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GlobalSIP 2019

The 7th IEEE Global Conference on Signal and Information Processing (GlobalSIP)  focuses on signal and information processing with an emphasis on up-and-coming signal processing themes. The conference features world-class plenary speeches, distinguished symposium talks, tutorials, exhibits, oral and poster sessions, and panels. GlobalSIP is comprised of co-located General Symposium and symposia selected based on responses to the call-for-symposia proposals.

A Multitaper Model for Quiet Voltage in Relative Ionospheric Opacity Meters


When modelling the stable baseline component of a riometer voltage series, the degradation of statistical performance can be significant if either the data are noisy or the underlying stochastic process is highly nonstationary. It is desirable to explore models which balance the high degree of stability of a quiet-day curve with low computation time. This paper introduces a multitaper method for generating quiet-day curves. A novel metric is introduced for determining the overlap fraction in a section-overlap model of the stable baseline component.

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Authors:
David J. Thomson, Glen Takahara, Robyn A. Fiori
Submitted On:
9 November 2019 - 6:56am
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Marshall_Francois_GlobalSIP_13_11_2019.pdf

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[1] David J. Thomson, Glen Takahara, Robyn A. Fiori, "A Multitaper Model for Quiet Voltage in Relative Ionospheric Opacity Meters", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4938. Accessed: Nov. 11, 2019.
@article{4938-19,
url = {http://sigport.org/4938},
author = {David J. Thomson; Glen Takahara; Robyn A. Fiori },
publisher = {IEEE SigPort},
title = {A Multitaper Model for Quiet Voltage in Relative Ionospheric Opacity Meters},
year = {2019} }
TY - EJOUR
T1 - A Multitaper Model for Quiet Voltage in Relative Ionospheric Opacity Meters
AU - David J. Thomson; Glen Takahara; Robyn A. Fiori
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4938
ER -
David J. Thomson, Glen Takahara, Robyn A. Fiori. (2019). A Multitaper Model for Quiet Voltage in Relative Ionospheric Opacity Meters. IEEE SigPort. http://sigport.org/4938
David J. Thomson, Glen Takahara, Robyn A. Fiori, 2019. A Multitaper Model for Quiet Voltage in Relative Ionospheric Opacity Meters. Available at: http://sigport.org/4938.
David J. Thomson, Glen Takahara, Robyn A. Fiori. (2019). "A Multitaper Model for Quiet Voltage in Relative Ionospheric Opacity Meters." Web.
1. David J. Thomson, Glen Takahara, Robyn A. Fiori. A Multitaper Model for Quiet Voltage in Relative Ionospheric Opacity Meters [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4938

Framework for promoting social interaction and physical activity in elderly people using gamification and fuzzy logic strategy


Elderly people commonly face health problems related to their sedentary life. Thus, their physical strength, mental capability, and motor skills are decreasing. Moreover, overweight and physical problems are becoming a serious health problem around the world. On the other hand, they suffer from the social isolation that directly affects their physical and mental health. Gamification for elderly people emerges to motivate them to exercise and socialize with their peers, through social interaction on mobile devices.

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Authors:
Pedro Ponce, Alan Meier, Therese Peffer, Omar Mata, and Arturo Molina
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9 November 2019 - 2:32pm
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FW for promoting SI and PA in elderly people using gamification and fuzzy logic strategy.pdf

