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arXiv 2022年

作者： Chen, Yi Chang, Zheng Min, Geyong Mao, Shiwen Hämäläinen, Timo School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Department of Computer Science University of Exeter ExeterEX4 4QF United Kingdom Department of Electrical and Computer Engineering Auburn University AL United States Faculty of Information Technology University of Jyväskylä P. O. Box 35 JyväskyläFIN-40014 Finland

IoT devices recently are utilized to detect the state transition in the surrounding environment and then transmit the status updates to the base station for future system operations. To satisfy the stringent timeliness requirement of the status updates for the accurate system control, age of information (AoI) is introduced to quantify the freshness of the sensory data. Due to the limited computing resources, the status update can be offloaded to the mobile edge computing (MEC) server for execution to ensure the information freshness. Since the status updates generated by insufficient sensing operations may be invalid and cause additional processing time, the data sensing and processing operations need to be considered simultaneously. In this work, we formulate the joint data sensing and processing optimization problem to ensure the freshness of the status updates and reduce the energy consumption of IoT devices. Then, the formulated NP-hard problem is decomposed into the sampling, sensing and computation offloading optimization problems. Afterwards, we propose a multi-variable iterative system cost minimization algorithm to optimize the system overhead. Simulation results show the efficiency of our method in decreasing the system cost and dominance of sensing and processing under different scenarios. Copyright © 2022, The Authors. All rights reserved.

关键词： computation offloading

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Improving Referring Expression Comprehension by Suppressing Expression-unrelated Proposals

Improving Referring Expression Comprehension by Suppressing ...

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electronic Information engineering and computer technology (EIECT), International Conference on

作者： Qun Wang Feng Zhu Xiang Li Ruida Ye Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Faculty of Computer Science and Engineering Northeastern University Shenyang China Department of Aerospace Engineering and Technology Space Engineering University Beijing China

The prevailing referring expression comprehension (REC) method is based on two stages: 1) detecting multiple candidate proposals using an object detector and 2) aligning proposals with text descriptions. Existing two-stage models have achieved significant improvements with excellent alignment modules. However, their alignment modules treat each proposal equally without filtering expression-unrelated proposals. These expression-unrelated proposals may interfere with the alignment modules’ ability to accurately reason about the target proposal. These proposals also increase the difficulty of training alignment modules. To solve this problem, we propose a new framework, that can suppress expression-unrelated proposals for alignment modules. Specifically, we first design a suppression module, which calculates the relevance scores between the proposals and the expression by using the semantics in the expression. Then, these scores are integrated into three basic alignment modules, including subject, location, and relationship modules, to guide each module to focus on the expression-related proposals. We conduct extensive experiments on three benchmark datasets, and the results show the effectiveness of our suppression module and performance improvement.

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A Numerical Approach to Design the Kretschmann Configuration Based Refractive Index Graphene-MoS_(2) Hybrid Layers With TiO_(2)-SiO_(2) Nano for Formalin Detection

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Photonic Sensors 2020年第2期10卷 134-146页

作者： Md.Biplob HOSSAIN Tamanna TASNIM Lway F.ABDULRAZAK Md.Masud RANA Md.Rabiul ISLAM Department of Electrical and Electronic Engineering Jashore University of Science and TechnologyJashore-7408Bangladesh Department of Electrical and Electronic Engineering Rajshahi University of Engineering&TechnologyRajshahi-6402Bangladesh Department of Computer Science Cihan University SlemaniSulaimaniya-46001Iraq School of Electrical Computer and Telecommunications Engineering Faculty of Engineering and Information SciencesUniversity of WollongongNSW 2522Australia

In this paper,a Kretschmann configuration based surface plasmon resonance(SPR)sensor is numerically designed using graphene-MoS_(2) hybrid structure TiO_(2)-SiO_(2) nano particles for formalin *** this design,the observations of SPR angle versus minimum reflectance and SPR frequency(FSPR)versus maximum transmittance(Tmax)are *** chitosan is used as probe legend to perform reaction with the formalin(40%formaldehyde)which acts as target *** this paper,both graphene and MoS_(2) are used as biomolecular acknowledgment element(BAE)and TiO_(2) as well as SiO_(2) bilayers is used to improve the sensitivity of the *** numerical results show that the variation of FSPR and SPR angles for inappropriate sensing of formalin is quite insignificant which confirms the absence of *** the other hand,these variations for appropriate sensing are considerably significant that confirm the presence of *** the end of this article,the variation of sensitivity of the proposed biosensor is measured in corresponding to the increment of a refractive index with a refractive index step 0.01 refractive index unit(RIU).In inclusion of TiO_(2)-SiO_(2) bilayers with graphene-MoS_(2),a maximum sensitivity of 85.375%is numerically calculated.

