient for full prostate coverage with 3-mm slices in at least one direction.
Conclusion
High quality T2w TSE prostate imaging can be performed routinely and within specific absorption rate limits at 7 T with an external transceive body array.
Die Nutzung von Prozessmodellierungsmethoden oder - werkzeugen kann erheblichen Einfluss auf die Effektivität von Prozessen haben. Das gilt insbesondere für Situationen, in denen Personen unter Stress stehen oder ungeübt sind. In diesen Fällen geben Prozessmodelle konkrete Empfehlungen, nach denen sich die handelnden Personen richten könnten. In Experimenten mit der Business-Simulation Apollo 13 haben wir den Effekt eines Einsatzes von Prozessmodellierungsmethoden und -werkzeugen untersucht. Bereits bekannte Theorien (z.B. über geeignete Verhältnisse von Kommunikationsinhalten) konnten bestätigt werden. Darüber hinaus haben wir eine besondere Bedeutung der Übertragbarkeit von Prozessmodellen in konkrete Handlungen identifiziert.
Objective
The purpose of this study is to (i) design a small and mobile Magnetic field ALert SEnsor (MALSE), (ii) to carefully evaluate its sensors to their consistency of activation/deactivation and sensitivity to magnetic fields, and (iii) to demonstrate the applicability of MALSE in 1.5 T, 3.0 T and 7.0 T MR fringe field environments.
Methods
MALSE comprises a set of reed sensors, which activate in response to their exposure to a magnetic field. The activation/deactivation of reed sensors was examined by moving them in/out of the fringe field generated by 7TMR.
Results
The consistency with which individual reed sensors would activate at the same field strength was found to be 100% for the setup used. All of the reed switches investigated required a substantial drop in ambient magnetic field strength before they deactivated.
Conclusions
MALSE is a simple concept for alerting MRI staff to a ferromagnetic object being brought into fringe magnetic fields which exceeds MALSEs activation magnetic field. MALSE can easily be attached to ferromagnetic objects within the vicinity of a scanner, thus creating a barrier for hazardous situations induced by ferromagnetic parts which should not enter the vicinity of an MR-system to occur.
Germanistik [Lexikoneintrag]
(1998)
Wie national ist die Germanistik? Die Scheu der Literaturwissenschaft vor der eigenen Vergangenheit
(1993)
Frauen und Revolution: Der weibliche Anteil an der Geschichte. Christa Wolf und das Ende der DDR
(1991)
Das Ich ist eine Illusion
(1990)
Innovation und Kommunikation
(2013)
Meine besten Rezepte
(2008)
The chemical industry is one of the most important industrial sectors in Germany in terms of manufacturing revenue. While thermodynamic boundary conditions often restrict the scope for reducing the energy consumption of core processes, secondary processes such as cooling offer scope for energy optimisation. In this contribution, we therefore model and optimise an existing cooling system. The technical boundary conditions of the model are provided by the operators, the German chemical company BASF SE. In order to systematically evaluate different degrees of freedom in topology and operation, we formulate and solve a Mixed-Integer Nonlinear Program (MINLP), and compare our optimisation results with the existing system.
Die steigende Popularität von mobilen Endgeräten im privaten und geschäftlichen Umfeld geht mit einem Anstieg an Sicherheitslücken und somit potentiellen Angriffsflächen einher. Als ein Element der technischen und organisatorischen Maßnahmen zum Schutz eines Netzwerkes können Monitoring-Apps dienen, die unerwünschtes Verhalten und Angriffe erkennen. Die automatisierte Überwachung von Endgeräten ist jedoch rechtlich und ethisch komplex. Dies in Kombination mit einer hohen Sensibilität der Nutzer und Nutzerinnen dieser Geräte in Bezug auf Privatsphäre, kann zu einer geringen Akzeptanz und Compliance führen. Eine datenschutzrechtlich und ethisch einwandfreie Konzeption solcher Apps bereits im Designprozess führt zu höherer Akzeptanz und verbessert so die Effizienz. Diese Analyse beschreibt Möglichkeiten zur Umsetzung.
Around 60% of the paper worldwide is made from recovered paper. Especially adhesive contaminants, so called stickies, reduce paper quality. To remove stickies but at the same time keep as many valuable fibers as possible, multi-stage screening systems with several interconnected pressure screens are used. When planning such systems, suitable screens have to be selected and their interconnection as well as operational parameters have to be defined considering multiple conflicting objectives. In this contribution, we present a Mixed-Integer Nonlinear Program to optimize system layout, component selection and operation to find a suitable trade-off between output quality and yield.
