Low-Cost Real-Time Vision Platform for Spatial Temperature Control Research Education Developments

2019 ◽  
Author(s):  
Jairo Viola ◽  
Alberto Radici ◽  
Sina Dehghan ◽  
YangQuan Chen
Keyword(s):  
Real Time ◽  
Temperature Control ◽  
Low Cost ◽  
Research Education ◽  
Heating And Cooling ◽  
Temperature Feedback ◽  
Peltier Module ◽  
Control Research ◽  
And Training ◽  
Lower Heating

Abstract Temperature control is present in many industrial processes, making this skill mandatory for the control engineers. For this reason, different training temperature platforms have been created for this purpose. However, many of these platforms are expensive, require elaborate facility accommodations, and have higher heating and cooling times, making not suitable for teaching and training. This paper presents a low-cost educational platform for temperature control training. The platform employs a Peltier module as a heating element, which has lower heating and cooling time than other thermal system implementations. A low-cost real-time thermal camera is employed as a temperature feedback sensor instead of a standard thermal sensor. The control algorithm is developed in Matlab-Simulink and employs an Arduino board as hardware in the loop to manage the Peltier module. A temperature control experiment is performed to show that the platform is suitable for teaching and training experiences not only in the classroom but for engineers in the industry.

Effect of Computerized Auditory Training on Speech Perception of Adults With Hearing Impairment

2013 ◽  
Vol 20 (3) ◽  
pp. 91-106 ◽  
Author(s):  
Rachel Pizarek ◽  
Valeriy Shafiro ◽  
Patricia McCarthy
Keyword(s):  
Hearing Loss ◽  
Speech Perception ◽  
Literature Review ◽  
Low Cost ◽  
Experimental Designs ◽  
Auditory Training ◽  
Hearing Impairments ◽  
Communicative Disorders ◽  
And Training

Computerized auditory training (CAT) is a convenient, low-cost approach to improving communication of individuals with hearing loss or other communicative disorders. A number of CAT programs are being marketed to patients and audiologists. The present literature review is an examination of evidence for the effectiveness of CAT in improving speech perception in adults with hearing impairments. Six current CAT programs, used in 9 published studies, were reviewed. In all 9 studies, some benefit of CAT for speech perception was demonstrated. Although these results are encouraging, the overall quality of available evidence remains low, and many programs currently on the market have not yet been evaluated. Thus, caution is needed when selecting CAT programs for specific patients. It is hoped that future researchers will (a) examine a greater number of CAT programs using more rigorous experimental designs, (b) determine which program features and training regimens are most effective, and (c) indicate which patients may benefit from CAT the most.

LOW COST REAL TIME ROCKET TELEMETRY SYSTEM DESIGN

2019 ◽  
Author(s):  
Gabriel de Almeida Souza ◽  
Larissa Barbosa ◽  
Glênio Ramalho ◽  
Alexandre Zuquete Guarato
Keyword(s):  
System Design ◽  
Real Time ◽  
Low Cost ◽  
Telemetry System

Low-Cost High-Speed Techniques for Real-Time Simulation of Power Electronic Systems

2007 ◽  
Author(s):  
R. E. Crosbie ◽  
J. J. Zenor ◽  
R. Bednar ◽  
D. Word ◽  
N. G. Hingorani
Keyword(s):  
Real Time ◽  
High Speed ◽  
Low Cost ◽  
Electronic Systems ◽  
Power Electronic ◽  
Real Time Simulation ◽  
Time Simulation

scholarly journals Application of Deep Learning in Integrated Pest Management: A Real-Time System for Detection and Diagnosis of Oilseed Rape Pests

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yong He ◽  
Hong Zeng ◽  
Yangyang Fan ◽  
Shuaisheng Ji ◽  
Jianjian Wu
Keyword(s):  
Deep Learning ◽  
Integrated Pest Management ◽  
Pest Management ◽  
Real Time ◽  
Oilseed Rape ◽  
Data Augmentation ◽  
Low Cost ◽  
Response Speed ◽  
Original Model ◽  
Real Time System

