检索结果-内蒙古大学图书馆

Artificial intelligence in cancer target identification and drug discovery

Signal Transduction and Targeted Therapy 2022年第6期7卷 1951-1974页

作者： Yujie You Xin Lai Yi Pan Huiru Zheng Julio Vera Suran Liu Senyi Deng Le Zhang College of Computer Science Sichuan UniversityChengdu 610065China Laboratory of Systems Tumor Immunology Friedrich-Alexander-Universität Erlangen-Nürnberg(FAU)and Universitätsklinikum ErlangenErlangen 91052Germany Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesRoom D5131068 Xueyuan AvenueShenzhen University TownShenzhen 518055China School of Computing Ulster UniversityBelfast BT151EDUK Institute of Thoracic Oncology Department of Thoracic SurgeryWest China HospitalSichuan UniversityChengdu 610065China Key Laboratory of Systems Biology Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesChinese Academy of SciencesHangzhou 310024China Key Laboratory of Systems Health Science of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as ***,we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover ***,we describe the scope of artificial intelligence biology analysis for novel anticancer target ***,we review and discuss the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence ***,we showcase the applications of artificial intelligence approaches in cancer target identification and drug *** together,the artificial intelligence models have provided us with a quantitative framework to study the relationship between network characteristics and cancer,thereby leading to the identification of potential anticancer targets and the discovery of novel drug candidates.

关键词： drugs cancer drug

来源：评论

学校读者我要写书评

暂无评论

Machine Learning and Computer Vision Techniques in Continuous Beehive Monitoring Applications: A Survey

arXiv

引用

arXiv 2022年

作者： Bilik, Simon Zemcik, Tomas Kratochvila, Lukas Ricanek, Dominik Richter, Miloslav Zambanini, Sebastian Horak, Karel Department of Control and Instrumentation Faculty of Electrical Engineering and Communication Brno University of Technology Technická 3058/10 Brno61600 Czech Republic Computer Vision and Pattern Recognition Laboratory Department of Computational Engineering Lappeenranta-Lahti University of Technology LUT Yliopistonkatu 34 Lappeenranta53850 Finland Computer Vision Lab Institute of Visual Computing & Human-Centered Technology Faculty of Informatics TU Wien Favoritenstr. 9/193-1 ViennaA-1040 Austria

Wide use and availability of machine learning and computer vision techniques allows development of relatively complex monitoring systems in many domains. Besides the traditional industrial domain, new applications appears also in biology and agriculture, where they may be used to detect infections, parasites and weeds, but also for automated monitoring and early warning systems. This goes in concordance with the introduction of the easily accessible hardware and development kits such as the Arduino, or RaspberryPi families. In this paper, we survey 50 papers focusing on the methods of automated beehive monitoring using computer vision techniques. Particularly on the pollen and Varroa mite detection together with the bee traffic monitoring. Such systems could also be used for monitoring of honeybee colonies and for the inspection of their health state, which could potentially identify dangerous states before the situation is critical, or to better plan periodic bee colony inspections and therefore save significant costs. Further on, we also include analysis of the research trends in this application field and we outline the possible directions of new development. Our paper is also aimed at veterinary and apidology professionals and experts, who may not be familiar with machine learning to introduce them to its capabilities, hence each family of techniques is prefaced by a brief theoretical introduction and motivation related to its base method. We hope that this paper will inspire other scientists to use machine learning techniques for other applications in beehive monitoring. © 2022, CC BY.

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

Prediction of multi-parameters in the inverse heat conduction problems

Prediction of multi-parameters in the inverse heat conductio...

