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Design of an ultrasharp silicon multimode waveguide bend assisted by multiregional subwavelength grating structures

JOURNAL OF NANOPHOTONICS 2021年第4期15卷

作者： Wang, Juanli Sun, Shangsen Zhang, Runsen Zhang, Fengchun Zhu, Ning South China Normal Univ Inst Semicond Sci & Technol Guangzhou Peoples R China Guangdong Engn Technol Res Ctr Low Carbon & New E Guangzhou Peoples R China SCNU Qingyuan Inst Sci & Technol Innovat Co Ltd Qingyuan Peoples R China

Sharp multimode waveguide bends are beneficial to improve the integration density of the on-chip mode-division multiplexing (MDM) systems, which can be used to increase the optical information transmission capacity. A method of designing a multimode bending structure based on subwavelength gratings is proposed in this paper, through the mode conversion and matching between the straight and bending waveguide. The proposed bending structure is composed of a 90-deg arc-bend with a radius of 5 mu m combined with the shallow-etched grating structures on the top, and two-mode converters on the input and output straight waveguide realized also with the help of nonuniform grating-like structures, achieving a total effective bending radius of 8.25 pm and high transmission efficiencies of the first three TE modes (TE0-TE2) in a wide wavelength range of 1500 to 1600 nm. At the center wavelength of 1550 nm, the calculated excess losses of the three modes TE0, TE1, and TE2 are 0.21, 0.19, and 0.59 dB, respectively, and the crosstalks for all modes are less than -26.58 dB. More importantly, we add a nonuniform grating converter in the straight waveguide region which pre-deviates the mode fields inside the straight waveguide to help further reduce the size of the bending part to only 5 mu m, which will be helpful for large scale integration when a great number of bends are cascaded. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： multimode waveguide bend grating mode converter integrated photonic circuits optimization algorithm

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Analysis and Optimal Design of a Novel Actuator System for a Camera Module

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IEEE ACCESS 2021年 9卷 3441-3450页

作者： Kwon, Tae-Hoon Ro, Jong-Suk Chung Ang Univ Dept Elect & Elect Engn Seoul 06974 South Korea

Owing to the fourth industrial revolution and the recent trend for compact, high-performance, and multifunctional electrical devices, the demand for a small and high-performance camera module has dramatically increased. To address this, in this study, a novel, miniaturized, high-performance, low-cost multifunctional camera module with optical image stabilization (OIS) via a novel two-axis motional actuator with 1-Stage is proposed. To date, a systematic analysis and optimal design method for the actuators of camera modules has not been proposed yet. Accurate and rapid analysis and optimal design methods are proposed herein. Based on the proposed methods, it is possible to reduce the time and cost for the development of actuators for camera modules. The usefulness of the proposed actuator system for small, high performance, and multifunctional camera modules, and the proposed analysis and optimal design method were verified experimentally in this study.

关键词： Cameras Actuators Magnetic resonance imaging Lenses Force Springs Optical imaging Actuator chamfered magnet coil diameter optical image stabilization (OIS) optimization algorithm voice coil motor (VCM)

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Optimal operation of small, numerous, and disparate DERs via aggregation in transactive distribution systems with universal metering

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IET GENERATION TRANSMISSION & DISTRIBUTION 2021年第17期15卷 2422-2434页

作者： Sabillon, Carlos Mohamed, Amr A. Golriz, Ali Venkatesh, Bala Ryerson Univ Ctr Urban Energy Elect Comp & Biomed Engn Dept Toronto ON Canada Independent Elect Syst Operator Toronto ON Canada

Transactive energy distribution systems (TEDS) have unleashed new economic opportunities in the distribution sector via a new local distribution operator (LDO) that enables transactions between peers and the LDO (P2LDO) and peer-to-peer transactions. Aiming to unleash full benefits from existing distributed energy resources (DERs), this paper introduces an optimization algorithm for the operation of small, numerous, and disparate DER aggregations. The proposed algorithm seeks to maximize aggregator profits obtained via P2LDO and peer-to-peer transactions for energy and demand response, while being cognizant of capacity obligations acquired during transactive energy distribution system planning phases. In addition, the concept of universal metering is introduced to upgrade the economic opportunity of DERs. Results obtained via case studies show that the proposed approach can help DER owners to increase their revenue. An aggregated case study for 300 m shows that the overall revenue can be increased by more than 100% when operating DERs in an aggregated fashion.

