scholarly journals Acoustic Sensing and Noise Identification of a Heating, Ventilation and Air Conditioning Unit: Industrial Case Study

2021 ◽  
Vol 11 (21) ◽  
pp. 9811
Author(s):  
Stephen Grigg ◽  
Zeyad Yousif Abdoon Al-Shibaany ◽  
Matthew Robert Pearson ◽  
Rhys Pullin ◽  
Paul Calderbank
Keyword(s):  
Air Conditioning ◽  
Human Perception ◽  
Noise Sources ◽  
Interior Space ◽  
Industrial Case Study ◽  
Data Set ◽  
Electric Cars ◽  
Recorded Data ◽  
Noise Identification

Reducing the noise and improving the sound quality of vehicles’ interior space is one of the challenges to enhance passengers’ experience. This is an ever-growing issue as entirely electric cars are becoming commonplace, making previously unnoticed noise a significant problem. Heating, Ventilation and Air Conditioning (HVAC) units are a major noise source in a vehicle’s interior space, yet automotive manufacturers only give a maximum dB specification to HVAC unit manufactures. Problematic noise is only typically identified once the unit is within the vehicle at the late stages of a project. Psychoacoustics is the study of human perception to sound, allowing unpleasant noise to be identified within recorded data. Within this study, an industrial prototype HVAC unit was analysed using a 96-channel acoustic camera capable of isolating and locating noise sources from the unit using beamforming. In addition to identifying the location of noise sources, several psychoacoustic metrics were used, such as sharpness and loudness, to identify undesirable noise within an extensive data set due to the vast range of test configurations. Testing was conducted to analyse the unit. Within the initial testing, an ‘annoying’ sound was identified at a particular motor RPM, and this was located using the camera to an area which indicated that it was a result of structural resonance. In addition, present was a high-frequency source which could not be located accurately. The results of this testing enable modifications to the unit to be made early in its’ development, either structurally to alter the resonance of the unit or within the settings to ensure certain RPMs are avoided.

scholarly journals Mnemonic Oasis: Interior architecture as a stimulus for wellbeing through sensorial experience

2021 ◽  
Author(s):  
◽  
Trevon Schubach
Keyword(s):  
Quality Of Life ◽  
Life Satisfaction ◽  
Human Perception ◽  
First Century ◽  
Interior Space ◽  
Interior Architecture ◽  
Design Component ◽  
Spatial Design ◽  
Stressful Environments

<p>In today’s society the priority of work and careers has resulted in highly stressful environments. In the twenty-first century the tendency of inflated urban centres has encouraged people to move to the cities and as the urban population increases, the quality of life, people’s wellbeing and overall life satisfaction, becomes a concern. Interested in the effect of human perception through spatial design, this thesis explores how sensorial experience can influence the design of interior architecture to promote productivity and wellbeing.  This research aims to explore the implications of environmental stimuli and sensory experience to enhance an occupant’s behaviour and wellbeing within an interior space. Looking closely at the built environment that we inhabit and identifying how it impacts its occupants would aid in how we as designers could design spaces that benefit the occupant’s quality of life.  This thesis asks how interior architecture may be utilised to enhance the sense of productivity, wellbeing and life satisfaction of the working class and city dwellers. In addition, this thesis aims to adaptively reuse a historic site in the Wellington CBD as the principal vehicle for the design component of this study.  Overall the research suggests providing multiple opportunities for occupants to engage with the built and natural environment whereby interior architecture, through atmospheres and sensorial experiences, contributes to the solution in establishing a sense of productivity, wellbeing and life satisfaction.</p>

Measuring gravity on ice: An example from Wanapitei Lake, Ontario, Canada

Geophysics ◽  
2006 ◽  
Vol 71 (3) ◽  
pp. J23-J29 ◽  
Author(s):  
Hernan A. Ugalde ◽  
Elizabeth L’Heureux ◽  
Richard Lachapelle ◽  
Bernd Milkereit
Keyword(s):  
Large Scale ◽  
Field Measurements ◽  
Noise Sources ◽  
Large Lakes ◽  
Data Set ◽  
Long Time ◽  
Calm Wind ◽  
Regional Gravity ◽  
The Impact

