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Modeling Dynamic Spatio-Temporal Correlations for Urban Traffic Flows Prediction IEEE Access (IF 3.745) Pub Date : 2021-02-03 Nabeela Awan; Ahmad Ali; Fazlullah Khan; Muhammad Zakarya; Ryan Alturki; Mahwish Kundi; Mohammad Dahman Alshehri; Muhammad Haleem
Prediction of traffic crowd movement is one of the most important component in many applications ’ domains ranging from urban management to transportation schedule. The key challenge of citywide crowd flows prediction is how to model spatial and dynamic temporal correlation. However, in recent years several studies have been done, but they lack the ability to effectively and simultaneously model spatial
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On Short-Term Load Forecasting Using Machine Learning Techniques and a Novel Parallel Deep LSTM-CNN Approach IEEE Access (IF 3.745) Pub Date : 2021-02-18 Behnam Farsi; Manar Amayri; Nizar Bouguila; Ursula Eicker
Since electricity plays a crucial role in countries’ industrial infrastructures, power companies are trying to monitor and control infrastructures to improve energy management and scheduling. Accurate forecasting is a critical task for a stable and efficient energy supply, where load and supply are matched. This article discusses various algorithms and a new hybrid deep learning model which combines
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The Method of Dance Movement Segmentation and Labanotation Generation Based on Rhythm IEEE Access (IF 3.745) Pub Date : 2021-02-18 Changrui Cui; Junhuai Li; Dandan Du; Huaijun Wang; Pengjia Tu; Ting Cao
Labanotation is a widely used dance recording system, which plays an important role in inheriting and protecting folk dances. However, manual drawing of dance notation is time-consuming and labor-intensive. Therefore, research on the automatic generation of Labanotation has received extensive attention. In this article, a method to automatically generate Labanotation based on motion capture data is
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A Finite-Time Fault-Tolerant Control Using Non-Singular Fast Terminal Sliding Mode Control and Third-Order Sliding Mode Observer for Robotic Manipulators IEEE Access (IF 3.745) Pub Date : 2021-02-16 Van-Cuong Nguyen; Anh-Tuan Vo; Hee-Jun Kang
In this paper, a fault-tolerant control (FTC) method for robotic manipulators is proposed to deal with the lumped uncertainties and faults in case of lacking tachometer sensors in the system. First, the third-order sliding mode (TOSM) observer is performed to approximate system velocities and the lumped uncertainties and faults. This observer provides estimation information with high precision, low
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Dynamic Data Integration for Resilience to Sensor Attacks in Multi-Agent Systems IEEE Access (IF 3.745) Pub Date : 2021-02-16 Luis Burbano; Luis Francisco Cómbita; Nicanor Quijano; Sandra Rueda
In recent years the number of security incidents affecting control systems has increased. These incidents have shown the need to develop strategies to improve system resilience to cyber-attacks. This paper presents a practical implementation of a strategy to detect cyber-attacks and mitigate their effects on sensors of a multi-agent system. The proposed approach computes, in real-time, a convex combination
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Fault Location of VSC Based DC Distribution Network Based on Traveling Wave Differential Current With Hausdorff Distance and Cubic Spline Interpolation IEEE Access (IF 3.745) Pub Date : 2021-02-16 Yanfang Wei; Pengyu Sun; Zhuoliang Song; Peng Wang; Zhihui Zeng; Xiaowei Wang
Compared with AC power system, DC distribution network is a low-damping system without natural zero crossing. The DC fault current will reach its peak value within a few milliseconds, posing a great threat to power electronic devices. Therefore, the rapid and high-precision identification of DC line faults is one of the technical difficulties faced by the VSC based DC distribution network. In this
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Quantum Half and Full Spinning Operator-Based Nonlinear Confusion Component IEEE Access (IF 3.745) Pub Date : 2021-02-19 Abdullah Alghafis
The structure of a substitution box (S-box) is one of the principal ideas of the modern encryption techniques. The security of a modern encryption algorithm highly depends on its nonlinear confusion component. This component adds confusion in any encryption mechanism which is one of the most important ingredients. The proposed mechanism is based on the quantum rotation and spinning operator along with
