scholarly journals Anti-Attack Scheme for Edge Devices Based on Deep Reinforcement Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Rui Zhang ◽  
Hui Xia ◽  
Chao Liu ◽  
Ruo-bing Jiang ◽  
Xiang-guo Cheng
Keyword(s):  
Reinforcement Learning ◽  
Internet Of Things ◽  
Real Time ◽  
Optimal Strategy ◽  
Experimental Results ◽  
The Mean ◽  
Current Sample ◽  
Traditional Industry ◽  
Zero Sum

Internet of Things realizes the leap from traditional industry to intelligent industry. However, it makes edge devices more vulnerable to attackers during processing perceptual data in real time. To solve the above problem, we use the zero-sum game to build the interactions between attackers and edge devices and propose an antiattack scheme based on deep reinforcement learning. Firstly, we make the k NN-DTW algorithm to find a sample that is similar to the current sample and use the weighted moving mean method to calculate the mean and the variance of the samples. Secondly, to solve the overestimation problem, we develop an optimal strategy algorithm to find the optimal strategy of the edge devices. Experimental results prove that the new scheme improves the payoff of attacked edge devices and decreases the payoff of attackers, thus forcing the attackers to give up the attack.

scholarly journals An improved transmitter system to accurately measure wet-bulb temperature of air

2019 ◽  
Vol 52 (7-8) ◽  
pp. 1002-1007
Author(s):  
Liangwen Yan ◽  
Peng Yu ◽  
Sijung Hu ◽  
Qiu Gao ◽  
Wei Li ◽  
...  
Keyword(s):  
Real Time ◽  
Latent Heat ◽  
Measurement Accuracy ◽  
Cost Effective ◽  
Mean Value ◽  
Experimental Results ◽  
Iteration Algorithm ◽  
Good Consistency ◽  
The Mean ◽  
Good Agreement

A cost-effective measurement of wet-bulb temperature of air has great benefits to fulfill a growing demand of industry, cultivation agriculture, and medication. Applying an appropriate algorithm to wet-bulb temperature of air measurement can effectively improve the accuracy and speed of its measurement. The study aims to research how an improved transmitter system along with the latent heat–based iteration algorithm is used to precisely measure wet-bulb temperature of air. The work consists of (1) simulation of the iteration algorithm and (2) validation via experimental protocol. The simulation results through latent heat–based iteration algorithm were in good agreement ( R2≥ 0.99) with the reference. The performance of the improved wet-bulb temperature of air transmitter system was tested by a latent heat–based iteration algorithm experimental setup. The experimental results demonstrate that the improved wet-bulb temperature of air in a good consistency with commercial wet-bulb temperature of air in a range of temperature (15°C–34°C) and relative humidity (28.8%–76.2%). The Bland–Altman plot also shows that the mean value and the standard deviation of the differences between these two systems are 0.14°C and 0.29°C, respectively, which indicates that the improved wet-bulb temperature of air has a good agreement as well. Compared with the commercial wet-bulb temperature of air transmitter system, an advanced processor (STM32F103C8T6) and real-time operating system was applied in the improved wet-bulb temperature of air transmitter system. The experimental results show that its measurement accuracy is closer to the previous study. This study provides an alternative and cost-effective solution to accurately and real-time measure wet-bulb temperature of air.

Operational “Feel” Adjustment by Reinforcement Learning for a Power-Assisted Positioning Task

2009 ◽  
Vol 3 (6) ◽  
pp. 671-680 ◽  
Author(s):  
Tetsuya Morizono ◽  
◽  
Yoji Yamada ◽  
Masatake Higashi ◽  
◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Task Performance ◽  
User Satisfaction ◽  
Learning Algorithm ◽  
Impedance Control ◽  
Experimental Results ◽  
Multiple Goals ◽  
And Task

Controlling “feel” when operating a power-assist robot is important for improving robot operability, user satisfaction, and task performance efficiency. Autonomous adjustment of “feel” is considered with robots under impedance control, and reinforcement learning in adjustment when a task includes repetitive positioning is discussed. Experimental results demonstrate that an operational “feel” pattern appropriate for positioning at a goal is developed by adjustment. Adjustment assuming a single fixed goal is expanded to cases including multiple goals, in which it is assumed that one goal is chosen by a user in real time. To adjust operational “feel” to individual goals, an algorithm infers the goal. The same result as that for a single fixed goal is obtained in experiments, but experimental results suggest that design must be improved to where the accuracy of inference to the goal is taken into account by the adjustment learning algorithm.

