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Data-driven Global Ocean Modeling for Seasonal to Decadal Prediction

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arXiv 2024年

作者： Guo, Zijie Lyu, Pumeng Ling, Fenghua Bai, Lei Luo, Jing-Jia Boers, Niklas Yamagata, Toshio Izumo, Takeshi Cravatte, Sophie Capotondi, Antonietta Ouyang, Wanli School of Computer Science Fudan University Shanghai China Shanghai Artificial Intelligence Laboratory Shanghai China School of Future Technology Nanjing University of Information Science and Technology Nanjing China Earth System Modelling School of Engineering and Design Technical University of Munich Munich Germany Potsdam Institute for Climate Impact Research Potsdam Germany Application Laboratory Japan Agency for Marine-Earth Science and Technology Yokohama Japan Tahiti French Polynesia LEGOS IRD UT3 CNES CNRS Université de Toulous Toulouse France Nouméa New Caledonia Cooperative Institute for Research in Environmental Sciences University of Colorado Boulder Colorado Boulder United States NOAA Physical Sciences Laboratory Colorado Boulder United States

Accurate ocean dynamics modeling is crucial for enhancing understanding of ocean circulation, predicting climate variability, and tackling challenges posed by climate change. Despite improvements in traditional numerical models, predicting global ocean variability over multi-year scales remains challenging. Here, we propose ORCA-DL (Oceanic Reliable foreCAst via Deep Learning), the first data-driven 3D ocean model for seasonal to decadal prediction of global ocean circulation. ORCA-DL accurately simulates three-dimensional ocean dynamics and outperforms state-of-the-art dynamical models in capturing extreme events, including El Niño-Southern Oscillation and upper ocean heatwaves. This demonstrates the high potential of data-driven models for efficient and accurate global ocean forecasting. Moreover, ORCA-DL stably emulates ocean dynamics at decadal timescales, demonstrating its potential even for skillful decadal predictions and climate projections. Copyright © 2024, The Authors. All rights reserved.

关键词： Digital elevation model

A novel Skin lesion prediction and classification technique: ViT-GradCAM

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Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) 2024年第9期30卷 e70040页

作者： Muhammad Shafiq Kapil Aggarwal Jagannathan Jayachandran Gayathri Srinivasan Rajasekhar Boddu Adugna Alemayehu School of Information Engineering Qujing Normal University Qujing China. Key Laboratory of Intelligent Sensor and System Design College of Information Engineering Qujing Normal University Qujing China. Department of CSE Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India. Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems Vellore Institute of Technology Katpadi Vellore India. Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India. Department of AIML Gokaraju Rangaraju Institute of Engineering and Technology Bachupally Hyderabad India. Lecturer in Software Engineering Wachemo University Hosaina Ethiopia.

BACKGROUND:Skin cancer is one of the highly occurring diseases in human life. Early detection and treatment are the prime and necessary points to reduce the malignancy of infections. Deep learning techniques are supplementary tools to assist clinical experts in detecting and localizing skin lesions. Vision transformers (ViT) based on image segmentation classification using multiple classes provide fairly accurate detection and are gaining more popularity due to legitimate multiclass prediction capabilities. MATERIALS AND METHODS:In this research, we propose a new ViT Gradient-Weighted Class Activation Mapping (GradCAM) based architecture named ViT-GradCAM for detecting and classifying skin lesions by spreading ratio on the lesion's surface area. The proposed system is trained and validated using a HAM 10000 dataset by studying seven skin lesions. The database comprises 10 015 dermatoscopic images of varied sizes. The data preprocessing and data augmentation techniques are applied to overcome the class imbalance issues and improve the model's performance. RESULT:The proposed algorithm is based on ViT models that classify the dermatoscopic images into seven classes with an accuracy of 97.28%, precision of 98.51, recall of 95.2%, and an F1 score of 94.6, respectively. The proposed ViT-GradCAM obtains better and more accurate detection and classification than other state-of-the-art deep learning-based skin lesion detection models. The architecture of ViT-GradCAM is extensively visualized to highlight the actual pixels in essential regions associated with skin-specific pathologies. CONCLUSION:This research proposes an alternate solution to overcome the challenges of detecting and classifying skin lesions using ViTs and GradCAM, which play a significant role in detecting and classifying skin lesions accurately rather than relying solely on deep learning models.

