scholarly journals Producing In Situ Data From a Distance With Mobile Instant Messaging Interviews (MIMIs): Examples From the COVID-19 Pandemic

2021 ◽  
Vol 20 ◽  
pp. 160940692110296
Author(s):  
Katja Kaufmann ◽  
Corinna Peil ◽  
Tabea Bork-Hüffer

Researching people in their chaotic and complex everyday lives is challenging for researchers at any time but especially during the application of social distancing measures. In this article, we make the case for the methodical potential of mobile messengers such as WhatsApp for qualitative mobile in situ research. We exemplify the productive use of the Mobile Instant Messaging Interview (MIMI), a research method developed by Kaufmann and Peil in 2020, to study participants’ everyday life in real-time. Based on two case studies from geography and communication studies conducted during the COVID-19 pandemic, we expound our experiences in the practical application of the MIMI approach and give recommendations. We conclude that MIMIs are a low-cost, easily feasible and short-term implemented approach for research interests across disciplines and possessing great potential for exceptional circumstances like the COVID-19 pandemic. They allow direct access to the practices and experiences of people in situ and in real-time that would otherwise stay hidden and inaccessible to social sciences. The method is suitable for research projects of any size, and can be applied as part of multi- and mixed methods designs and as well for longitudinal designs. Nonetheless, the MIMIs have to be well prepared, demand smart ways of nudging participants into elaborating their responses and require careful coordination between larger teams of researchers.

1991 ◽  
Vol 222 ◽  
Author(s):  
B. Johs ◽  
J. L. Edwards ◽  
K. T. Shiralagi ◽  
R. Droopad ◽  
K. Y. Choi ◽  
...  

ABSTRACTA modular spectroscopic ellipsometer, capable of both in-situ and ex-situ operation, has been used to measure important growth parameters of GaAs/AIGaAs structures. The ex-situ measurements provided layer thicknesses and compositions of the grown structures. In-situ ellipsometric measurements allowed the determination of growth rates, layer thicknesses, and high temperature optical constants. By performing a regression analysis of the in-situ data in real-time, the thickness and composition of an AIGaAs layer were extracted during the MBE growth of the structure.


Author(s):  
Juan Carlos Laso Bayas ◽  
Linda See ◽  
Hedwig Bartl ◽  
Tobias Sturn ◽  
Mathias Karner ◽  
...  

There are many new land use and land cover (LULC) products emerging yet there is still a lack of in-situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in-situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens, and the photographs submitted through the app were not always of sufficient quality. For this reason, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree and a near real-time quality assurance system to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was the implementation of a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to present these new features and to compare the results obtained by the citizens with authoritative LUCAS data from 2018 in terms of LULC and change in LC. We also compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. Finally, we present the results from a user survey to discuss challenges encountered during the campaign and what further improvements could be made in the future, including better in-app navigation and offline maps, making FotoQuest a model for enabling the collection of large amounts of land cover data at a low cost.


2009 ◽  
Vol 26 (3) ◽  
pp. 556-569 ◽  
Author(s):  
Ananda Pascual ◽  
Christine Boone ◽  
Gilles Larnicol ◽  
Pierre-Yves Le Traon

Abstract The timeliness of satellite altimeter measurements has a significant effect on their value for operational oceanography. In this paper, an Observing System Experiment (OSE) approach is used to assess the quality of real-time altimeter products, a key issue for robust monitoring and forecasting of the ocean state. In addition, the effect of two improved geophysical corrections and the number of missions that are combined in the altimeter products are also analyzed. The improved tidal and atmospheric corrections have a significant effect in coastal areas (0–100 km from the shore), and a comparison with tide gauge observations shows a slightly better agreement with the gridded delayed-time sea level anomalies (SLAs) with two altimeters [Jason-1 and European Remote Sensing Satellite-2 (ERS-2)/Envisat] using the new geophysical corrections (mean square differences in percent of tide gauge variance of 35.3%) than those with four missions [Jason-1, ERS/Envisat, Ocean Topography Experiment (TOPEX)/Poseidoninterlaced, and Geosat Follow-On] but using the old corrections (36.7%). In the deep ocean, however, the correction improvements have little influence. The performance of fast delivery products versus delayed-time data is compared using independent in situ data (tide gauge and drifter data). It clearly highlights the degradation of real-time SLA maps versus the delayed-time SLA maps: four altimeters are needed in real time to get the similar quality performance as two altimeters in delayed time (sea level error misfit around 36%, and zonal and meridional velocity estimation errors of 27% and 33%, respectively). This study proves that the continuous improvement of geophysical corrections is very important, and that it is essential to stay above a minimum threshold of four available altimetric missions to capture the main space and time oceanic scales in fast delivery products.


