检索结果-内蒙古大学图书馆

IEEE International Conference on Services computing (SCC)

作者： Yi Pan Xiaoning Sun Yunni Xia Wanbo Zheng Xin Luo College of Computer Science Chongqing University Chongqing China Data Science Research Center Faculty of Science Kunming University of Science and Technology Kunming China Chongqing Engineering Research Center of Big Data Application for Smart Cities Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China Hengrui (Chongqing) Artificial Intelligence Research Center Cloudwalk China

ISBN: (数字)9781728187891

ISBN: (纸本)9781728187907

The cloud computing paradigm is featured by its ability to offer elastic computational resource provisioning patterns and deliver on-demand and versatile services. It's thus getting increasingly popular to build business process and workflow-based applications upon cloud computing platforms. However, it remains a difficulty to guarantee cost-effectiveness and quality of service of cloud-based workflows because real-world cloud services are usually subject to real-time performance variations or fluctuations. Existing researches mainly consider that cloud are with constant performance and formulate the scheduling decision-making as a static optimization problem. In this work, instead, we consider that scientific computing processes to be supported by decentralized cloud infrastructures are with fluctuating QoS and aim at managing the monetary cost of workflows with the completion-time constraint to be satisfied. We address the performance-trend-aware workflow scheduling problem by leveraging a time-series-based prediction model and a Critical-Path-Duration-Estimation-based (CPDE for short) scheduling strategy. The proposed method is capable of exploiting real-time trends of performance changes of cloud infrastructures and generating dynamic workflow scheduling plans. To prove the effectiveness of our proposed method, we build a large-prime-number-generation workflow supported by real-world third-party commercial clouds and show that our method clearly beats existing approaches in terms of cost, workflow completion time, and Service-Level-Agreement (SLA) violation rate.

关键词： Cloud computing Processor scheduling Computational modeling Quality of service Predictive models Dynamic scheduling Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Simulation of reverse power relay in 11 kV generator protection

引用

AIP Conference Proceedings 2021年第1期2339卷 020029页

作者： C. L. Wooi Y. Y. Lee H. Nabipour-Afrouzi M. I. Mousa S. N. M. Arshad K. Mehranzamir M. N. K. H. Rohani Centre of Excellence for Renewable Energy School of Electrical Systems Engineering Universiti Malaysia Perlis Pauh Putra Campus 02600 Arau Perlis Malaysia Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak 93350 Kuching Malaysia Institute of High Voltage and High Current School of Electrical Engineering Faculty of Engineering Universiti Teknologi Malaysia 81310 Johor Bahru Malaysia Department of Electrical and Electronic Engineering Faculty of Science and Engineering University of Nottingham Malaysia Jalan Broga 43500 Semenyih Selangor Malaysia

This paper proposed the modelling and simulation of generator protection for power system using digital reverse power relay. The operations of the power plant are often interrupted by the reverse power generation. Therefore, generators need to be closely monitored and controlled. In this study, 11 kV synchronous generators are connected to 220 kV load through a step-up transformer, and a new model of reverse power relay is added for generator protection. The reverse power relay proposed in this paper is a digital relay with high accuracy and high reacting speed. Several cases based on various types of mechanical inputs to the generator were studied to test the operation of the reverse power relay. This simulation was done using MATLAB/Simulink. The results show that the 11 kV generator protection is successful with this new model reverse power relay. Besides, the simulation results were similar result compared to the theory result. From the simulation results, the integral output of the relay will reach the threshold value ‘L’ whenever there is a reversed power flow fault found in the system. Consequently, the relay will be triggered to provide protection for the generator. This model has been added into online resources of MATLAB Power System Tools. In addition, this model may also help the engineers to develop the analytical skills under various conditions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The YAG Lidar System Applied in LHAASO 37

