Low Cost Laboratory Environment for the Use of Optical Methods for Transmission of Audio Signals

Author(s):  
Tsvetan Valkovski ◽  
Kalin Dimitrov
2021 ◽  
Vol 7 (2) ◽  
pp. 356-362
Author(s):  
Harry Coppock ◽  
Alex Gaskell ◽  
Panagiotis Tzirakis ◽  
Alice Baird ◽  
Lyn Jones ◽  
...  

BackgroundSince the emergence of COVID-19 in December 2019, multidisciplinary research teams have wrestled with how best to control the pandemic in light of its considerable physical, psychological and economic damage. Mass testing has been advocated as a potential remedy; however, mass testing using physical tests is a costly and hard-to-scale solution.MethodsThis study demonstrates the feasibility of an alternative form of COVID-19 detection, harnessing digital technology through the use of audio biomarkers and deep learning. Specifically, we show that a deep neural network based model can be trained to detect symptomatic and asymptomatic COVID-19 cases using breath and cough audio recordings.ResultsOur model, a custom convolutional neural network, demonstrates strong empirical performance on a data set consisting of 355 crowdsourced participants, achieving an area under the curve of the receiver operating characteristics of 0.846 on the task of COVID-19 classification.ConclusionThis study offers a proof of concept for diagnosing COVID-19 using cough and breath audio signals and motivates a comprehensive follow-up research study on a wider data sample, given the evident advantages of a low-cost, highly scalable digital COVID-19 diagnostic tool.


Author(s):  
Rahul Bhadoriya ◽  
Manju K. Chattopadhyay ◽  
Prakash W. Dandekar

Anales AFA ◽  
2020 ◽  
Vol 31 (2) ◽  
pp. 55-61
Author(s):  
D. Chacón ◽  
M. Romero ◽  
F. Mattea ◽  
M. Valente

Advances of the medical application of ionizing radiation, and specifically in cancer treatment, are continuously evolving and gaining higher degrees of complexity. Therefore, the ability to determine and ensure the safety and precision of these techniques must be accompanied by novel dosimetry systems. Polymer gel dosimetry is one of the new and re-markable dosimetry systems that can quantitatively record the absorbed dose and register 3D dose distributions with high resolution while maintaining tissue-equivalent properties. Typical methods used to read the recorded signal in a polymer gel dosimeter, such as magnetic resonance imaging, X-ray tomography, and ultrasound-based techniques in-clude complex and expensive instruments. On the other hand, there are low-cost alternatives like optical methods that can be optimized and designed for the study of polymer gel dosimetry. The objective of this study is to present the de-sign, construction, development, and characterization of a low-cost laser scanner for bi-dimensional PGD analysis. With this equipment, characterization and optimization assays were performed on typical samples, and compared to those obtained by commercial or validated instruments with similar results, proving the capacity of the designed instrument as a reading tool for polymeric gel dosimetry.


Biosensors ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 76 ◽  
Author(s):  
Shashi Bhuckory ◽  
Joshua C. Kays ◽  
Allison M. Dennis

Solution-phase and intracellular biosensing has substantially enhanced our understanding of molecular processes foundational to biology and pathology. Optical methods are favored because of the low cost of probes and instrumentation. While chromatographic methods are helpful, fluorescent biosensing further increases sensitivity and can be more effective in complex media. Resonance energy transfer (RET)-based sensors have been developed to use fluorescence, bioluminescence, or chemiluminescence (FRET, BRET, or CRET, respectively) as an energy donor, yielding changes in emission spectra, lifetime, or intensity in response to a molecular or environmental change. These methods hold great promise for expanding our understanding of molecular processes not just in solution and in vitro studies, but also in vivo, generating information about complex activities in a natural, organismal setting. In this review, we focus on dyes, fluorescent proteins, and nanoparticles used as energy transfer-based optical transducers in vivo in mice; there are examples of optical sensing using FRET, BRET, and in this mammalian model system. After a description of the energy transfer mechanisms and their contribution to in vivo imaging, we give a short perspective of RET-based in vivo sensors and the importance of imaging in the infrared for reduced tissue autofluorescence and improved sensitivity.