关键词： Grad‐CAM Multi‐Headed Self attention (MSA) linear patch projection multilayer perceptron (MLP) skin lesion transformer encoder vision transformer (ViT)

Identifying and Anticipating Cyberattacks That Could Cause Physical Damage to Industrial Control systems

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IEEE Power and Energy Technology systems Journal 2019年第4期6卷 172-182页

作者： Angle, Matthew G. Madnick, Stuart Kirtley, James L. Khan, Shaharyar Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Sloan School of Management School of Engineering Massachusetts Institute of Technology CambridgeMA02139 United States System Design and Management Program Massachusetts Institute of Technology CambridgeMA02139 United States

Physical control systems are increasingly controlled by reconfigurable, network-enabled devices to increase flexibility and ease commissioning and maintenance. Such capability creates vulnerabilities. Devices may be remotely reprogrammed by a malicious actor to act in unintended ways, causing physical damage to mechanical equipment, infrastructure, and life and limb. In this paper, past examples of actual damage to cyber-physical systems are shown, threats posed by software-controlled variable frequency drives (VFDs) are analyzed, and a small-scale version of an attack on ubiquitous VFD equipment is demonstrated. © 2014 IEEE.

关键词： Embedded systems

A study on AI-FML robotic agent for student learning behavior ontology construction

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arXiv 2020年

作者： Lee, Chang-Shing Wang, Mei-Hui Kuan, Wen-Kai Ciou, Zong-Han Tsai, Yi-Lin Chang, Wei-Shan Li, Lian-Chao Kubota, Naoyuki Huang, Tzong-Xiang Sato-Shimokawara, Eri Yamaguchi, Toru Dept. of Computer Science and Information Engineering National University of Tainan Tainan Taiwan Dept. of Mechanical Systems Engineering Tokyo Metropolitan University Tokyo Japan Dept. of System Design Tokyo Metropolitan University Tokyo Japan

In this paper, we propose an AI-FML robotic agent for student learning behavior ontology construction which can be applied in English speaking and listening domain. The AI-FML robotic agent with the ontology contains the perception intelligence, computational intelligence, and cognition intelligence for analyzing student learning behavior. In addition, there are three intelligent agents, including a perception agent, a computational agent, and a cognition agent in the AI-FML robotic agent. We deploy the perception agent and the cognition agent on the robot Kebbi Air. Moreover, the computational agent with the Deep Neural Network (DNN) model is performed in the cloud and can communicate with the perception agent and cognition agent via the Internet. The proposed AI-FML robotic agent is applied in Taiwan and tested in Japan. The experimental results show that the agents can be utilized in the human and machine co-learning model for the future education. Copyright © 2020, The Authors. All rights reserved.

关键词： Ontology

Facial Emotions Recognition using Convolutional Neural Net

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arXiv 2020年

作者： Ghaffar, Faisal Ali, Imad Khan, Sarwar Ahmad, Wasim Ali, Khursheed System Design Engineering Department University of Waterloo Canada Department of Computer Science University of Swat KP Pakistan Institute of Information Sciences Academia Sinica Taiwan Department of Computer Science National ChengChi University Taiwan Department of Computer Science Insititute of Bussiness Administration Sindh Sukkur Pakistan

Facial expressions vary from person to person, and the brightness, contrast, and resolution of every random image are different. This is why recognizing facial expressions is very difficult. This article proposes an efficient system for facial emotion recognition for the seven basic human emotions (angry, disgust, fear, happy, sad, surprise, and neutral), using a convolution neural network (CNN), which predicts and assigns probabilities to each emotion. Since deep learning models learn from data, thus, our proposed system processes each image with various pre-processing steps for better prediction. Every image was first passed through the face detection algorithm to include in the training dataset. As CNN requires a large amount of data, we duplicated our data using various filters on each image. Pre-processed images of size 80*100 are passed as input to the first layer of CNN. Three convolutional layers were used, followed by a pooling layer and three dense layers. The dropout rate for the dense layer was 20%. The model was trained by combining two publicly available datasets, JAFFE and KDEF. 90% of the data was used for training, while 10% was used for testing. We achieved maximum accuracy of 78.1 % using the combined dataset. Moreover, we designed an application of the proposed system with a graphical user interface that classifies emotions in real-time. Copyright © 2020, The Authors. All rights reserved.

关键词： Emotion Recognition

Improvement of mid-air acoustic tweezers for non-contact particle picker

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Improvement of mid-air acoustic tweezers for non-contact par...

IEEE International Ultrasonics Symposium

作者： Yutaka Yamamoto Kan Okubo Electrical Engineering and Computer Science System Design Tokyo Metropolitan University Tokyo Japan

In recent years, there are some studies that report the method to levitate and manipulate a particle in air using ultrasonic transducers array. In previous study, we proposed the method to pick up a particle like a tweezers using ultrasonic waves and low-reflection stages. This method has the potential which increase applications of ultrasonic levitation. In this study, we designed and fabricated high-power ultrasonic transducers array and compared new and original array.

