检索结果-内蒙古大学图书馆

CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Lian, Chuanyu Sun, Hongyi Huang, Yi-Siou Vitale, Steven A. Hu, Juejun Takeuchi, Ichiro Youngblood, Nathan Vagionas, Christos Ríos Ocampo, Carlos A. Department of Materials Science & Engineering University of Maryland College ParkMD20742 United States Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States Advanced Materials and Microsystems Group MIT Lincoln Laboratory LexingtonMA02139 United States Department of Materials Science & Engineering MIT CambridgeMA02139 United States Quantum Materials Center Department of Physics University of Maryland College ParkMD20742 United States Electrical & Computer Engineering Department The University of Pittsburgh PittsburghPA15213 United States Department of Informatics Center for Interdisciplinary Research and Innovation Aristotle University of Thessaloniki Thessaloniki Greece

We experimentally demonstrate the first electrically programmable, non-volatile silicon photonic content addressable memory cell using Sb2Se3 phase change material on microring resonators, opening the path for light-based search operations in zero-power look-up tables. © Optica Publishing Group 2024

关键词： Silicon photonics

来源：评论

学校读者我要写书评

暂无评论

Privacy-preserving data aggregation achieving completeness of data queries in smart grid

Privacy-preserving data aggregation achieving completeness o...

引用

作者： Li, Xinyang Zhao, Meng Ding, Yong Yang, Changsong Wang, Huiyong Liang, Hai Wang, Yujue Guangxi Key Laboratory of Cryptography and Information Security School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic Technology Guilin China Hangzhou Innovation Institute of Beihang University Hangzhou China Institute of Cyberspace Technology HKCT Institute for Higher Education Hong Kong School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin China

In smart grid systems, the control center formulates strategies and provides services by analyzing electricity consumption data. However, ensuring the privacy and security of user data is a critical concern. While traditional data aggregation schemes can provide a certain level of privacy protection for users, they also impose limitations on the control center's access to fine-grained data. To address these challenges, we propose a privacy-preserving data aggregation scheme supporting data query (PAQ). We designed a multi-level data aggregation mechanism based on Paillier semi-homomorphic encryption to achieve efficient aggregation of user data in the control center. Additionally, a data query mechanism based on electricity consumption intervals is introduced, allowing the control center to query aggregated ciphertexts for different user categories from outsourced data on the cloud server. Security analysis demonstrates that PAQ design effectively solves security issues in data aggregation and query processes. Performance analysis indicates that the proposed scheme outperforms existing solutions in terms of efficiency. © 2024 John Wiley & Sons, Ltd.

关键词： Smart power grids

来源：评论

学校读者我要写书评

暂无评论

Touchstone benchmark: are we on the right way for evaluating AI algorithms for medical segmentation? 24

Touchstone benchmark: are we on the right way for evaluating...

引用

Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Pedro R. A. S. Bassi Wenxuan Li Yucheng Tang Fabian Isensee Zifu Wang Jieneng Chen Yu-Cheng Chou Saikat Roy Yannick Kirchhoff Maximilian Rokuss Ziyan Huang Jin Ye Junjun He Tassilo Wald Constantin Ulrich Michael Baumgartner Klaus H. Maier-Hein Paul Jaeger Yiwen Ye Yutong Xie Jianpeng Zhang Ziyang Chen Yong Xia Zhaohu Xing Lei Zhu Yousef Sadegheih Afshin Bozorgpour Pratibha Kumari Reza Azad Dorit Merhof Pengcheng Shi Ting Ma Yuxin Du Fan Bai Tiejun Huang Bo Zhao Haonan Wang Xiaomeng Li Hanxue Gu Haoyu Dong Jichen Yang Maciej A. Mazurowski Saumya Gupta Linshan Wu Jiaxin Zhuang Hao Chen Holger Roth Daguang Xu Matthew B. Blaschko Sergio Decherchi Andrea Cavalli Alan L. Yuille Zongwei Zhou Department of Computer Science Johns Hopkins University and Department of Pharmacy and Biotechnology University of Bologna and Center for Biomolecular Nanotechnologies Istituto Italiano di Tecnologia Department of Computer Science Johns Hopkins University NVIDIA Division of Medical Image Computing German Cancer Research Center (DKFZ) and Helmholtz Imaging German Cancer Research Center (DKFZ) ESAT-PSI KU Leuven Division of Medical Image Computing German Cancer Research Center (DKFZ) and Faculty of Mathematics and Computer Science Heidelberg University Division of Medical Image Computing German Cancer Research Center (DKFZ) and Faculty of Mathematics and Computer Science Heidelberg University and HIDSS4Health - Helmholtz Information and Data Science School for Health Shanghai Jiao Tong University Shanghai Artificial Intelligence Laboratory Division of Medical Image Computing German Cancer Research Center (DKFZ) Division of Medical Image Computing German Cancer Research Center (DKFZ) and Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Helmholtz Imaging German Cancer Research Center (DKFZ) and Interactive Machine Learning Group (IML) DKFZ School of Computer Science and Engineering Northwestern Polytechnical University Australian Institute for Machine Learning The University of Adelaide College of Computer Science and Technology Zhejiang University Hong Kong University of Science and Technology (Guangzhou) Hong Kong University of Science and Technology (Guangzhou) and Hong Kong University of Science and Technology Faculty of Informatics and Data Science University of Regensburg Faculty of Electrical Engineering and Information Technology RWTH Aachen University Faculty of Informatics and Data Science University of Regensburg and Fraunhofer Institute for Digital Medicine MEVIS Electronic & Information Engineering School Harbin Institute of Technology (Shenzhen) Shanghai Jiao Tong University and Beijing Academy of Artificial Intelligence (BAAI) S

