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Nonsaturated large magnetoresistance and transport dynamics in a n-doped cryogenic WSe2 field-effect device

Physical Review B 2025年第12期111卷 125307-125307页

作者： Wei-Chen Lin Ching-Chen Yeh Jia-Zhu Zou Nhat Anh Nguyen Phan Inayat Uddin Hai Yen Le Thi Kenji Watanabe Takashi Taniguchi Gil-Ho Kim Department of Engineering and System Science National Tsing Hua University Hsinchu 300 Taiwan Taiwan International Graduate Program Academia Sinica Taipei 115 Taiwan Department of Physics National Taiwan University Taipei 106 Taiwan Department of Electrical and Computer Engineering Sungkyunkwan University (SKKU) Suwon 164 Republic of Korea Sungkyunkwan Advanced Institute of Nano Technology (SAINT) Sungkyunkwan University (SKKU) Suwon 16419 Republic of Korea Research Center for Electronic and Optical Materials National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan Research Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba 305-0044 Japan

Interest in the two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) continues to intensify, driven by their suitable band gaps to supplant silicon as next-generation semiconductor materials. Among various TMDs, tungsten diselenide (WSe2) is renowned for its superior electrical properties in carrier density and mobility under ambient conditions. Despite its notable attributes, the behavior of monolayer WSe2 in the electron-doped regime under cryogenic conditions remains largely uncharted, particularly concerning its magnetotransport properties. In this study, we reveal the transport mechanisms of monolayer WSe2 from high temperatures down to the cryogenic regime. As evident by Efros–Shklovskii variable-range hopping (E-S VRH) in the cryogenic regime, strong Coulomb interactions arise between electrons. Above 8 K, an uncommon nonsaturated quadratic large magnetoresistance (MR) can be explained by the wave-function shrinkage model, which is consistent with the E-S VRH transport mechanism. Notably, the nonsaturated quadratic large MR shows a magnitude up to 1740% at 13 T. These findings underscore the potential applications for monolayer WSe2 in cryogenic field-effect devices, magnetic sensors, and memory devices and mark a significant advance in magnetotransport research.

关键词： Monolayers

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Automated Waste Sorting Using Convolutional Neural Network 7

Automated Waste Sorting Using Convolutional Neural Network

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7th NAFOSTED Conference on Information and computer science, NICS 2020

作者： Huynh, Minh-Hieu Pham-Hoai, Phu-Thinh Tran, Anh-Kiet Nguyen, Thanh-Dat Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

The waste classification has become a crucial mission for sustaining worldwide economic growth and preserving the environment. Using deep learning to sort solid waste automatically is necessary since it could minimize the time taken to categorize a large amount of rubbish manually and health risks created by working with polluted waste. In this study, we take advantage of several Convolutional Neural Networks such as VGG, Resnet, Efficientnet, etc. to solve this problem. The test accuracies achieved by training Resnet101, EfficientNet-B0, and EfficientNet-B1 on the dataset of 6640 images are 92.43%, 90.02%, and 91.53% respectively. We also build an ensemble model on the base of these three models, which attains an accuracy of 94.11%. The dataset is from the Trashnet dataset of Stanford and images collected on the Internet. This approach can be potentially applied to real-life environmental problems. © 2020 IEEE.

关键词： Statistical tests

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Chiral exceptional point enhanced active tuning and nonreciprocity in micro-resonators

arXiv

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arXiv 2024年

作者： Lee, Hwaseob Chang, Lorry Kecebas, Ali Mao, Dun Xiao, Yahui Li, Tiantian Alù, Andrea Özdemir, Sahin K. Gu, Tingyi Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States Department of Engineering Science and Mechanics Pennsylvania State University University ParkPA16802 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States Department of Electrical and Computer Engineering Saint Louis University Saint LouisMO63103 United States

Exceptional points (EPs) have been extensively explored in mechanical, acoustic, plasmonic, and photonic systems. However, little is known about the role of EPs in tailoring the dynamic tunability of optical devices. A specific type of EPs known as chiral EPs has recently attracted much attention for controlling the flow of light and for building sensors with better responsivity. A recently demonstrated route to chiral EPs via lithographically defined symmetric Mie scatterers on the rim of resonators has not only provided the much-needed mechanical stability for studying chiral EPs, but also helped reduce losses originating from nanofabrication imperfections, facilitating the insitu study of chiral EPs and their contribution to the dynamics and tunability of resonators. Here, we use asymmetric Mie scatterers to break the rotational symmetry of a microresonator, to demonstrate deterministic thermal tuning across a chiral EP, and to demonstrate EP-mediated chiral optical nonlinear response and efficient electro-optic tuning. Our results indicate asymmetric electro-optic modulation with up to 17dB contrast at GHz and CMOS-compatible voltage levels. Such wafer-scale nano-manufacturing of chiral electro-optic modulators and the chiral EP-tailored tunning may facilitate new micro-resonator functionalities in quantum information processing, electromagnetic wave control, and optical interconnects. © 2024, CC BY.

