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

An Optimal Home Energy Management Paradigm With an Adaptive Neuro-Fuzzy Regulation

June 11, 2020


In the smart grid paradigm, residential consumers should participate actively in the energy exchange mechanisms by adjusting their consumption and generation. To this end, a proper home energy management system (HEMS), in addition to achieving a high level of comfort for the consumers, should handle the practical difficulties due to the uncertainty and technical limits. With this aim, in this paper, a new HEMS is proposed to carry out day-ahead management and real-time regulation. Read more

Multi-Level Time-Sensitive Networking (TSN) Using the Data Distribution Services (DDS) for Synchronized Three-Phase Measurement Data Transfer

May 29, 2020


This paper presents the design and implementation of a Multi-level Time Sensitive Networking (TSN) protocol based on a real-time communication platform utilizing Data Distribution Service (DDS) middleware for data transfer of synchronous three phase measurement data. To transfer ultra-high three phase measurement samples, the DDS open-source protocol is exploited to shape the network’s data traffic according to specific Quality of Service (QoS) profiles, leading to low packet loss and low latency by synchronizing and prioritizing the data in the network. Read more

Smartphone and Smartwatch-Based Biometrics Using Activities of Daily Living

May 18, 2020


Smartphones and smartwatches, which include powerful sensors, provide a readily available platform for implementing and deploying mobile motion-based behavioral biometrics. However, the few studies that utilize these commercial devices for motion-based biometrics are quite limited in terms of the sensors and physical activities that they evaluate. In many such studies, only the smartwatch accelerometer is utilized and only one physical activity, walking, is investigated. In this study we consider the accelerometer and gyroscope sensor on both the smartphone and smartwatch, Read more

Text Detection and Recognition for Images of Medical Laboratory Reports With a Deep Learning Approach

May 6, 2020


The adoption of electronic health records (EHRs) is an important step in the development of modern medicine. However, complete health records are not often available during treatment because of the functional problem of the EHR system or information barriers. This paper presents a deep-learning-based approach for textual information extraction from images of medical laboratory reports, which may help physicians solve the data-sharing problem. The approach consists of two modules: text detection and recognition. Read more

Smart Power Control for Quality-Driven Multi-User Video Transmissions: A Deep Reinforcement Learning Approach

April 21, 2020


Device-to-device (D2D) communications have been regarded as a promising technology to meet the dramatically increasing video data demand in the 5G network. In this paper, we consider the power control problem in a multi-user video transmission system. Due to the non-convex nature of the optimization problem, it is challenging to obtain an optimal strategy. In addition, many existing solutions require instantaneous channel state information (CSI) for each link, which is hard to obtain in resource-limited wireless networks. Read more

Deep Learning Applications in Medical Image Analysis

April 9, 2020


The tremendous success of machine learning algorithms at image recognition tasks in recent years intersects with a time of dramatically increased use of electronic medical records and diagnostic imaging. This review introduces the machine learning algorithms as applied to medical image analysis, focusing on convolutional neural networks, and emphasizing clinical aspects of the field. The advantage of machine learning in an era of medical big data is that significant hierarchal relationships within the data can be discovered algorithmically without laborious hand-crafting of features. Read more

Blockchains and Smart Contracts for the Internet of Things

March 20, 2020


Motivated by the recent explosion of interest around blockchains, we examine whether they make a good fit for the Internet of Things (IoT) sector. Blockchains allow us to have a distributed peer-to-peer network where non-trusting members can interact with each other without a trusted intermediary, in a verifiable manner. We review how this mechanism works and also look into smart contracts-scripts that reside on the blockchain that allow for the automation of multi-step processes. Read more

Reinforcement Learning Based MAC Protocol (UW-ALOHA-Q) for Underwater Acoustic Sensor Networks

February 28, 2020


The demand for regular monitoring of the marine environment and ocean exploration is rapidly increasing, yet the limited bandwidth and slow propagation speed of acoustic signals leads to low data throughput for underwater networks used for such purposes. This study describes a novel approach to medium access control that engenders efficient use of an acoustic channel. ALOHA-Q is a medium access protocol designed for terrestrial radio sensor networks and reinforcement learning is incorporated into the protocol to provide efficient channel access. Read more

A Study on the Elimination of Thermal Reflections

January 31, 2020


Recently, thermal cameras have been used in various surveillance and monitoring systems. In particular, in camera-based surveillance systems, algorithms are being developed for detecting and recognizing objects from images acquired in dark environments. However, it is difficult to detect and recognize an object due to the thermal reflections generated in the image obtained from a thermal camera. For example, thermal reflection often occurs on a structure or the floor near an object, Read more

Direct Control Strategy of Real-Time Tracking Power Generation Plan for Wind Power and Battery Energy Storage Combined System

January 9, 2020


To improve the overall economy of the wind-energy storage power station, a direct control strategy is proposed to track the deviation of the wind power plan. Compared with the traditional strategy of wind power fluctuation mitigation, the control strategy in this paper can change the charge and discharge power of energy storage in real-time according to the deviation of wind power and the state of charge (SOC). When the power of wind power changes suddenly, Read more

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