ISBN: (纸本)9798331314385

How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified metrics, unfair comparisons, and short-term outcome pressure. As a consequence, good performance on standard benchmarks does not guarantee success in real-world scenarios. To address these problems, we present Touchstone, a large-scale collaborative segmentation benchmark of 9 types of abdominal organs. This benchmark is based on 5,195 training CT scans from 76 hospitals around the world and 5,903 testing CT scans from 11 additional hospitals. This diverse test set enhances the statistical significance of benchmark results and rigorously evaluates AI algorithms across out-of-distribution scenarios. We invited 14 inventors of 19 AI algorithms to train their algorithms, while our team, as a third party, independently evaluated these algorithms. In addition, we also evaluated pre-existing AI frameworks—which, differing from algorithms, are more flexible and can support different algorithms—including MONAI from NVIDIA, nnU-Net from DKFZ, and numerous other open-source frameworks. We are committed to expanding this benchmark to encourage more innovation of AI algorithms for the medical domain.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Electrically Programmable Non-Volatile Silicon Photonic Content Addressable Memory (CAM) cell

Electrically Programmable Non-Volatile Silicon Photonic Cont...

引用

2024 Conference on Lasers and Electro-Optics, CLEO 2024

ISBN: (纸本)9781957171395

关键词： Silicon photonics

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence is transforming the study of proteins:Structures and beyond

微生物与宿主健康（英文）

引用

微生物与宿主健康（英文） 2025年第4期3卷 162-163页

作者： Haiyan Liu Quan Chen Yufeng Liu MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics School of Life SciencesDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaAnhuiChina Biomedical Sciences and Health Laboratory of Anhui Province Anhui Basic Discipline Research Center of Artificial Intelligence Biotechnology and Synthetic BiologyUniversity of Science and Technology of ChinaAnhuiChina School of Biomedical Engineering Suzhou Institute for Advanced ResearchUniversity of Science and Technology of ChinaJiangsuChina MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics School of Life SciencesDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaAnhuiChina Biomedical Sciences and Health Laboratory of Anhui Province Anhui Basic Discipline Research Center of Artificial Intelligence Biotechnology and Synthetic BiologyUniversity of Science and Technology of ChinaAnhuiChina Department of Rheumatology and Immunology The First Affiliated Hospital of USTCDivision of Life Sciences and MedicineHefei National Research Center for Physical Sciences at the MicroscaleCenter for Advanced Interdisciplinary Science and Biomedicine of IHMUniversity of Science and Technology of ChinaAnhuiChina MOE Key Laboratory for Membraneless Organelles and Cellular Dynamics School of Life SciencesDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaAnhuiChina Department of Rheumatology and Immunology The First Affiliated Hospital of USTCDivision of Life Sciences and MedicineHefei National Research Center for Physical Sciences at the MicroscaleCenter for Advanced Interdisciplinary Science and Biomedicine of IHMUniversity of Science and Technology of ChinaAnhuiChina

Recently,the Royal Swedish Academy of sciences announced that one-half of the 2024 Nobel Prize in Chemistry was awarded to David Baker for computational protein design,and the other half was awarded jointly to Demis Hassabis and John Jumper for protein structure prediction. Proteins are the molecule tools of *** carry out their func-tions,many proteins need to fold into particular three-dimen-sional(3D)structures,which are programmed by the amino acid sequences of the proteins[1].The goal of protein structure prediction is to predict the 3D structures from given amino acid ***,protein design aims to identify amino acid sequences that achieve desired structural or func-tional goals.