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Higher-Order Graph Convolutional Networks With Multi-Scale Neighborhood Pooling for Semi-Supervised Node Classification IEEE Access (IF 3.745) Pub Date : 2021-02-18 Xun Liu; Guoqing Xia; Fangyuan Lei; Yikuan Zhang; Shihui Chang
Existing popular methods for semi-supervised node classification with high-order convolution improve the learning ability of graph convolutional networks (GCNs) by capturing the feature information from high-order neighborhoods. However, these methods with high-order convolution usually require many parameters and high computational complexity. To address these limitations, we propose HCNP, a new higher-order
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A Novel Thévenin Equivalent Model Considering the Correlation of Source-Grid-Load in Power Systems IEEE Access (IF 3.745) Pub Date : 2021-02-19 Pingfeng Ye; Xueshan Han; Ming Yang; Yumin Zhang; Younan Pei; Xuan Zhang
The coupled single-port circuit has been proposed for online voltage stability assessment based on wide-area measurements and grid equations. This circuit can explicitly reflect the influence of grid and load on voltage stability. However, it does not consider the impact of power generation. A novel Thévenin equivalent (TE) circuit considering the influence of source-grid-load on voltage stability
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Closed-Form Representations of Friction IEEE Access (IF 3.745) Pub Date : 2021-02-04 Jin Huang; Xingyu Li; Huiqian Li; Ye-Hwa Chen; Zhihua Zhong
The current developed friction models are basically based on the assumption of the normal forces exerted between the contact surfaces known in advance, less work has been done for closed-form (i.e., analytic) modeling in complex mechanical systems where the normal forces vary greatly over time. In this paper, the closed-form representations of friction forces in mechanical systems are newly derived
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Harmonic Characteristics Data-Driven THD Prediction Method for LEDs Using MEA-GRNN and Improved-AdaBoost Algorithm IEEE Access (IF 3.745) Pub Date : 2021-02-15 Jingjian Yang; Hongyan Ma; Jiaming Dou; Rong Guo
Light-emitting Diode (LED) lamps have been widely used due to versatility and energy efficiency. However, LEDs are nonlinear loads, the massive usage will inject harmonics into the lighting system, which has influenced the power quality. Total Harmonic Distortion (THD) is an important parameter to evaluate the power quality, but the prediction of THD for LEDs is a challenging task. This paper addresses
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A Comprehensive Review of Authentication Schemes in Vehicular Ad-Hoc Network IEEE Access (IF 3.745) Pub Date : 2021-02-18 Farooque Azam; Sunil Kumar Yadav; Neeraj Priyadarshi; Sanjeevikumar Padmanaban; R. C. Bansal
Vehicular ad-hoc network (VANET) has been gaining importance due to the fast growing technology as well as its requirements in intelligent transportation systems (ITS) and vehicular social network (VSN). VANET facilitates vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication and improves the ride quality with value added services. The number of connected vehicles is expected to
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Knowledge Graph Completeness: A Systematic Literature Review IEEE Access (IF 3.745) Pub Date : 2021-02-02 Subhi Issa; Onaopepo Adekunle; Fayçal Hamdi; Samira Si-Said Cherfi; Michel Dumontier; Amrapali Zaveri
The quality of a Knowledge Graph (also known as Linked Data) is an important aspect to indicate its fitness for use in an application. Several quality dimensions are identified, such as accuracy, completeness, timeliness, provenance, and accessibility, which are used to assess the quality. While many prior studies offer a landscape view of data quality dimensions, here we focus on presenting a systematic
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A Multi-Donor Ex Vivo Platelet Activation and Growth Factor Release Study Using Electric Pulses With Durations Up to 100 Microseconds IEEE Access (IF 3.745) Pub Date : 2021-02-19 Bogdan Neculaes; Allen L. Garner; Steve Klopman; Christine A. Morton; Andrew S. Torres
In vitro platelet activation is established in various clinical settings for wound healing and tissue regeneration. After separating platelet rich plasma (PRP) from whole blood, a biochemical activator, typically bovine thrombin (BT), is applied to activate PRP, which clots the PRP and releases growth factors beneficial for wound healing. BT’s drawbacks, particularly cost, availability, workflow challenges
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A Comprehensive Fuzzy Ontology-Based Decision Support System for Alzheimer’s Disease Diagnosis IEEE Access (IF 3.745) Pub Date : 2020-12-31 Nora Shoaip; Amira Rezk; Shaker El-Sappagh; Louai Alarabi; Sherif Barakat; Mohammed M. Elmogy