关键词： Microresonators

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Facial Expression Recognition in the Wild: Efficiency of Modified-Category and Ensemble Learning Methods 7

Facial Expression Recognition in the Wild: Efficiency of Mod...

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7th NAFOSTED Conference on Information and computer science, NICS 2020

作者： Bui-Xuan, Bao Nguyen-Hoang, Bao-Minh Truong, Cong-Anh Nguyen-Tran, Quang-Duy Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

Human facial expression plays a significant role in the medical field, the automotive industry, and so on. Recent research and achievements in recognizing the expressions by using CNNs have been published, conducted on old datasets, i.e. CKP, FER+, etc. However, those are unnatural and less challenging. We authors propose two methods to deal with a new and more realistic dataset called CAER-S first introduced in ICCV 2019. Instead of using the original images of CAER-S, we prepare our dataset by extracting the faces to focus mainly on facial expressions. The first method is to merge some categories sharing the most mispredictions mutually. Nonetheless, the results are indecisive to conclude this method's efficiency. The other is to use plenty of pre-trained models to find the best three of them for ensembles. The ensembles are weighted majority voting and soft voting. These are applied to fuse the three models' results to return the final one whose accuracy is higher than each's separately. This work contributes to advanced facial expression recognition research, especially with using the new dataset CAER-S. © 2020 IEEE.

关键词： Automotive industry

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Vehicle Counting: Survey and Experiments 7

Vehicle Counting: Survey and Experiments

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7th NAFOSTED Conference on Information and computer science, NICS 2020

作者： La, Hoang-Phong Ha, Minh-Thao Nguyen, Hai-Long Nguyen, Manh-Thien Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

Traffic management needs information about traffic to control the flow of transports. With millions of traffic video cameras acting as sensors around the world, collecting the information about traffic flow in real-time is quite easy, but using that information to process and control the traffic flow is a challenge. For detecting vehicles, old methods like inductive loop detectors (ILD), infrared detectors (IRDs), laser sensors, etc. have problems with high cost, efficiency, difficulty, etc. The methods we use in this paper are detection-based counting, regression-based counting. The authors propose a new method that is the combination of two methods above to achieve better results. We also evaluate the viability of using Deep Learning pre-trained models include Faster R-CNN, SSD, YOLO for detection-based. We experiment on 2018 AI CITY CHALLENGE datasets and Vehicles Nepal datasets. Our results show the effectiveness of the combining method in accuracy compares to using each of the methods separately. © 2020 IEEE.

关键词： Object detection

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Hit Song Prediction based on Gradient Boosting Decision Tree 7

Hit Song Prediction based on Gradient Boosting Decision Tree

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7th NAFOSTED Conference on Information and computer science, NICS 2020

作者： Pham, Bang-Dang Tran, Minh-Triet Pham, Hoang-Long Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

Record companies invest billions of dollars in new talent around the globe each year. Gaining insight into what actually makes a hit song would provide tremendous benefits for the music industry. In this research, we tackle this question by focusing on predicting rank of hit songs in the next 6 months. Our dataset is used in ZALO AI CHALLENGE 2019 in Hit Song Prediction problem including not only songs but also its information such as composer, artist name, released date, etc. Because of that, while most previous work formulates hit song prediction as a regression or classification problem, we present in this paper how to apply Gradient Boosting technique to treat it as a ranking problem. The resulting best model has a good performance when predicting whether a song is a top 10 dance hit versus a lower listed position with 1.48815 Root Mean Square Error - our result dominates most of the solution in this competition (better than 3rd ranked solution of 87 in total). Moreover, it is possible to further improve by extracting chords, tones and more information from each song to obtain the highlights of songs and by using linguistics model to offer high-level features of metadata. © 2020 IEEE.