关键词： intelligence beyond study artificial proteins structures transforming

来源：评论

学校读者我要写书评

暂无评论

Expedited Block Transmission in Blockchain Network by using Clusters

Expedited Block Transmission in Blockchain Network by using ...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Xiaoqi Hua Jian Chen Peiyun Zhang Zhangjie Fu Haibin Zhu Kezhong Lu Jigang Ren School of Software Nanjing University of Information Science and Technology Nanjing China Engineering Research Center of Digital Forensics of Ministry of Education and the School of Computer Science Nanjing University of Information Science and Technology Nanjing China School of Computer Science Nanjing University of Information Science and Technology Nanjing China Department of Computer Science and Mathematics Nipissing University North Bay ON Canada School of Big Data and Artificial Intelligence Chizhou University Chizhou China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Blockchain technology has garnered increasing attention from researchers. Because blockchain systems may contain malicious or spatially limited nodes that may delay block verification and reduce block transmission rate, this work proposes a block transmission model by designing and using special clusters. This work proposes the cluster formation and selection mechanisms. Nodes are grouped into clusters in a blockchain, and clusters with high fitness values are chosen to transmit blocks by calculating their trust values and block transmission rates. The proposed method is compared with the peers: Layer-Chain, BlockP2P-EP and RNS. According to experimental findings, the proposed method is superior to its peers regarding the time needed for block synchronization and transmission, block occupation storage ratio, transaction throughput, and block transmission success ratio.

关键词： Throughput Blockchains Peer-to-peer computing Delays Synchronization Cybernetics

来源：评论

学校读者我要写书评

暂无评论

An enzyme-free interdigitated electrode for ketamine detection

引用

Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A 2023年第5期46卷 441-452页

作者： Phan, Thien Luan Van Hieu, Nguyen Lin, Jing-Jenn Wu, Hsing-Ju Chu, Pei-Yi Hsiao, Chin-Sung Yao, Fiona Yan-Dong Lin, Yung-Kai Ching, Congo Tak Shing Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung Taiwan Viet Nam Department of Applied Materials and Optoelectronic Engineering National Chi Nan University Taiwan Research Assistant Center Show Chwan Memorial Hospital Taiwan Department of Medical Research Chang Bing Show Chwan Memorial Hospital Taiwan Department of Pathology Show Chwan Memorial Hospital Taiwan School of Medicine College of Medicine Fu Jen Catholic University Taiwan Computer Science and Information Engineering Asia University Taiwan Division of Science Engineering and Health Studies College of Professional and Continuing Education The Hong Kong Polytechnic University Hong Kong Department of Food Science National Taiwan Ocean University Taiwan Department of Electrical Engineering National Chi Nan University Nantou County Taiwan

Ketamine is an anesthetic, which when used wrongly would affect judgment and behavior, increasing risks to individual such as unwanted or risky sexual behavior. This study reports the development of an admittance- and capacitance-spectroscopy-based sensor to detect ketamine in solution, such as whiskey, a popular alcoholic drink. The result confirms the proposed method is capable of detecting the presence of ketamine in whiskey, in concentration as low as 6.25 ng/μL, by using admittance and capacitance measured at 6.75 MHz, as well as quantifying the measured admittance (sensitivity: 300 μΩ−1/Log (ng/μL);limit of detection (LOD): 0.16 ng/μL) or capacitance data (sensitivity: 2 nF/Log (ng/μL);LOD: 0.73 ng/μL) at 18 kHz and 7.69 MHz, respectively. © 2023 The Chinese Institute of Engineers.

关键词： Capacitance

来源：评论

学校读者我要写书评

暂无评论

High-Bandwidth,Low-Power CMOS Transistor Based CAB for Field Programmable Analog Array

引用

computers, Materials & Continua 2023年第3期74卷 5885-5900页

作者： Ameen Bin Obadi Alaa El-Din Hussein Samir Salem Al-Bawri Kabir Hossain Abdullah Abdulhameed Muzammil Jusoh Thennarasan Sabapathy Ahmed Jamal Abdullah Al-Gburi Mahmoud A.Albreem Advanced Communication Engineering(ACE) Centre of ExcellenceUniversiti Malaysia Perlis(UniMAP)Faculty of Electronic Engineering TechnologyKangar01000Malaysia Electrical Engineering King Fahd University of Petroleum and MineralsDhahranEastern31261Saudi Arabia Space Science Centre Climate Change InstituteUniversiti Kebangsaan MalaysiaBangi43600Malaysia Department of Electronics&Communication Engineering Faculty of Engineering&PetroleumHadhramout UniversityAl-MukallaHadhramout50512Yemen Faculty of Engineering Norwegian University of Science and Technology(NTNU)GjovikN-2815Norway Faculty of Electronic Engineering Technology Universiti Malaysia Perlis(UniMAP)Kampus Alam UniMAP Pauh PutraArau02600Malaysia Department of General Educational Development Faculty of Science and Information Technology(FSIT)Daffodil International UniversityDhaka1207Bangladesh Department of Electronics and Computer Engineering(FKEKK) Center for Telecommunication Research and Innovation(CeTRI)Universiti Teknikal Malaysia Melaka(UTeM)Durian Tungal76100Malaysia Department of Electrical Engineering University of SharjahSharjah27272United Arab Emirates

