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3rd International Conference on Advancement in Electronics and Communication engineering, AECE 2023

作者： Salama, Ramiz Al-Turjman, Sinem Altrjman, Chadi Al-Turjman, Fadi Prakash, R.Om Yadav, Satya Prakash Vats, Satvik Ai and Robotics Institute Research Center for Ai and IoT Department of Computer Engineering Near East University Near East Boulevard TRNC Mersin 10 Nicosia99138 Turkey Ai and Robotics Institute Near Artificial Intelligence Engineering Dept Near East University Mersin10 Nicosia Turkey Waterloo University Department of Chemical Engineering ONN2L 3G1 Canada Noida Instue Engineering and Technology U.P Greator Noida201306 India Department of Computer Science and Engineering Greater Noida201306 India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350330724

Smart cities are cities that are designed to be more efficient, sustainable, and connected. As our cities grow and become more complex, it's important to find new ways to address the challenges that arise, such as security, privacy, and mobility. This is where mobile cloud computing and biometric authentication come in. Mobile cloud computing is a way to provide cloud computing services to mobile devices, which means people can access services and data from anywhere and at any time. Biometric authentication is a method of identifying people based on their unique physical or behavioral characteristics, like fingerprints, facial recognition, or voice recognition. These two technologies can be combined to create a secure and personalized environment for residents and visitors in smart cities. By using mobile devices, IoT devices, wireless sensor networks, and edge computing, we can collect real-time data that can be used for big data analytics and machine learning. This means we can optimize city services, like traffic management, waste management, or energy consumption, and enhance the quality of life for people living in smart cities. However, the use of these technologies also poses significant security and privacy risks, so it's important to design systems that are secure and privacy-preserving. This requires interdisciplinary research and collaboration between experts in different fields. In summary, mobile cloud computing and biometric authentication have the potential to transform smart cities by creating a more secure and personalized environment for residents and visitors. But we must also be mindful of the potential risks and work together to address them. © 2023 IEEE.

关键词： Mobile cloud computing

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A NovelMethod for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

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computer Modeling in engineering & sciences 2024年第2期138卷 1951-1979页

作者： Salma Khan Muhammad Gulistan NasreenKausar Seifedine Kadry Jungeun Kim Department of Mathematics and Statistics Hazara UniversityMansehra21120Pakistan Department of Mathematics Faculty of Arts and SciencesYildiz Technical UniversityEsenlerIstanbul34210Turkey Department of Applied Data Science Noroff University CollegeKristiansand4612Norway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityP.O.Box 13-5053ByblosLebanon Department of Software and CMPSI Konju National UniversityCheonan31080Korea

Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set(q−ROFHS)to enhance the formal representation of human thought processes and evaluate tourism carrying *** approach can capture the imprecision and ambiguity often present in human *** the advanced mathematical tools in this field,the study has also incorporated the Einstein aggregation operator and score function into the q−ROFHS values to supportmultiattribute decision-making *** implementing this technique,effective plans can be developed for social and economic development while avoiding detrimental effects such as overcrowding or environmental damage caused by tourism.A case study of selected tourism carrying capacity will demonstrate the proposed methodology.

关键词： q−Rung orthopair fuzzy hypersoft set decision-making tourism carrying capacity aggregation operator

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Framework for Ship Trajectory Forecasting Based on Linear Stationary Models Using Automatic Identification System

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Procedia computer science 2023年 218卷 1463-1474页

作者： Smita Srivastava Lovneet Kumar R. Jeyanthi K. Deepa Vinay Aggrawal Department of Computer Science and Engineering Centre for Artificial Intelligence and Robotics Defense Research and Development Organization Bangalore Karnataka Department of Electronics and Communication Engineering Department of Electrical and Electronics Engineering Amrita School of Engineering Bengaluru Amrita Vishwa Vidyapeetham India

Maritime surveillance is of utmost priority for a nation's security, and hence it's economy. For maritime awareness, coastal surveillance, and maritime activities in the Region of Interest (ROI) should be monitored. One of the ways to keep this in check is to restrain unwanted infiltration. Monitoring unwanted infiltration is feasible through vessel trajectory forecasting and anomaly detection in real time. Most solutions for trajectory predictions are available but require a huge amount of historical data, and high-power computing resources. Here, the requirement is developing a decision support framework consisting of both lite weight approaches for short-term predictions and deep learning-based techniques for long-term forecasting. This paper aims to find the suitability of Linear Stationary Models (LSM) like the Auto-Regressive Integrated Moving Average Model (ARIMA) for predicting and forecasting the Vessel Trajectory as means of lite weight short-term predictions. For this purpose, the Automatic Identification System (AIS) dataset of the U.S. West Coast is used. The significant effort was for data pre-processing to create a robust dataset for model training. An appropriate model after the model-selection process is used for trajectory forecasting. The model's accuracy is validated using Root Mean Square Error (RMSE) performance indices for residual and forecast errors. A window generator model is integrated with the best-fitted ARIMA model for recursive real-time predictions, with varied sizes and visualization. The proposed time-series model provided a very high accuracy as the RMSE value for prediction and 48 hours forecast are 0.023 and 0.017, respectively.