Large lakes have always represented a problem for regional gravity databases; the difficulty of access means gaps or coarse spacing in the sampling. Satellite, airborne, and shipborne gravity techniques are options, but the resolution and/or cost of these systems make them impractical or inaccurate for exploration or environmental studies, where the required resolution is [Formula: see text]. In this study, the feasibility of a ground gravity survey over a frozen lake where ice moves because of windy conditions is assessed. Lake Wanapitei, widely accepted as resulting from the impact of a meteorite 37 million years ago, is one of these cases in which the necessity of expanding coverage over poorly sampled regions arose from a significant gap between surface and airborne geophysical maps. Two gravity surveys were completed on the ice of Lake Wanapitei in the winters of 2003 and 2004. To study the structure, longtime series of gravity field measurements were recorded for 98 stations, allowing for improved control over the noise sources in the data. Final processing and integration with an existing regional data set in the area and the application of terrain corrections reduced the amplitude of the circular anomaly from 15 to [Formula: see text] and its diameter from 11 to [Formula: see text]. The feasibility of gravity surveys on ice was assessed, and we determined that for large-scale studies such as this one, the quality of the data, even under noisy conditions, was acceptable. However, for more detailed mapping, calm wind conditions and long time series are required.

scholarly journals Mnemonic Oasis: Interior architecture as a stimulus for wellbeing through sensorial experience

2021 ◽  
Author(s):  
◽  
Trevon Schubach
Keyword(s):  
Quality Of Life ◽  
Life Satisfaction ◽  
Human Perception ◽  
First Century ◽  
Interior Space ◽  
Interior Architecture ◽  
Design Component ◽  
Spatial Design ◽  
Stressful Environments

<p>In today’s society the priority of work and careers has resulted in highly stressful environments. In the twenty-first century the tendency of inflated urban centres has encouraged people to move to the cities and as the urban population increases, the quality of life, people’s wellbeing and overall life satisfaction, becomes a concern. Interested in the effect of human perception through spatial design, this thesis explores how sensorial experience can influence the design of interior architecture to promote productivity and wellbeing.  This research aims to explore the implications of environmental stimuli and sensory experience to enhance an occupant’s behaviour and wellbeing within an interior space. Looking closely at the built environment that we inhabit and identifying how it impacts its occupants would aid in how we as designers could design spaces that benefit the occupant’s quality of life.  This thesis asks how interior architecture may be utilised to enhance the sense of productivity, wellbeing and life satisfaction of the working class and city dwellers. In addition, this thesis aims to adaptively reuse a historic site in the Wellington CBD as the principal vehicle for the design component of this study.  Overall the research suggests providing multiple opportunities for occupants to engage with the built and natural environment whereby interior architecture, through atmospheres and sensorial experiences, contributes to the solution in establishing a sense of productivity, wellbeing and life satisfaction.</p>

Analysis of color Image Enhancement Using DWT, Wavelet Shrinkageand FHE Methods

2017 ◽  
Vol 7 (8) ◽  
pp. 56
Author(s):  
Ashish Dwivedi ◽  
Nirupma Tiwari
Keyword(s):  
Image Enhancement ◽  
Color Image ◽  
Human Perception ◽  
Histogram Equalization ◽  
Wavelet Shrinkage ◽  
Visual Appearance ◽  
Enhancement Method ◽  
Fuzzy Histogram ◽  
Rgb Image

Image enhancement (IE) is very important in the field where visual appearance of an image is the main. Image enhancement is the process of improving the image in such a way that the resulting or output image is more suitable than the original image for specific task. With the help of image enhancement process the quality of image can be improved to get good quality images so that they can be clear for human perception or for the further analysis done by machines.Image enhancement method enhances the quality, visual appearance, improves clarity of images, removes blurring and noise, increases contrast and reveals details. The aim of this paper is to study and determine limitations of the existing IE techniques. This paper will provide an overview of different IE techniques commonly used. We Applied DWT on original RGB image then we applied FHE (Fuzzy Histogram Equalization) after DWT we have done the wavelet shrinkage on Three bands (LH, HL, HH). After that we fuse the shrinkage image and FHE image together and we get the enhance image.

scholarly journals Calling for improved quality in the registration of traditional Chinese medicine during the public health emergency: a survey of trial registries for COVID-19, H1N1, and SARS

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhuoran Kuang ◽  
◽  
Xiaoyan Li ◽  
Jianxiong Cai ◽  
Yaolong Chen ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Secondary Outcome ◽  
Specific Information ◽  
Clinical Trial Registry ◽  
Data Set ◽  
Diagnosis Criteria