引用

2020 International Conference on Physics, Mechanics and Mathematical Science, PMMS 2020

作者： Abdelhamid, Talaat Chen, Rongliang Alam, Mahbub Shenzhen Institutes of Advanced Technology Chinese Academy of Science Shenzhen China Institute for Turbulence-Noise-Vibration Interaction and Control Shenzhen Graduate School Harbin Institute of Technology Shenzhen China Physics and Mathematical Engineering Department Faculty of Electronic Engineering Menoufiya University Menouf Egypt Shenzhen Key Laboratory for Exascale Engineering and Scientific Computing Shenzhen China

This paper studies the prediction of the spatial-dependent-heat transfer coefficient γ(x) and- heat flux q(x), using the modified conjugate gradient method (MCGM). The mathematical formulation of the problem well defined and the existence of the minimizer is investigated. We establish the sensitivity and adjoint equations for computing the gradient with respect to γ(x) and q(x). The proposed algorithm 4.1 is derived for reconstructing γ(x) and q(x) using the MCGM. The numerical experiments are examined to show the efficiency and accuracy of the proposed method. Finally, some conclusions and remarks are given. © Published under licence by IOP Publishing Ltd.

关键词： Conjugate gradient method

来源：评论

学校读者我要写书评

暂无评论

A general framework for lifelong localization and mapping in changing environment

arXiv

引用

arXiv 2021年

作者： Zhao, Min Guo, Xin Song, Le Qin, Baoxing Shi, Xuesong Lee, Gim Hee Sun, Guanghui Gaussian Robotics Shanghai China Intel Labs China Beijing China Computer Vision and Robotic Perception Lab Department of Computer Science School of Computing National University of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology China

The environment of most real-world scenarios such as malls and supermarkets changes at all times. A prebuilt map that does not account for these changes becomes out-of-date easily. Therefore, it is necessary to have an up-todate model of the environment to facilitate long-term operation of a robot. To this end, this paper presents a general lifelong simultaneous localization and mapping (SLAM) framework. Our framework uses a multiple session map representation, and exploits an efficient map updating strategy that includes map building, pose graph refinement and sparsification. To mitigate the unbounded increase of memory usage, we propose a maptrimming method based on the Chow-Liu maximum-mutualinformation spanning tree. The proposed SLAM framework has been comprehensively validated by over a month of robot deployment in real supermarket environment. Furthermore, we release the dataset collected from the indoor and outdoor changing environment with the hope to accelerate lifelong SLAM research in the community. Our dataset is available at https://***/sanduan168/lifelong-SLAM-dataset. © 2021, CC BY.

关键词： Retail stores

来源：评论

学校读者我要写书评

暂无评论

Nonreciprocal Bundle Emissions of Quantum Entangled Pairs

arXiv

引用

arXiv 2024年

作者： Bin, Qian Jing, Hui Wu, Ying Nori, Franco Lü, Xin-You School of Physics Institute for Quantum Science and Engineering Huazhong University of Science and Technology Wuhan Institute of Quantum Technology Wuhan430074 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China Theoretical Quantum Physics Laboratory Cluster for Pioneering Research RIKEN Wakoshi Saitama351-0198 Japan Center for Quantum Computing RIKEN Wakoshi Saitama351-0198 Japan Physics Department The University of Michigan Ann ArborMI48109-1040 United States

Realizing precise control over multiquanta emission is crucial for quantum information processing, especially when integrated with advanced techniques of manipulating quantum states. Here, by spinning the resonator to induce the Sagnac effect, we can obtain nonreciprocal photon-phonon and photon-magnon super-Rabi oscillations under conditions of optically driving resonance transitions. Opening dissipative channels for such super-Rabi oscillations enables the realization of directional bundle emissions of entangled photon-phonon pairs and photon-magnon pairs by transferring pure multiquanta state to bundled multiquanta outside of the system. This nonreciprocal emission is a flexible switch that can be controlled with precision, and simultaneous emissions of different entangled pairs (such as photon-phonon or photon-magnon pairs) can even emerge but in opposite directions by driving the resonator from different directions. This ability to flexibly manipulate the system allows us to achieve directional entangled multiquanta emitters, and has also potential applications for building hybrid quantum networks and on-chip quantum communications. © 2024, CC BY.

