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Camera-based object detection is widely used in safety-critical applications such as advanced driver assistance systems (ADAS) and autonomous vehicle research. Road infrastructure has been designed for human vision, so computer vision, with RGB cameras, is a vital source of semantic information from the environment. Sensors, such as LIDAR and RADAR, are also often utilized for these applications; however, cameras provide a higher spatial resolution and color information. The spatial frequency response (SFR), or sharpness of a camera, utilized in object detection systems must be sufficient to allow a detection algorithm to localize objects in the environment over its lifetime reliably. This study explores the relationship between object detection performance and SFR. Six state-of-the-art object detection models are evaluated with varying levels of lens defocus. A novel raw image dataset is created and utilized, containing pedestrians and cars over a range of distances up to 100-m from the sensor. Object detection performance for each defocused dataset is analyzed over a range of distances to determine the minimum SFR necessary in each case. Results show that the relationship between object detection performance and lens blur is much more complex than previous studies have found due to lens field curvature, chromatic aberration, and astigmatisms. We have found that smaller objects are disproportionately impacted by lens blur, and different object detection models have differing levels of robustness to lens blur
Over the past decades, research in room acoustics has established several derivative measures of an impulse response, some of which are incorporated in the ISO 3382 standards. These parameters intend to represent perceptual qualities, but were developed without a consistent modeling of room acoustical perception. More recent research proposed comprehensive inventories of room acoustic perception that are purely based on evaluations by human subjects, such as the Room Acoustical Quality Index (RAQI). In this work RA-QI scores acquired for 70 room impulse responses were predicted from room acoustical parameters. Except for Reverberance, the prediction of RAQI factors performed rather poor. In most cases, the sound source had a greater impact on RAQI scores. All analyses are published in an online tool, where users can upload omnidirectional and binaural impulse responses, and instantly obtain and visualize several physical descriptors, as well as predicted RAQI scores for three different sound sources. So far, acceptable prediction accuracy is achieved for Reverberance, Strength, Irregular Decay, Clarity and Intimacy. Larger data sets of evaluated impulse responses are required to improve the model performance and enable reliable predictions of room acoustical quality. Therefore, the administration of RAQI evaluations within the website is currently being developed.
We present a process to develop secure software with an extensive pattern-based security requirements engineering phase. It supports identifying and analyzing conflicts between different security requirements. In the design phase, we proceed by selecting security software components that achieve security requirements. The process enables software developers to systematically identify, analyze, and finally realize security requirements using security software components. We illustrate our approach by a lawyer agency software example.
Considering legal aspects during software development is a challenging problem, due to the cross-disciplinary expertise required. The problem is even more complex for cloud computing systems, because of the international distribution, huge amounts of processed data, and a large number of stakeholders that own or process the data. Approaches exist to deal with parts of the problem, but they are isolated from each other. We present an integrated method for elicitation of legal requirements. A cloud computing online banking scenario illustrates the application of our methods. The running example deals with the problem of storing personal information in the cloud and based upon the BDSG (German Federal Data Protection Act). We describe the structure of the online banking cloud system using an existing pattern-based approach. The elicited information is further refined and processed into functional requirements for software development. Moreover, our method covers the analysis of security-relevant concepts such as assets and attackers particularly with regard to laws. The requirements artifacts then serve as inputs for existing patterns for the identification of laws relevant for the online banking cloud system. Finally, our method helps to systematically derive functional as well as security requirements that realize the previously identified laws.
Leading edge serrations are well-known for their aeroacoustic potential in reducing aerofoil-turbulence interaction noise and are also associated with certain aerodynamic advantages. To prepare leading edge serrations for industrial application, two obstacles remain to be addressed. First is a combined analysis of the aeroacoustic and the aerodynamic performance of leading edge serrations to develop optimum designs. Second is the need to examine the transferability of the known effects of leading edge serrations from a single aerofoil to full rotors, which are considered to be the final area of application.
This thesis aims to assist in the transfer of a well-investigated aerofoil with serrated leading edges from the rigid to the rotating domain. With this purpose, a single aerofoil type is selected and thoroughly analysed, experimentally and numerically, to generate a reliable data basis for aerodynamic performance and noise reduction capability. Aside from gathering information on the overall performance, the spatial distribution of the noise sources is localised, and the spectral composition of the noise reduction is found to follow a clearly defined scaling law. Aerodynamically, generated vortices are found to be responsible for a complex three-dimensional separation mechanism of the leading edge serrations, causing a delay of stall.