The World Health Organization (WHO) indicates that the proportion of the elderly will soon include nearly a quarter of the world population. Ensuring that health systems are prepared to deal with this phenomenal rate of aging and associated diseases generates many challenges. Among these challenges is facing Alzheimer’s Disease (AD) that may occur at some point in the elderly life and may harm societies
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A Novel Tracking Control Algorithm With Finite-Time Disturbance Observer for a Class of Second-Order Nonlinear Systems and its Applications IEEE Access (IF 3.745) Pub Date : 2021-02-19 Anh Tuan Vo; Thanh Nguyen Truong; Hee-Jun Kang
This study aims to build a novel tracking control algorithm using a finite-time disturbance observer which obtains fast convergence within a predetermined amount of time and strong stability for a class of second-order nonlinear systems. Firstly, a nonlinear sliding mode manifold with fast finite-time convergence is introduced. Then, according to the designed manifold for the guarantee of finite-time
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Intra Block Copy Mirror Mode for Screen Content Coding in Versatile Video Coding IEEE Access (IF 3.745) Pub Date : 2021-02-19 Jian Cao; Fan Liang; Jun Wang
Intra Block Copy (IBC) cannot work well for blocks with symmetry or mirror characteristic, because it is based on the translational block matching technique. In order to solve this problem, in this paper, an adequately designed IBC-Mirror mode is proposed for Versatile Video Coding (VVC), which extends our previous work. The newly proposed IBC-Mirror mode consists of two sub-modes, including IBC-Mirror
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An Accurate Time-Based MPPT Circuit With Two-Period Tracking Algorithm and Convergence Range Averaging Technique for IoT Applications IEEE Access (IF 3.745) Pub Date : 2021-02-18 Van-Thai Dang; Myeong-Gyu Yang; Yong Shim; Woojoo Lee; Kwang-Hyun Baek
This article proposes a highly efficient Time-Based Maximum-Power-Point-Tracking (TB-MPPT) integrated-circuit. Conventional TB-MPPT circuit shows unstable status (oscillation) near the Maximum Power Point (MPP), which causes the degradation of the overall power tracking efficiency. To overcome this critical issue, the proposed circuit separates the tracking operation into two periods, and it utilizes
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Designing Transactive Market for Combined Heat and Power Management in Energy Hubs IEEE Access (IF 3.745) Pub Date : 2021-02-16 Manijeh Alipour; Mehdi Abapour; Sajjad Tohidi; Saeid Gholami Farkoush; Sang-Bong Rhee
This paper introduces a transactive market design for a combined heat and power (CHP) based energy hub (hub). The proposed model allows a hub operator to supply the hub’s demands by participating in the day-ahead market and a transactive market with CHPs and also in the real-time market by using a recursive moving window algorithm. The proposed local energy market for a hub operator and CHPs is based
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An Edge Assisted Secure Lightweight Authentication Technique for Safe Communication on the Internet of Drones Network IEEE Access (IF 3.745) Pub Date : 2021-02-19 Muktar Yahuza; Mohd Yamani Idna Idris; Ainuddin Wahid Abdul Wahab; Tarak Nandy; Ismail Bin Ahmedy; Roziana Ramli
Security and privacy are among the most critical challenges on the internet of drones (IoD) network. The communication entities of the IoD network can communicate securely with the use of authenticated key agreement (AKA) based techniques. However, the design of such techniques must balance the tradeoff between security and lightweight features. Recently, Chen et al. proposed an authentication and
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A Simple Framework for Identifying Dynamical Systems in Closed-Loop IEEE Access (IF 3.745) Pub Date : 2021-02-18 Ichiro Maruta; Toshiharu Sugie
In this paper, we propose a simple framework for closed-loop system identification: the stabilized output error method. Traditional closed-loop system identification methods rely on the linearity of the target system, and they require the identification of noise models or prior knowledge or identifiability of the feedback controllers to obtain unbiased estimates. But in many real-world applications
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Extended Dissipativity and Non-Fragile Synchronization for Recurrent Neural Networks With Multiple Time-Varying Delays via Sampled-Data Control IEEE Access (IF 3.745) Pub Date : 2021-02-18 R. Anbuvithya; S. Dheepika Sri; R. Vadivel; Nallappan Gunasekaran; Porpattama Hammachukiattikul