关键词： Acoustics Ultrasonic transducer arrays Ultrasonic transducers Acoustic arrays Phased arrays Acoustic measurements

Observation of intrinsic chiral bound states in the continuum

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arXiv 2022年

作者： Chen, Yang Deng, Huachun Sha, Xinbo Chen, Weijin Wang, Ruize Chen, Yuhang Wu, Dong Chu, Jiaru Kivshar, Yuri S. Xiao, Shumin Qiu, Cheng-Wei Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Chinese Academy of Sciences Key Laboratory of Mechanical Behavior and Design of Materials Department of Precision Machinery and Precision Instrumentation University of Science and Technology of China Hefei230027 China Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Harbin Institute of Technology Shenzhen518055 China Nonlinear Physics Center Research School of Physics Australian National University CanberraACT2601 Australia Pengcheng Laboratory Shenzhen518055 China

Photons with spin angular momentum possess intrinsic chirality which underpins many phenomena including nonlinear optics1, quantum optics2, topological photonics3 and chiroptics4. Intrinsic chirality is weak in natural materials, and recent theoretical proposals5-7 aimed to enlarge circular dichroism by resonant metasurfaces supporting bound states in the continuum that enhance substantially chiral light-matter interaction. Those insightful works resort to three-dimensional sophisticated geometries, which are too challenging to be realized for optical frequencies8. Therefore, most of the experimental attempts9-11 showing strong circular dichroism rely on false/extrinsic chirality by employing either oblique incidence9, 10 or structural anisotropy11. Here, we report on the experimental realization of true/intrinsic chiral response with resonant metasurfaces where the engineered slant geometry breaks both in-plane and out-of-plane symmetries. Our result marks the first observation of intrinsic chiral bound states in the continuum with near-unity chiral dichroism of 0.93 and record-high quality factor exceeding 2663 for visible frequencies. Our chiral metasurfaces promise a plethora of applications in chiral light sources and detectors, chiral sensing, valleytronics and asymmetric photocatalysis. © 2022, CC BY.

关键词： Dichroism

Variations in the acoustic measurement of earbud earphones in an ane-choic chamber due to changes in the earphone placement in ear Concha

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Canadian Acoustics - Acoustique Canadienne 2020年第4期48卷 29-40页

作者： Pawar, S.J. Liu, Y.C. Huang, Jin H. Department of Applied Mechanics Motilal Nehru National Institute of Technology Allahabad Prayagraj India Bachelor's Program in Precision System Design Feng Chia University Taichung Taiwan Department of Mechanical and Computer-Aided Engineering Feng Chia University Taichung Taiwan

The growth of consumer electronic products is encouraged by innovations and has stimulated the persistent development of earphones for high-quality sound reproduction. Earbud earphone is located in the concha of the human ear facing an ear-canal. The placement of earphones in the concha plays a remarkable role in the sound pressure level response of an earphone. In this study, ten earphones were tested for frequency response and total harmonic distortion using head and torso simulator in an anechoic chamber. Three positions and two orientations of earphones in the concha were identified for measurement. Based on the responses of all earphones at all orientations and positions, it is concluded that there is a variation in the frequency response and total harmonic distortion. Even though the variation is small in magnitude, its effect on sound perception, sound exposure, and the hearing threshold is phenomenal. Based on the proposition presented in this work and the safe daily sound exposure, it has been determined that the variation in the frequency response affects the perceived loudness of sound and can cause signif-icant differences in the daily sound exposure limit for a human being. © 2020, Canadian Acoustical Association. All rights reserved.

关键词： Frequency response

Low-cost low-power in-vehicle occupant detection with mm-wave FMCW radar

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Low-cost low-power in-vehicle occupant detection with mm-wav...

IEEE Sensors

作者： Mostafa Alizadeh Hajar Abedi George Shaker Electrical and Computer Engineering University of Waterloo Ontario Canada System Design Engineering University of Waterloo Ontario Canada

In this paper, we use a low-cost low-power mm-wave frequency modulated continuous wave (FMCW) radar for the in-vehicle occupant detection. We propose an algorithm using Capon filter for the joint range-azimuth estimation. Then, the minimum necessary features are extracted to train machine learning classifiers to have reasonable computational complexity while achieving high accuracy. In addition, experiments were carried out in a minivan to detect occupancy of each row using support vector machine (SVM). Finally, our proposed system achieved 97.8% accuracy on average in finding the defined scenarios. Moreover, the system can correctly identify if the vehicle is occupied or not with 100% accuracy.

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