Title 1: Fire Disaster Notification Management (FDNM) for Military Storage and Supply Operation Centers
Published: Proceedings of ICTC 2019
Title 2: Delay-aware Computation Offloading Based-on Task Segmentation for IIoT System (A)
Published: Proceedings of KICS fall 2019
Title 3: Optimal Relay Selection Scheme for Mobile-Fog Enabled Cyber-Physical Systems.
Target: Not fixed
Title 4: Sparsely Connected CNN for Efficient Automatic Modulation Recognition
Target: IEEE Transactions on Vehicular Technology
Submitted: July 1, 2020 (Original paper)
Re-submitted (Revised paper): Oct 6, 2020
Accepted: Nov 30, 2020
Status: Published (early access)
Title 5: Multi-shuffled Convolutional Blocks for Low complex Modulation Recognition (A)
Target: ICTC 2020
Submitted: Aug 15, 2020
Status: Accepted
Date: 13/09/2020
Title 6: Learning Spatiotemporal Features by using CNN for efficient Modulation Recognition (A)
Target: KICS summer 2020
Status: Accepted
Title 7: Automatic Modulation Recognition using Deep CNN with Multilevel Fusion Mechanism (Pr)
Target: Not fixed
Title 4
[1]. Received acceptance notification.
[2]. The article was published with DOI: 10.1109/TVT.2020.3042638
Title 5
[1]. Awaiting the publication.
Title 6
[1]. Awaiting the publication.
Title 7
[1]. Experiments and investigation on feature a map permutation.
[2]. Finetuned a network architecture based on the ideas.
[3]. Investigation on hyperparameter optimization.
Title 5
[1]. Awaiting the publication.
Title 6
[1]. Awaiting the publication.
Title 7
[1]. Continue with Experiments.
[2]. Finetuning a network architecture.
[3]. Apply the ideas from literature to modify the current architecture.
[4]. Continue with the Investigation on hyperparameter optimization.
[5]. Finalize the network architecture setup.
Anti-Drone
[1]. Literature review on the low complex Deep learning architectures.
[2]. Working on LabVIEW communication design toolkit to configure a multiple channel SDR receiver.
[1]. Continue with a Literature review on the low-complex Deep learning architectures.
[2]. Prepare the environment for data acquisition.
[3]. Testing the data acquisition model with a drone.
[1]. Master MATLAB communication, deep learning, and optimization toolboxes.
[2]. Improve the algorithm of title [7] and finalize experiments of the summer intensive.
[3]. Finish the LabVIEW USSRP module modules and Start RF data collection for the Anti-drone project.
[4]. Prepare the drone-based dataset and the idea for winter intensive and KICS winter conference
[1]. To submit at least one paper to the SCI journal.
[2]. Attend international and domestic conferences recommended by NSL.
[3]. Acquiring knowledge and skills of NSL technical tools.