This paper deals with the extended dissipativity and non-fragile synchronization of delayed recurrent neural networks (RNNs) with multiple time-varying delays and sampled-data control. A suitable Lyapunov-Krasovskii Functional (LKF) is built up to prove the quadratically stable and extended dissipativity condition of delayed RNNs using Jensen inequality and limited Bessel-Legendre inequality approaches
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A Whittle Index Approach to Minimizing Age of Multi-Packet Information in IoT Network IEEE Access (IF 3.745) Pub Date : 2021-02-16 Mianlong Chen; Kui Wu; Linqi Song
Age of information (AoI) captures the freshness of information and has been used broadly as an important performance metric in big data analytics in the Internet of Things (IoT). We consider a general scenario where a meaningful piece of information consists of multiple packets and the information is not complete until all related packets have been correctly received. Minimizing AoI in this general
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A Student Attendance Management Method Based on Crowdsensing in Classroom Environment IEEE Access (IF 3.745) Pub Date : 2021-02-18 Zhigang Gao; Yucai Huang; Leilei Zheng; Xiaodong Li; Huijuan Lu; Jianhui Zhang; Qingling Zhao; Wenjie Diao; Qiming Fang; Jinglong Fang
In smart cities, intelligent learning environment is an important application scenario, and class attendance checking is an important measure to urge students to attend on time and ensure the quality of learning. Aiming at the existing problems in class attendance checking, such as low efficiency and easy to cheat, this paper proposes a student attendance management method named AMMoC (Attendance Management
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Multilayer Mapping Kit for Autonomous UAV Navigation IEEE Access (IF 3.745) Pub Date : 2021-01-27 Shengyang Chen; Han Chen; Ching-Wei Chang; Chih-Yung Wen
Mapping, as the back-end of perception and the front-end of path planning in the modern UAV navigation system, draws our interest. Considering the requirements of UAV navigation and the features of the current embedded computation platforms, we designed and implemented a novel multilayer mapping framework. In this framework, we divided the map into three layers: awareness, local, and global. The awareness
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Multi-Information Hybrid Network Spreading Model Based on Competition Consciousness IEEE Access (IF 3.745) Pub Date : 2021-02-08 Yaxi Wang; Xuyang Wang; Nianxi Yue
In fact, information is not transmitted in a single message, but rather multiple messages are transmitted simultaneously and interact with each other as they are transmitted. Based on this phenomenon, a multi-information overlay network model that differs from the traditional network structure is first constructed on the basis of two classical network models, BA scale-free and WS Small World. When
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A 24 GHz Microwave Sensor With Built-in Calibration Capability Designed in MMIC Technology IEEE Access (IF 3.745) Pub Date : 2021-02-19 Robert Smolarz; Kamil Staszek; Krzysztof Wincza; Slawomir Gruszczynski
A microwave sensor realized in monolithic technology, intended for permittivity estimation with the use of a highly sensitive coupled-line section, is presented in this paper. It also contains a dedicated measurement circuitry realized as a five-port correlator, therefore, a simple scalar power measurement can be utilized to obtain vector signal corresponding to the measured material without the usage
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Machine Learning for Broad-Sensed Internet Congestion Control and Avoidance: A Comprehensive Survey IEEE Access (IF 3.745) Pub Date : 2021-02-18 Huifen Huang; Xiaomin Zhu; Jiedong Bi; Wenpeng Cao; Xinchang Zhang
It is challenging to deal with the Internet congestion problem because of several factors such as ever-growing traffic and distributed network architecture. The congestion problem can be solved or alleviated by various methods, including rate control, bandwidth-guarantee routing and bandwidth reservation. We use the term broad-sensed Internet congestion control and avoidance (BICC&A) to generally denote
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An Improved wNAF Scalar-Multiplication Algorithm With Low Computational Complexity by Using Prime Precomputation IEEE Access (IF 3.745) Pub Date : 2021-02-22 Huang Hai; Na Ning; Xing Lin; Liu Zhiwei; Yu Bin; Zhao Shilei
To reduce the computational complexity of scalar multiplication, an improved wNAF scalar-multiplication algorithm is proposed by using prime precomputation. It replaces odd number with prime number in the precomputation stage, and makes up the difference between prime and odd by building the tiny multi-base chains. Thanks to the proposed algorithm, the computational complexity, the cost of precomputation