关键词： Maritime Surveillance Trajectory Forecast Time Series Analysis Auto-Regressive Integrated Moving Average Model Automatic Identification System Window Generator

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Simultaneous strain and temperature monitoring through resonance frequency mapping with identical PM-FBGs 28

Simultaneous strain and temperature monitoring through reson...

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28th International Conference on Optical Fiber Sensors, OFS 2023

作者： Choe, Wontae Kim, Gyeong Hun Kim, Chang-Seok Chung, Youngjoo Department of Optics and Mechatronics Engineering Pusan National University Busan Korea Republic of Engineering Research Center for Color-Modulated Extra-Sensory Perception Technology Pusan National University Busan Korea Republic of School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju Korea Republic of

ISBN: (纸本)9781957171302

This study introduces a novel quasi-distributed sensing system that utilizes identical weak polarization maintaining-fiber Bragg gratings (PM-FBGs) and resonance frequency mapping (RFM) for simultaneous strain and temperature measurements. By considering the differences in cavity length change response based on the polarization axes. © Optica Publishing Group 2023, © 2023 The Author(s)

关键词： Fiber Bragg gratings

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OUS: Bridging Scene Context and Facial Features to Overcome the Rigid Cognitive Problem 39

OUS: Bridging Scene Context and Facial Features to Overcome ...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Mai, Xinji Wang, Haoran Tao, Zeng Lin, Junxiong Yan, Shaoqi Wang, Yan Yu, Jiawen Tong, Xuan Li, Yating Zhang, Wenqiang Shanghai Engineering Research Center of AI & Robotics Academy for Engineering & Technology Fudan University China School of Electrical and Electronic Engineering Shanghai Insittute of Techonlogy China Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University China Engineering Research Center of AI & Robotics Ministry of Education Fudan University China

ISBN: (纸本)157735897X

Dynamic Facial Expression Recognition (DFER) is crucial for affective computing but often overlooks the impact of scene context. We have identified a significant issue in current DFER tasks: human annotators typically integrate emotions from various angles, including environmental cues and body language, whereas existing DFER methods tend to consider the scene as noise that needs to be filtered out, focusing solely on facial information. We refer to this as the Rigid Cognitive Problem. The Rigid Cognitive Problem can lead to discrepancies between the cognition of annotators and models in some samples. To align more closely with the human cognitive paradigm of emotions, we propose an Overall Understanding of the Scene DFER method (OUS). OUS effectively integrates scene and facial features, combining scene-specific emotional knowledge for DFER. Extensive experiments on the two largest datasets in the DFER field, DFEW and FERV39k, demonstrate that OUS significantly outperforms existing methods. By analyzing the Rigid Cognitive Problem, OUS successfully understands the complex relationship between scene context and emotional expression, closely aligning with human emotional understanding in real-world scenarios. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Quantum-dot and organic hybrid light-emitting diodes employing a blue common layer for simple fabrication of full-color displays

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Nano research 2022年第7期15卷 6477-6482页

作者： Suhyeon Lee Donghyo Hahm Suk-Young Yoon Heesun Yang Wan Ki Bae Jeonghun Kwak Department of Electrical and Computer Engineering Seoul National UniversitySeoul 08826Republic of Korea Inter-university Semiconductor Research Center(ISRC) Seoul National UniversitySeoul 08826Republic of Korea SKKU Advanced Institute of Nanotechnology(SAINT) School of Nano Science&TechnologySungkyunkwan University(SKKU)Suwon 16419Republic of Korea Department of Materials Science and Engineering Hongik UniversitySeoul 04066Republic of Korea

Colloidal quantum-dot(QD)light-emitting diodes(QLEDs)have been in the forefront of future display devices due to their outstanding optoelectronic ***,a complicated solution-process for patterning the red,green,and blue QDs deteriorates the QLED performance and limits the resolution of full-color ***,we report a novel concept of QD–organic hybrid light-emitting diodes by introducing an organic blue common layer(BCL)which is deposited through a common mask over the entire *** from the optimized device structure,red and green QLEDs retained their color coordinates despite the presence of the ***,adopting the BCL improved the external quantum efficiency of green and red QLEDs by 38.4%and 11.7%,respectively,due to the Förster resonance energy transfer from the BCL to the adjacent QD *** the BCL structure,we could simply demonstrate a full-color QD-organic hybrid device in a single *** believe that this device architecture is practically applicable for easier fabrication of solution-processed,highresolution,and full-color displays with reduced process steps.

关键词： quantum-dot light-emitting diode(QLEDs) organic light-emitting diode blue common layer full-color display reduced process step

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Probabilistically Robust Trajectory Planning of Multiple Aerial Agents

Probabilistically Robust Trajectory Planning of Multiple Aer...

