Report

Holycrab

August 26, 2019 - September 1, 2019

Papers

Chi-Yun Kim

[1] Design of Condition Based Maintenance System using Machine Learning for Military Vehicle
[군용 차량을 위한 머신 러닝 기반 상태 기준 정비 시스템 설계]

[2] Design Performance Analysis of Asymmetric Time Division Multiple Access Method for Improving Response Time and Throughput in Tactical Radio Communication
[전술 무선통신망의 응답시간 및 처리량 개선을 위한 비대칭 다중접속기법 설계 및 성능분석]

[3] A edge computing industrial cyber-physical system for embedded low-latency machine learning Industry 4.0 applications[가제]

30% Progress
Last Week's Progress

[1] Design of Condition Based Maintenance System using Machine Learning for Military Vehicle
[군용 차량을 위한 머신 러닝 기반 상태 기준 정비 시스템 설계]
- Submitted at 2019 KICS summer
- Obtain a vehicle's dataset
- Testing Machine Learning Technique Availability


[2] Design Performance Analysis of Asymmetric Time Division Multiple Access Method for Improving Response Time and Throughput in Tactical Radio Communication
[전술 무선통신망의 응답시간 및 처리량 개선을 위한 비대칭 다중접속기법 설계 및 성능분석]
- Research on related International & domestic papers
- Creating Test Bed


[3] A fog computing industrial cyber-physical system for embedded low-latency machine learning Industry 4.0 applications
- Research on Google coral DEV board
- Paper research for Machine Leaning using tensor

This Week Todo's

[1] Design of Condition Based Maintenance System using Machine Learning for Military Vehicle
[군용 차량을 위한 머신 러닝 기반 상태 기준 정비 시스템 설계]
- Submitted at 2019 KICS summer
- Obtain a vehicle's dataset
- Testing Machine Learning Technique Availability


[2] Design Performance Analysis of Asymmetric Time Division Multiple Access Method for Improving Response Time and Throughput in Tactical Radio Communication
[전술 무선통신망의 응답시간 및 처리량 개선을 위한 비대칭 다중접속기법 설계 및 성능분석]
- Research on related International & domestic papers
- Creating Test Bed using Matlab


[3] A edge computing industrial cyber-physical system for embedded low-latency machine learning Industry 4.0 applications
- Research on Google coral DEV board
- Paper research for Machine Leaning using tensor

Project Progress

Measurement of Natural frequency of the Building

75% Progress
Last Week's Project

[1] Intelligent Black Box Based on Smart Platform
[스마트플랫폼 기반의 지능형 블랙박스 설계 및 구현]
- A Research on the Communication Techniques to Substitute Bluetooth
- Apply Machine Learning Algorithms that using Tensorflow


[2] Measurement of Natural frequency of the building
[빌딩의 고유진동수 측정]
- Research to improve accuracy through machine learning

This Week's Project

[1] Intelligent Black Box Based on Smart Platform
[스마트플랫폼 기반의 지능형 블랙박스 설계 및 구현]
- A Research on the Communication Techniques to Substitute Bluetooth
- Apply Machine Learning Algorithms that using Tensorflow


[2] Measurement of Natural frequency of the building
[빌딩의 고유진동수 측정]
- Research to improve accuracy through machine learning

Monthly Goals

[1] Study on python's Tensorflow
[2] Apply machine learning algorithm in an ongoing project

Annual Goals

[1] Try to submit a international conference