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Efficiency Optimization of IPOP DC/DC System for HEV IEEE Access (IF 3.745) Pub Date : 2021-02-18 Fengwang Lu; Liangzong He; Qingyang Tan; Hongyan Zhou
Input parallel output parallel (IPOP) DC/DC system is widely utilized in many occasions like data center and hybrid electric vehicle (HEV). However, the efficiency characteristics of different converters usually differs from each other, and the conventional control strategy has difficult to realize efficient conversion of overall power of the system. To address this issue, Buck converter is taken as
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Biospeckle-Based Sensor for Characterization of Charcoal Rot (Macrophomina Phaseolina (Tassi) Goid) Disease in Soybean (Glycine Max (L.) Merr.) Crop IEEE Access (IF 3.745) Pub Date : 2021-02-16 Puneet Singh; Amit Chatterjee; Laxman Singh Rajput; Sanjeev Kumar; Vennampally Nataraj; Vimal Bhatia; Shashi Prakash
Charcoal rot is one of the most destructive fungal diseases of soybean, caused by the pathogen called Macrophomina phaseolina . This disease thrives in warm and dry conditions, affecting the yield of soybean and other important agronomic crops. Existing methods used to screen the disease suffer from several drawbacks including, manual rating, low accuracy, high operating time, and high system complexity
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Enhanced Thermal Conductivity and Mechanical Toughness of the Epoxy Resin by Incorporation of Mesogens Without Nanofillers IEEE Access (IF 3.745) Pub Date : 2021-02-10 Kaiyi Tian; Senyuan Yang; Jiaxuan Niu; Hanxiang Wang
Epoxy resin is widely used due to its electrical insulation performances, but low elongation defects at the break, low thermal conductivity, and high brittleness limit its application scenarios. In this paper, the mesogen is utilized to improve the thermal conductivity and mechanical toughness of the traditional epoxy resin. Both the mechanical performances, including the impact strength, tensile strength
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Towards Test-Driven Development for FPGA-Based Modules Across Abstraction Levels IEEE Access (IF 3.745) Pub Date : 2021-02-16 Julián Caba; Fernando Rincón; Jesús Barba; José A. De La Torre; Julio Dondo; Juan C. López
High-Level Synthesis (HLS) tools help engineers to deal with the complexity of building heterogeneous embedded systems that make it use of reconfigurable technology. Also, HLS opens up a way for introducing, into the development flow of custom hardware components, techniques well known in the software industry such as Test-Driven Development (TDD). However, the support provided by HLS tools for verification
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Physical Layer Security: Detection of Active Eavesdropping Attacks by Support Vector Machines IEEE Access (IF 3.745) Pub Date : 2021-02-16 Tiep M. Hoang; Trung Q. Duong; Hoang Duong Tuan; Sangarapillai Lambotharan; Lajos Hanzo
This article presents a framework for converting wireless signals into structured datasets, which can be fed into machine learning algorithms for the detection of active eavesdropping attacks at the physical layer. More specifically, a wireless communication system, which consists of an access point (AP), $K$ legitimate users and an active eavesdropper, is considered. To detect the eavesdropper who
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Security Evaluation of Y00 Protocol Based on Time-Translational Symmetry Under Quantum Collective Known-Plaintext Attacks IEEE Access (IF 3.745) Pub Date : 2021-02-02 Takehisa Iwakoshi
In this paper, we concretely formulate to derive the attacker’s success probability of obtaining the shared secret keys for the Y00 protocol under a combination of a quantum collective attack with infinitely-long known-plaintext, naming it “collective known-plaintext attack” in this work. In contrast, our previous work showed only the necessary condition to design Y00 transmitters to be information-theoretic
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In-situ Detection of Micro Crystals During Cooling Crystallization Based on Deep Image Super-Resolution Reconstruction IEEE Access (IF 3.745) Pub Date : 2021-02-18 Yan Huo; Fangkun Zhang
In this paper, a new image analysis method based on an in-situ microscopic imaging system is proposed for detecting micro crystals in cooling crystallization. Due to the limitation of measurement technology, it is a challenge to extract the evolutionary information of micro crystals, which are too small to be precisely analyzed by in-situ images, e.g. crystals at the initial crystallization stage.