关键词： Photons

来源：评论

学校读者我要写书评

暂无评论

Rethinking CNN Models for Audio Classification

arXiv

引用

arXiv 2020年

作者： Palanisamy, Kamalesh Singhania, Dipika Yao, Angela Department of Instrumentation and Control Engineering National Institute of Technology Tiruchirappalli India School of Computing National University of Singapore Singapore

In this paper, we show that ImageNet-Pretrained standard deep CNN models can be used as strong baseline networks for audio classification. Even though there is a significant difference between audio Spectrogram and standard ImageNet image samples, transfer learning assumptions still hold firmly. To understand what enables the ImageNet pretrained models to learn useful audio representations, we systematically study how much of pretrained weights is useful for learning spectrograms. We show (1) that for a given standard model using pretrained weights is better than using randomly initialized weights (2) qualitative results of what the CNNs learn from the spectrograms by visualizing the gradients. Besides, we show that even though we use the pretrained model weights for initialization, there is variance in performance in various output runs of the same model. This variance in performance is due to the random initialization of linear classification layer and random mini-batch orderings in multiple runs. This brings significant diversity to build stronger ensemble models with an overall improvement in accuracy. An ensemble of ImageNet pretrained DenseNet achieves 92.89% validation accuracy on the ESC-50 dataset and 87.42% validation accuracy on the UrbanSound8K dataset which is the current state-of-the-art on both of these datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Spectrographs

来源：评论

学校读者我要写书评

暂无评论

Innovation, Research and Development in engineering Education. Activities of the Spanish Chapter of the IEEE Education Society: Directive Board of the IEEE Education Society Spanish Chapter 2020-2021

Innovation, Research and Development in Engineering Educatio...

引用

Technologies Applied to Electronics Teaching (TAEE)

作者： Ó scar Martí nez Bonastre Cristina Ferná ndez Lluí s Vicent Francisco Mur Manuel Castro Gabriel Diaz Jose Carpio Elio Sancristobal Sergio Martin Jose Sá nchez Francisco Javier Arcega Solsona Juan Suardiaz Muro Manuel Caeiro-Rodrí guez Martí n Llamas Inmaculada Plaza Baltasar Ferná ndez Manjó n Pedro Muñ oz-Merino Edmundo Tovar Telmo Zarraonandia Ayo Javier Garcia Zubia José Antonio Delgado Pení n Department of Statistics Mathematics and Computing Science Operations Research Centre Universidad Miguel Hern&#x00E1 ndez Elche Spain Department of Electronic Technology Universidad Carlos III de Madrid Madrid Spain UPF Barcelona School of Management Barcelona Spain Department of Electrical Electronic and Control Engineering UNED Madrid Spain Department of Electrical Engineering Universidad de Zaragoza Zaragoza Spain Department of Automatics Electrical Engineering and Electronic Technology Technical University of Cartagena Cartagena Spain atlanTTic Research Center University of Vigo Vigo Spain Department of Electronics and Communication Universidad de Zaragoza Zaragoza Spain Department of Software Engineering and Artificial Intelligence Complutense University of Madrid Madrid Spain Department of Telematic Engineering Universidad Carlos III de Madrid Madrid Spain Department of Computer Languages and Systems and Software Engineering Universidad Polit&#x00E9 cnica de Madrid Madrid Spain Department of Computer Science and Engineering Universidad Carlos III de Madrid Madrid Spain Department of Electronic Engineering Universidad de Deusto Bilbao Spain Universitat Polit&#x00E8 cnica de Catalunya Barcelona Spain

ISBN: (数字)9781665421614

ISBN: (纸本)9781665421621

The Technical Committee of the CESEI (Spanish Chapter of the IEEE Education Society) is focused on the Innovation, Research and Development (I+R+D) of the education in engineering, mainly Electric and Computer engineering. As in other interdisciplinary fields, the I+R+D involves several sources of information and different stakeholders, each one with its own focus and purpose. As a result, sometimes it may be complex for practitioners and researchers to identify the more appropriate entities for their interests. This paper shows how the CESEI Technical Committee tries to solve this difficulty by providing updated information regarding the main publications (journals), events (conferences) and awards to the best academic works. The paper focuses special attention on the activities held during 2020–2021.

