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Nanophotonics and Micro/Nano Optics IX 2023

作者： Sharma, Anjali Choure, Kamal Kishor Saharia, Ankur Mudgal, Nitesh Tiwari, Manish Singh, Ghanshyam Kumar, Santosh Department of Electronics and Communication Engineering Malaviya National Institute of Technology Jaipur India Manipal University Jaipur India Poornima College of Engineering Jaipur India Shandong Key Laboratory of Optical Communication Science and Technology School of Physics Science and Information Technology Liaocheng University Liaocheng China

ISBN: (纸本)9781510667952

The current work proposes an optimized design for 2-bit synchronous up counter using silicon nitride on insulator optical microring resonators (MRRs). The research involves exploring the existing designs of up counter structures based on MRRs, and then minimizing the number of rings being used in the proposed model. The proposed design uses four MRRs for Synchronous up counter operation and the model has been validated through the MATLAB simulation result. The main component of the design is the MRR which can act as a switch depending upon the output at the drop port or the through port according to the MRR being in an on-resonance or off-resonance state respectively. The principle of the MRR is that on applying a vertical pump signal over the ring, the non-linear refractive index of the ring undergoes a temporary blue shift resulting due to π- phase shift in the ring, changing the resonant frequency of operation of the ring. The average pump power required for the blue shift can be obtained from the phase shift vs. the average pump power graph simulated in MATLAB. This shift in resonance frequency is employed to switching action for the signal to be output at the drop port or the through port of the MRR and based on the drive signal inputs of the present state and the clock to the rings in the resonator structure which act as pump signal over the ring, the next state of the counter is determined. © 2023 SPIE. All rights reserved.

关键词： Silicon nitride

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Adaptive Occlusion Face Recognition Feature Fusion Network Based on Precise Guidance Mask Extraction

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Journal of Shanghai Jiaotong University (science) 2025年 1-12页

作者： Ye, Jihua Zhang, Lei Wang, Chao Tu, Qixuan Zheng, Rehua Huang, Huiyuan Jiang, Aiwen School of Computer and Information Engineering Jiangxi Normal University Nanchang330022 China Jiangxi Provincial Key Laboratory for High Performance Computing Jiangxi Normal University Nanchang330022 China State International Science & Technology Cooperation Base of Networked Supporting Software Jiangxi Normal University Nanchang330022 China

The uncertainty in the position and size of occluding objects greatly affects the extraction of identity features in facial recognition, which is a challenge that existing methods fail to effectively address. To tackle this issue, this paper introduces a novel feature fusion network for occluded facial recognition that adaptively handles arbitrary occlusions and accurately extracts occlusion information masks. The network effectively mitigates the impact of occlusions on facial identity features through a feature fusion module. The proposed method employs an occlusion classification module and an occlusion classification loss to precisely guide the extraction of accurate occlusion masks. Subsequently, an occlusion-aware hybrid attention module is introduced, which focuses on the relationship between facial features and occlusion masks across channel and spatial dimensions. This fusion strategy enables the extraction of facial identity features that are resilient to occlusions. Experimental results indicate that the proposed method holds a significant advantage in handling facial recognition tasks with arbitrary occlusions. On the LFW and MF1 synthetic occlusion datasets, the average accuracy rates reached 93.19% and 72.57%, respectively, showing improvements of 1.7 and 2.39 percent points over mainstream methods. © Shanghai Jiao Tong University 2025.

关键词： A feature fusion occluded facial recognition occlusion mask occlusion perception TP391.41

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AI algorithms for Autonomous Robotics Navigation 2

AI algorithms for Autonomous Robotics Navigation

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2nd International Conference Computational and Characterization Techniques in engineering and sciences, IC3TES 2024

作者： Komala, C.R. Raja, J. Marotrao, Sarange Shreepad Neelima, Nalla Sujatha, R. Chidambarathanu, K. East Point College of Engineering and Technology Department of Information Science and Engineering Karnataka Bengaluru560049 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering School of Computing Tamil Nadu Chennai600062 India Ajeenkya D Y Patil School of Engineering Department of Mechanical Engineering Maharashtra Pune412105 India R.V.R & J.C. College of Engineering Department of Information Technology Andhra Pradesh Chowdavaram522019 India Subbalakshmi Lakshmipathy College of Science Department of Computer Science Tamil Nadu Madurai625022 India R.M.K. Engineering College Department of Computer Science and Business Systems Tamil Nadu Chennai601206 India

ISBN: (纸本)9798350364699

Robotic systems depend much on autonomous navigation since it allows them to operate on their own in environments constantly changing and lacking clarity. The most evolved artificial intelligence (AI) techniques applied in self-driving robot navigation are briefly reviewed in this work. These approaches call for classical methodologies, machine learning, and deep learning as well. We examine the advantages and drawbacks of numerous approaches applied in route planning, location finding, map creation, obstacle avoidance. We investigate how neural networks, sensor fusion, and reinforcement learning may be applied to provide increased dependability and flexibility for guiding systems. Case examples illustrating the advantages and drawbacks of applying artificial intelligence (AI) in practical contexts including service robots, drones, and self-driving cars abound. Combining modern AI algorithms with conventional approaches indicates that it is feasible to create self-driving robots more dependable and efficient based on the increased tracking performance. © 2024 IEEE.