关键词： DER owners aggregator profits P2LDO DER aggregations Power system management, operation and economics Optimisation techniques optimization algorithm optimal operation transactive energy distribution system planning phases universal metering demand side management Distribution networks optimisation power distribution economics peer-to-peer transactions local distribution operator economic opportunity aggregated case study demand response distributed energy resources

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Big data analytics with oppositional moth flame optimization based vehicular routing protocol for future smart cities

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EXPERT SYSTEMS 2022年第5期39卷

作者： Aljehane, Nojood O. Mansour, Romany F. Univ Tabuk Fac Comp & Informat Technol Tabuk Saudi Arabia New Valley Univ Fac Sci Dept Math El Kharga 72511 Egypt

Presently, smart city is designed to enhance the quality of life in city, fulfil the safety of the people, safe travelling, etc. Besides, big data has attracted significant attention among researchers in different fields as a large amount of data is being produced with diverse day-to-day applications. Besides, Vehicular adhoc network (VANET) is a kind of mobile adhoc network (MANET) that considers the vehicles as the nodes in a network. Since the VANET generates large amount of data, big data analytics can be used to gain meaningful understanding for improving the traffic management process such as planning, engineering, and operations. This paper designs a Big Data Analytics with Oppositional Moth Flame optimization based Vehicular Routing Protocol for Future Smart Cities. The presented model maps the features of VANET with the attributes of the big data. In addition, oppositional moth flame optimization based vehicular routing (OMFOVR) technique is developed for VANET over the Hadoop Map Reduce standalone distributed framework. For validating the effectual performance of the proposed OMFOVR technique, a series of experiments were performed and the results are compared with the conventional NetBeans IDE platform. The experimental values showcased the betterment of the OMFOVR technique on the selection of routes over the compared methods.

关键词： big data analytics Hadoop optimization algorithm routing smart city vehicular networks

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Optimal Dynamic Recharge Scheduling for Two-Stage Wireless Power Transfer

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2021年第8期17卷 5719-5729页

作者： Pandiyan, Akshayaa Y. S. Boyle, David E. Kiziroglou, Michail E. Wright, Steven W. Yeatman, Eric M. Imperial Coll London Dept Elect & Elect London SW7 2AZ England Int Hellenic Univ Dept Ind Engn & Management Nea Moudania 57001 Greece Imperial Coll London Dyson Sch Design Engn London SW7 2AZ England

Many industrial-Internet-of-Things applications require autonomous operation and incorporate devices in inaccessible locations. Recent advances in wireless power transfer (WPT) and autonomous vehicle technologies, in combination, have the potential to solve a number of residual problems concerning the maintenance of, and data collection from embedded devices. Equipping inexpensive unmanned aerial vehicles (UAV) and embedded devices with subsystems to facilitate WPT allows a UAV to become a viable mobile power delivery vehicle (PDV) and data collection agent. A key challenge is, therefore, to ensure that a PDV can optimally schedule power delivery across the network, such that it is as reliable and resource efficient as possible. To achieve this and out-perform naive on-demand recharging strategies, in this article, we propose a two-stage wireless power network (WPN) approach in which a large network of devices may be grouped into small clusters, where packets of energy inductively delivered to each cluster by the PDV are acoustically distributed to devices within the cluster. In this article, we describe a novel dynamic recharge scheduling algorithm that combines genetic weighted clustering with nearest neighbor search to jointly minimize PDV travel distance and WPT losses. The efficacy and performance of the algorithm are evaluated in simulation using experimentally derived traces, and the algorithm is shown to achieve similar to 90% throughput for large, dense networks.