关键词： Technological innovation Collaboration Stakeholders engineering education Research and development

来源：评论

学校读者我要写书评

暂无评论

The energy revolution: Cyber physical advances and opportunities for smart local energy systems

arXiv

引用

arXiv 2021年

作者： Verba, Nandor Gaura, Elena McArthur, Stephen Konstantopoulos, George Wu, Jianzhoug Fan, Zhong Athanasiadis, Dimitrios Monasterios, Pablo Rodolfo Baldivieso Morris, Euan Hardy, Jeffrey Centre for Data Science Coventry University United Kingdom Department of Electronic and Electrical Engineering University of Strathclyde United Kingdom Department of Automatic Control & Systems Engineering University of Sheffield United Kingdom Department of Electrical and Electronic Engineering Cardiff University United Kingdom School of Computing and Mathematics Keele University United Kingdom Grantham Institute Imperial College London United Kingdom

来源：评论

学校读者我要写书评

暂无评论

Time-in-action RL

引用

IET Cyber-Systems and Robotics 2019年第1期1卷 28-37页

作者： Jiangcheng Zhu Zhepei Wang Douglas Mcilwraith Chao Wu Chao Xu Yike Guo Institute of Cyber-Systems and Control Department of Control Science and EngineeringZhejiang UniversityHangzhouPeople's Republic of China Data Science Institute Department of ComputingImperial College LondonLondonUK School of Public Affairs Zhejiang UniversityHangzhouPeople's Republic of China

The authors propose a novel reinforcement learning(RL)framework,where agent behaviour is governed by traditional control *** integrated approach,called time-in-action RL,enables RL to be applicable to many real-world systems,where underlying dynamics are known in their control theoretical *** key insight to facilitate this integration is to model the explicit time function,mapping the state-action pair to the time accomplishing the action by its underlying *** their framework,they describe an action by its value(action value),and the time that it takes to perform(action time).An action-value results from the policy of RL regarding a *** time is estimated by an explicit time model learnt from the measured activities of the underlying *** value network is then trained with embedded time model to predict action *** approach is tested using a variant of Atari Pong and proved to be convergent.

关键词： action policy agent

来源：评论

学校读者我要写书评

暂无评论

Towards practical and massively parallel quantum computing emulation for quantum chemistry

arXiv

引用

arXiv 2023年

作者： Shang, Honghui Fan, Yi Shen, Li Guo, Chu Liu, Jie Duan, Xiaohui Li, Fang Li, Zhenyu Institute of Computing Technology Chinese Academy of Sciences Beijing China Hefei National Laboratory University of Science and Technology of China Hefei230088 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China School of Software Shandong University Jinan China National Research Center of Parallel Computer Engineering and Technology Beijing China

Quantum computing is moving beyond its early stage and seeking for commercial applications in chemical and biomedical sciences. In the current noisy intermediate-scale quantum computing era, quantum resource is too scarce to support these explorations. Therefore, it is valuable to emulate quantum computing on classical computers for developing quantum algorithms and validating quantum hardware. However, existing simulators mostly suffer from the memory bottleneck so developing the approaches for large-scale quantum chemistry calculations remains challenging. Here we demonstrate a high-performance and massively parallel variational quantum eigensolver (VQE) simulator based on matrix product states, combined with embedding theory for solving large-scale quantum computing emulation for quantum chemistry on HPC platforms. We apply this method to study the torsional barrier of ethane and the quantification of the protein-ligand interactions. Our largest simulation reaches 1000 qubits, and a performance of 216.9 PFLOPS is achieved on a new Sunway supercomputer, which sets the state-of-the-art for quantum computing emulation for quantum chemistry. © 2023, CC BY.

关键词： Computational chemistry

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：