2017 ◽  
Vol 01 (01) ◽  
pp. E8-E15 ◽  
Author(s):  
Francisco Manoel ◽  
Danilo da Silva ◽  
Jorge Lima ◽  
Fabiana Machado

AbstractThis study compared the effects of 4 weeks of training prescribed by peak velocity (Vpeak) or velocity associated with maximum oxygen uptake (vVO2max) in moderately trained endurance runners. Study participants were 14 runners (18–35 years) randomized into 2 groups, named group VO2 (GVO2) and group Vpeak (GVP). The GVO2 had training prescribed by vVO2max and its time limit (tlim), whereas the GVP had training prescribed by Vpeak and its tlim. Four tests were performed on a treadmill: 2 maximum incremental for Vpeak and vVO2max and 2 for their tlim. Performance (10 km) was evaluated on a 400 m track. Evaluations were repeated after 4 weeks of endurance training. The results showed a significant effect of training on Vpeak [GVP (16.7±1.2–17.6±1.5 km.h−1), GVO2 (17.1±1.9–17.7±1.6 km·h−1)]; vVO2max [GVP (16.4±1.4–17.0±1.3 km·h−1), GVO2 (17.2±1.7–17.5±1.9 km·h−1)]; and 10 km performance [GVP (41.3±2.4–39.9±2.7 min), GVO2 (40.1±3.4–39.2±2.9 min)]. The Vpeak highly correlated with performance in both pre- and post-training in GVP (–0.97;–0.86) and GVO2 (–0.95;–0.94), as well as with vVO2max in GVP (–0.82;–0.88) and GVO2 (–0.99; –0.98). It is concluded that training prescribed by Vpeak promoted similar improvements compared to training prescribed by vVO2max. The use of Vpeak is recommended due to its practical application and the low cost of determination.


Author(s):  
C. Gowri Shankar ◽  
Manasa Ranjan Behera

Abstract Tropical cyclones have always proved the extent of its catastrophe on several occurrences over the years. In particular, the Bay of Bengal (BoB) basin in the Northern Indian Ocean has produced such historic devastating events, thereby mandating accurate real-time predictions. Numerical modeling of storm surge has always been an arduous task, as it is integrated with various uncertain factors. Among those, the major governing component being the wind forcing or the wind stress — that signifies, the computational accuracy of simulated surge and wave parameters. The present study is aimed at analysing the most suited wind drag evaluation method for real-time predictions of storm surge along the BoB. Cyclone Phailin (2013) was considered for the numerical simulations. To evaluate the wind drag coefficient, three most extensively used linear empirical relations along with the enhanced Wave Boundary Layer Model (e_WBLM) were used. The surge was subsequently simulated (using the coupled hydrodynamic circulation and wave model: ADCIRC and SWAN, respectively), individually for each of the above wind stress methods to obtain the corresponding storm surge (residual) and the storm wave features. The modeled values were further validated with the in-situ data obtained from tide gauge station and buoys respectively. It was quite intuitively observed that, e_WBLM based results correlated well with the in-situ values than its linear counterparts since, the former pragmatically includes the effects of air-sea interaction at high wind speeds in the model. The e_WBLM-based computation of significant wave heights (Hs) in deep as well as shallow water, nevertheless enabled efficient and reasonably-reliable estimations of the peak incidents.


2017 ◽  
Vol 2017 ◽  
pp. 1-13
Author(s):  
Yu Luo ◽  
Bo Bai ◽  
Honglun Wang ◽  
Yourui Suo ◽  
Yiliang Yao

Alginate has been extensively used as absorbents due to its excellent properties. However, the practical application of pure alginate has been restricted since the saturated adsorbent has weak physical structure and could not be regenerated easily. In this study, a low-cost and renewable composite MnO2@alginate/Mn adsorbent has been prepared facilely for the absorptive removal of antibiotic wastewater. FE-SEM, FTIR, and XRD analyses were used to characterize the samples. The norfloxacin (NOR) was used as an index of antibiotics. More specifically, the batch absorption efficiency of the adsorbents was evaluated by pH, contact time with different NOR concentration, and the temperature. Thus, the performance of absorption kinetic dynamics and isotherm equations were estimated for the adsorptive removal process. Parameters includingΔG0,ΔH0, andΔS0were utilized to describe the feasible adsorption process. To regenerate the saturated absorptive sites of the adsorbent, the heterogeneous Fenton-like reactions were trigged by introduction of H2O2. The results showed that the in situ regenerating has exhibited an excellent recycling stability. The high activity and the simple fabrication of the adsorbents make them attractive for the treatment of wastewater containing refractory organic compound and also provide fundamental basis and technology for further practical application.


Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5508
Author(s):  
Mira Jeong ◽  
MinJi Park ◽  
Jaeyeal Nam ◽  
Byoung Chul Ko

As the need for wildfire detection increases, research on wildfire smoke detection combining low-cost cameras and deep learning technology is increasing. Camera-based wildfire smoke detection is inexpensive, allowing for a quick detection, and allows a smoke to be checked by the naked eye. However, because a surveillance system must rely only on visual characteristics, it often erroneously detects fog and clouds as smoke. In this study, a combination of a You-Only-Look-Once detector and a long short-term memory (LSTM) classifier is applied to improve the performance of wildfire smoke detection by reflecting on the spatial and temporal characteristics of wildfire smoke. However, because it is necessary to lighten the heavy LSTM model for real-time smoke detection, in this paper, we propose a new method for applying the teacher–student framework to deep LSTM. Through this method, a shallow student LSTM is designed to reduce the number of layers and cells constituting the LSTM model while maintaining the original deep LSTM performance. As the experimental results indicate, our proposed method achieves up to an 8.4-fold decrease in the number of parameters and a faster processing time than the teacher LSTM while maintaining a similar detection performance as deep LSTM using several state-of-the-art methods on a wildfire benchmark dataset.


2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Adriel Latorre-Pérez ◽  
Javier Pascual ◽  
Manuel Porcar ◽  
Cristina Vilanova

Abstract High-throughput metagenomic sequencing is considered one of the main technologies fostering the development of microbial ecology. Widely used second-generation sequencers have enabled the analysis of extremely diverse microbial communities, the discovery of novel gene functions, and the comprehension of the metabolic interconnections established among microbial consortia. However, the high cost of the sequencers and the complexity of library preparation and sequencing protocols still hamper the application of metagenomic sequencing in a vast range of real-life applications. In this context, the emergence of portable, third-generation sequencers is becoming a popular alternative for the rapid analysis of microbial communities in particular scenarios, due to their low cost, simplicity of operation, and rapid yield of results. This review discusses the main applications of real-time, in situ metagenomic sequencing developed to date, highlighting the relevance of this technology in current challenges (such as the management of global pathogen outbreaks) and in the next future of industry and clinical diagnosis.


Author(s):  
J. Craig Prather ◽  
Michael Bolt ◽  
Haley Harrell ◽  
Tyler Horton ◽  
Mark L. Adams

Weather affects many aspects of our daily lives from our individual commutes to the global economy. Although much progress has been made in understanding atmospheric physics and weather forecasting, there is still a need for better in situ atmospheric data. Forecasts are based on high performance computer models which solve the differential equations that represent the dynamics of the atmosphere. In all of these models, initial conditions based on the current state of the atmosphere are ingested into the models. The initial conditions are based on data from many sources including remote sensing satellites, ground based weather stations, weather balloons and even aircraft. However, the amount of in situ atmospheric data is very limited and so often times the initial conditions for the models are not truly representative of the current atmosphere. This is especially true for severe storms such as super cell thunderstorms, tornadoes, and hurricanes. Severe weather impacts millions of people every year costing both human life and substantial resources. A better understanding of severe weather will have a significant impact on human safety and infrastructure protection. Electronics miniaturization and advances in manufacturing such as 3D printing have allowed for the development of low-cost, light-weight probes capable of providing real-time in situ information about the atmosphere which can improve forecasts models and provide a better understanding to atmospheric scientists. The probes provide temperature, relative humidity, pressure, position, and velocity data. MEMS sensors are used to monitor the ambient weather conditions and an on-board GPS receiver provides position information. The sensors are combined with a microcontroller and radio to transmit data back to a receiver on the ground. Power is provided by zinc-air batteries and antennas for both the GPS and data radio are integrated into the package. In order to ensure correct operation of the electronics, 3D printing is used to generate a custom electronics/mechanical package that is both functional and robust while maintaining low weight and high drag coefficient. The desire is for the probes to stay airborne as long as possible without any active means of propulsion or buoyancy. The probes designed are small, light-weight, and low cost. They can be deployed from aircraft, weather balloons, or dropped directly into a storm. The design of the probes was simulated through CFD to determine the optimal mechanical packaging of the device. The probes have been tested to validate the range of the probes and the accuracy of the measurements. Although most probes can be recovered after testing, designs focus on minimizing the environmental impact of unrecovered probes. This was done by utilizing 3D printing to create custom mechanical packaging for the electronics that is environmentally friendly along with using zinc air batteries which are a less hazardous battery chemistry. The devices have been designed, fabricated, and tested and the results will be presented. This paper will explain the design processes, design decisions, and testing procedures utilized along with the testing results.


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