The YAG Lidar System Applied in LHAASO

引用

37th International Cosmic Ray Conference, ICRC 2021

作者： Sun, Q.N. Geng, L.S. Li, X. Chen, L. Liu, H. Wang, Y. Zhu, F.R. Zhang, Y. Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, L.X. Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, H. Cai, J.T. Cao, Zhe Chang, J. Chang, J.F. Chen, B.M. Chen, E.S. Chen, J. Chen, Liang Chen, Liang Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, X.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, S.W. Cui, X.H. Cui, Y.D. D’Ettorre Piazzoli, B. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.J. Duan, K.K. Fan, J.H. Fan, Y.Z. Fan, Z.X. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, Y.L. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Ge, M.M. Geng, L.S. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, J.G. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.C. He, S.L. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, C. Hu, H.B. Hu, S. Hu, S.C. Hu, X.J. Huang, D.H. Huang, Q.L. Huang, W.H. Huang, X.T. Huang, X.Y. Huang, Z.C. Ji, F. Ji, X.L. Jia, H.Y. Jiang, K. Jiang, Z.J. Jin, C. Ke, T. Kuleshov, D. Levochkin, K. Li, B.B. Li, Cheng Li, Cong Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, K. Li, W.L. Li, X.R. Li, Xin Li, Xin Li, Y. Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.S. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Liu, Z.X. Long, W.J. Lu, R. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Masood, A. Min, Z. Mitthumsiri, W. Montaruli, T. Nan, Y.C. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Rulev, V. Sáiz, A. Shao, L. Shchegolev, O. Sheng, X.D. Shi, J.Y. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. Sun, Z.B. Tam, P.H.T. School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China Key Laboratory of Particle Astrophyics Experimental Physics Division Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China Key Laboratory of Particle Astrophyics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin02 Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China College of Physics Sichuan University Sichuan Chengdu610065 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China School of Physics and Technology Wuhan University Hubei Wuhan430072 China Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-sen University Guangdong Zhuhai519000 China Dipartimento di Fisica dell’Università di Napoli `‘Federico II" Complesso Universitario di Monte Sant’Angelo

The atmospheric quality plays an important role in the air shower observation by the Wide Field-of-view Cherenkov Telescope Array (WFCTA) of LHAASO. A YAG imaging lidar system was developed to continuously monitor the calorimetric information. The accuracy of atmospheric monitoring is dependent on the pulse energy, the YAG laser’s beam parameters and the angular repeatability of a High-precision 3D lifting Rotating Platform (HiRoP). Therefore, we designed an optical system for this lidar with a beam splitter to divide the laser beam into a reference beam and a calibrating beam with a certain ratio and coupled the beam paths with the movement of HiRoP. Thus, every pulse energy of the calibrating beam, which has the same energy fluctuation with respect to the reference beam recorded by a power meter, could be calculated by the ratio of the two beams. Great cares were also taken to characterize the beam size, polarization and divergence of the laser. Meanwhile, a high-precision home-made thermotank was designed to control the temperature and humidity to improve the performance and stability of our laser system, which resulting in a thermal fluctuation less than 2 ◦C inside the container in the winter at an altitude of 4410 m. As a result, the pulse energy fluctuation of the laser beam for calibration was improved from 5 % to less than 2 %. As a result, we have successfully attained distinguishable full-WFCTA-view scanning Laser images in different air conditions, which could be used for the atmospheric quality analysis in further. © Copyright owned by the author(s).

关键词： Yttrium aluminum garnet

来源：评论

学校读者我要写书评

暂无评论

Monitoring the daily variation of Sun-Earth magnetic fields using galactic cosmic rays

arXiv

引用

arXiv 2024年

作者： Cao, Zhen Aharonian, F. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Bian, W. Bukevich, A.V. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, H.X. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, J.H. Fang, K. Feng, C.F. Feng, H. Feng, L. Feng, S.H. Feng, X.T. Feng, Y. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. Hasan, M. He, H.H. He, H.N. He, J.Y. He, Y. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Karpikov, I. Kuleshov, D. Kurinov, K. Li, B.B. Li, C.M. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, Jian Li, Jie Li, K. Li, S.D. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, D.B. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Luo, Q. Luo, Y. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, L.J. Pattarakijwanich, P. Pei, Z.Y. Qi, J.C. Qi, M.Y. Qiao, B.Q. Qin, J.J. Raza, A. Ruffolo, D. S'aiz, A. Saeed, M. Semikoz, D. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, D.X. University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Institute for Nuclear Research Russian Academy of Sciences Moscow117312 Russia Hebei Normal University Hebei Shijiazhuang050024 China University of Science and Technology of China Anhui Hefei230026 China State Key Laboratory of Particle Detection and Electronics China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Research Center for Astronomical Computing Zhejiang Laboratory Zhejiang Hangzhou311121 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China Key Laboratory of Radio Astronomy and Technology National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-sen University Guangdong Zhuhai51900 China Sun Yat-sen University Guangdong Guangzhou510275 China Institute of Frontier and Interdisciplinary Science Shandong University Shandong Qingdao266237 China APC Universit'e Paris Cit'e CNRS IN2P3 CEA IRFU Observatoire de Paris Paris11