关键词： Surface plasmon resonance formalin detection grapheme refractive index sensitivity

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Comorbidity Diseases Diagnosis Using Machine Learning Methods and Chi-Square Feature Selection Technique

Comorbidity Diseases Diagnosis Using Machine Learning Method...

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International Conference on Developments in eSystems engineering (DESE)

作者： Dheyauldeen M. Mukhlif Dhafar Hamed Abd Ridha Ejbali Adel M. Alimi National Engineering School of Sfax (ENIS) University of Sfax Sfax Tunisia College of Computer Science and Information Technology University of Anbar Ramadi Iraq Research Team in Intelligent Machines (RTIM) University of Gabes Gabes Tunisia Research Groups in Intelligent Machines National Engineering School of Sfax (ENIS) University of Sfax Sfax Tunisia Department of Electrical and Electronic Engineering Science Faculty of Engineering and the Built Environment University of Johannesburg Johannesburg South Africa

The diagnosis of common diseases, in which people suffer from several bad health conditions, is a complex medical challenge. This study investigated the use of machine learning methods combined with the Chi-square feature selection technique to improve the accuracy and efficiency of comorbidity diseases diagnosis. Using various decision trees of machine learning algorithms, random forest, Gradient Boost, AdaBoost, Bagging, and extra trees, this research aimed to improve the identification and prediction of comorbid conditions and ultimately advance early detection and treatment strategies. Using the selection of Chi-Square features helped give priority to the most relevant attributes, reduce noise, and refine the models. The results showed that both the AdaBoost and Gradient Boost algorithms obtained an accuracy rate of 91.33%, confirming their efficacy in comorbidity diseases diagnosis. However, it is essential to ensure their reliability and efficacy in the real clinical environment, including the practical implementation and validation of these methods, to improve patient care and medical decisions.

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Phyllotaxis-inspired nanosieves with multiplexed orbital angular momentum

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eLight 2021年第1期1卷 46-56页

作者： Zhongwei Jin David Janoschka Junhong Deng Lin Ge Pascal Dreher Bettina Frank Guangwei Hu Jincheng Ni Yuanjie Yang Jing Li Changyuan Yu Dangyuan Lei Guixin Li Shumin Xiao Shengtao Mei Harald Giessen Frank Meyer zu Heringdorf Cheng-Wei Qiu Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Singapore College of Optical and Electronic Technology China Jiliang UniversityHangzhou 310018China Faculty of Physics and Center for Nanointegration Duisburg-Essen(CENIDE) University of Duisburg-EssenLotharstrasse 1-2147057 DuisburgGermany Department of Materials Science and Engineering Shenzhen Institute for Quantum Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China Beijing Qianjunyide Technology Co.Ltd Beijing 100031China. Physics Institute and Stuttgart Center of Photonics Engineering(SCoPE) University of Stuttgart70569 Stutt-gartGermany. School of Physics University of ElectronicScience and Technology of ChinaChengdu 611731China. Key Laboratory of Optoelectronic Materials Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China. Department of Electronic and Information Engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong Kong SARChina. Department of Materials Science and Engineering City University of Hong Kong83 Tat Chee AvenueKowloonHong Kong SARChina. State Key Laboratory On Tunable Laser Technology Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information SystemShenzhen Graduate SchoolHarbin Institute of TechnologyShenzhen 518055China.

Nanophotonic platforms such as metasurfaces,achieving arbitrary phase profiles within ultrathin thickness,emerge as miniaturized,ultracompact and kaleidoscopic optical vortex ***,it is often required to segment or interleave independent sub-array metasurfaces to multiplex optical vortices in a single nano-device,which in turn affects the device’s compactness and channel ***,inspired by phyllotaxis patterns in pine cones and sunflowers,we theoretically prove and experimentally report that multiple optical vortices can be produced in a single compact phyllotaxis nanosieve,both in free space and on a chip,where one meta-atom may contribute to many vortices *** time-resolved dynamics of on-chip interference wavefronts between multiple plasmonic vortices was revealed by ultrafast time-resolved photoemission electron *** nature-inspired optical vortex generator would facilitate various vortex-related optical applications,including structured wavefront shaping,free-space and plasmonic vortices,and high-capacity information metaphotonics.

