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RISS 인기검색어
- 검색키워드
- 저자 : ( Xiang-guan Deng ) (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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The Design of an Intelligent Aquaculture Systsm Based on Iot and Lora Technologies
( Yun-hsiang Tang ),( Xiang-guan Deng ),( Ming-yen Lin ),( Yi-jung Pai ),( Chao-wang Young ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
In Taiwan, the export-oriented economy of traditional aquaculture is faced with the harshest conditions, such as environmental pollution, diseases and drug overdose. In addition, the traditional aquaculture fields are usually open-air for costing a lot on employing labors. Consequently, it is necessary to set up an intelligent aquaculture system for solving the above problems effectively. This study which was based on these technologies of internet of things (IoT), cloud computing and Long Range Low Power Wide Area Network (LoRa LPWAN), was designed a daily management system for auto-controlling on production planning, energy conservation and reducing labor costs. The users can operate this system which can both monitor the water quality and control these real-time aquaculture parameters (temperature, pH, illuminance and electrical conductivity) by simply using the remote user interface. This system is a modular design that is user-friendly and portable. After all, we expect that it will be great helpful to construct an automatic control platform for improving aquaculture efficiency in future.
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Feasibility of using Machine to Learn & Analyze Brainwave Signal for Establishing Emotional System
( Wei-tsang Huang ),( Xiang-guan Deng ),( Chun-yu Tsai ),( Chyung Ay ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
「Emotion」 is a kind of psychological experience with delight, anger, sorrow, happiness and fear. This kind of experience is a reflection of ordinary people toward the attitude of objective matters. However, it is not an easy thing to see the emotion of inner heart from the appearance and change in eye or different kind of limb expression. This study is to concretize and digitize the various emotional changes of abstract conception through the brainwave analysis, and become a real-time emotional scale. As classified form the analysis and measured data, it is used as the reference standard for assessing emotion. The experiment is implemented by selecting three (3) different emotional categories of films respectively, including three (3) emotions i.e. scared, happy and inspiring emotions and editing as the visual samples, and let the subjects wearing the electroencephalograph (EEG) instrument of Emotiv EPOC with 14 channels on their heads, and use the Python program for writing to perform the measurement together with the EGG measuring system, after transforming the measured brainwave through the fast Fourier, record the energy change of each band, access the experiment data, find out the change of each band at the regular mood swings, derive the emotional conversion formula for quantification, classify the size of emotional changes, and then make the real-time scale of emotion to show the results. In addition, when the different machine learns and analyzes the test samples, it is found when analyze the T7 channel of brainwave detecting point, the success rate of highest test sample is approximately 58%, the success rate of other channels is over 50%, the more suitable operation mode will be found out in the future, and allow the emotional recognition technology can be used in the life.
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( Ssu-yi Lu ),( Xiang-guan Deng ),( Sheng-shu Huang ),( Chun-yu Tsai ),( Chyung Ay ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
With the pressure of society and the large population of insomnia, the sleep problem is becoming more and more serious as the population ages. This study hopes to replace medicines with music and enable patients to relax and enter sleep more quickly. According to clinical experiments, hemi-sync can relax the body and mind and improve the difficulty of sleep. In this experiment, 3.4Hz binaural beats with three different styles of our own sleeping piano music were tested on college students. Emotiv 14-channel wireless EEG device was used to measure and record, analyze the experimental data and present as the spectrogram. For each music beats style, 30 students were selected to perform listening experiments. Calculated the success rate of hemi-sync generated by EEG device, and compared the degree of influence of the three music pieces on the listeners and the differences of frequency band in EEG. The experiment results showed that the hemi-sync appear, with a success rate of more than 40%. Different styles of binaural beats piano music and hemi-sync provide a variety of styles of self-created beats piano music for the public to choose, to shorten the time required to get into sleep and solve the problem of insomnia. In addition, we must observe the feasibility of hemi-sync to the subjects. Using the machine learning algorithm, it was found that in the F7 of the brain area, the accuracy of using the RF algorithm can reach 70.1%, while using XGB it reaches 70.4%, which means that the detection of correlation of hemi-sync and F7 in EEG can improve the verification of the influence of binaural beats on EEG. It shows a clear picture in the future that the beats music can influence the brain, so that people with insomnia can be treated with the most suitable music.
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