A spherical microphone array‐based system for the determination of spatial information in reverberant sound fields

2001 ◽  
Vol 110 (5) ◽  
pp. 2748-2748
Author(s):  
Bradford N. Gover ◽  
James G. Ryan ◽  
Michael R. Stinson
Keyword(s):  
Spatial Information ◽  
Microphone Array ◽  
Sound Fields

scholarly journals Regularised reconstruction of sound fields with a spherical microphone array

2013 ◽  
Author(s):  
Alba Granados ◽  
Finn Jacobsen ◽  
Efren Fernandez-Grande
Keyword(s):  
Microphone Array ◽  
Sound Fields

scholarly journals Abandoned Land Classification Using Classical Theory Method

2019 ◽  
Vol 10 ◽  
pp. 60-68 ◽  
Author(s):  
Jūrate Sužiedelyte Visockiene ◽  
Egle Tumeliene
Keyword(s):  
Agricultural Land ◽  
Spatial Information ◽  
Region Growing ◽  
Cost Effective ◽  
Accurate Method ◽  
Land Classification ◽  
Information Portal ◽  
Abandoned Land ◽  
Rgb Images

According to the official statistics the areas of abandoned agricultural land in Lithuania are gradually decreasing, but very slightly. The aim of this study is to research spatial determination and abandoned land classification in the territory of Vilnius District Municipality. Vilnius District Municipality was chosen for the research because it, although located near the capital of the country and has a high population density, it is still the district having the largest percent of abandoned land plots. A fast, cost-effective and sufficiently accurate method for determination of abandoned land plots would allow to constantly monitor, to fix changes and foresee the abandoned land plots reduction possibilities. In the study there was used the multispectral RGB and NIR color Sentinel-2 satellite images, the layer of the administrative boundary of Vilnius County and layer of abandoned agriculture land, which is available in Lithuanian Spatial Information Portal (www.geoportal.lt). The data was processed by Geographic Information System (GIS) techniques using classical classification Region Growing Algorithm. The research shows that NIR image classification result is more reliable than the result from RGB images.

A Method for Estimating the Area of Damaged Croplands and Woodlands with the Use of Unmanned Aerial Vehicles (Drones)

2017 ◽  
Author(s):  
Tomasz Podciborski ◽  
Jacek Kil
Keyword(s):  
Natural Disasters ◽  
Unmanned Aerial Vehicles ◽  
Spatial Information ◽  
Rapid Development ◽  
Spatial Development ◽  
Measurement Methods ◽  
Loss Assessment ◽  
Aerial Vehicles ◽  
Extent Of Damage

Growing social demand for access to spatial information spurs the rapid development of measurement methods and systems for registering the results of spatial evaluations and analyses (Kwietniewski 2008). Any assessment of spatial development is carried out on the basis of information obtained from specific sources (Kowalczyk 2007). The main objective of this study was to propose a method for assessing the extent of damage caused by natural disasters to croplands and woodlands with the use of unmanned aerial vehicles (drones). The main aim was achieved through detailed goals, including determination of the causes of natural disasters, description of the field inspection procedure and development of loss assessment principles. The proposed method was verified in selected research sites, and the resulting damage report detailing cropland losses is presented in the study.

Hemispheric Specialization in Normally and Slowly Developing Children: A Tachistoscopic and Dichaptic Evaluation

1980 ◽  
Vol 51 (3_suppl2) ◽  
pp. 1187-1201 ◽  
Author(s):  
H. G. Williams ◽  
V. A. Keough ◽  
J. M. Fisher ◽  
C. J. Seymour ◽  
M. G. Tanner
Keyword(s):  
Information Processing ◽  
Response Latency ◽  
Spatial Information ◽  
Hemispheric Specialization ◽  
Verbal Information ◽  
Considerable Evidence ◽  
Left Handed ◽  
Information Number

