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 (Published)

Title 3: Automatic Wireless Signal Classification using Combined CNN and LSTM Algorithm in Multimedia IoT (ETFA 2020)

Title 4: Real-time Data Recovery using Multi-directional LSTM in Wireless Sensor Networks - Winter Intensive (Submitted in Wireless Communications Letters)

Title 5: UAV-Based Sensor Nodes Localization Scheme utilizing Shallow Neural Network - Extension (Submitted in IEEE Transaction of Wireless Communications)

Title 6: Sensor Failure Recovery using Deep Learning Technique in Industrial Internet of Things (New Work)

Last Week's Progress

Title 4:
- Submitted.

Title 5:
- Submitted.

Title 6:
- Elaborated on the issues.
- Started to write the first draft of the paper
- Conducted simple simulation of LSTM
- Conducted the simulation of existing algorithms (SARIMA, MLP, DNN)

This Week Todo's

Title 6:
- Try to find a more complex dataset.
- Simulate all the algorithms using the new dataset.

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 book (tutorial on how to build the system)


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


Hanhwa System:
- Normalized the dataset
- Split the dataset into several batches.
- Simulated the prediction algorithm using LSTM.

This Week's Project

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:
- Find recent 7 SCI papers regarding RUL research works.
- Summarize the trends of those papers.

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)
- April: Finalisation & Submission

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)