The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives.
Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge.
The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps’ characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer’s point of view, keeping in mind the economically important trade-off between investment and operation costs.
Component failures within water supply systems can lead to significant performance losses. One way to address these losses is the explicit anticipation of failures within the design process. We consider a water supply system for high-rise buildings, where pump failures are the most likely failure scenarios. We explicitly consider these failures within an early design stage which leads to a more resilient system, i.e., a system which is able to operate under a predefined number of arbitrary pump failures. We use a mathematical optimization approach to compute such a resilient design. This is based on a multi-stage model for topology optimization, which can be described by a system of nonlinear inequalities and integrality constraints. Such a model has to be both computationally tractable and to represent the real-world system accurately. We therefore validate the algorithmic solutions using experiments on a scaled test rig for high-rise buildings. The test rig allows for an arbitrary connection of pumps to reproduce scaled versions of booster station designs for high-rise buildings. We experimentally verify the applicability of the presented optimization model and that the proposed resilience properties are also fulfilled in real systems.
Digital forensics of smartphones is of utmost importance in many criminal cases. As modern smartphones store chats, photos, videos etc. that can be relevant for investigations and as they can have storage capacities of hundreds of gigabytes, they are a primary target for forensic investigators. However, it is exactly this large amount of data that is causing problems: extracting and examining the data from multiple phones seized in the context of a case is taking more and more time. This bears the risk of wasting a lot of time with irrelevant phones while there is not enough time left to analyze a phone which is worth examination. Forensic triage can help in this case: Such a triage is a preselection step based on a subset of data and is performed before fully extracting all the data from the smartphone. Triage can accelerate subsequent investigations and is especially useful in cases where time is essential. The aim of this paper is to determine which and how much data from an Android smartphone can be made directly accessible to the forensic investigator – without tedious investigations. For this purpose, an app has been developed that can be used with extremely limited storage of data in the handset and which outputs the extracted data immediately to the forensic workstation in a human- and machine-readable format.
The problem of fair and privacy-preserving ordered set reconciliation arises in a variety of applications like auctions, e-voting, and appointment reconciliation. While several multi-party protocols have been proposed that solve this problem in the semi-honest model, there are no multi-party protocols that are secure in the malicious model so far. In this paper, we close this gap. Our newly proposed protocols are shown to be secure in the malicious model based on a variety of novel non-interactive zero-knowledge-proofs. We describe the implementation of our protocols and evaluate their performance in comparison to protocols solving the problem in the semi-honest case.
In the future, we expect manufacturing companies to follow a new paradigm that mandates more automation and autonomy in production processes. Such smart factories will offer a variety of production technologies as services that can be combined ad hoc to produce a large number of different product types and variants cost-effectively even in small lot sizes. This is enabled by cyber-physical systems that feature flexible automated planning methods for production scheduling, execution control, and in-factory logistics.
During development, testbeds are required to determine the applicability of integrated systems in such scenarios. Furthermore, benchmarks are needed to quantify and compare system performance in these industry-inspired scenarios at a comprehensible and manageable size which is, at the same time, complex enough to yield meaningful results.
In this chapter, based on our experience in the RoboCup Logistics League (RCLL) as a specific example, we derive a generic blueprint for how a holistic benchmark can be developed, which combines a specific scenario with a set of key performance indicators as metrics to evaluate the overall integrated system and its components.
Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.
A new trend in automation is to deploy so-called cyber-physical systems (CPS) which combine computation with physical processes. The novel RoboCup Logistics League Sponsored by Festo (LLSF) aims at such CPS logistic scenarios in an automation setting. A team of robots has to produce products from a number of semi-finished products which they have to machine during the game. Different production plans are possible and the robots need to recycle scrap byproducts. This way, the LLSF is a very interesting league offering a number of challenging research questions for planning, coordination, or communication in an application-driven scenario. In this paper, we outline the objectives of the LLSF and present steps for developing the league further towards a benchmark for logistics scenarios for CPS. As a major milestone we present the new automated referee system which helps in governing the game play as well as keeping track of the scored points in a very complex factory scenario.