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Musicians and music professionals are often considered to be expert listeners for listening tests on room acoustics. However, these tests often target acoustic parameters other than those typically relevant in music such as pitch, rhythm, amplitude, or timbre. To assess the expertise in perceiving and understanding room acoustical phenomena, a listening test battery was constructed to measure the perceptual sensitivity and cognitive abilities in the identification of rooms with different reverberation times and different spectral envelopes. Performance in these tests was related to data from the Goldsmiths Musical Sophistication Index, self-reported previous experience in music recording and acoustics, and academic knowledge on acoustics. The data from 102 participants show that sensory and cognitive abilities are both correlated significantly with musical training, analytic listening skills, recording experience, and academic knowledge on acoustics, whereas general interest in and engagement with music do not show any significant correlations. The regression models, using only significantly correlated criteria of musicality and professional expertise, explain only small to moderate amounts (11%–28%) of the variance in the “room acoustic listening expertise” across the different tasks of the battery. Thus, the results suggest that the traditional criteria for selecting expert listeners in room acoustics are only weak predictors of their actual performances.
Artificial intelligence and design of experiments for resource adequacy assessment in power systems
(2024)
Airborne volcanic ash particles are a known hazard to aviation. Currently, there are no means available to detect ash in flight as the particles are too fine (radii < 30 μm) for on-board radar detection and, even in good visibility, ash clouds are difficult or impossible to detect by eye. The economic cost and societal impact of the April/May 2010 Icelandic eruption of Eyjafjallajökull generated renewed interest in finding ways to identify airborne volcanic ash in order to keep airspace open and avoid aircraft groundings. We have designed and built a bi-spectral, fast-sampling, uncooled infrared camera device (AVOID) to examine its ability to detect volcanic ash from commercial jet aircraft at distances of more than 50 km ahead. Here we report results of an experiment conducted over the Atlantic Ocean, off the coast of France, confirming the ability of the device to detect and quantify volcanic ash in an artificial ash cloud created by dispersal of volcanic ash from a second aircraft. A third aircraft was used to measure the ash in situ using optical particle counters. The cloud was composed of very fine ash (mean radii ~10 μm) collected from Iceland immediately after the Eyjafjallajökull eruption and had a vertical thickness of ~200 m, a width of ~2 km and length of between 2 and 12 km. Concentrations of ~200 μg m(-3) were identified by AVOID at distances from ~20 km to ~70 km. For the first time, airborne remote detection of volcanic ash has been successfully demonstrated from a long-range flight test aircraft.
CAD/CAM techniques are used increasingly in dentistry for design and fabrication of teeth restorations. An important issue is preserving occlusal contacts of teeth after restoration. Traditional techniques based on the use of casts with mechanical articulators require manual adjustment of occlusal surface, which becomes impractical when hard restoration materials like porcelain are used; they are also time and labor consuming. Most existing computer systems ignore completely such an articulation check, or perform the check at the level of a tooth and its immediate neighbors. We present a new mathematical model and a related user interface for global articulation simulation, developed for the Intelligent Dental Care System project. The aim of the simulation is elimination of the use of mechanical articulators and manual adjustment in the process of designing dental restorations and articulation diagnostic. The mathematical model is based upon differential topological modeling of the jawbs considered as a mechanical system. The user interface exploits metaphors that are familiar to dentists from everyday practice. A new input device designed specifically for use with articulation simulation is proposed.
Mobile live video streaming is becoming an increasingly popular form of interaction both in social media and remote collaboration scenarios. However, in most cases the streamed video does not take mobile devices' spatial data into account (e.g., the viewers do not know the spatial orientation of a streamer), or use such data only in specific scenarios (e.g., to navigate around a spherical video stream).
Applicability of Aeroacoustic Scaling Laws of Leading Edge Serrations for Rotating Applications
(2020)
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.