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Intrusive Passive Optical Tapping Device IEEE Access (IF 3.745) Pub Date : 2021-02-19 Ismel Dominguez; Ignacio Del Villar; Jorge Montoya-Cardona; Omar Fuentes; Nelson D. Gómez-Cardona; Jesus M. Corres; Ignacio R. Matias
Passive optical tapping can be implemented by stacking multiple layers of polydimethylsiloxane (PDMS), which is used as planar waveguides for the transmission and capturing of light. Once the main waveguide is installed in the communications system, each additional stacked waveguide represents an optical sniffer where it is possible to intercept the data from an input optical fibre, allowing the information
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A Review of Text-Based Recommendation Systems IEEE Access (IF 3.745) Pub Date : 2021-02-12 Safia Kanwal; Sidra Nawaz; Muhammad Kamran Malik; Zubair Nawaz
Many websites over the Internet are producing a variety of textual data; such as news, research articles, ebooks, personal blogs, and user reviews. In these websites, the textual data is so large that the process of finding pertinent information by a user often becomes cumbersome. To overcome this issue, “Text-based Recommendation Systems (RS)” are being developed. They are the systems with the capability
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Hybrid Binary Grey Wolf With Harris Hawks Optimizer for Feature Selection IEEE Access (IF 3.745) Pub Date : 2021-02-18 Ranya Al-Wajih; Said Jadid Abdulkadir; Norshakirah Aziz; Qasem Al-Tashi; Noureen Talpur
Despite Grey Wolf Optimizer’s (GWO) superior performance in many areas, stagnation in local optima areas may still be a concern. Several significant GWO factors can be explored to enhance the performance of selection in classification, with two conflicting concepts to be considered in using or modeling a metaheuristic method, exploring a search field, and exploiting optimal solutions. Balancing exploration
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A Parameterized Approximation Algorithm for the Chromatic k-Median Problem IEEE Access (IF 3.745) Pub Date : 2021-02-19 Zhen Zhang; Jinchuan Zhang; Lingzhi Zhu
Chromatic $k$ -median is a frequently encountered problem in the determination of the topological structures of chromosomes. This problem considers a set $\mathcal {C}$ of colored clients and a set $\mathcal {F}$ of facilities located in a metric space, where $|\mathcal {C}\cup \mathcal {F}|=n$ . The goal is to open $k$ facilities and assign each client to an opened facility, such that clients with
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A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System IEEE Access (IF 3.745) Pub Date : 2021-02-16 Ameema Zainab; Dabeeruddin Syed; Ali Ghrayeb; Haitham Abu-Rub; Shady S. Refaat; Mahdi Houchati; Othmane Bouhali; Santiago Bañales Lopez
For the utility to plan the resources accurately and balance the electricity supply and demand, accurate and timely forecasting is required. The proliferation of smart meters in the grids has resulted in an explosion of energy datasets. Processing such data is challenging and usually takes a longer time than the requirement of a short-term load forecast. The paper addresses this concern by utilizing
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Web of Things: Security Challenges and Mechanisms IEEE Access (IF 3.745) Pub Date : 2021-02-08 Ruhma Sardar; Tayyaba Anees
Web of things (WoT) is an improved and most promising infrastructure of the internet of things (IoT) which permits the smart things to not only integrate to the internet but also to the web. It allows the users to share and create content as well as provide capabilities for data aggregation and analysis through a network to become part of the World Wide Web (W3). Despite these advances, it has shown
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Time-Difference-of-Arrival-Based Localization Methods of Underwater Mobile Nodes Using Multiple Surface Beacons IEEE Access (IF 3.745) Pub Date : 2021-02-19 Feng Liu; Huifang Chen; Luyixin Zhang; Lei Xie
In this paper, we investigate the mobile node localization problem in an underwater positioning system using multiple surface beacons, where time synchronization between the surface beacons and underwater mobile nodes is not required. First, we propose a Time-Difference-of-Arrival-based (TDoA-based) node localization method. In the proposed method, as the underwater node receives the positioning messages
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Research on the Parameter Design Method and System Simulation of Multimode Microwave Remote Sensors Operating in Scatterometer Modes IEEE Access (IF 3.745) Pub Date : 2021-02-16 Peng Zhou; Lian Xue; Zhenhua Zhang; Ying Wang; Xi Zhang
Multimode microwave remote sensors are a new type of radar system that operates in SAR (synthetic aperture radar), scatterometer, altimeter, and spectrometer modes in a time-sharing manner according to the current task scheduled on small satellites. High flexibility through mode switching is the outstanding advantage of this new microwave remote sensor. Two or more small satellites operating in different
