Papers

Ade Pitra Hermawan

Title 1: Toward Deep Learning-based Low Latency Communication in Industrial IoT – KICS Summer 2019

Title 2: CNN-based Automatic Modulation Classification for 5G Communications - IEEE Communications Letters (Accepted)

Title 3: Fast and Robust Modulation Recognition using Combined CNN and LSTM algorithms (International Conference Paper)

Title 4: Real-time Data Recovery using Bi-directional LSTM in Wireless Sensor Networks (Winter Intensive)

Title 5: UAV-Based Sensor Nodes Localization Scheme utilizing Shallow Neural Network (Extension)

Last Week's Progress

Title 2:
- Published in Early Access.

Title 3:
- Finish the first version of the paper (5 pages)

Title 4:
- Conduct simulation using ARIMA algorithm
- Compare the performance of LSTM, Bi-LSTM, and ARIMA
- Grammar and typography checking

Title 5:
- Revised the paper as per revisions

This Week Todo's

Title 4:
- Finalize the paper
- Revised the format as provided by the journal (IEEE Communications Letters)
- Put the LSTM and Bi-LSTM into 1 table
- Submission Decision by Prof Kim and Prof Lee

Title 5:
- Match the paper into IEEE transaction on wireless communications format
- Grammar and writing issue checking
- Resubmit soon

Project Progress

Capstone Design Class Project: MERCI for Wild Animal, Website management, Hanhwa System

Last Week's Project

E-WAMS (Edge Computing-Based Wild Animals Monitoring System)
- Making the manual book (tutorial on how to build the system)


Website management
- Create a manual guide of NSL Website (How to create new menu, make a menu private, etc)
- Added newcomers profile
- Move some members to alumni


Hanhwa System:
- Normalized the dataset

This Week's Project

E-WAMS (Edge Computing-Based Wild Animals Monitoring System)
- Finish the manual book (tutorial on how to build the system)


Website management
- Explore each sub-menu of the database
- Create a manual guide of NSL Website (How to add new journal menu, etc)


Hanhwa System:
- Split the dataset into several batches.

Monthly Goals

- Able to use supporting tools to do a simulation (Python, Matlab, NS3, Tensorflow)
- Increase simulation skill every month (self-measurement)

Winter Intensive:
- January: Finish 80% of the simulation, finish the abstract, introduction, related works, all the references are fixed.
- February: Finish the 2nd simulation (enhance the accuracy, comparison, etc)
- March: Finish the 1st version of the paper (before revision)

Annual Goals

2019
- Paper Accepted in the domestic conference (Done)
- Paper Accepted in the international conference
- Submit at least one journal (Done)

2020
- Paper Accepted in the domestic conference
- Paper Accepted in the international conference
- Paper Accepted in the International Journal (Done)