scholarly journals Distant temperature and humidity monitoring: prediction and measurement

2021 ◽  
Vol 24 (3) ◽  
pp. 1405
Author(s):  
Farrukh Hafeez ◽  
Usman Ullah Sheikh ◽  
Attaullah Khidrani ◽  
Muhammad Akram Bhayo ◽  
Saleh Masoud Abdallah Altbawi ◽  
...  
Keyword(s):  
Neural Network ◽  
Daily Life ◽  
Ventilation Rate ◽  
Industrial Applications ◽  
Outdoor Environment ◽  
Accurate Information ◽  
Energy Prediction ◽  
Daily Life Activities ◽  
Rate Calculation ◽  
Humidity Monitoring

Sensing environmental measuring parameters has a pivotal role in our everyday lives. Most of our daily life activities depend upon environmental conditions. Accurate information about these parameters also helps in several industrial applications like ventilation rate calculation, energy prediction, stock maintenance in warehouses, and saving from harmful conditions. The emergence of machine learning can make it easy to predict such time series problems. This paper describes the design of a remotely controlled robotic car for measuring and predicting humidity and temperature. A customized app for accessing the robotic car is designed to indicate predicted and realtime measured values of humidity and temperature. A sensor installed builtin helps in the measurement. The recurrent neural network (RNN) model is used to predict humidity and temperature. For this purpose, experiments are carried out in both outdoor and indoor settings. Accuracy of 85% and 90% is achieved in an outdoor environment and indoor settings.

scholarly journals Nanoporous Gold as a VOC Sensor, Based on Nanoscale Electrical Phenomena and Convolutional Neural Networks

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2851
Author(s):  
Timothy S.B. Wong ◽  
Roger Newman
Keyword(s):  
Neural Network ◽  
Capillary Condensation ◽  
Daily Life ◽  
Industrial Applications ◽  
Nanoporous Gold ◽  
Volatile Organic ◽  
Sensitivity And Selectivity ◽  
Classification And Regression ◽  
Voc Sensor ◽  
Significant Health

Volatile organic compounds (VOCs) are prevalent in daily life, from the lab environment to industrial applications, providing tremendous functionality but also posing significant health risk. Moreover, individual VOCs have individual risks associated with them, making classification and sensing of a broad range of VOCs important. This work details the application of electrochemically dealloyed nanoporous gold (NPG) as a VOC sensor through measurements of the complex electrical frequency response of NPG. By leveraging the effects of adsorption and capillary condensation on the electrical properties of NPG itself, classification and regression is possible. Due to the complex nonlinearities, classification and regression are done through the use of a convolutional neural network. This work also establishes key strategies for improving the performance of NPG, both in sensitivity and selectivity. This is achieved by tuning the electrochemical dealloying process through manipulations of the starting alloy and through functionalization with 1-dodecanethiol.

Mobile phone apps’ support for people with mild dementia: A systematic review (Preprint)

2019 ◽  
Author(s):  
Leona Cilar ◽  
Lucija Gosak ◽  
Amanda Briggs ◽  
Klavdija Čuček Trifkovič ◽  
Tracy McClelland ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Thematic Analysis ◽  
Daily Life ◽  
General Term ◽  
Cognitive Domain ◽  
Mild Dementia ◽  
Daily Life Activities ◽  
Human Needs ◽  
People With Dementia ◽  
System Usability Scale

BACKGROUND Dementia is a general term for various disorders characterized by memory impairment and loss of at least one cognitive domain. People with dementia are faced with different difficulties in their daily life activities (DLA). With the use of modern technologies, such as mobile phone apps – often called health apps, their difficulties can be alleviated. OBJECTIVE The aim of this paper was to systematically search, analyze and synthetize mobile phone apps designed to support people with mild dementia in daily life activities in two apps bases: Apple App Store and Google Play Store. METHODS A search was conducted in May 2019 following PRISMA recommendations. Results were analyzed and displayed as tables and graphs. Results were synthetized using thematic analysis which was conducted from 14 components, based on human needs for categorized nursing activities. Mobile phone apps were assessed for quality using the System Usability Scale. RESULTS A total of 15 mobile phone apps were identified applying inclusion and exclusion criteria. Five major themes were identified with thematic analysis: multi-component DLA, communication and feelings, recreation, eating and drinking, and movement. Most of the apps (73%) of the apps were not mentioned in scientific literature. CONCLUSIONS There are many mobile phone apps available in mobile phone markets for the support for people with mild dementia; yet only a few of them are focused on challenges in daily life activities. Most of the available apps were not evaluated nor assessed for quality.