关键词： Reinforcement learning

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A Patch-Based Multiple Imputation Transformer Model for Time Series Data Completion

A Patch-Based Multiple Imputation Transformer Model for Time...

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International Conference on Big Data and information Analytics (BigDIA)

作者： Wenbo Yuan Chaofan Dai Huahua Ding Qideng Tang National Key Laboratory of Information Systems Engineering National University of Defense Technology ChangSha China

ISBN: (数字)9798350354621

ISBN: (纸本)9798350354638

In the real world, collecting time series data often encounters difficulties and uncertainties, leading to prevalent data missing issues. The time series imputation task aims to restore data integrity and improve prediction performance. Existing models mainly use single imputation to handle missing data. This paper proposes a Patch-based Multiple Imputation Transformer (PMIT), which learns data correlations within the same feature through patch operations and channel-independent (CI) operations. The model employs multiple imputation training, optimizing imputed data propagation across different modules, and incorporates attention mechanisms and dynamic adjustment methods to address complex dependencies. Experimental results show that PMIT outperforms recent models in imputation performance and generalization ability across various realworld datasets.

关键词： Training Analytical models Uncertainty Data integrity Time series analysis Predictive models Transformers Imputation Data models Robustness

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Heterogeneous optomechanical crystal cavity coupled by a wavelength-scale mechanical waveguide

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Photonics Research 2023年第9期11卷 1509-1516页

作者： YANG LUO HONGYI HUANG LEI WAN WEIPING LIU ZHAOHUI LI Department of Electronic Engineering College of Information Science and TechnologyJinan UniversityGuangzhou 510632China International Institute for Innovative Design and Intelligent Manufacturing Tianjin UniversityShaoxing 312000China Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems Sun Yat-sen UniversityGuangzhou 510275China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519000China

Integrated optomechanical crystal(OMC)cavities provide a vital device prototype for highly efficient microwave to optical conversion in quantum information *** this work,we propose a novel heterogeneous OMC cavity consisting of a thin-film lithium niobate(TFLN)slab and chalcogenide(ChG)photonic crystal nanobeam coupled by a wavelength-scale mechanical *** optomechanical coupling rate of the heterogeneous OMC cavity is optimized up to 340 kHz at 1.1197 *** with phononic band and power decomposition,17.38%energy from the loaded RF power is converted into dominant fundamental horizontal shear mode(SH0)in the narrow LN mechanical *** on this fraction,as a result,3.51%power relative to the loaded RF energy is scattered into the fundamental longitudinal mode(L0)facing the TFLN-ChG heterogeneous *** acoustic breathing mode of the heterogeneous OMC is successfully excited under the driving of the propagating L0 mode in the heterogeneous waveguide,demonstrating the great potentials of the heterogeneous piezo-optomechanical transducer in high-performance photon–phonon interaction fields.

关键词： waveguide cavity crystal

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Augmented Reality With Authentic GeometryGo App to Help Geometry Learning and Assessments

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IEEE Transactions on Learning Technologies 2023年第5期16卷 769-779页

作者： Hwang, Wu-Yuin Nurtantyana, Rio Purba, Siska Wati Dewi Hariyanti, Uun Suprapto National Dong Hwa University Department of Computer Science and Information Engineering College of Science and Engineering Hualien974 Taiwan National Central University Graduate Institute of Network Learning Technology Taoyuan City320 Taiwan Telkom University School of Computing Bandung40257 Indonesia Universitas Pelita Harapan Department of Master of Educational Technology Kota Tangerang15811 Indonesia Brawijaya University Information Systems Department Kota Malang65145 Indonesia State University Yogyakarta Department of Electronics Engineering Education Yogyakarta55281 Indonesia

We developed an Authentic GeometryGo (AGG) app to help students application of geometry in authentic contexts through authentic measurements and peer assessments. The study included an experimental group (EG) using an AGG app and a control group (CG) using paper-based methods. The results showed that the EG outperformed the CG in terms of estimation. Measuring authentic geometry shapes using the app could foster students' estimation. Furthermore, meaningful peer assessments with visual representations in authentic contexts can facilitate the evaluation of peers' work and improve students' geometry understanding. Therefore, we encourage educators to use augmented reality with appropriate learning activities to sharpen students' measurement quality and visual representations by measuring real geometry shapes and applying mathematics knowledge in authentic contexts. © 2008-2011 IEEE.

关键词： Augmented reality

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Energy-Saving VM in SDN-Driven Cloud Data Center with the Operational Vacation Policy 3

Energy-Saving VM in SDN-Driven Cloud Data Center with the Op...