The purpose of the study was a description of hemispheric specialization characteristics of normally developing right- and left-handed children and determination of what differences in such characteristics, if any, existed between young normally developing and older slowly developing children. With dichaptic and tachistoscopic methods, hemispheric specialization characteristics of 15 slowly developing children (5-0 to 9-6 yr.) and 25 normally developing children (6-0 to 6-11 yr.) were assessed. Latencies and the number of correct responses were analyzed. Both right- and left-handed normally developing 6-yr.-olds showed considerable evidence of bilateralization of hemispheric functions for spatial and verbal information processing; slowly developing children exhibited unusual patterns of hemispheric specialization usually opposite those typically expected in children or adults. Response latency measures of performances of slowly developing children suggested a bilateralization of hemispheric function for processing of verbal and spatial information; number of correct responses indicated that lateralization of such functions was present.

scholarly journals Investigation of Laminar–Turbulent Transition on a Rotating Wind-Turbine Blade of Multimegawatt Class with Thermography and Microphone Array

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2102 ◽  
Author(s):  
Torben Reichstein ◽  
Alois Peter Schaffarczyk ◽  
Christoph Dollinger ◽  
Nicolas Balaresque ◽  
Erich Schülein ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Turbine ◽  
Microphone Array ◽  
Suction Side ◽  
Flow Transition ◽  
Turbulent Transition ◽  
Start Up ◽  
Open Question ◽  
Laminar Turbulent Transition

Knowledge about laminar–turbulent transition on operating multi megawatt wind turbine (WT) blades needs sophisticated equipment like hot films or microphone arrays. Contrarily, thermographic pictures can easily be taken from the ground, and temperature differences indicate different states of the boundary layer. Accuracy, however, is still an open question, so that an aerodynamic glove, known from experimental research on airplanes, was used to classify the boundary-layer state of a 2 megawatt WT blade operating in the northern part of Schleswig-Holstein, Germany. State-of-the-art equipment for measuring static surface pressure was used for monitoring lift distribution. To distinguish the laminar and turbulent parts of the boundary layer (suction side only), 48 microphones were applied together with ground-based thermographic cameras from two teams. Additionally, an optical camera mounted on the hub was used to survey vibrations. During start-up (SU) (from 0 to 9 rpm), extended but irregularly shaped regions of a laminar-boundary layer were observed that had the same extension measured both with microphones and thermography. When an approximately constant rotor rotation (9 rpm corresponding to approximately 6 m/s wind speed) was achieved, flow transition was visible at the expected position of 40% chord length on the rotor blade, which was fouled with dense turbulent wedges, and an almost complete turbulent state on the glove was detected. In all observations, quantitative determination of flow-transition positions from thermography and microphones agreed well within their accuracy of less than 1%.

scholarly journals Robust Traffic Light and Arrow Detection Using Digital Map with Spatial Prior Information for Automated Driving

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1181
Author(s):  
Keisuke Yoneda ◽  
Akisuke Kuramoto ◽  
Naoki Suganuma ◽  
Toru Asaka ◽  
Mohammad Aldibaja ◽  
...  
Keyword(s):  
Urban Areas ◽  
Spatial Information ◽  
Recognition Performance ◽  
Computational Cost ◽  
Region Of Interest ◽  
Traffic Light ◽  
Automated Driving ◽  
Digital Map ◽  
Traffic Lights

Traffic light recognition is an indispensable elemental technology for automated driving in urban areas. In this study, we propose an algorithm that recognizes traffic lights and arrow lights by image processing using the digital map and precise vehicle pose which is estimated by a localization module. The use of a digital map allows the determination of a region-of-interest in an image to reduce the computational cost and false detection. In addition, this study develops an algorithm to recognize arrow lights using relative positions of traffic lights, and the arrow light is used as prior spatial information. This allows for the recognition of distant arrow lights that are difficult for humans to see clearly. Experiments were conducted to evaluate the recognition performance of the proposed method and to verify if it matches the performance required for automated driving. Quantitative evaluations indicate that the proposed method achieved 91.8% and 56.7% of the average f-value for traffic lights and arrow lights, respectively. It was confirmed that the arrow-light detection could recognize small arrow objects even if their size was smaller than 10 pixels. The verification experiments indicate that the performance of the proposed method meets the necessary requirements for smooth acceleration or deceleration at intersections in automated driving.

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