The generated data basis is then used to design low-pressure axial fans of minimum complexity by keeping the initially chosen aerofoil type. The experimentally identified noise reduction mechanisms for the serrated axial fans are found to be more diverse than the single aerofoil and highly dependent on the inflow conditions and the operation point of the fan. A highly similar pattern for the spectral scaling of the noise reduction supports the finding that at optimum operation conditions, the previously identified noise reduction mechanisms for the single aerofoils are transferable to the rotating domain. On the other hand, additional aerodynamic mechanisms are found to dominate the noise reduction for the instability region of the fan, also contributing to reduced blade-to-blade interaction effects. Moreover, the blade-tip leakage flow is altered by delaying the development of coherent structures.
The next step towards a more general description of the aeroacoustic and aerodynamic dependencies is developing a comprehensive model based on artificial neural networks. This model allows a combined analysis of the aerodynamic and acoustic performance of rotors with serrated leading edges and shows an accurate prediction of the overall performance and the spectral composition of the radiated noise. It also enables the development of multi-objective optima for serration designs and motivates further studies into the generalisability of the observed trends. Furthermore, the developed model represents a feasible tool to create tailored serration designs for maximum efficiency in both aeroacoustics and aerodynamics, contributing to the development of future low-noise fans and rotating machinery.
The Chylla–Haase polymerization reactor is widely accepted as a benchmark process for the evaluation of control strategies for batch reactors. In this contribution a control concept based on Exact I/O-Linearization is proposed and compared to a conventional cascade control structure. In order to adapt the exact linearization control strategy to various polymerization products and batch conditions, an advanced probabilistic inference algorithm (Sigma-Point Kalman Filter) is applied and investigated. Sigma-Point Kalman Filters have the major improvement of simplified implementation compared to local linearization methods (i.e. Extended Kalman Filter) because no analytical Jacobians are required. Stochastic simulation studies are introduced and show the effectiveness, accuracy and benefit of the control concept. Within several scenarios a satisfying robustness against structural errors in the underlying model equations for the nonlinear control law and the inference algorithm is demonstrated. Furthermore it is pointed out, that with little effort in reassembling the plant design, control performance can be improved significantly.
To power dynamic processes in cells, the actin and microtubule cytoskeletons organize into complex structures. Although it is known that cytoskeletal coordination is vital for cell function, the mechanisms by which cross-linking proteins coordinate actin and microtubule activities remain poorly understood. In particular, it is unknown how the distinct mechanical properties of different actin architectures modulate the outcome of actin-microtubule interactions. To address this question, we engineered the protein TipAct, which links growing microtubule ends via end-binding proteins to actin filaments. We show that growing microtubules can be captured and guided by stiff actin bundles, leading to global actin-microtubule alignment. Conversely, growing microtubule ends can transport, stretch and bundle individual actin filaments, thereby globally defining actin filament organization. Our results provide a physical basis to understand actin-microtubule cross-talk, and reveal that a simple cross-linker can enable a mechanical feedback between actin and microtubule organization that is relevant to diverse biological contexts.
Actin droplet machine
(2019)
The actin droplet machine is a computer model of a three-dimensional network of actin bundles developed in a droplet of a physiological solution, which implements mappings of sets of binary strings. The actin bundle network is conductive to travelling excitations, i.e. impulses. The machine is interfaced with an arbitrary selected set of k electrodes through which stimuli, binary strings of length k represented by impulses generated on the electrodes, are applied and responses are recorded. The responses are recorded in a form of impulses and then converted to binary strings. The machine's state is a binary string of length k: if there is an impulse recorded on the ith electrode, there is a '1' in the ith position of the string, and '0' otherwise. We present a design of the machine and analyse its state transition graphs. We envisage that actin droplet machines could form an elementary processor of future massive parallel computers made from biopolymers.
The PSFC, or Pioneer Sound Field Controller, is a DSP-driven hemispherical loudspeaker array, installed at the University of Aizu Multimedia Center. The PSFC features realtime manipulation of the primary components of sound spatialization for each of two audio sources located in a virtual environment, including the content (apparent direction and distance) and context (room characteristics: reverberation level, room size and liveness). In an alternate mode, it can also direct the destination of the two separate input signals across 14 loudspeakers, manipulating the direction of the virtual sound sources with no control over apparent distance other than that afforded by source loudness (including no simulated environmental reflections or reverberation). The PSFC speaker dome is about 10 m in diameter, accommodating about fifty simultaneous users, including about twenty users comfortably standing or sitting near its ``sweet spot,'' the area in which the illusions of sound spatialization are most vivid. Collocated with a large screen rear-projection stereographic display, the PSFC is intended for advanced multimedia and virtual reality applications.