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3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Dash, Bibhuti Bhusan Patra, Sudhansu Shekhar Barik, Lalbihari Ghosh, Akash Pandey, Trilok Nath Gourisaria, Mahendra Kumar KIIT Deemed to Be University School of Computer Applications Bhubaneswar India King Abdul Aziz University Faculty of Computing and Information Technology in Rabigh Department of Information Systems Saudi Arabia Vellore Institute of Technology School of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350343632

The increasing use of the Internet of Things (IoT), which has resulted in an exponential growth in network traffic, has serious implications on energy consumption and network performance. To reduce power consumption in cloud data centers, a server vacation-based energy-efficient traffic management solution is recommended. The primary idea is that using software-defined network (SDN) technologies, cloud system virtual machines (VMs) can take vacations. The goal of the energy-saving optimization task is to reduce the number of virtual machines (VMs) in use while maintaining service quality standards. This research study focuses on impatient client behaviour, several vacations, limited buffer and queuing system with many servers. Impatient customers may be kept in the cloud system by implementing certain customer retention strategies. The steady-state probability for the proposed SDN-assisted cloud system have been determined using recurrences. To determine the efficiency of the proposed system, several performance studies are conducted. © 2023 IEEE.

关键词： Cloud data center Energy optimization Performance measurement Queueing model Software Defined Network Vacation policy

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Ultrabroadband chiral metasurface for linear polarization conversion and asymmetric transmission based on enhanced interference theory

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Chinese Optics Letters 2023年第11期21卷 147-154页

作者：赵京城李南程用志 School of Electronics Information Engineering Beihang UniversityBeijing 100191China Aerospace Institute of Advanced Material&Processing Technology Beijing 100074China School of Information Science and Engineering Wuhan University of Science and TechnologyWuhan 430081China Hubei Longzhong Laboratory Xiangyang 441000China

In this paper,we propose an ultrabroadband chiral metasurface(CMS)composed of S-shaped resonator structures situated between two twisted subwavelength gratings and dielectric *** innovative structure enables ultrabroadband and high-efficiency linear polarization(LP)conversion,as well as asymmetric transmission(AT)effect in the microwave *** enhanced interference effect of the Fabry-Perot-like resonance cavity greatly expands the bandwidth and efficiency of LP conversion and AT *** numerical simulations,it has been revealed that the cross-polarization transmission coefficients for normal forward(-z)and backward(+z)incidence exceed 0.8 in the frequency range of 4.13 to 17.34 GHz,accompanied by a polarization conversion ratio of over 99%.Furthermore,our microwave experimental results validate the consistency among simulation,theory,and ***,we elucidate the distinct characteristics of ultrabroadband LP conversion and significant AT effect through analysis of polarization azimuth rotation and ellipticity angles,total transmittance,AT coefficient,and electric field *** proposed CMS structure shows excellent polarization conversion properties via AT effect and has potential applications in areas such as radar,remote sensing,and satellite communication.

关键词： chiral metasurface linear polarization conversion asymmetric transmission Fabry-Perot-like resonance electromagnetic interference model

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Modeling of Sensor Enabled IrrigationManagement for Intelligent Agriculture Using Hybrid Deep Belief Network

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Computer systems science & engineering 2023年第8期46卷 2319-2335页

作者： Saud Yonbawi Sultan Alahmari B.R.S.S.Raju Chukka Hari Govinda Rao Mohamad Khairi Ishak Hend Khalid Alkahtani JoséVarela-Aldás Samih M.Mostafa Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Aditya Engineering College Affiliated to JNTUK(Kakinada) SurampalemIndia Department of MBA Vignan’s Institute of Information and Technology(A)DuvvadaVisakhapatnamAP530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11564Saudi Arabia SISAu Research Group Universidad Tecnológica IndoaméricaAmbato180103Ecuador Faculty of Computers and Information South Valley UniversityQena83523Egypt

Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual *** the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart *** irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation *** learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an *** this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent *** MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination ***,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not *** MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.

关键词： Agriculture smart farming hyperparameter tuning artificial intelligence irrigation management sensors deep learning

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Analysis and Modeling of UAV Data Collection in IoT systems Based on Markov Fluid

Analysis and Modeling of UAV Data Collection in IoT Systems ...

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International Conference on Big Data and information Analytics (BigDIA)

作者： Chaofan Dai Haohao Zhou QiDeng Tang National Key Laboratory of Information Systems Engineering National University of Defense Technology Changsha China

ISBN: (数字)9798350354621

ISBN: (纸本)9798350354638

The rapid development of technologies such as the Internet of Things (IoT) has greatly facilitated various aspects of people's lives and profoundly transformed their daily routines and work environments. Sensor devices, a vital component of the IoT, offer a reliable and real-time data source for the advancement of applications like artificial intelligence and the industrial internet. However, there are still numerous unresolved issues in the data collection process of sensor devices, particularly in harsh conditions. Utilizing drone platforms for real-time data collection appears to be a viable approach at present. This paper addresses the optimization and control of energy consumption in unmanned aerial vehicle (UAV) data collection. It comprehensively considers factors such as the distribution of sensor devices, UAV speed control, and sensor energy consumption. By integrating Markov fluid theory, we provide a mathematical expression of the relationship between UAV energy consumption, the distribution of sensor devices, and data collection transmission variables in this scenario.

关键词： Energy consumption Liquids Soft sensors Velocity control Autonomous aerial vehicles Real-time systems Mathematical models Internet of Things Reliability Optimization

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