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Read overviews of these IEEE Access articles below and access the full article for free on IEEE Xplore.

Network Representation Learning: From Traditional Feature Learning to Deep Learning

April 23, 2021

Network representation learning (NRL) is an effective graph analytics technique and promotes users to deeply understand the hidden characteristics of graph data. It has been successfully applied in many real-world tasks related to network science, such as social network data processing, biological information processing, and recommender systems. Deep Learning is a powerful tool to learn data features. However, it is non-trivial to generalize deep learning to graph-structured data since it is different from the regular data such as pictures having spatial information and sounds having temporal information. Read more

A Simple and Adjustable Technique for Effective Linearization of Power Amplifiers Using Harmonic Injection

April 19, 2021

A simple and effective method for linearization of power amplifiers (PAs) is proposed. The method is based on the second harmonic injection into the input of the PA. The second harmonic is generated in a feedback path by taking the low-power transistors of a pseudo-differential pair amplifier to their nonlinear regime. The amplitude and phase of the second harmonics are controlled by tunable matching networks of the pseudo-differential pair which include trimmer capacitors. Read more

Sensing Methodologies in Agriculture for Soil Moisture and Nutrient Monitoring

April 9, 2021

Development and deployment of sensing technologies is one of the main steps in achieving sustainability in crop production through precision agriculture. Key sensing methodologies developed for monitoring soil moisture and nutrients with recent advances in the sensing devices reported in literature using those techniques are overviewed in this article. The soil moisture determination has been divided into four main sections describing soil moisture measurement metrics and laboratory-based testing, followed by in-situ, remote and proximal sensing techniques. Read more

Agent Architecture for Adaptive Behaviors in Autonomous Driving

April 8, 2021

Evolution has endowed animals with outstanding adaptive behaviours which are grounded in the organization of their sensorimotor system. This paper uses inspiration from these principles of organization in the design of an artificial agent for autonomous driving. After distilling the relevant principles from biology, their functional role in the implementation of an artificial system are explained. The resulting Agent, developed in an EU H2020 Research and Innovation Action, is used to concretely demonstrate the emergence of adaptive behaviour with a significant level of autonomy. Read more

In-Bore Dynamic Measurement and Mechanism Analysis of Multi-Physics Environment for Electromagnetic Railguns

March 31, 2021

Electromagnetic launch technology has important applications in many fields. However, the extremely harsh multi-physics environment during the launch is quite different from that of conventional guns. Little experimental research studied the dynamic distribution of the extreme impact environment and magnetic fields in the projectile. To this end, this paper designs a projectile-borne storage testing system for the dynamic measurement of harsh multi-physics environments. The detailed assessment of the measured dynamic multi-physics field shows that the velocity skin effect (VSE) is an important factor affecting the dynamic results. Read more

Collision Avoidance in Pedestrian-Rich Environments With Deep Reinforcement Learning

March 30, 2021

Collision avoidance algorithms are essential for safe and efficient robot operation among pedestrians. This work proposes using deep reinforcement (RL) learning as a framework to model the complex interactions and cooperation with nearby, decision-making agents, such as pedestrians and other robots. Existing RL-based works assume homogeneity of agent properties, use specific motion models over short timescales, or lack a principled method to handle a large, possibly varying number of agents. Therefore, this work develops an algorithm that learns collision avoidance among a variety of heterogeneous, Read more

A Simple Sum of Products Formula to Compute the Reliability of the KooN System

March 16, 2021

Reliability block diagram (RBD) is a well-known, high-level abstract modeling method for calculating systems reliability. Increasing redundancy is the most important way for increasing Fault-tolerance and reliability of dependable systems. K-out-of-N (KooN) is one of the known redundancy models. The redundancy causes repeated events and increases the complexity of the computing system’s reliability, and researchers use techniques like factorization to overcome it. Current methods lead to the cumbersome formula that needs a lot of simplification to change in the form of Sum of the Products (SoP) in terms of reliabilities of its constituting components. Read more

Design and Fabrication of Magnetic System Using Multi-Material Topology Optimization

March 9, 2021

This paper presents the design and fabrication schemes of a magnetic system consisting of segmented permanent magnet (PM) blocks, back-iron and frame structures. Here, a frame structure aims to bind PM blocks and iron structure. Non-intuitive design of segmented PMs and back-iron are obtained using multi-material topology optimization formulation. Subsequently, a non-magnetic frame structure is designed through a post-processing procedure, which is proposed using the smoothed fields of optimized PM and back-iron densities. Read more

Highly Sensitive Reflective-Mode Phase-Variation Permittivity Sensor Based on a Coplanar Waveguide Terminated With an Open Complementary Split Ring Resonator (OCSRR)

March 3, 2021

This paper presents a one-port reflective-mode phase-variation microwave sensor consisting of a coplanar waveguide (CPW) transmission line terminated with a grounded open complementary split ring resonator (OCSRR). The sensor is useful for measuring the dielectric constant of the so-called material under test (MUT), which should be placed in contact with the OCSRR, the sensitive element. The output variable is the phase of the reflection coefficient. Design guidelines for the implementation of highly sensitive sensors are derived in the paper, Read more

Improving Predictability of User-Affecting Metrics to Support Anomaly Detection in Cloud Services

February 22, 2021

Anomaly detection systems aim to detect and report attacks or unexpected behavior in networked systems. Previous work has shown that anomalies have an impact on system performance, and that performance signatures can be effectively used for implementing an IDS. In this paper, we present an analytical and an experimental study on the trade-off between anomaly detection based on performance signatures and system scalability. The proposed approach combines analytical modeling and load testing to find optimal configurations for the signature-based IDS. Read more

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