The Experimental Results Analysis of Shortwave Channel Reciprocity

2013 ◽  
Vol 339 ◽  
pp. 419-424
Author(s):  
Hua Ping Lu ◽  
Ai Min Zhu ◽  
Ding Jun Hu ◽  
Lei Zhang
Keyword(s):  
Real Time ◽  
Doppler Shift ◽  
Experimental Results ◽  
Scattering Function ◽  
Time Frequency ◽  
Channel Simulation ◽  
Frequency Selection ◽  
The Mean ◽  
Shortwave Propagation ◽  
Channel Reciprocity

The shortwave channel reciprocity is important for shortwave channel simulation and shortwave real-time frequency-selection. In order to study the reciprocity of shortwave channel. This paper analyzed experimental results on shortwave reciprocity between Wuhan and Wanning in March 2009, the experimental results obtained by the WIOBSS. The experimental results of the contrary paths shortwave propagation displays that the mean difference value of MUF is small, and the scattering function and Doppler shift are similarsim. Removing the inaccuracy of measurement, we can get that the two propagation paths basically satisfy the reciprocity.

scholarly journals Real-Time QoE Monitoring System for Video Streaming Services with Adaptive Media Playout

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mingfu Li ◽  
Chien-Lin Yeh ◽  
Shao-Yu Lu
Keyword(s):  
Real Time ◽  
Video Streaming ◽  
Monitoring System ◽  
Quality Of Experience ◽  
Experimental Results ◽  
Media Player ◽  
Opinion Score ◽  
Streaming Services ◽  
The Mean

Quality of Experience (QoE) of video streaming services has been attracting more and more attention recently. Therefore, in this work we designed and implemented a real-time QoE monitoring system for streaming services with Adaptive Media Playout (AMP), which was implemented into the VideoLAN Client (VLC) media player to dynamically adjust the playout rate of videos according to the buffer fullness of the client buffer. The QoE monitoring system reports the QoE of streaming services in real time so that network/content providers can monitor the qualities of their services and resolve troubles immediately whenever their subscribers encounter them. Several experiments including wired and wireless streaming were conducted to show the effectiveness of the implemented AMP and QoE monitoring system. Experimental results demonstrate that AMP significantly improves the QoE of streaming services according to the Mean Opinion Score (MOS) estimated by our developed program. Additionally, some challenging issues in wireless streaming have been easily identified using the developed QoE monitoring system.

Perancangan Sistem Informasi “DIAMONS” (Diabetes Monitoring System) Berbasis Internet of Things (IoT)

2019 ◽  
Vol 6 (1) ◽  
pp. 39-51
Author(s):  
Endang Sri Rahayu ◽  
Nurul Amalia
Keyword(s):  
Internet Of Things ◽  
World Health Organization ◽  
Real Time ◽  
Monitoring System ◽  
World Health ◽  
Health Organization ◽  
Diabetes Monitoring

Diabetes merupakan penyakit “silent killer” yang ditandai dengan peningkatan kadar glukosa darahdan kegagalan sekresi insulin. World Health Organization (WHO) pada tahun 2016 menyatakanbahwa diabetes menduduki urutan ke-6 sebagai penyakit mematikan di Indonesia. Sehingga upayapencegahan dan penanganan diabetes perlu mendapat perhatian yang serius. Internet of Things (IoT)dapat dijadikan sarana penunjang dalam penanganan penyakit diabetes. Inovasi ini memungkinkanperangkat perawatan kesehatan terhubung dengan jaringan internet, sehingga data pasien dapatdiperbaharui dan diakses secara real-time. Selain mempermudah akses, penggunaan IoT juga akanmemberikan nilai tambah pada efisiensi biaya pelayanan kesehatan. Penelitian ini bertujuan untukmerancang software sistem monitoring gula darah berbasis web yang terintegrasi dengan IoT,sehingga pasien dapat melakukan pemeriksaan, konsultasi dengan dokter dan melihat data rekammedis dari jarak jauh. Data hasil pemeriksaan akan disimpan didalam cloud dan ditampilkan secaraonline. Penelitian ini menggunakan Node MCU ESP8266 sebagai mikrokontroller yang telahdilengkapi dengan modul WiFi, Thingspeak sebagai cloud, aplikasi online dengan “Diamons” sebagaidashboard yang mampu menampilkan presentasi data grafis, dibangun dengan bahasa HypertextPreprocessor (PHP) sebagai bahasa pemogramannya. Penelitian ini akan melibatkan pihak medisdalam pengambilan keputusan. Umpan balik yang diberikan kepada pasien berupa anjuran sepertiresep obat, pola makan, dan kegiatan fisik yang harus dilakukan oleh pasien.

Sign in / Sign up

Export Citation Format

Share Document