关键词： Dynamic recharge scheduling genetic algorithm (GA) optimization algorithm wireless power network (WPN) wireless rechargeable sensor network

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Evolutionary Computation in Social Propagation over Complex Networks: A Survey

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International Journal of Automation and computing 2021年第4期18卷 503-520页

作者： Tian-Fang Zhao Wei-Neng Chen Xin-Xin Ma Xiao-Kun Wu School of Computer Science&Engineering South China University of TechnologyGuangzhou 510006China School of Journalism and Communication South China University of TechnologyGuangzhou 510006China

Social propagation denotes the spread phenomena directly correlated to the human world and society, which includes but is not limited to the diffusion of human epidemics, human-made malicious viruses, fake news, social innovation, viral marketing, etc. Simulation and optimization are two major themes in social propagation, where network-based simulation helps to analyze and understand the social contagion, and problem-oriented optimization is devoted to contain or improve the infection results. Though there have been many models and optimization techniques, the matter of concern is that the increasing complexity and scales of propagation processes continuously refresh the former conclusions. Recently, evolutionary computation(EC) shows its potential in alleviating the concerns by introducing an evolving and developing perspective. With this insight, this paper intends to develop a comprehensive view of how EC takes effect in social propagation. Taxonomy is provided for classifying the propagation problems, and the applications of EC in solving these problems are reviewed. Furthermore, some open issues of social propagation and the potential applications of EC are *** paper contributes to recognizing the problems in application-oriented EC design and paves the way for the development of evolving propagation dynamics.

关键词： Evolutionary computation complex network propagation dynamics social diffusion evolution model optimization algorithm

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Self-adaptive differential evolution applied to combustion engine calibration

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SOFT COMPUTING 2021年第1期25卷 109-135页

作者： Fachin, Jose Marcio Reynoso-Meza, Gilberto Mariani, Viviana Cocco Coelho, Leandro dos Santos Univ Fed Parana Dept Elect Engn Elect Engn Grad Program PPGEE Curitiba Parana Brazil Pontificia Univ Catolica Parana Ind & Syst Engn Grad Program PPGEPS Curitiba Parana Brazil Pontificia Univ Catolica Parana Dept Mech Engn Curitiba Parana Brazil

In this paper, a new population-based stochastic optimization algorithm called Hybrid Self-Adaptive Differential Evolution (HSADE) is proposed. The algorithm addresses unconstrained global optimization problems, exploring and combining the best features of some Differential Evolution (DE), obtaining a good balance between exploration and exploitation. These approaches are important for increasing the accuracy and efficiency of a population-based stochastic algorithm and for adapting the control parameter values during the optimization process. Further, they are crucial for increasing the convergence speed and reducing the risk of search stagnation. To verify the performance of the HSADE, 25 benchmark functions were tested presenting an optimal performance when compared to some state-of-the-art DEs algorithms. Furthermore, an experimental problem in an automotive sector, related to automatic internal combustion engine calibration, was used adjusting 300 decision variables. The HSADE achieved a reliable calibration, reducing the time required to perform approximately 90% when comparing to other optimization algorithms.

关键词： optimization algorithm Differential evolution algorithm Hybrid approach Unconstrained optimization

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A Barzilai-Borwein Gradient algorithm for Spatio-Temporal Internet Traffic Data Completion via Tensor Triple Decomposition

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JOURNAL OF SCIENTIFIC COMPUTING 2021年第3期88卷 1-24页

作者： Chen, Yannan Zhang, Xinzhen Qi, Liqun Xu, Yanwei South China Normal Univ Sch Math Sci Guangzhou Peoples R China Tianjin Univ Sch Math Tianjin 300354 Peoples R China Huawei Technol Investment Co Ltd Labs 2012 Future Network Theory Lab Shatin Hong Kong Peoples R China Hangzhou Dianzi Univ Dept Math Sch Sci Hangzhou 310018 Peoples R China Hong Kong Polytech Univ Dept Appl Math Hung Hom Kowloon Hong Kong Peoples R China Huawei Theory Res Lab Kowloon Hong Kong Peoples R China

With the coming of high-speed network and 5G era, internet traffic data is crucial for various network tasks such as traffic engineering, capacity planning and anomaly detection. To explore the natural spatio-temporal structure of network flow, we use the novel triple decomposition of tensors to establish an optimization model with the spatio-temporal regularization for completing the internet traffic data. A Barzilai-Borwein gradient algorithm is designed for solving the spatio-temporal internet traffic tensor completion problem. We prove the convergence of this algorithm and analyze its convergence rate with the tool of the Kurdyka-Lojasiewicz property. Numerical experiments on Abilene and GeANT datasets report that the proposed tensor completion method is effective.