Author(s):  
I. V. Chushkina

The relevance of the research. Currently, filtration losses from water-bearing systems and controlling constructions are more than 30% which can be predominantly explained by unsatisfactory technical state of hydraulic engineering structures (HESs). Diagnostics of technical state of HESs of agricultural assignment, relating to a failure effect (responsibility) class CC-1 (i.e. minor effects), is performed usually with the help of visual inspection during inter-vegetation period when irrigation system (IS) is waterless. Searching for low-cost techniques to estimate state of soil HESs as well as determination of areas within them requiring for priority repair is a topical theoretical and practical task. Methods of the research. Geophysical method of natural impulse electromagnetic Earth’s field (NIEEF) may become such a technique; however, a problem of electromagnetic impulses (EMI) generation within soil masses is understudied  despite the fact that they are the basic studied environment in the process of diagnostics of soil HESs of irrigation systems using the technique. To make theoretical and experimental substantiation of the NIEEF method to identify zones of filtration as well as zones of raised watering within the body of small soil geotechnical structures, nature of EMI amplitude changes while transferring uniaxial static load to clay samples in laboratory environment has been analyzed. Similar experiments using idealized model validate opportunity to apply the NIEEF technique for estimation of engineering state of HESs. Research results. The experiments were carried out using clay samples with natural moisture and those experienced additional watering. Soil porosity and soil porosity coefficient, being auxiliary characteristics to plot compression curves, were determined before compression tests and after them; standard calculation techniques were applied. The studies involved usual odometer; electromagnetic impulses were recorded with the help of МІЕМП-14/4 device (SIMEIZ series). The clay samples were loaded in accordance with actual pressure from plates and 4.2 m water layer within filled regulating pool (RP) which dimension was 4.789 kN/m2. Analysis of results of the compression tests has verified the following: increased EMI values correspond to maximum stress state of loose soil, and vice versa – their decrease is typical for relaxations of soil samples as well as for their additional watering. Hence, extreme values of EMI oscillation amplitudes are registered at the beginning of the compression tests when the sample experiences the most intensive compression. Peak excitation results insignificant “fall” of EMI number; then it’s slow increase is observed depending upon the decreased intensity of soil compression. Conclusions. The regularity makes it possible to substantiate theoretically the opportunity to apply rapid and low time-consuming as well as low-cost NIEEF method for diagnostics of engineering state of soil HESs. Previously, such experiments, concerning EMI generation, were carried out using crystalline rocks; loose rocks were involved for the first time.


2006 ◽  
Vol 14 (1) ◽  
Author(s):  
H. Torun ◽  
H. Urey

AbstractThis paper reports a novel uncooled infrared FPA whose performance is comparable to the cooled FPA’s in terms of noise parameters. FPA consists of bimaterial microcantilever structures that are designed to convert IR radiation energy into mechanical energy. Induced deflection by mechanical energy is detected by means of optical methods that measure sub nanometer thermally induced deflections. Analytical solutions are developed for calculating the figure of merits for the FPA. FEM simulations and the analytical solution agree well. Calculations show that for an FPA, NETD of < 5 mK is achievable in the 8–12 μm band. The design and optimization for the detectors are presented. The mechanical structure of pixels is designed such that it can be possible to form large array size FPA’s. Microfabrication of the devices to improve the performance further, employs low cost standard MEMS processes.


2021 ◽  
Vol 20 ◽  
pp. 176-181
Author(s):  
Debalina Banerjee ◽  
Akashjyoti Banik ◽  
Sanjib Kumar Singh ◽  
Kandarpa Kumar Sarma

Surveillance operations designed to be carried out by a robotic vehicle for entry into an area of higher risks and perform hazardous tasks form the core of this work. The system is integrated with a robotic vehicle that is controlled through a virtual interface and well supported by live video streaming. Here, the motion detection sensor is used as a simple but powerful human presence detector and alarm trigger. Also, the design has a metal detector and gas detecting sensor that can provide precaution against potential landmines present in the operations area and presence of chemicals, high energy materials or poisonous gases on regular and event-based occurrence. The real-time data of the gas sensor is stored in the local machine and also uses a speech recognition system developed using Raspberry Pi microcomputer to detect audio signals. It generates routine alarms on special/unknown/ first time patterns of audio threats. The system is designed using low-cost components.


2021 ◽  
Author(s):  
Md Zakir Hossain ◽  
Md. Bashir Uddin ◽  
Khandaker Asif Ahmed

AbstractThe COVID-19 pandemic has a devastating impact on the health and well-being of global population. Cough audio signals classification showed potential as a screening approach for diagnosing people, infected with COVID-19. Recent approaches need costly deep learning algorithms or sophisticated methods to extract informative features from cough audio signals. In this paper, we propose a low-cost envelope approach, called CovidEnvelope, which can classify COVID-19 positive and negative cases from raw data by avoiding above disadvantages. This automated approach can pre-process cough audio signals by filter-out back-ground noises, generate an envelope around the audio signal, and finally provide outcomes by computing area enclosed by the envelope. It has been seen that reliable datasets are also important for achieving high performance. Our approach proves that human verbal confirmation is not a reliable source of information. Finally, the approach reaches highest sensitivity, specificity, accuracy, and AUC of 0.92, 0.87, 0.89, and 0.89 respectively. The automatic approach only takes 1.8 to 3.9 minutes to compute these performances. Overall, this approach is fast and sensitive to diagnose the people living with COVID-19, regardless of having COVID-19 related symptoms or not, and thus have vast applicability in human well-being by designing HCI devices incorporating this approach.


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