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arXiv 2023年

作者： Amaral, Paulo Carbonell-Sala, Silvia De La Vega, Francisco M. Faial, Tiago Frankish, Adam Gingeras, Thomas Guigo, Roderic Harrow, Jennifer L. Hatzigeorgiou, Artemis G. Johnson, Rory Murphy, Terence D. Pertea, Mihaela Pruitt, Kim D. Pujar, Shashikant Takahashi, Hazuki Ulitsky, Igor Varabyou, Ales Wells, Christine A. Yandell, Mark Carninci, Piero Salzberg, Steven L. INSPER Institute of Education and Research SP São Paulo Brazil Dr. Aiguader 88 Catalonia Barcelona08003 Spain Department of Biomedical Data Science Stanford University School of Medicine StanfordCA United States Tempus Labs Inc. ChicagoIL United States Nature Genetics San FranciscoCA United States European Molecular Biology Laboratory European Bioinformatics Institute Wellcome Genome Campus Hinxton CambridgeCB10 1SD United Kingdom Department of Functional Genomics Cold Spring Harbor Laboratory Cold Spring HarborNY United States Catalonia Barcelona Spain Centre for Genomics Research Discovery Sciences AstraZeneca Da Vinci Building. Melbourn Science Park RoystonSG8 6HB United Kingdom Universithy of Thessaly Department of Computer Science and Biomedical Informatics Lamia Greece Hellenic Pasteur Institute Athens Greece School of Biology and Environmental Science University College Dublin DublinD04 V1W8 Ireland Conway Institute of Biomedical and Biomolecular Research University College Dublin DublinD04 V1W8 Ireland Department of Medical Oncology Inselspital Bern University Hospital University of Bern Bern3010 Switzerland Department for BioMedical Research University of Bern Bern3008 Switzerland National Center for Biotechnology Information National Library of Medicine National Institutes of Health BethesdaMD20894 United States Center for Computational Biology Johns Hopkins University BaltimoreMD United States Department of Biomedical Engineering Johns Hopkins University BaltimoreMD United States Laboratory for Transcriptome Technology RIKEN Center for Integrative Medical Sciences Kanagawa Yokohama230-0045 Japan Department of Immunology and Regenerative Biology Department of Molecular Neuroscience Weizmann Institute of Science Rehovot76100 Israel Department of Computer Science Johns Hopkins University BaltimoreMD United States Stem Cell Systems Department of Anatomy and Physiology Faculty of Medicine Dentistry and Health Scien

Scientists have been trying to identify all of the genes in the human genome since the initial draft of the genome was published in 2001. Over the intervening years, much progress has been made in identifying protein-coding genes, and the estimated number has shrunk to fewer than 20,000, although the number of distinct protein-coding isoforms has expanded dramatically. The invention of high-throughput RNA sequencing and other technological breakthroughs have led to an explosion in the number of reported non-coding RNA genes, although most of them do not yet have any known function. A combination of recent advances offers a path forward to identifying these functions and towards eventually completing the human gene catalogue. However, much work remains to be done before we have a universal annotation standard that includes all medically significant genes, maintains their relationships with different reference genomes, and describes clinically relevant genetic variants. © 2023, CC BY.

关键词： Genes

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SPA-SSD: Exploit Heterogeneity and Parallelism of 3D SLC-TLC Hybrid SSD to Improve Write Performance

SPA-SSD: Exploit Heterogeneity and Parallelism of 3D SLC-TLC...

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IEEE International Conference on computer Design: VLSI in computers and Processors, (ICCD)

作者： Wenhui Zhang Qiang Cao Hong Jiang Jie Yao Yuanyuan Dong Puyuan Yang Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Huazhong University of Science and Technology Wuhan China Department of Computer Science and Engineering University of Texas at Arlington Arlington Texas School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Alibaba Group. Hangzhou China