Abstract Objective To assess the registration quality of traditional Chinese medicine (TCM) clinical trials for COVID-19, H1N1, and SARS. Method We searched for clinical trial registrations of TCM in the WHO International Clinical Trials Registry Platform (ICTRP) and Chinese Clinical Trial Registry (ChiCTR) on April 30, 2020. The registration quality assessment is based on the WHO Trial Registration Data Set (Version 1.3.1) and extra items for TCM information, including TCM background, theoretical origin, specific diagnosis criteria, description of intervention, and outcomes. Results A total of 136 records were examined, including 129 severe acute respiratory syndrome coronavirus 2 (COVID-19) and 7 H1N1 influenza (H1N1) patients. The deficiencies in the registration of TCM clinical trials (CTs) mainly focus on a low percentage reporting detailed information about interventions (46.6%), primary outcome(s) (37.7%), and key secondary outcome(s) (18.4%) and a lack of summary result (0%). For the TCM items, none of the clinical trial registrations reported the TCM background and rationale; only 6.6% provided the TCM diagnosis criteria or a description of the TCM intervention; and 27.9% provided TCM outcome(s). Conclusion Overall, although the number of registrations of TCM CTs increased, the registration quality was low. The registration quality of TCM CTs should be improved by more detailed reporting of interventions and outcomes, TCM-specific information, and sharing of the result data.

Simple Index to Assess the Calibration Quality of Safety Performance Functions Based on Multiple Goodness-of-Fit Metrics

2021 ◽  
pp. 036119812110088
Author(s):  
Raul E. Avelar ◽  
Karen Dixon ◽  
Boniphace Kutela ◽  
Sam Klump ◽  
Beth Wemple ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Synthetic Data ◽  
Calibration Procedure ◽  
Safety Performance ◽  
Absolute Deviation ◽  
Data Set ◽  
Safety Database ◽  
Simple Index ◽  
Safety Performance Functions

The calibration of safety performance functions (SPFs) is a mechanism included in the Highway Safety Manual (HSM) to adjust SPFs in the HSM for use in intended jurisdictions. Critically, the quality of the calibration procedure must be assessed before using the calibrated SPFs. Multiple resources to aid practitioners in calibrating SPFs have been developed in the years following the publication of the HSM 1st edition. Similarly, the literature suggests multiple ways to assess the goodness-of-fit (GOF) of a calibrated SPF to a data set from a given jurisdiction. This paper uses the calibration results of multiple intersection SPFs to a large Mississippi safety database to examine the relations between multiple GOF metrics. The goal is to develop a sensible single index that leverages the joint information from multiple GOF metrics to assess overall quality of calibration. A factor analysis applied to the calibration results revealed three underlying factors explaining 76% of the variability in the data. From these results, the authors developed an index and performed a sensitivity analysis. The key metrics were found to be, in descending order: the deviation of the cumulative residual (CURE) plot from the 95% confidence area, the mean absolute deviation, the modified R-squared, and the value of the calibration factor. This paper also presents comparisons between the index and alternative scoring strategies, as well as an effort to verify the results using synthetic data. The developed index is recommended to comprehensively assess the quality of the calibrated intersection SPFs.

scholarly journals Facing the needs for clean bicycle data – a bicycle-specific approach of GPS data processing

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Sven Lißner ◽  
Stefan Huber
Keyword(s):  
Data Processing ◽  
Gps Data ◽  
Data Set ◽  
Specific Data ◽  
Driving Mode ◽  
Mode Detection ◽  
Current State ◽  
Mode Recognition ◽  
Recorded Data ◽  
Gps Tracks

Abstract Background GPS-based cycling data are increasingly available for traffic planning these days. However, the recorded data often contain more information than simply bicycle trips. GPS tracks resulting from tracking while using other modes of transport than bike or long periods at working locations while people are still tracking are only some examples. Thus, collected bicycle GPS data need to be processed adequately to use them for transportation planning. Results The article presents a multi-level approach towards bicycle-specific data processing. The data processing model contains different steps of processing (data filtering, smoothing, trip segmentation, transport mode recognition, driving mode detection) to finally obtain a correct data set that contains bicycle trips, only. The validation reveals a sound accuracy of the model at its’ current state (82–88%).

scholarly journals The newly developed airborne radio-echo sounding system of the AWI as a glaciological tool