The interplanetary magnetic field (IMF) between the Sun and Earth is an extension of the solar magnetic field carried by the solar wind into interplanetary space. Monitoring variations in the IMF upstream of the Earth would provide very important information for the prediction of space weather effects, such as effects of solar storms and the solar wind, on human activity. In this study, the IMF between the Sun and Earth was measured daily for the first time using a cosmic-ray observatory. Cosmic rays mainly consist of charged particles that are deflected as they pass through a magnetic field. Therefore, the cosmic-ray Sun shadow, caused by high-energy charged cosmic rays blocked by the Sun and deflected by the magnetic field, can be used to explore the transverse IMF between the Sun and Earth. By employing the powerful kilometer-square array at the Large High Altitude Air Shower Observatory, the cosmic-ray Sun shadows were observed daily with high significance for the first time. The displacement of the Sun shadow measured in 2021 correlates well with the transverse IMF component measured in situ by spacecraft near the Earth, with a time lag of 3:31 ± 0:12 days. The displacement of the Sun shadow was also simulated using Parker’s classic IMF model, yielding a time lag of 2:06 ± 0:04 days. This deviation may provide valuable insights into the magnetic field structure, which can improve space weather research. Copyright © 2024, The Authors. All rights reserved.

关键词： Cosmology

来源：评论

学校读者我要写书评

暂无评论

Sign language recognition using the fusion of image and hand landmarks through multi-headed convolutional neural network

引用

Scientific reports 2023年第1期13卷 16975页

作者： Refat Khan Pathan Munmun Biswas Suraiya Yasmin Mayeen Uddin Khandaker Mohammad Salman Ahmed A F Youssef Department of Computing and Information Systems School of Engineering and Technology Sunway University 47500 Bandar Sunway Selangor Malaysia. Department of Computer Science and Engineering BGC Trust University Bangladesh Chittagong 4381 Bangladesh. Department of Computer and Information Science Graduate School of Engineering Tokyo University of Agriculture and Technology Koganei Tokyo 184-0012 Japan. Centre for Applied Physics and Radiation Technologies School of Engineering and Technology Sunway University 47500 Bandar Sunway Selangor Malaysia. mayeenk@sunway.edu.my. Faculty of Graduate Studies Daffodil International University Daffodil Smart City Birulia Savar Dhaka 1216 Bangladesh. mayeenk@sunway.edu.my. College of Engineering and Technology American University of the Middle East Egaila Kuwait.

Sign Language Recognition is a breakthrough for communication among deaf-mute society and has been a critical research topic for years. Although some of the previous studies have successfully recognized sign language, it requires many costly instruments including sensors, devices, and high-end processing power. However, such drawbacks can be easily overcome by employing artificial intelligence-based techniques. Since, in this modern era of advanced mobile technology, using a camera to take video or images is much easier, this study demonstrates a cost-effective technique to detect American Sign Language (ASL) using an image dataset. Here, "Finger Spelling, A" dataset has been used, with 24 letters (except j and z as they contain motion). The main reason for using this dataset is that these images have a complex background with different environments and scene colors. Two layers of image processing have been used: in the first layer, images are processed as a whole for training, and in the second layer, the hand landmarks are extracted. A multi-headed convolutional neural network (CNN) model has been proposed and tested with 30% of the dataset to train these two layers. To avoid the overfitting problem, data augmentation and dynamic learning rate reduction have been used. With the proposed model, 98.981% test accuracy has been achieved. It is expected that this study may help to develop an efficient human-machine communication system for a deaf-mute society.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Kronecker CP decomposition with fast multiplication for compressing RNNs

arXiv

引用

arXiv 2020年

作者： Wang, Dingheng Wu, Bijiao Zhao, Guangshe Yao, Man Chen, Hengnu Deng, Lei Yan, Tianyi Li, Guoqi School of Automation Science and Engineering Faculty of Electronic and Information Engineering Xi'an Jiaotong University Shaanxi Xi'an710049 China Department of Precision Instrumentation Center for Brain Inspired Computing Research Beijing Innovation Center for Future Chip Tsinghua University Beijing100084 China University of California Santa BarbaraCA93106 United States School of Life Science Beijing Institute of Technology Beijing100084 China

