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 (Re-submitted)

Title 3: Fast and Robust Modulation Recognition using Lightweight Convolutional Neural Network (International Conference)

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

Last Week's Progress

Title 2:
Minor Revision


Title 3:
- Finished the 1st version of the draft and simulation


Title 4:
- Working on simulation (error on MemoryError) -> Local CPU, using Spyder
- Simulated simple sensor data estimation (Forward LSTM) -> Cloud-based GPU, Google Colab
- Extended the Introduction and system model

This Week Todo's

Title 2:
- Revise the paper as per review (Explain more the simulation, add zoom-in graph feature)
- Resubmit soon this week


Title 3:
- Check grammatical error and similarity
- Finalize the paper

Title 4:
- Extend the Proposed System section
- Add more related works content
- Find or create a suitable dataset
- Simulate Back-ward LSTM

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)
- Finish the manual guide per section

Website management
- Explore each sub-menu of the database
- Understanding of how to add new sub-menu (MySQL), find the class CD of each sub-menu
- Created The database & menu of the Winter Intensive 2020 period

Hanhwa System:
- Literature reviews
- Collect the required information.

This 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
- Explore each sub-menu of the database
- Create manual guide of NSL Website (How to create new menu, make a menu private, etc)


Hanhwa System:
- Waiting for the dataset.
- Conduct a simple simulation.

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 the 1st 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