关键词： Phyllotaxis vortex nanosieve Free-space Plasmonic vortices Ultrafast time-resolved

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SOLAS: Superpositioning an Optical Lens in Automotive Simulation

arXiv

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arXiv 2025年

作者： Jakab, Daniel Barthel, Julian Braun, Alexander Mohandas, Reenu Deegan, Brian Michael Kumbham, Mahendar Molloy, Dara Collins, Fiachra Scanlan, Anthony Eising, Ciarán Dept. of Electronic and Computer Engineering University of Limerick Castletroy Co. Limerick V94 T9PX Ireland Faculty of Electrical Engineering & Information Technology University of Applied Sciences Düsseldorf40476 Germany Dept. of Electrical and Electronic Engineering University of Galway GalwayH91 TK33 Ireland Valeo Vision Systems Tuam GalwayDY1 22DJ Ireland Lero the Science Foundation Ireland Research Centre for Software University of Limerick LimerickV94 T9PX Ireland

Automotive Simulation is a potentially cost-effective strategy to identify and test corner case scenarios in automotive perception. Recent work has shown a significant shift in creating realistic synthetic data for road traffic scenarios using a video graphics engine. However, a gap exists in modeling realistic optical aberrations associated with cameras in automotive simulation. This paper builds on the concept from existing literature to model optical degradations in simulated environments using the Python-based ray-tracing library KrakenOS. As a novel pipeline, we degrade automotive fisheye simulation using an optical doublet with +/-2◦ Field of View(FOV), introducing realistic optical artifacts into two simulation images from SynWoodscape and Parallel Domain Woodscape. We evaluate KrakenOS by calculating the Root Mean Square Error (RMSE), which averaged around 0.023 across the RGB light spectrum compared to Ansys Zemax OpticStudio, an industrial benchmark for optical design and simulation. Lastly, we measure the image sharpness of the degraded simulation using the ISO12233:2023 Slanted Edge Method and show how both qualitative and measured results indicate the extent of the spatial variation in image sharpness from the periphery to the center of the degradations. © 2025, CC BY.

关键词： Ray tracing

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Image Inpainting and Classification Agent Training Based on Reinforcement Learning and Generative Models with Attention Mechanism

Image Inpainting and Classification Agent Training Based on ...

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International Conference on Microelectronics, ICM

作者： Chiagoziem C. Ukwuoma Md Belal Bin Heyat Mahmoud Masadeh Faijan Akhtar Qin Zhiguang Emmanuel Bondzie - Selby Omar AlShorman Fahad Alkahtani School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu Sichuan China IoT Research Center College of Computer Science and Software Engineering Shenzhen University Shenzhen Guangdong China Hijjawi Faculty for Engineering Yarmouk University Irbid Jordan School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu Sichuan China Faculty of Engineering and AlShrouk Trading Company Najran University Najran KSA Faculty of Engineering Najran University Najran KSA

ISBN: (纸本)9781665408400

What distinguishes the field of artificial intelligence (AI) from others is to develop fully independent agents that learn optimal behavior, change, and evolve solely through the communication of trial and error with the surrounding environment. Reinforcement learning (RL) can be seen in multiple aspects of Machine Learning (ML), provided the environment, reward, actions, the state will be defined. Agent training in previous years is seen to only relate to robotics, games, and self-driving cars. While trying to divert the focus of researchers from the view of self-driving cars, games, robots, etc. Here, we investigated using reinforcement learning in the aspect of task completion. We deployed our architecture in an inpainting task where the agent generates the distorted or missing image content into an eminent fidelity completed the image by using reinforcement learning to influence the generative model utilized. The Generative Adversary Network (GAN) problem of not being steady and challenging to train was overwhelmed by utilizing latent space representation. The dimension is reduced compared to the distorted or corrupted image in training the GAN. Then reinforcement learning was deployed to pick the correct GAN input to get the image’s latent space representation that is most suitable for the current input of the missing or distorted image region. In this paper, we also learned that the trained agent enhances the accuracy in a classification task of images with missing data. We successfully examined the classification enhancement on images missing 30%, 50%, and 70%.

关键词： Training Pipelines Reinforcement learning Games Generative adversarial networks Real-time systems Autonomous automobiles

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Double-SP Method to Enhance Privacy and Security of Smart City Applications

Double-SP Method to Enhance Privacy and Security of Smart Ci...