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International Conference on Control, Automation, robotics and Vision (ICARCV)

作者： Christian Vitale Savvas Papaioannou Panayiotis Kolios Georgios Ellinas Department of Electrical and Computer Engineering KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus Department of Computer Science KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Current research on robust trajectory planning for autonomous agents aims to mitigate uncertainties arising from disturbances and modeling errors while ensuring guaranteed safety. Existing methods primarily utilize stochastic optimal control techniques with chance constraints to maintain a minimum distance among agents with a guaranteed probability. However, these approaches face challenges, such as the use of simplifying assumptions that result in linear system models or Gaussian disturbances, which limit their practicality in complex realistic scenarios. To address these limitations, this work introduces a novel probabilistically robust distributed controller enabling autonomous agents to plan safe trajectories, even under non-Gaussian uncertainty and nonlinear systems. Leveraging exact uncertainty propagation techniques based on mixed-trigonometric-polynomial moment propagation, this method transforms non-Gaussian chance constraints into deterministic ones, seamlessly integrating them into a distributed model predictive control framework solvable with standard optimization tools. Simulation results demonstrate the effectiveness of this technique, highlighting its ability to consistently handle various types of uncertainty, ensuring robust and accurate path planning in complex scenarios.

关键词： Uncertainty Trajectory planning Simulation Stochastic processes Transforms Probabilistic logic Autonomous agents Safety Trajectory Standards

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HPPS: A Hierarchical Progressive Perception System for Luggage Trolley Detection and Localization at Airports

arXiv

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arXiv 2024年

作者： Sun, Zhirui Zhang, Zhe Zhao, Jieting Ye, Hanjing Wang, Jiankun Shenzhen Key Laboratory of Robotics Perception and Intelligence Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China Shenzhen Key Laboratory of Robotics and Computer Vision Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China

The robotic autonomous luggage trolley collection system employs robots to gather and transport scattered luggage trolleys at airports. However, existing methods for detecting and locating these luggage trolleys often fail when they are not fully visible. To address this, we introduce the Hierarchical Progressive Perception System (HPPS), which enhances the detection and localization of luggage trolleys under partial occlusion. The HPPS processes the luggage trolley’s position (x, y) and orientation (θ) separately, which requires only RGB images for labeling and training, eliminating the need for 3D coordinates and alignment. The HPPS can accurately determine the position of the luggage trolley with just one well-detected keypoint and estimate the luggage trolley’s orientation when it is partially occluded. Once the luggage trolley’s initial pose is detected, HPPS updates this information continuously to refine its accuracy until the robot begins grasping. The experiments on detection and localization demonstrate that HPPS is more reliable under partial occlusion compared to existing methods. Its effectiveness and robustness have also been confirmed through practical tests in actual luggage trolley collection tasks. A website about this work is available at HPPS. Copyright © 2024, The Authors. All rights reserved.

关键词： robotics

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Single-photon optical modulation at room temperature enabled by an electron avalanche in a photodiode

Single-photon optical modulation at room temperature enabled...

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Sychev, Demid V. Chen, Peigang Yang, Morris Fruhling, Colton Lagutchev, Alexei Kildishev, Alexander V. Boltasseva, Alexandra Shalaev, Vladimir M. Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Quantum Science Center National Quantum Information Science Research Center of the U.S. Department of Energy Oak RidgeTN37931 United States

We show all-optical modulation of a 1550-nm wavelength beam with a power of around 10mW controlled by a single-photon intensity signal in an avalanche photodiode. © 2024 The Author(s) © Optica Publishing Gro... 详细信息

ISBN: (纸本)9781957171395

关键词： Avalanche photodiodes

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Semantic Template-based Convolutional Neural Network for Text Classification

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ACM Transactions on Asian and Low-Resource Language Information Processing 2023年第11期22卷 1-21页

作者： Chang, Yung-Chun Ng, Siu Hin Chen, Jung-Peng Liang, Yu-Chi Hsu, Wen-Lian Graduate Institute of Data Science Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan Snhcc Tigp Academia Sinica National Cheng Chi University Taipei Taiwan Institute of Information Systems and Applications National Tsing Hua University Hsinchu Taiwan Department of Computer Science and Information Engineering College of Information and Electrical Engineering Asia University Taichung Taiwan Pervasive Ai Research Labs Ministry of Science and Technology Hsinchu City Taiwan

We propose a semantic template-based distributed representation for the convolutional neural network called Semantic Template-based Convolutional Neural Network (STCNN) for text categorization that imitates the perceptual behavior of human comprehension. STCNN is a highly automatic approach that learns semantic templates that characterize a domain from raw text and recognizes categories of documents using a semantic-infused convolutional neural network that allows a template to be partially matched through a statistical scoring system. Our experiment results show that STCNN effectively classifies documents in about 140,000 Chinese news articles into predefined categories by capturing the most prominent and expressive patterns and achieves the best performance among all compared methods for Chinese topic classification. Finally, the same knowledge can be directly used to perform a semantic analysis task. © 2023 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Semantics

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