In this paper, we proposed an approach to detect oilseed rape pests based on deep learning, which improves the mean average precision (mAP) to 77.14%; the result increased by 9.7% with the original model. We adopt this model to mobile platform to let every farmer able to use this program, which will diagnose pests in real time and provide suggestions on pest controlling. We designed an oilseed rape pest imaging database with 12 typical oilseed rape pests and compared the performance of five models, SSD w/Inception is chosen as the optimal model. Moreover, for the purpose of the high mAP, we have used data augmentation (DA) and added a dropout layer. The experiments are performed on the Android application we developed, and the result shows that our approach surpasses the original model obviously and is helpful for integrated pest management. This application has improved environmental adaptability, response speed, and accuracy by contrast with the past works and has the advantage of low cost and simple operation, which are suitable for the pest monitoring mission of drones and Internet of Things (IoT).

scholarly journals Contribution of ICOH to Address the Different OSH Needs among Countries: Results of a Survey

2021 ◽  
Vol 18 (9) ◽  
pp. 4665
Author(s):  
Bruna Rondinone ◽  
Antonio Valenti ◽  
Valeria Boccuni ◽  
Erika Cannone ◽  
Pierluca Dionisi ◽  
...  
Keyword(s):  
Occupational Safety ◽  
Multidisciplinary Approach ◽  
Multiple Correspondence Analysis ◽  
Gdp Per Capita ◽  
Online Questionnaire ◽  
Research Education ◽  
Country Level ◽  
Safety And Health ◽  
Per Capita ◽  
And Training

The aim of this study is to map the coverage of occupational safety and health (OSH) rules and provisions and their enforcement at a country level worldwide. Members’ participation in the International Commission on Occupational Health (ICOH) activities was also investigated. We used a questionnaire-based survey to collect data. An online questionnaire was administered from February 14 to March 18, 2018 to all ICOH members for the triennium 2015 to 2017 (n = 1929). We received 384 completed questionnaires from 79 countries, with a 20% response rate. To synthesize information about the coverage of OSH rules and provisions and their level of enforcement, a synthetic coverage index was calculated and combined with country, gross domestic product (GDP) per capita and the human development index (HDI). We used multiple correspondence analysis (MCA) to analyze the members’ participation in ICOH activities. More than 90.0% of the sample declared that in their own country there is a set of rules and provisions regulating OSH in the workplace, and training procedures and tools to improve workers’ awareness. However, these rules and training procedures are mainly “partially” enforced and utilized (39.0% and 45.4%). There was no statistically significant association between country and GDP per capita and the synthetic coverage index, whilst controlling for HDI. The level of engagement in ICOH activities is higher in senior members (aged 65 years or older), coming from high-income countries, having held a position within ICOH, with a higher level of education and a researcher position. An integrated and multidisciplinary approach, which includes research, education and training, is needed to address OSH issues and their impact both at global and country level.

scholarly journals Low-Cost Embedded System Using Convolutional Neural Networks-Based Spatiotemporal Feature Map for Real-Time Human Action Recognition

2021 ◽  
Vol 11 (11) ◽  
pp. 4940
Author(s):  
Jinsoo Kim ◽  
Jeongho Cho
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Action Recognition ◽  
Processing Speed ◽  
Recognition Accuracy ◽  
Low Cost ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Data ◽  
Feature Maps

The field of research related to video data has difficulty in extracting not only spatial but also temporal features and human action recognition (HAR) is a representative field of research that applies convolutional neural network (CNN) to video data. The performance for action recognition has improved, but owing to the complexity of the model, some still limitations to operation in real-time persist. Therefore, a lightweight CNN-based single-stream HAR model that can operate in real-time is proposed. The proposed model extracts spatial feature maps by applying CNN to the images that develop the video and uses the frame change rate of sequential images as time information. Spatial feature maps are weighted-averaged by frame change, transformed into spatiotemporal features, and input into multilayer perceptrons, which have a relatively lower complexity than other HAR models; thus, our method has high utility in a single embedded system connected to CCTV. The results of evaluating action recognition accuracy and data processing speed through challenging action recognition benchmark UCF-101 showed higher action recognition accuracy than the HAR model using long short-term memory with a small amount of video frames and confirmed the real-time operational possibility through fast data processing speed. In addition, the performance of the proposed weighted mean-based HAR model was verified by testing it in Jetson NANO to confirm the possibility of using it in low-cost GPU-based embedded systems.

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