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Nour Mahmoud Bahbouh Abdulelah Alhussain Hassan Hakami Yaser Mohammed Aljohani Adnan Ahmed Abi Sen Ahmad Alkhodre Aeshah Alsughayyir Department of Information and Communication Sciences Granada University Granada Spain Saudi Electronic University Al-Madinah Saudi Arabia YasRef Program Yanbu Saudi Arabia Computing and Information Technology Islamic University Al-Madinah Saudi Arabia Faculty of Computer and Information Systems Islamic University Al-Madinah Saudi Arabia College of Computer Science and Engineering Taibah University Al-Madinah Saudi Arabia

Smart cities promise a lot of well-being to their users in all areas of life through millions of applications and services. Smart services rely heavily on collecting data and the preferences of users. But on the dark side, the users' information is posed to threat and penetration during transmission or stored far in the clouds. Depending on encryption only is not sufficient if the attacker has strong resources or if the attacker is the service provider (SP) itself. In addition, changing data before sending is not a practical solution in many systems because of the adverse impact on the quality of a main service. This research presented a new idea to address the issue of protection. The proposed method enhanced the privacy and security of users' data without affecting the accuracy of service. The core of the suggested solution relies on a knowledge base of services that are managed by experts. Also, the solution depends on fog nodes to measure the level of security and privacy of users' queries without delay. Moreover, the fog nodes manage contact with SPs. Finally, the proposed method divided the SP into two, one for user queries and the other for user data. The simulation and analytical discussion on a practical case in smart cities demonstrated the superiority of the proposed approach over previous methods in the level of protection by maintaining the quality of services, and the resistance to attacks.

关键词： Resistance Privacy Data privacy Machine learning algorithms Smart cities Knowledge based systems Quality of service

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On the outage performance of partial relay selection aided noma system with energy harvesting and outdated csi over non-identical channels

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Progress In Electromagnetics Research C 2019年 95卷 107-117页

作者： Owolawi Odeyemi, Kehinde O. Department of Computer Systems Engineering Tshwane University of Technology Pretoria0001 South Africa Department of Electrical and Electronic Engineering Faculty of Technology University of Ibadan Nigeria

In this paper, the outage probability performance of energy harvesting based partial relay selection aided non-orthogonal multiple access (NOMA) system under outdated channel state information is studied. The source to relays link is assumed to follow Rayleigh fading distribution while the relay nodes to users are subjected to Nakagami-m distribution. The relay nodes employ an energy harvesting power splitting-based relaying protocol to transmit the source information to the users. At the destination, each user is equipped with multiple antennas, and maximum ratio combining is considered for signal reception. In order to evaluate the system performance, the outage probability closed-form expression for the concerned system is derived. The results demonstrate the significant impact of system and channel parameters on the system performance. In addition, the advantage of NOMA over the conventional orthogonal multiple access is also presented. Finally, the accuracy of the derived outage expression is validated through the Monte-Carlo simulation. © 2019, Electromagnetics Academy. All rights reserved.

关键词： Energy harvesting

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Inverse Design with Dynamic Mode Decomposition

arXiv

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arXiv 2025年

作者： Zhu, Yunpeng Cheng, Liangliang Jing, Anping Huo, Hanyu Lang, Ziqiang Zhang, Bo Kutz, J. Nathan School of Engineering and Material Science Queen Mary University of London LondonE1 4NS United Kingdom ENTEG Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands School of Mechanical Engineering Ningxia University Yinchuan750021 China School of Chemistry and Material Science University of Science and Technology of China Hefei230026 China School of Electrical and Electronic Engineering The University of Sheffield SheffieldS10 2TN United Kingdom Department of Applied Mathematics and Electrical and Computer Engineering University of Washington SeattleWA United States

We introduce a computationally efficient method for the automation of inverse design in science and engineering. Based on simple least-square regression, the underlying dynamic mode decomposition algorithm can be used to construct a low-rank subspace spanning multiple experiments in parameter space. The proposed inverse design dynamic mode composition (ID-DMD) algorithm leverages the computed low-dimensional subspace to enable fast digital design and optimization on laptop-level computing, including the potential to prescribe the dynamics themselves. Moreover, the method is robust to noise, physically interpretable, and can provide uncertainty quantification metrics. The architecture can also efficiently scale to large-scale design problems using randomized algorithms in the ID-DMD. The simplicity of the method and its implementation are highly attractive in practice, and the ID-DMD has been demonstrated to be an order of magnitude more accurate than competing methods while simultaneously being 3-5 orders faster on challenging engineering design problems ranging from structural vibrations to fluid dynamics. Due to its speed, robustness, interpretability, and ease-of-use, ID-DMD in comparison with other leading machine learning methods represents a significant advancement in data-driven methods for inverse design and optimization, promising a paradigm shift in how to approach inverse design in *** Codes 37M05, 37M10, 37M21 Copyright © 2025, The Authors. All rights reserved.

关键词： Dynamic mode decomposition

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