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A Residual Dense U-Net Neural Network for Image Denoising IEEE Access (IF 3.745) Pub Date : 2021-02-22 Javier Gurrola-Ramos; Oscar Dalmau; Teresa E. Alarcón
In recent years, convolutional neural networks have achieved considerable success in different computer vision tasks, including image denoising. In this work, we present a residual dense neural network (RDUNet) for image denoising based on the densely connected hierarchical network. The encoding and decoding layers of the RDUNet consist of densely connected convolutional layers to reuse the feature
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Filtering Quasi-Yagi Strip-Loaded DRR Antenna With Enhanced Gain and Selectivity by Metamaterial IEEE Access (IF 3.745) Pub Date : 2021-02-22 Yan-Hui Ke; Ling-Ling Yang; Yan-Yuan Zhu; Jianpeng Wang; Jian-Xin Chen
This paper presents a design approach of broadband filtering quasi-Yagi DRR Antenna using a strip-loaded dielectric ring resonator (DRR) and near-zero-index (NZI) metamaterial (NZIM). The ring strip is loaded to the inside wall of the DRR so that the TE $_{01 \delta }$ and TE $_{21\delta }$ modes of the DRR can be close. Meanwhile, they function as a dual-mode magnetic dipole (M-dipole) driver and
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Synchronization of CVNNs: A Time-Scale Impulsive Strategy IEEE Access (IF 3.745) Pub Date : 2021-02-16 Qiuyuan Chen; Honghua Bin; Zhenkun Huang
In this paper, we mainly investigate global exponential synchronization for master-slave complex-valued neural networks (CVNNs) under a time-scale impulsive strategy. CVNNs are separated into real and imaginary parts, which lead to two real-valued neural networks (RVNNs). Firstly, impulsive Halanay differential inequality on time scales as well as the comparison between general exponential function
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A Multilevel Monte Carlo Method for Performing Time-Variant Reliability Analysis IEEE Access (IF 3.745) Pub Date : 2021-02-16 Jian Wang; Xiang Gao; Runan Cao; Zhili Sun
Even though a great number of methods have been developed for time-variant reliability analysis (TRA), crude Monte Carlo simulation (MCS) is still widely used alone or combined with other methods to enhance the efficiency and accuracy of TRA. Multilevel Monte Carlo (MLMC) is introduced to TRA herein in order to reduce the computational complexity of MCS. MLMC first discretizes the time interval of
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Cooperative Inter-ISP Traffic Control Scheme Based on Bargaining Game Approach IEEE Access (IF 3.745) Pub Date : 2021-02-10 Sungwook Kim
New applications in 5G networks are becoming very popular, and internet service providers (ISPs) may take the opportunity to provide various services to their clients. Today, one of the challenging problems facing ISPs is how the profitability can be increased while maintaining an excellent network performance. In this work, we seek to understand the fundamental issues on interactions among ISPs, and
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Underwater Image Restoration and Enhancement Based on a Fusion Algorithm With Color Balance, Contrast Optimization, and Histogram Stretching IEEE Access (IF 3.745) Pub Date : 2021-02-22 Weilin Luo; Shunqiang Duan; Jiwen Zheng
A fusion algorithm is proposed for the restoration and enhancement of underwater images. Color balance, contrast optimization and histogram stretching are carried out. To alleviate the effect of color shift in an underwater image, the scalar values of R, G, B channels are renewed so that the distributions of the three channels in histogram are similar. Instead of refining the transmittance in dark
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Hiding Data Using Efficient Combination of RSA Cryptography, and Compression Steganography Techniques IEEE Access (IF 3.745) Pub Date : 2021-02-18 Osama Fouad Abdel Wahab; Ashraf A. M. Khalaf; Aziza I. Hussein; Hesham F. A. Hamed
Data compression is an important part of information security because compressed data is more secure and easy to handle. Effective data compression technology creates efficient, secure, and easy-to-connect data. There are two types of compression algorithm techniques, lossy and lossless. These technologies can be used in any data format such as text, audio, video, or image file. The main objective
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MRCC: A Practical Covert Channel Over Monero With Provable Security IEEE Access (IF 3.745) Pub Date : 2021-02-18 Zhaozhong Guo; Liucheng Shi; Maozhi Xu; Hong Yin
Covert channels are designed to protect the communication relationship of the sender and receiver. Traditional covert channels have become insecure due to the continuous improvement of traffic analysis techniques. In this context, there is an urgent need to identify new approaches for covert channels. Blockchain is an emerging technique with characteristics of user anonymity, a flooding propagation
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Development of an Optimized Regression Model to Predict Blast-Driven Ground Vibrations IEEE Access (IF 3.745) Pub Date : 2021-02-12 Sayed S. R. Moustafa; Mohamed S. Abdalzaher; Mohamed H. Yassien; Taotao Wang; Mohamed Elwekeil; Hesham E. Abdel Hafiez