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[1] Pedro Ponce, Alan Meier, Therese Peffer, Omar Mata, and Arturo Molina, "Framework for promoting social interaction and physical activity in elderly people using gamification and fuzzy logic strategy", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4937. Accessed: Nov. 11, 2019.
@article{4937-19,
url = {http://sigport.org/4937},
author = {Pedro Ponce; Alan Meier; Therese Peffer; Omar Mata; and Arturo Molina },
publisher = {IEEE SigPort},
title = {Framework for promoting social interaction and physical activity in elderly people using gamification and fuzzy logic strategy},
year = {2019} }
TY - EJOUR
T1 - Framework for promoting social interaction and physical activity in elderly people using gamification and fuzzy logic strategy
AU - Pedro Ponce; Alan Meier; Therese Peffer; Omar Mata; and Arturo Molina
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4937
ER -
Pedro Ponce, Alan Meier, Therese Peffer, Omar Mata, and Arturo Molina. (2019). Framework for promoting social interaction and physical activity in elderly people using gamification and fuzzy logic strategy. IEEE SigPort. http://sigport.org/4937
Pedro Ponce, Alan Meier, Therese Peffer, Omar Mata, and Arturo Molina, 2019. Framework for promoting social interaction and physical activity in elderly people using gamification and fuzzy logic strategy. Available at: http://sigport.org/4937.
Pedro Ponce, Alan Meier, Therese Peffer, Omar Mata, and Arturo Molina. (2019). "Framework for promoting social interaction and physical activity in elderly people using gamification and fuzzy logic strategy." Web.
1. Pedro Ponce, Alan Meier, Therese Peffer, Omar Mata, and Arturo Molina. Framework for promoting social interaction and physical activity in elderly people using gamification and fuzzy logic strategy [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4937

Robust Direction of Arrival Estimation in the Presence of Array Faults using Snapshot Diversity

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Authors:
Gary C.F. Lee, Ankit S. Rawat, Gregory W. Wornell
Submitted On:
11 November 2019 - 5:51pm
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[1] Gary C.F. Lee, Ankit S. Rawat, Gregory W. Wornell, "Robust Direction of Arrival Estimation in the Presence of Array Faults using Snapshot Diversity", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4936. Accessed: Nov. 11, 2019.
@article{4936-19,
url = {http://sigport.org/4936},
author = {Gary C.F. Lee; Ankit S. Rawat; Gregory W. Wornell },
publisher = {IEEE SigPort},
title = {Robust Direction of Arrival Estimation in the Presence of Array Faults using Snapshot Diversity},
year = {2019} }
TY - EJOUR
T1 - Robust Direction of Arrival Estimation in the Presence of Array Faults using Snapshot Diversity
AU - Gary C.F. Lee; Ankit S. Rawat; Gregory W. Wornell
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4936
ER -
Gary C.F. Lee, Ankit S. Rawat, Gregory W. Wornell. (2019). Robust Direction of Arrival Estimation in the Presence of Array Faults using Snapshot Diversity. IEEE SigPort. http://sigport.org/4936
Gary C.F. Lee, Ankit S. Rawat, Gregory W. Wornell, 2019. Robust Direction of Arrival Estimation in the Presence of Array Faults using Snapshot Diversity. Available at: http://sigport.org/4936.
Gary C.F. Lee, Ankit S. Rawat, Gregory W. Wornell. (2019). "Robust Direction of Arrival Estimation in the Presence of Array Faults using Snapshot Diversity." Web.
1. Gary C.F. Lee, Ankit S. Rawat, Gregory W. Wornell. Robust Direction of Arrival Estimation in the Presence of Array Faults using Snapshot Diversity [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4936

Training of Deep Bidirectional RNNs for Hand Motion Filtering via Multimodal Data Fusion


Pathological Hand Tremor (PHT) is one of the most prevalent symptoms of some neurological movement disorders such as Parkinson’s Disease (PD) and Essential Tremor (ET). Characterization, estimation, and extraction of PHT is a crucial requirement for assistive and robotic rehabilitation technologies that aim to counteract or resist PHT as an input noise to the system. In general, research in the literature on the topic of PHT removal can be categorized into two major categories, namely, classic and data-driven methods.

