Deep Reinforcement Learning for Orchestrating Cost-Aware Reconfigurations of vRANs

Virtualized Radio Access Networks (vRANs) are fully configurable and can be implemented at a low cost over commodity platforms to enable network management flexibility. In this paper, a novel vRAN reconfiguration problem is formulated to jointly reconfigure the functional splits of the base stations (BSs), locations of the virtualized central...

A Fixed-Wing UAV Formation Algorithm Based on Vector Field Guidance

The vector field method was originally proposed to guide a single fixed-wing Unmanned Aerial Vehicle (UAV) towards a desired path. In this work, a non-uniform vector field method is proposed that changes in both magnitude and direction, for the purpose of achieving formations of UAVs. As compared to related work in the literature, the...

Reinforcement Learning for Intelligent Healthcare Systems: A Review of Challenges, Applications, and Open Research Issues

The rise of chronic disease patients and the pandemic pose immediate threats to healthcare expenditure and mortality rates. This calls for transforming healthcare systems away from one-on-one patient treatment into intelligent health systems, leveraging the recent advances of Internet of Things and smart sensors. Meanwhile, reinforcement...

Efficiency of Double-barrier Magnetic Tunnel Junction-based Digital eNVM Array for Neuro-Inspired Computing

This brief deals with the impact of spin-transfer torque magnetic random access memory (STT-MRAM) cell based on double-barrier magnetic tunnel junction (DMTJ) on the performance of a two-layer multilayer perceptron (MLP) neural network. The DMTJ-based cell is benchmarked against the conventional single-barrier MTJ (SMTJ) counterpart by means...

Employing Deep Ensemble Learning for Improving the Security of Computer Networks against Adversarial Attacks

In the past few years, Convolutional Neural Networks (CNN) have demonstrated promising performance in various real-world cybersecurity applications, such as network and multimedia security. However, the underlying fragility of CNN structures poses major security problems, making them inappropriate for use in security-oriented applications,...

Data Compression Versus Signal Fidelity Tradeoff in Wired-OR Analog-to-Digital Compressive Arrays for Neural Recording

Future high-density and high channel count neural interfaces that enable simultaneous recording of tens of thousands of neurons will provide a gateway to study, restore and augment neural functions. However, building such technology within the bit-rate limit and power budget of a fully implantable device is challenging. The wired-OR...

SCA Strikes Back: Reverse Engineering Neural Network Architectures using Side Channels

This paper was selected for Top Picks in Hardware and Embedded Security 2020 and it presents a physical side-channel attack aiming at reverse engineering neural networks implemented on an edge device. The attack does not need access to training data and allows for neural network recovery by feeding known random inputs. We successfully reverse...

A Wideband IQ-Mapping Direct-Digital RF Modulator for 5G Transmitters

This article presents a wideband 2× 12 -bit direct-digital RF modulator (DDRM) operating in a 0.5-to-3-GHz band for 5G transmitters. The proposed digital Cartesian modulator features an advanced IQ-mapping technique to boost RF power by 3 dB and suppress the I/Q image. To verify the proposed concept, a 40-nm CMOS prototype is implemented...

Interactive Learning of Temporal Features for Control: Shaping Policies and State Representations From Human Feedback

Current ongoing industry revolution demands more flexible products, including robots in household environments and medium-scale factories. Such robots should be able to adapt to new conditions and environments and be programmed with ease. As an example, let us suppose that there are robot manipulators working on an industrial production line and...

Automatic Defect Detection of Fasteners on the Catenary Support Device Using Deep Convolutional Neural Network

The excitation and vibration triggered by the long-term operation of railway vehicles inevitably result in defective states of catenary support devices. With the massive construction of high-speed electrified railways, automatic defect detection of diverse and plentiful fasteners on the catenary support device is of great significance for...

Memory and Communication Profiling for Accelerator-Based Platforms

The growing demand of processing power is being satisfied mainly by an increase in the number of homogeneous and heterogeneous computing cores in a system. Efficient utilization of these architectures demands analysis of memory-access behaviour of applications and perform data-communication aware mapping of applications on these architectures....