关键词： Internet traffic tensor Tensor completion Triple tensor decomposition optimization algorithm

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Optimal approach for wind resource assessment using Kolmogorov-Smirnov statistic: A case study for large-scale wind farm in Pakistan

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RENEWABLE ENERGY 2021年 168卷 1229-1248页

作者： Saeed, Muhammad Abid Ahmed, Zahoor Zhang, Weidong Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Govt Coll Univ Dept Elect Lahore 54000 Pakistan

Weibull distribution has been widely utilized for better understanding, quantification, and optimal utilization of wind energy globally. Although numerical approaches are widely used for Weibull parameters estimation (WPE), their results still lack consistency. In this situation, Artificial Intelligence optimization Techniques (AIOT) might be a powerful tool to attaining high precision;however, in the case of WPE, standard methods may not ensure convergence. In this work, a generalized mathematical model is derived for AIOT convergence in the case of WPE. Based on the mathematical model Kolmogorov-Smirnov statistic is utilized to establish a convergence optimizer function (C-opt) for WPE. The Weibull fitness tests are computed using real-time data from 13 different locations of Pakistan to check the effeteness of C-opt that illustrates that C-opt shows better results than numerical methods. For the economic aspect, Levelized economic cost is carried out for all the targeted sites using ten commercially available wind turbines. It is observed that five of the targeted sites are very promising for wind power production. The study is expected to provide an alternative method for WPE and the deployment of wind energy technology as a future power source in the country. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Weibull distribution Energy assessment optimization algorithm Levelized economic cost Kolmogorov-smirnov statistic

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Opposition-Based Quantum Bat algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters

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IEEE ACCESS 2021年 9卷 103610-103626页

作者： Islam, Jahedul Meraj, Sheikh Tanzim Masaoud, Ammar Mahmud, Md. Apel Nazir, Amril Kabir, Muhammad Ashad Hossain, Md. Moinul Mumtaz, Farhan Univ Teknol PETRONAS Dept Fundamental & Appl Sci Seri Iskandar 32610 Perak Darul Rid Malaysia Univ Teknol PETRONAS Dept Elect & Elect Engn Seri Iskandar 32610 Perak Darul Rid Malaysia Al Baath Univ Fac Mech & Elect Engn Damascus Syria Deakin Univ Sch Engn Elect Power & Energy Syst Res Lab EPESRL Geelong Vic 3217 Australia Zayed Univ Dept Informat Syst Abu Dhabi U Arab Emirates Charles Sturt Univ Sch Comp & Math Bathurst NSW 2795 Australia Univ Kent Sch Engn & Digital Arts Canterbury CT2 7NT Kent England

Selective harmonic elimination (SHE) technique is used in power inverters to eliminate specific lower-order harmonics by determining optimum switching angles that are used to generate Pulse Width Modulation (PWM) signals for multilevel inverter (MLI) switches. Various optimization algorithms have been developed to determine the optimum switching angles. However, these techniques are still trapped in local optima. This study proposes an opposition-based quantum bat algorithm (OQBA) to determine these optimum switching angles. This algorithm is formulated by utilizing habitual characteristics of bats. It has advanced learning ability that can effectively remove lower-order harmonics from the output voltage of MLI. It can eventually increase the quality of the output voltage along with the efficiency of the MLI. The performance of the algorithm is evaluated with three different case studies involving 7, 11, and 17-level three-phase MLIs. The results are verified using both simulation and experimental studies. The results showed substantial improvement and superiority compared to other available algorithms both in terms of the harmonics reduction of harmonics and finding the correct solutions.

关键词： Harmonic analysis Switches Pulse width modulation Power harmonic filters Genetic algorithms Standards Multilevel inverters Power electronics multilevel inverter (MLI) optimization algorithm pulse width modulation (PWM) selective harmonic elimination (SHE) total harmonic distortions (THD)

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