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Authors:
Soroosh Shahtalebi, S. Farokh Atashzar, Rajni V. Patel, Arash Mohammadi
Submitted On:
8 November 2019 - 7:28pm
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Training of Deep Bidirectional RNNs for Hand Motion Filtering via Multimodal Data Fusion

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[1] Soroosh Shahtalebi, S. Farokh Atashzar, Rajni V. Patel, Arash Mohammadi, "Training of Deep Bidirectional RNNs for Hand Motion Filtering via Multimodal Data Fusion", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4935. Accessed: Nov. 11, 2019.
@article{4935-19,
url = {http://sigport.org/4935},
author = {Soroosh Shahtalebi; S. Farokh Atashzar; Rajni V. Patel; Arash Mohammadi },
publisher = {IEEE SigPort},
title = {Training of Deep Bidirectional RNNs for Hand Motion Filtering via Multimodal Data Fusion},
year = {2019} }
TY - EJOUR
T1 - Training of Deep Bidirectional RNNs for Hand Motion Filtering via Multimodal Data Fusion
AU - Soroosh Shahtalebi; S. Farokh Atashzar; Rajni V. Patel; Arash Mohammadi
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4935
ER -
Soroosh Shahtalebi, S. Farokh Atashzar, Rajni V. Patel, Arash Mohammadi. (2019). Training of Deep Bidirectional RNNs for Hand Motion Filtering via Multimodal Data Fusion. IEEE SigPort. http://sigport.org/4935
Soroosh Shahtalebi, S. Farokh Atashzar, Rajni V. Patel, Arash Mohammadi, 2019. Training of Deep Bidirectional RNNs for Hand Motion Filtering via Multimodal Data Fusion. Available at: http://sigport.org/4935.
Soroosh Shahtalebi, S. Farokh Atashzar, Rajni V. Patel, Arash Mohammadi. (2019). "Training of Deep Bidirectional RNNs for Hand Motion Filtering via Multimodal Data Fusion." Web.
1. Soroosh Shahtalebi, S. Farokh Atashzar, Rajni V. Patel, Arash Mohammadi. Training of Deep Bidirectional RNNs for Hand Motion Filtering via Multimodal Data Fusion [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4935

Kernel Node Embeddings


Learning representations of nodes in a low dimensional space is a crucial task with many interesting applications in network analysis, including link prediction and node classification. Two popular approaches for this problem include matrix factorization and random walk-based models. In this paper, we aim to bring together the best of both worlds, towards learning latent node representations. In particular, we propose a weighted matrix factorization model which encodes random walk-based information about the nodes of the graph.

Paper Details

Authors:
Abdulkadir Celikkanat, Fragkiskos D. Malliaros
Submitted On:
8 November 2019 - 4:58pm
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[1] Abdulkadir Celikkanat, Fragkiskos D. Malliaros, "Kernel Node Embeddings", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4934. Accessed: Nov. 11, 2019.
@article{4934-19,
url = {http://sigport.org/4934},
author = {Abdulkadir Celikkanat; Fragkiskos D. Malliaros },
publisher = {IEEE SigPort},
title = {Kernel Node Embeddings},
year = {2019} }
TY - EJOUR
T1 - Kernel Node Embeddings
AU - Abdulkadir Celikkanat; Fragkiskos D. Malliaros
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4934
ER -
Abdulkadir Celikkanat, Fragkiskos D. Malliaros. (2019). Kernel Node Embeddings. IEEE SigPort. http://sigport.org/4934
Abdulkadir Celikkanat, Fragkiskos D. Malliaros, 2019. Kernel Node Embeddings. Available at: http://sigport.org/4934.
Abdulkadir Celikkanat, Fragkiskos D. Malliaros. (2019). "Kernel Node Embeddings." Web.
1. Abdulkadir Celikkanat, Fragkiskos D. Malliaros. Kernel Node Embeddings [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4934

Image Alpha Matting via Residual Convolutional Grid Network


Alpha matting is an important topic in areas of computer vision. It has various applications, such as virtual reality, digital image and video editing, and image synthesis. Conventional approaches for alpha matting do not perform well when they encounter complicated background or when foreground and background color distributions overlap. It is also difficult to extract alpha matte accurately when the foreground objects are semi-transparent or hairy.