A swirling pulverized coal flame is computationally investigated. A Eulerian–Lagrangian formulation is used to describe the two-phase flow. Turbulence is modelled within a RANS (Reynolds averaged numerical simulation) framework. Four turbulence viscosity- (TV) based models, namely the standard k-ε model, realizable k-ε model, renormalization group theory k-ε model, and the shear stress transport k-ω model are used. In addition, a Reynolds stress transport model (RSM) is employed. The models are assessed by comparing the predicted velocity fields with the measurements of other authors. In terms of overall average values, the agreement of the predictions to the measurements is observed to be within the range 20–40%. A better performance of the RSM compared to the TV models is observed, with a nearly twice as better overall agreement to the experiments, particularly for the swirl velocity. In the second part of the investigation, the resolution of the discrete particle phase in modelling the turbulent particle dispersion (TPD) and particle size distribution (SD) is investigated. Using the discrete random walk model for the TPD, it is shown that even five random walks are sufficient for an accuracy that is quite high, with a less than 1% mean deviation from the solution obtained by thirty random walks. The approximation of the measured SD is determined by a continuous Rosin–Rammler distribution function, and inaccuracies that can occur in its subsequent discretization are demonstrated and discussed. An investigation on the resolution of the SD by discrete particle size classes (SC) indicates that 12 SC are required for an accuracy with a less than 1% mean deviation from the solution with 18 SC. Although these numbers may not necessarily be claimed to be sufficiently universal, they may serve as guidance, at least for SD with similar characteristics
We give an enumeration of possible problem frames, based on domain characteristics, and comment on the usefulness of the obtained frames. In particular, we investigate problem domains and their characteristics in detail. This leads to fine-grained criteria for describing problem domains. As a result, we identify a new type of problem domain and come up with integrity conditions for developing useful problem frames. Taking a complete enumeration of possible problem frames (with at most three problem domains, of which only one is constrained) as a basis, we find 8 new problem frames, 7 of which we consider as useful in practical software development.
A Sound Spatialization Server for a Speaker Array as an Integrated Part of a Virtual Environment
(1998)
Spatial sound plays an important role in virtual reality environments, allowing orientation in space, giving a feeling of space, focusing the user on events in the scene, and substituting missing feedback cues (e.g., force feedback). The sound spatialization framework of the University of Aizu, which supports number of spatialization backends, has been extended to include a sound spatialization server for a multichannel loudspeaker array (Pioneer Sound Field Control System). Our goal is that the spatialization server allows easy integration into virtual environments. Modeling of distance cues, which are essential for full immersion, is discussed. Furthermore, the integration of this prototype into different applications allowed us to reveal the advantages and problems of spatial sound for virtual reality environments.
In a virtual reality environment, users are immersed in a scene with objects which might produce sound. The responsibility of a VR environment is to present these objects, but a practical system has only limited resources, including spatialization channels (mixels), MIDI/audio channels, and processing power. A sound spatialization resource manager, introduced in this thesis, controls sound resources and optimizes fidelity (presence) under given conditions, using a priority scheme based on psychoacoustics. Objects which are spatially close together can be coalesced by a novel clustering algorithm, which considers listener localization errors. Application programmers and VR scene designers are freed from the burden of assigning mixels and predicting sound source locations. The framework includes an abstract interface for sound spatialization backends, an API for the VR environments, and multimedia authoring tools.
Today, the use of renewable energies and recycling of climate-changing gases are increasingly important. In this context,coupling of methanation with small, decentralized CO2sources such as biogas plants provides one possibility. However,fluctuating availability of renewables for hydrogen production in combination with small storage volumes result in anenhanced demand for dynamic process operation. This leads to new research challenges with respect to the required cata-lysts and the overall process design. To draw reliable conclusions about the catalytic performance under dynamic processoperation, the mechanism of the methanation reaction as well as typical deactivation procedures of the catalyst appliedunder steady-state conditions have to be reviewed thoroughly.
We present a security engineering process based on security problem frames and concretized security problem frames. Both kinds of frames constitute patterns for analyzing security problems and associated solution approaches. They are arranged in a pattern system that makes dependencies between them explicit. We describe step-by-step how the pattern system can be used to analyze a given security problem and how solution approaches can be found. Further, we introduce a new frame that focuses on the privacy requirement anonymity.