Recurrent neural networks (RNNs) are powerful in the tasks oriented to sequential data, such as natural language processing and video recognition. However, since the modern RNNs, including long-short term memory (LSTM) and gated recurrent unit (GRU) networks, have complex topologies and expensive space/computation complexity, compressing them becomes a hot and promising topic in recent years. Among plenty of compression methods, tensor decomposition, e.g., tensor train (TT), block term (BT), tensor ring (TR) and hierarchical Tucker (HT), appears to be the most amazing approach since a very high compression ratio might be obtained. Nevertheless, none of these tensor decomposition formats can provide both the space and computation efficiency. In this paper, we consider to compress RNNs based on a novel Kronecker CANDECOMP/PARAFAC (KCP) decomposition, which is derived from Kronecker tensor (KT) decomposition, by proposing two fast algorithms of multiplication between the input and the tensor-decomposed weight. According to our experiments based on UCF11, Youtube Celebrities Face and UCF50 datasets, it can be verified that the proposed KCP-RNNs have comparable performance of accuracy with those in other tensor-decomposed formats, and even 278,219× compression ratio could be obtained by the low rank KCP. More importantly, KCP-RNNs are efficient in both space and computation complexity compared with other tensor-decomposed ones under similar ranks. Besides, we find KCP has the best potential for parallel computing to accelerate the calculations in neural networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Tensors

来源：评论

学校读者我要写书评

暂无评论

Damage Analysis of Grassland from Aerial Images Applying Convolutional Neural Networks

Damage Analysis of Grassland from Aerial Images Applying Con...

引用

International Conference on Software, Telecommunications and Computer Networks (SoftCOM)

作者： Maximilian Johenneken Ahmad Drak Rainer Herpers Bonn-Rhein-Sieg University of Applied Sciences Sankt Augustin Germany Institute of Visual Computing Bonn-Rhein-Sieg University of Applied Sciences Sankt Augustin Germany Faculty of Computer Science University of New Brunswick Fredericton Canada Lassonde School of Engineering York University Toronto Canada

ISBN: (数字)9789532900996

ISBN: (纸本)9781728175386

Damage to grasslands is mainly caused by wild boar during foraging. Farmers in Germany thereby register yield losses and expenses for damage repair. This contribution analyzes the acquisition and processing of aerial images to orthomosaics and image segmentation to perform spatial measurements of damaged patches in grasslands. A sample set of manually annotated orthomosaics is analyzed. Preliminary classification results applying a convolutional neural network approach to segment damaged patches are presented. First results show the applicability of the applied methods in the detection of damage caused by wild boar and suggest that other damage causes (e.g., mole damage) should be considered to improve results.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Arm order recognition in multi-armed bandit problem with laser chaos time series

arXiv

引用

arXiv 2020年

作者： Narisawa, Naoki Chauvet, Nicolas Hasegawa, Mikio Naruse, Makoto Department of Mathematical Engineering and Information Physics Faculty of Engineering University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Department of Information Physics and Computing Graduate School of Information Science and Technology University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Department of Electrical Engineering Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-0051 Japan

By exploiting ultrafast and irregular time series generated by lasers with delayed feedback, we have previously demonstrated a scalable algorithm to solve multi-armed bandit (MAB) problems utilizing the time-division multiplexing of laser chaos time series. Although the algorithm detects the arm with the highest reward expectation, the correct recognition of the order of arms in terms of reward expectations is not achievable. Here, we present an algorithm where the degree of exploration is adaptively controlled based on confidence intervals that represent the estimation accuracy of reward expectations. We have demonstrated numerically that our approach did improve arm order recognition accuracy significantly, along with reduced dependence on reward environments, and the total reward is almost maintained compared with conventional MAB methods. This study applies to sectors where the order information is critical, such as efficient allocation of resources in information and communications technology. Copyright © 2020, The Authors. All rights reserved.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Airr Community Curation and Standardised Representation for Immunoglobulin and T Cell Receptor Germline Sets