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Authors:
Yang Zhou, Lei Chen, Jiying Zhao
Submitted On:
8 November 2019 - 1:26pm
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Image Alpha Matting via Residual Convolutional Grid Network_Poster.pdf

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[1] Yang Zhou, Lei Chen, Jiying Zhao, "Image Alpha Matting via Residual Convolutional Grid Network", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4933. Accessed: Nov. 11, 2019.
@article{4933-19,
url = {http://sigport.org/4933},
author = {Yang Zhou; Lei Chen; Jiying Zhao },
publisher = {IEEE SigPort},
title = {Image Alpha Matting via Residual Convolutional Grid Network},
year = {2019} }
TY - EJOUR
T1 - Image Alpha Matting via Residual Convolutional Grid Network
AU - Yang Zhou; Lei Chen; Jiying Zhao
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4933
ER -
Yang Zhou, Lei Chen, Jiying Zhao. (2019). Image Alpha Matting via Residual Convolutional Grid Network. IEEE SigPort. http://sigport.org/4933
Yang Zhou, Lei Chen, Jiying Zhao, 2019. Image Alpha Matting via Residual Convolutional Grid Network. Available at: http://sigport.org/4933.
Yang Zhou, Lei Chen, Jiying Zhao. (2019). "Image Alpha Matting via Residual Convolutional Grid Network." Web.
1. Yang Zhou, Lei Chen, Jiying Zhao. Image Alpha Matting via Residual Convolutional Grid Network [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4933

Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications

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Authors:
Ryuhei Takahashi, Koji Ishibashi
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8 November 2019 - 11:47am
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[1] Ryuhei Takahashi, Koji Ishibashi, "Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4932. Accessed: Nov. 11, 2019.
@article{4932-19,
url = {http://sigport.org/4932},
author = {Ryuhei Takahashi; Koji Ishibashi },
publisher = {IEEE SigPort},
title = {Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications},
year = {2019} }
TY - EJOUR
T1 - Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications
AU - Ryuhei Takahashi; Koji Ishibashi
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4932
ER -
Ryuhei Takahashi, Koji Ishibashi. (2019). Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications. IEEE SigPort. http://sigport.org/4932
Ryuhei Takahashi, Koji Ishibashi, 2019. Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications. Available at: http://sigport.org/4932.
Ryuhei Takahashi, Koji Ishibashi. (2019). "Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications." Web.
1. Ryuhei Takahashi, Koji Ishibashi. Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4932

Estimating Correlation Coefficients for Quantum Radar and Noise Radar

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Authors:
David Luong, Sreeraman Rajan, Bhashyam Balaji
Submitted On:
8 November 2019 - 11:03am
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GlobalSIP 2019 Presentation: Estimating Correlation Coefficients for Quantum Radar and Noise Radar

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[1] David Luong, Sreeraman Rajan, Bhashyam Balaji, "Estimating Correlation Coefficients for Quantum Radar and Noise Radar", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4931. Accessed: Nov. 11, 2019.
@article{4931-19,
url = {http://sigport.org/4931},
author = {David Luong; Sreeraman Rajan; Bhashyam Balaji },
publisher = {IEEE SigPort},
title = {Estimating Correlation Coefficients for Quantum Radar and Noise Radar},
year = {2019} }
TY - EJOUR
T1 - Estimating Correlation Coefficients for Quantum Radar and Noise Radar
AU - David Luong; Sreeraman Rajan; Bhashyam Balaji
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4931
ER -
David Luong, Sreeraman Rajan, Bhashyam Balaji. (2019). Estimating Correlation Coefficients for Quantum Radar and Noise Radar. IEEE SigPort. http://sigport.org/4931
David Luong, Sreeraman Rajan, Bhashyam Balaji, 2019. Estimating Correlation Coefficients for Quantum Radar and Noise Radar. Available at: http://sigport.org/4931.
David Luong, Sreeraman Rajan, Bhashyam Balaji. (2019). "Estimating Correlation Coefficients for Quantum Radar and Noise Radar." Web.
1. David Luong, Sreeraman Rajan, Bhashyam Balaji. Estimating Correlation Coefficients for Quantum Radar and Noise Radar [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4931