scholarly journals Robust Quadrotor Control through Reinforcement Learning with Disturbance Compensation

2021 ◽  
Vol 11 (7) ◽  
pp. 3257
Author(s):  
Chen-Huan Pi ◽  
Wei-Yuan Ye ◽  
Stone Cheng
Keyword(s):  
Neural Network ◽  
Reinforcement Learning ◽  
Control Strategy ◽  
External Disturbance ◽  
Control Agent ◽  
Network Control ◽  
Outdoor Environment ◽  
Disturbance Compensation ◽  
Tracking Accuracy ◽  
Control Scheme

In this paper, a novel control strategy is presented for reinforcement learning with disturbance compensation to solve the problem of quadrotor positioning under external disturbance. The proposed control scheme applies a trained neural-network-based reinforcement learning agent to control the quadrotor, and its output is directly mapped to four actuators in an end-to-end manner. The proposed control scheme constructs a disturbance observer to estimate the external forces exerted on the three axes of the quadrotor, such as wind gusts in an outdoor environment. By introducing an interference compensator into the neural network control agent, the tracking accuracy and robustness were significantly increased in indoor and outdoor experiments. The experimental results indicate that the proposed control strategy is highly robust to external disturbances. In the experiments, compensation improved control accuracy and reduced positioning error by 75%. To the best of our knowledge, this study is the first to achieve quadrotor positioning control through low-level reinforcement learning by using a global positioning system in an outdoor environment.

Algorithmic Analysis of Automatic Attendance System using Facial Recognition

2022 ◽  
Vol 14 (1) ◽  
pp. 0-0
Keyword(s):  
Face Recognition ◽  
Daily Life ◽  
Real Life ◽  
Student Attendance ◽  
Surveillance Camera ◽  
Daily Life Activities ◽  
The Face ◽  
Algorithmic Analysis ◽  
Human Faces ◽  
Face Biometrics

Attendance management can become a tedious task for teachers if it is performed manually.. This problem can be solved with the help of an automatic attendance management system. But validation is one of the main issues in the system. Generally, biometrics are used in the smart automatic attendance system. Managing attendance with the help of face recognition is one of the biometric methods with better efficiency as compared to others. Smart Attendance with the help of instant face recognition is a real-life solution that helps in handling daily life activities and maintaining a student attendance system. Face recognition-based attendance system uses face biometrics which is based on high resolution monitor video and other technologies to recognize the face of the student. In project, the system will be able to find and recognize human faces fast and accurately with the help of images or videos that will be captured through a surveillance camera. It will convert the frames of the video into images so that our system can easily search that image in the attendance database.

Mental time travel and functional daily life activities in neglect patients: Recovery effects of rehabilitation by prism adaptation

Cortex ◽  
2019 ◽  
Vol 113 ◽  
pp. 141-155 ◽  
Author(s):  
Filomena Anelli ◽  
Stefano Avanzi ◽  
Alessio Damora ◽  
Mauro Mancuso ◽  
Francesca Frassinetti
Keyword(s):  
Daily Life ◽  
Time Travel ◽  
Prism Adaptation ◽  
Mental Time Travel ◽  
Daily Life Activities

scholarly journals Participation in daily life activities and its relationship to strength and functional measures in boys with Duchenne muscular dystrophy

2014 ◽  
Vol 36 (22) ◽  
pp. 1918-1923 ◽  
Author(s):  
Roxanna M. Bendixen ◽  
Donovan J. Lott ◽  
Claudia Senesac ◽  
Sunita Mathur ◽  
Krista Vandenborne
Keyword(s):  
Duchenne Muscular Dystrophy ◽  
Muscular Dystrophy ◽  
Daily Life ◽  
Daily Life Activities ◽  
Functional Measures
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