关键词： Decision trees

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Efficient One-Shot Video Object Segmentation 7

Efficient One-Shot Video Object Segmentation

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7th NAFOSTED Conference on Information and computer science, NICS 2020

作者： Hoang-Xuan, Nhat Nguyen, E-Ro Pham-Le, Thuy-Dung Hoang-Nguyen, Khoi Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

Video object segmentation is the problem of labelling the foreground object of interest that has widespread applications. We reevaluate One-shot Video Object Segmentation (OSVOS), a simple method that adapts VGG to image segmentation using a structure similar to a Fully Convolutional Network. We propose a range of improvements to make OSVOS competitive to newer methods while keeping its simplicity. Specifically, we replace VGG with EfficientNet, and adopt the U-net architecture. We also utilize Focal Loss and Dice Loss to handle the imbalanced binary classification, and finally we remove the boundary snapping module. With our amendments, we achieve 82.4% J&F on DAVIS 2016 validation set, an improvement over the original 80.2% of OSVOS. We also achieve much faster inference time per frame than OSVOS. © 2020 IEEE.

关键词： Image segmentation

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Lightweight Learner for Shared Knowledge Lifelong Learning

arXiv

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arXiv 2023年

作者： Ge, Yunhao Li, Yuecheng Wu, Di Xu, Ao Jones, Adam M. Rios, Amanda Sofie Fostiropoulos, Iordanis Wen, Shixian Huang, Po-Hsuan Murdock, Zachary William Sahin, Gozde Ni, Shuo Lekkala, Kiran Sontakke, Sumedh Anand Itti, Laurent Thomas Lord Department of Computer Science University of Southern California United States Neuroscience Graduate Program University of Southern California United States Intel Labs United States Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China Dornsife Department of Psychology University of Southern California United States

In Lifelong Learning (LL), agents continually learn as they encounter new conditions and tasks. Most current LL is limited to a single agent that learns tasks sequentially. Dedicated LL machinery is then deployed to mitigate the forgetting of old tasks as new tasks are learned. This is inherently slow. We propose a new Shared Knowledge Lifelong Learning (SKILL) challenge, which deploys a decentralized population of LL agents that each sequentially learn different tasks, with all agents operating independently and in parallel. After learning their respective tasks, agents share and consolidate their knowledge over a decentralized communication network, so that, in the end, all agents can master all tasks. We present one solution to SKILL which uses Lightweight Lifelong Learning (LLL) agents, where the goal is to facilitate efficient sharing by minimizing the fraction of the agent that is specialized for any given task. Each LLL agent thus consists of a common task-agnostic immutable part, where most parameters are, and individual task-specific modules that contain fewer parameters but are adapted to each task. Agents share their task-specific modules, plus summary information ("task anchors") representing their tasks in the common task-agnostic latent space of all agents. Receiving agents register each received task-specific module using the corresponding anchor. Thus, every agent improves its ability to solve new tasks each time new task-specific modules and anchors are received. If all agents can communicate with all others, eventually all agents become identical and can solve all tasks. On a new, very challenging SKILL-102 dataset with 102 image classification tasks (5,033 classes in total, 2,041,225 training, 243,464 validation, and 243,464 test images), we achieve much higher (and SOTA) accuracy over 8 LL baselines, while also achieving near perfect parallelization. Code and data can be found at https://***/gyhandy/Shared-Knowledge-Lifelong-Learning Copyr

关键词： Statistical tests

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Biomedical data and AI

引用

science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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Sport Field Reservation Based on Mobile Application 7

Sport Field Reservation Based on Mobile Application

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Claudinus, Tonto Prayoga Wicaksana, Made Kornelius Sitorus, Nicolas Ariqi Gustiandza, Marsa Oktavia, Tanty Lumban Gaol, Ford Hosoda, Takaaki Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan

ISBN: (纸本)9781665404228

This paper presents the sports apps based on a mobile application that has a function to help the provider or the owner of the sports field and sports vendor to promote their business in the apps. Due to the popularity and convenience that mobile applications had and high interest from many people in having a healthy life, it is a great opportunity to combine both of them. Therefore, this study focusses to build mobile sports application using object-oriented analysis and design method, that could meet the demand of lots of peoples that wants to do a sport especially a ball sport. Otherwise, the application can help and support the community and public, especially for ball sports fans, to make reservations for the sports field easier without having to come to the location and also meet their sporting needs. © 2020 IEEE.

关键词： Sports

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