SSRN

引用

SSRN 2022年

作者： Lees, William D. Christley, Scott Peres, Ayelet Kos, Justin T. Corrie, Brian Ralph, Duncan Breden, Felix Cowell, Lindsay G. Yaari, Gur Corcoran, Martin Karlsson Hedestam, Gunilla B. Ohlin, Mats Collins, Andrew M. Watson, Corey T. Busse, Christian E. Institute of Structural and Molecular Biology Birkbeck College London United Kingdom Human-Centered Computing and Information Science Institute for Systems and Computer Engineering Technology and Science Porto Portugal Peter O’Donnell Jr School of Public Health Department of Immunology UT Southwestern Medical Center Texas United States Bioengineering Program Faculty of Engineering Bar-Ilan University Ramat Gan Israel Department of Biochemistry and Molecular Genetics School of Medicine University of Louisville Kentucky United States Department of Biological Sciences Simon Fraser University BurnabyBC Canada Fred Hutchinson Cancer Research Center SeattleWA United States Department of Microbiology Tumor and Cell Biology Karolinska Institute Stockholm Sweden Department of Immunotechnology Lund University Lund Sweden School of Biotechnology and Biomolecular Sciences University of New South Wales SydneyNSW Australia Division of B Cell Immunology German Cancer Research Center Heidelberg Germany

Analysis of an individual’s immunoglobulin or T cell receptor gene repertoire can provide important insights into immune function. High-quality analysis of adaptive immune receptor repertoire sequencing data depends upon accurate and relatively complete germline sets, but current sets are known to be incomplete. Established processes for the review and systematic naming of receptor germline genes and alleles require specific evidence and data types, but the discovery landscape is rapidly changing. To exploit the potential of emerging data, and to provide the field with improved state-of-the-art germline sets, an intermediate approach is needed that will allow the rapid publication of consolidated sets derived from these emerging sources. These sets must use a consistent naming scheme and allow refinement and consolidation into genes as new information emerges. Name changes should be minimised, but, where changes occur, the naming history of a sequence must be traceable. Here we outline the current issues and opportunities for the curation of germline IG/TR genes and present a forward-looking data model for building out more robust germline sets that can dovetail with current established processes and provides transparency based on principles of findability, accessibility, interoperability, and reusability. We describe results obtained by applying the data model and associated principles within the AIRR Community, including supporting software and databases. © 2022, The Authors. All rights reserved.

关键词： Genes

来源：评论

学校读者我要写书评

暂无评论

Autonomous Demand Side Management of Electric Vehicles in a Distribution Grid 7

Autonomous Demand Side Management of Electric Vehicles in a ...

引用

7th International Youth Conference on Energy, IYCE 2019

作者： Ireshika, Muhandiram Arachchige Subodha Tharangi Preissinger, Markus Kepplinger, Peter Josef Ressel Center for Applied Scientific Computing in Energy Finance and Logistics Vorarlberg University of Applied Sciences Dornbirn Austria Illwerke Vkw Professorship for Energy Efficiency Energy Research Center Vorarlberg University of Applied Sciences Dornbirn Austria Faculty of Engineering and Science University of Agder Grimstad Norway

ISBN: (纸本)9781728139234

The electricity demand due to the increasing number of EVs presents new challenges for the operation of the electricity network, especially for the distribution grids. The existing grid infrastructure may not be sufficient to meet the new demands imposed by the integration of EVs. Thus, EV charging may possibly lead to reliability and stability issues, especially during the peak demand periods. Demand side management (DSM) is a potential and promising approach for mitigation of the resulting impacts. In this work, we developed an autonomous DSM strategy for optimal charging of EVs to minimize the charging cost and we conducted a simulation study to evaluate the impacts to the grid operation. The proposed approach only requires a one way communicated incentive. Real profiles from an Austrian study on mobility behavior are used to simulate the usage of the EVs. Furthermore, real smart meter data are used to simulate the household base load profiles and a real low voltage grid topology is considered in the load flow simulation. Day-ahead electricity stock market prices are used as the incentive to drive the optimization. The results for the optimum charging strategy is determined and compared to uncontrolled EV charging. The results for the optimum charging strategy show a potential cost saving of about 30.8% compared to uncontrolled EV charging. Although autonomous DSM of EVs achieves a shift of load as pursued, distribution grid operation may be substantially affected by it. We show that in the case of real time price driven operation, voltage drops and elevated peak to average powers result from the coincident charging of vehicles during favourable time slots. © 2019 IEEE.

关键词： Demand side management

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：