Compressive Super-Pixel LiDAR for High-Framerate 3D Depth Imaging


We propose a new sampling and reconstruction framework for full frame depth imaging using synchronised, programmable laser diode and photon detector arrays. By adopting a measurement scheme that probes the environment with sparse, pseudo-random patterns, our method enables eyesafe LiDAR operation, while guaranteeing fast reconstruction of

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Authors:
Brian Stewart, Joao F.C. Mota, Andrew M. Wallace
Submitted On:
8 November 2019 - 6:40am
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SuperPixel LiDAR GlobalSIP19 print.pdf

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[1] Brian Stewart, Joao F.C. Mota, Andrew M. Wallace, "Compressive Super-Pixel LiDAR for High-Framerate 3D Depth Imaging", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4930. Accessed: Nov. 11, 2019.
@article{4930-19,
url = {http://sigport.org/4930},
author = {Brian Stewart; Joao F.C. Mota; Andrew M. Wallace },
publisher = {IEEE SigPort},
title = {Compressive Super-Pixel LiDAR for High-Framerate 3D Depth Imaging},
year = {2019} }
TY - EJOUR
T1 - Compressive Super-Pixel LiDAR for High-Framerate 3D Depth Imaging
AU - Brian Stewart; Joao F.C. Mota; Andrew M. Wallace
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4930
ER -
Brian Stewart, Joao F.C. Mota, Andrew M. Wallace. (2019). Compressive Super-Pixel LiDAR for High-Framerate 3D Depth Imaging. IEEE SigPort. http://sigport.org/4930
Brian Stewart, Joao F.C. Mota, Andrew M. Wallace, 2019. Compressive Super-Pixel LiDAR for High-Framerate 3D Depth Imaging. Available at: http://sigport.org/4930.
Brian Stewart, Joao F.C. Mota, Andrew M. Wallace. (2019). "Compressive Super-Pixel LiDAR for High-Framerate 3D Depth Imaging." Web.
1. Brian Stewart, Joao F.C. Mota, Andrew M. Wallace. Compressive Super-Pixel LiDAR for High-Framerate 3D Depth Imaging [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4930

Integrated Power and D2D Communications Simulator for Future Power Systems

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Authors:
Kevin Shimotakahara, Medhat Elsayed, Melike Erol-Kantarci, Karin Hinzer
Submitted On:
7 November 2019 - 9:37pm
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GlobalSIP2019 Main.pdf

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[1] Kevin Shimotakahara, Medhat Elsayed, Melike Erol-Kantarci, Karin Hinzer, "Integrated Power and D2D Communications Simulator for Future Power Systems", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4929. Accessed: Nov. 11, 2019.
@article{4929-19,
url = {http://sigport.org/4929},
author = {Kevin Shimotakahara; Medhat Elsayed; Melike Erol-Kantarci; Karin Hinzer },
publisher = {IEEE SigPort},
title = {Integrated Power and D2D Communications Simulator for Future Power Systems},
year = {2019} }
TY - EJOUR
T1 - Integrated Power and D2D Communications Simulator for Future Power Systems
AU - Kevin Shimotakahara; Medhat Elsayed; Melike Erol-Kantarci; Karin Hinzer
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4929
ER -
Kevin Shimotakahara, Medhat Elsayed, Melike Erol-Kantarci, Karin Hinzer. (2019). Integrated Power and D2D Communications Simulator for Future Power Systems. IEEE SigPort. http://sigport.org/4929
Kevin Shimotakahara, Medhat Elsayed, Melike Erol-Kantarci, Karin Hinzer, 2019. Integrated Power and D2D Communications Simulator for Future Power Systems. Available at: http://sigport.org/4929.
Kevin Shimotakahara, Medhat Elsayed, Melike Erol-Kantarci, Karin Hinzer. (2019). "Integrated Power and D2D Communications Simulator for Future Power Systems." Web.
1. Kevin Shimotakahara, Medhat Elsayed, Melike Erol-Kantarci, Karin Hinzer. Integrated Power and D2D Communications Simulator for Future Power Systems [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4929

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