1999 ◽  
Vol 29 ◽  
pp. 231-238 ◽  
Author(s):  
U. Nixdorf ◽  
D. Steinhage ◽  
U. Meyer ◽  
L. Hempel ◽  
M. Jenett ◽  
...  
Keyword(s):  
Digital Data ◽  
Radar Signal ◽  
Ice Shelves ◽  
System Sensitivity ◽  
Ice Caps ◽  
Radio Echo Sounding ◽  
Recorded Data ◽  
Along Track ◽  
Echo Sounding

AbstractSince 1994 the Alfred Wegener Institute (AWI) has operated an airborne radio-echo sounding system for remote-sensing studies of the polar ice caps in Antarctica and in Greenland. It is used to map ice thicknesses and internal layernigs of glaciers, ice sheets and ice shelves, and is capable of penetrating ice thicknesses of up to 4 km. The system was designed and built by AWI in cooperation with Aerodata Flugmeßtechnik GmbH, Technische Umversitat Hamburg-Harburg and the Deutsches Zentrum fur Luft- und Raumfahrt e.V. The system uses state-of-the-art techniques, and results in high vertical (5 m) as well as along-track (3.25 m) resolution. The radar signal is a 150 MHz burst with a duration of 60 or 600 ns. The peak power is 1.6 kW, and the system sensitivity is 190 dB. The short backfire principle has been adopted and optimized for antennae used on Polar2, a Dormer 228-100 aircraft, resulting in an antenna gain of 14 dB each. Digital data recording allows further processing. The quality of the recorded data can be monitored on screen and as online analogue plots during the flight.

A Study on the Performance of Stratified Air Conditioning Design in Assembly Halls – A Case Study at the Dazhi Cultural Center in Taiwan

2013 ◽  
Vol 368-370 ◽  
pp. 599-602 ◽  
Author(s):  
Ian Hung ◽  
Hsien Te Lin ◽  
Yu Chung Wang
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Indoor Air ◽  
Air Conditioning ◽  
Cfd Simulation ◽  
Indoor Temperature ◽  
Cultural Center ◽  
Computational Fluid Dynamics Cfd

This study focuses on the performance of air conditioning design at the Dazhi Cultural Center and uses a computational fluid dynamics (CFD) simulation to discuss the differences in wind velocity and ambient indoor temperature between all-zone air conditioning design and stratified air conditioning design. The results have strong implications for air conditioning design and can improve the indoor air quality of assembly halls.

scholarly journals Leveraging Road Characteristics and Contributor Behaviour for Assessing Road Type Quality in OSM

2021 ◽  
Vol 10 (7) ◽  
pp. 436
Author(s):  
Amerah Alghanim ◽  
Musfira Jilani ◽  
Michela Bertolotto ◽  
Gavin McArdle
Keyword(s):  
Machine Learning ◽  
Spatial Data ◽  
Classification Accuracy ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Data Set ◽  
Semantic Inference ◽  
Road Type ◽  
The Impact

Volunteered Geographic Information (VGI) is often collected by non-expert users. This raises concerns about the quality and veracity of such data. There has been much effort to understand and quantify the quality of VGI. Extrinsic measures which compare VGI to authoritative data sources such as National Mapping Agencies are common but the cost and slow update frequency of such data hinder the task. On the other hand, intrinsic measures which compare the data to heuristics or models built from the VGI data are becoming increasingly popular. Supervised machine learning techniques are particularly suitable for intrinsic measures of quality where they can infer and predict the properties of spatial data. In this article we are interested in assessing the quality of semantic information, such as the road type, associated with data in OpenStreetMap (OSM). We have developed a machine learning approach which utilises new intrinsic input features collected from the VGI dataset. Specifically, using our proposed novel approach we obtained an average classification accuracy of 84.12%. This result outperforms existing techniques on the same semantic inference task. The trustworthiness of the data used for developing and training machine learning models is important. To address this issue we have also developed a new measure for this using direct and indirect characteristics of OSM data such as its edit history along with an assessment of the users who contributed the data. An evaluation of the impact of data determined to be trustworthy within the machine learning model shows that the trusted data collected with the new approach improves the prediction accuracy of our machine learning technique. Specifically, our results demonstrate that the classification accuracy of our developed model is 87.75% when applied to a trusted dataset and 57.98% when applied to an untrusted dataset. Consequently, such results can be used to assess the quality of OSM and suggest improvements to the data set.

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