Design of a Real – Time Ocean Data – Logging Drifter Thru CLOUD Technology for Collecting Tidal Parameters

Author(s):  
Florian Agbuya ◽  
Gerard Francesco Apolinario ◽  
Dianne Marie Ramos ◽  
JD Mark Villanueva ◽  
Princess Zafe ◽  
...  
Author(s):  
Yu-Hsiang Wu ◽  
Jingjing Xu ◽  
Elizabeth Stangl ◽  
Shareka Pentony ◽  
Dhruv Vyas ◽  
...  

Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small.


2018 ◽  
Vol 15 (4) ◽  
pp. 046014 ◽  
Author(s):  
Song Luan ◽  
Ian Williams ◽  
Michal Maslik ◽  
Yan Liu ◽  
Felipe De Carvalho ◽  
...  

1999 ◽  
Vol 1999 (1) ◽  
pp. 1265-1267 ◽  
Author(s):  
Nir Barnea ◽  
Roger Laferriere

ABSTRACT SMART (Scientific Monitoring of Advanced Response Technologies) is a new monitoring program designed to provide the Unified Command with real-time field data when in situ burning and dispersants are used during oil spill response. For dispersant monitoring, SMART recommends a three-tiered approach. Tier I has visual observation by trained observers from vessels or from aerial platforms. Tier II combines visual observations with water-column sampling using a fluorometer at a single depth. Tier III expands the fluorometry monitoring to several water depths, and uses a water-quality lab. Water samples for later analysis and correlation of fluorometry readings are taken both in Tier II and Tier III. For in situ burning, SMART recommends deploying three or more monitoring teams, each equipped with a real-time particulate monitor with data-logging capability. The teams deploy downwind of the burn at sensitive locations, and report particulate concentration trends to the Unified Command.


Real time data logging of different parameters of Air jet looms should be implemented to reduce the time-consuming method in the textile manufacturing industry. Implementation area of this system is a reduction of efforts and errors done by workers in the textile looms. Existing system is not able to give real time data required by the user at the required time. This system actually keeps record of different stoppages that leads to break the continuity of the machine and hence reduces the machine efficiency. This is a real time system in which wireless communication is used to transfer the recorded data to user’s computer. This recorded detail in turn is transmitted to the PC of the user to do further computation of wages of the worker and manage their work efficiency. This is a real time system in which wireless communication is used to transfer the recorded data to user’s computer as well as on mobile phone. This will provide an additional facility of monitoring the working condition of machine whether it is proper or not and thus user can also keep watch on the workers.


2020 ◽  
Vol 18 (3) ◽  
pp. 57-77
Author(s):  
Wing-Kwong Wong ◽  
Kai-Ping Chen ◽  
Jia-Wei Lin

The results of PISA 2015 indicate that Taiwanese students have excellent mathematical and scientific knowledge but are weak in applying such knowledge and in conducting practical experiments in the laboratory. To support students conducting practical experiments in physics laboratories, a real-time data logging system and an online tool for fitting experimental data were developed. During data logging in an experiment, the data was immediately plotted, which enabled students to observe the characteristics of the plot. The online curve fitting system, which employed Internet of Things technologies, allowed students to fit experimental data to various mathematical functions and plot a function curve superimposed on the data. Two empirical studies were conducted involving first-year university students and secondary school teachers. The results indicated that these developed tools improved students' understanding of an experiment's mathematical characteristics. The average curve fitting error rates of students and teachers were 4.62% and 1.4%, respectively.


2021 ◽  
Author(s):  
Saif Al Arfi ◽  
Mohamed Sarhan ◽  
Olawole Adene ◽  
Muhammad Rizky ◽  
Agung Baruno ◽  
...  

Abstract The challenges of drilling new wells are increasingly associated with minimizing HSE risks, that relate to chemical radioactive sources in the Bottom Hole Assembly for formation evaluation. Drilling risks such as differential sticking, also necessitates investigation of alternative petrophysical data gathering methodologies that can fulfil these requirements. Surface Data Logging presents a viable alternative in mature fields, satisfying petrophysical data gathering and interpretation in real-time as well, as traditional geological applications and offset well correlations in a way, to optimize well construction costs. During the planning phase, a fully integrated approach was adopted including advanced cutting and advanced gas analysis to be deployed, in this case study, well together with experienced well site personnel. A comprehensive pre-well study was conducted reviewing all offset nearby wells data. The workflow included provision of full real-time advanced cuttings and gas analysis for formation evaluation and reservoir fluid composition, lithology description, and addressing effective hole cleaning concerns. The advanced Mud Logging services was run in parallel to the Logging While Drilling services for a few pilot wells, in order to correlate downhole tool parameters, with respect to data quality control, to identify the petrophysical character of the formation markers for benchmarking future data gathering requirements. In addition to the potential use of standalone fully integrated advanced Mud Logging to reduce risks and minimize field development costs. With the help of experienced wellsite geologist on location and real time advanced gas detection utilizing high resolution mass spectrometer and X-Ray fluorescence (XRF) and X-Ray Diffraction (XRD) data, geological boundaries and formations tops were accurately identified across the whole drilled interval. Modern and advanced interpretation techniques for the integrated analysis were proven to be effective in determining sweet spots of the reservoir, fluid type, and overall reservoir quality. Deployment of fully integrated mud logging solutions with new interpretation methodologies can be effective in providing a better understanding of reservoir geological and petrophysical characteristics in real-time, offering viable alternative for minimizing formation evaluation sensors in the BHA, particularly eliminating radioactive sources, while reducing overall developments costs, without sacrificing formation evaluation requirements.


1997 ◽  
Vol 20 (1) ◽  
pp. 7-17
Author(s):  
A. Udina ◽  
Lc Jain

The design of a skylight intensity data logging system is presented. The proposed system is able to accept 32 inputs in two 16 input blocks with capabilities for further expansion. A typical application would be to simultaneously monitor real time change in light intensity in two skylight units, over a chosen periods of minutes, hours or days.


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