This article presents an integrated current mode configurable analog block(CAB)system for field-programmable analog array(FPAA).The proposed architecture is based on the complementary metal-oxide semiconductor(CMOS)transistor level design where MOSFET transistors operating in the saturation region are *** proposed CAB architecture is designed to implement six of thewidely used current mode operations in analog processing systems:addition,subtraction,integration,multiplication,division,and pass *** functionality of the proposed CAB is demonstrated through these six operations,where each operation is chosen based on the user’s selection in the CAB interface *** architecture of the CAB system proposes an optimized way of designing and integrating only three functional cells with the interface circuitry to achieve the six ***,optimized programming and digital tuning circuitry are implemented in the architecture to control and interface with the functional ***,these designed programming and tuning circuitries play an essential role in optimizing the performance of the proposed *** of the proposed CMOS Transistor Based CAB system is carried out using Tanner EDA Tools in 0.35μm standard CMOS *** design uses a±1.5 V power supply and results in maximum 3 dB bandwidth of 34.9 MHz and an approximate size of 0.0537 *** demonstrates the advantages of the design over the current state-of-the-art designs presented for comparison in this ***,the proposed design has a clear aspect of simplicity,low power consumption,and high bandwidth operation,which makes it a suitable candidate for mobile telecommunications applications.

关键词： CMOS field programmable analog array configurable analog block current mode circuit

来源：评论

学校读者我要写书评

暂无评论

Bilateral Contract for Load Frequency and Renewable Energy Sources Using advanced Controller

引用

computers, Materials & Continua 2022年第11期73卷 3165-3180页

作者： Krishan Arora Gyanendra Prasad Joshi Mahmoud Ragab Muhyaddin Rawa Ahmad H.Milyani Romany F.Mansour Eunmok Yang School of Electronics and Electrical Engineering Lovely Professional UniversityPhagwara144001PunjabIndia School of Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre for Artificial Intelligence in Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia King Abdullah City for Atomic and Renewable Energy(K.A.CARE) RiyadhSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt Department of Information Security Cryptologyand MathematicsKookmin UniversitySeoul02707Korea

Reestablishment in power system brings in significant transformation in the power sector by extinguishing the possession of sound consolidated ***,the collaboration of various manufacturing agencies,autonomous power manufacturers,and buyers have created complex installation *** regular active load and inefficiency of best measures among varied associates is a huge *** sudden load deviation will give rise to immediate amendment in frequency and tie-line power *** is essential to deal with every zone’s frequency and tie-line power within permitted confines followed by fluctuations within the ***,it can be proficient by implementing Load Frequency Control under the Bilateral case,stabilizing the power and frequency distinction within the interrelated power *** the net deviation in multiple areas is possible by minimizing the unbalance of Bilateral Contracts with the help of proportional integral and advanced controllers like Harris Hawks *** proposed the advanced controller Harris Hawk optimizer-based model and validated it on a test *** experiment results show that the delay time is 0.0029 s and the settling time of 20.86 s *** model can also be leveraged to examine the decision boundaries of the Bilateral case.

关键词： Bilateral contract load frequency control optimization harris hawks optimizer

来源：评论

学校读者我要写书评

暂无评论

Transfer learning enhanced graph neural network for aldehyde oxidase metabolism prediction and its experimental application

引用

Acta Pharmaceutica Sinica B 2024年第2期14卷 623-634页

作者： Jiacheng Xiong Rongrong Cui Zhaojun Li Wei Zhang Runze Zhang Zunyun Fu Xiaohong Liu Zhenghao Li Kaixian Chen Mingyue Zheng Drug Discovery and Design Center State Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China University of Chinese Academy of Sciences Beijing 100049China College of Computer and Information Engineering Dezhou UniversityDezhou 253023China AI Department Suzhou Alphama Biotechnology Co.Ltd.Suzhou 215000China Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and TechnologyShanghaiTech UniversityShanghai 200031China State Key Laboratory of Pharmaceutical Biotechnology Nanjing UniversityNanjing 210023China

Aldehyde oxidase(AOX)is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other ***-mediated metabolism can result in unexpected outcomes,such as the production of toxic metabolites and high metabolic clearance,which can lead to the clinical failure of novel therapeutic *** models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism *** this study,we developed a novel graph neural network called AOMP for predicting AOX-mediated *** integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction,while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both *** significantly outperformed the benchmark methods in both cross-validation and external *** AOMP,we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability,which were validated through in vitro ***,for the convenience of the community,we established the first online service for AOX metabolism prediction based on AOMP,which is freely available at https://***.

关键词： Drugmetabolism Aldehyde oxidase Transferlearning Graph neural network Kinase inhibitor

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：