Ground vibrations caused by blasting operations in cement canisters is among the main mining issues that cause significant disruptions to nearby buildings and infrastructure. This research was performed in a limestone quarry situated southeast of Helwan City, Egypt, to investigate the impact of ground motion vibration due to cement blast action in limestone rocks. To reduce the environmental impact
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Modular Framework and Instances of Pixel-Based Video Quality Models for UHD-1/4K IEEE Access (IF 3.745) Pub Date : 2021-02-16 Steve Göring; Rakesh Rao Ramachandra Rao; Bernhard Feiten; Alexander Raake
The popularity of video on-demand streaming services increased tremendously over the last years. Most services use http-based adaptive video streaming methods. Today’s movies and TV shows are typically recorded in UHD-1/4K and streamed using settings attuned to the end-device and current network conditions. Video quality prediction models can be used to perform an extensive analysis of video codec
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Improving the Reliability of the Prediction of Terrestrial Water Storage in Yunnan Using the Artificial Neural Network Selective Joint Prediction Model IEEE Access (IF 3.745) Pub Date : 2021-01-12 Zhuoya Shi; Wei Zheng; Wenjie Yin
Although Gravity Recovery and Climate Experiment (GRACE) can provide accurate estimates in water storage, there are about 11 months gaps between GRACE and its successor GRACE-Follow On (GRACE-FO). To improve the accuracy of bridging the gaps, this study combines the partial least squares regression (PLSR) model with the learning-based models for the first time, and construct an artificial neural network
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Emotional Deep Learning Programming Controller for Automatic Voltage Control of Power Systems IEEE Access (IF 3.745) Pub Date : 2021-02-19 Linfei Yin; Chenwei Zhang; Yaoxiong Wang; Fang Gao; Jun Yu; Lefeng Cheng
In recent years, the rapid development of artificial intelligence, especially deep learning technology, makes machine learning have application scenarios in the fields of power system stability analysis, coordination along with scheduling and load forecasting. This paper designs an emotional deep learning programming controller (EDLPC) for automatic voltage control of power systems. The designed EDLPC
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DNA Encoding and STR Extraction for Anomaly Intrusion Detection Systems IEEE Access (IF 3.745) Pub Date : 2021-01-28 Omar Fitian Rashid; Zulaiha Ali Othman; Suhaila Zainudin; Noor Azah Samsudin
Deoxyribonucleic acid (DNA) can be used to discover the presence of diseases in the human body. Similarly, its functionality can be leveraged in an intrusion detection system (IDS) to detect attacks against computer systems and network traffic. Various approaches have been proposed for using DNA sequences in IDSs. The most popular is the DNA sequence matching method, which is also used in biology.
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Adaptive Predefined-Time Synchronization of Two Different Fractional-Order Chaotic Systems With Time-Delay IEEE Access (IF 3.745) Pub Date : 2021-02-16 Lixiong Lin; Qing Wang; Bingwei He; Yanjie Chen; Xiafu Peng; Ruilin Mei
This paper devotes to the adaptive globally synchronization within predefined-time of two time-delayed fractional-order chaotic systems. Firstly, through fractional calculus, two novel different fractional-order systems with time-delay are proposed, whose convergence is guaranteed and phase trajectory is given. Secondly, by exploiting the non-negative Lyapunov function and inequality theorem, a novel
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A Backstepping Global Fast Terminal Sliding Mode Control for Trajectory Tracking Control of Industrial Robotic Manipulators IEEE Access (IF 3.745) Pub Date : 2021-02-18 Thanh Nguyen Truong; Anh Tuan Vo; Hee-Jun Kang
We propose a backstepping global fast terminal sliding mode control for trajectory tracking control of industrial robotic manipulators in this article. An integral of the global fast terminal sliding mode surface is firstly suggested to improve the dynamic performance and fast convergence of Sliding Mode Control (SMC) and Terminal SMC (TSMC), which also obtains a finite-time convergence. A controller
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A Fast and Robust Heuristic Algorithm for the Minimum Weight Vertex Cover Problem IEEE Access (IF 3.745) Pub Date : 2021-01-14 Yang Wang; Zhipeng Lü; Abraham P. Punnen
The minimum weight vertex cover problem (MWVCP) is a fundamental combinatorial optimization problem with various real-world applications. The MWVCP seeks a vertex cover of an undirected graph such that the sum of the weights of the selected vertices is as small as possible. In this paper, we present an effective algorithm to solve the MWVCP. First, a master-apprentice evolutionary algorithm based on
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