To address the write performance problem suffered by MLC/TLC flash, researchers have proposed hybrid SSD that aims to combine the strengths of SLC flash, used as the write-buffer zone for its superior write performance, and MLC/TLC flash, as the capacity zone for its high storage density. While leveraging SLC as a physical write-buffer zone is proven effective in traditional 2D hybrid SSDs, how to effectively incorporate SLC into a 3D-stacked TLC to form a hybrid SSD has not been studied to the best of our knowledge. Yet this is a timely and important performance issue for 3D-stacked TLC given its one-shot programming scheme that results in much worse write performance than the programming scheme in 2D TLC where pages are associated with different bits of a cell and programmed in sequence separately. We believe that naively adopting the two-physical-zone approach to 3D hybrid SSD will miss a great opportunity for performance optimization because it ignores the inherent four-level parallelism (channel/chip/die/plane) of the flash chip array. To this end, we propose in this paper an SLC and Parallelism Aware hybrid SSD (SPA-SSD) to take full advantages of SLC's superior write performance, the internal multi-level parallelism of SSD, and the high storage density of 3D-stacked TLC flash. Two novel techniques enable SPA-SSD to be highly effective: (1) Type-Parallelism Joint Page Allocation (TPJ-PA), which allocates pages for write transactions according to not only available SLC pages but also parallelism to maximize resource utilization within the hybrid SSD, and (2) Queue-length and Parallelism Constrained Data Migration (QPC-DM), which triggers data migration without degrading user write performance by analyzing the device queue length and available flash resources. To evaluate performance of SPA-SSD, a hybrid SSD simulator, called HybridSim, is developed based on MQSim. Experimental results on HybridSim show that TPJ-PA improves write throughput by 60%, while QPC-DM

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Fourier-based rotation-invariant feature boosting: An efficient framework for geospatial object detection

arXiv

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arXiv 2019年

作者： Wu, Xin Hong, Danfeng Chanussot, Jocelyn Xu, Yang Tao, Ran Wang, Yue School of Information and Electronics Beijing Institute of Technology Beijing Key Laboratory of Fractional Signals and Systems School of Information and Electronics Beijing Institute of Technology Beijing100081 China Wessling82234 Germany Munich80333 Germany Univ. Grenoble Alpes CNRS Grenoble INP GIPSA-lab GrenobleF-38000 France Faculty of Electrical and Computer Engineering University of Iceland Reykjavik101 Iceland School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

This is the pre-acceptance version, to read the final version please go to IEEE Geoscience and Remote Sensing Letters on IEEE Xplore. Geospatial object detection of remote sensing imagery has been attracting an increasing interest in recent years, due to the rapid development in spaceborne imaging. Most of previously proposed object detectors are very sensitive to object deformations, such as scaling and rotation. To this end, we propose a novel and efficient framework for geospatial object detection in this letter, called Fourier-based rotation-invariant feature boosting (FRIFB). A Fourier-based rotation-invariant feature is first generated in polar coordinate. Then, the extracted features can be further structurally refined using aggregate channel features. This leads to a faster feature computation and more robust feature representation, which is good fitting for the coming boosting learning. Finally, in the test phase, we achieve a fast pyramid feature extraction by estimating a scale factor instead of directly collecting all features from image pyramid. Extensive experiments are conducted on two subsets of NWPU VHR-10 dataset, demonstrating the superiority and effectiveness of the FRIFB compared to previous state-of-the-art methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Aggregates

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MMC-HVDC transmission line protection based on Bergeron model and state estimation

MMC-HVDC transmission line protection based on Bergeron mode...

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8th Renewable Power Generation Conference (RPG 2019)

作者： Binglin Wang Yu Liu Dayou Lu Xiaodong Zheng School of Information Science and Technology ShanghaiTech University Shanghai China Key Laboratory of Control of Power Transmission and Conversion Ministry of Education Shanghai China Key Laboratory of Control of Power Transmission and Conversion Ministry of Education Shanghai China Department of Electrical Power Engineering Shanghai Jiao University Shanghai China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

This paper presents a novel protection scheme for MMC-HVDC transmission lines. The physical laws that the MMC-HVDC transmission line should obey is firstly described using the Bergeron model, to fully consider distributed shunt capacitance of the line. Afterwards, the proposed protection method checks the consistency between the instantaneous measurements and the model of the MMC-HVDC line under protection and trips the transmission line if any inconsistency is detected. State estimation algorithm is utilized to make full use of the redundancy of available measurements as well as minimize the influence of measurement errors. Simulation results prove that the protection algorithm can quickly and dependably trip internal faults as well as securely ignore external faults, independent of fault type, location and impedances. In addition, the protection algorithm also demonstrates robustness towards measurement errors.

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PID2018 Benchmark Challenge: Model-based Feedforward Compensator with A Conditional Integrator

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IFAC-PapersOnLine 2018年第4期51卷 888-893页

作者： Yuan, Jie Ates, Abdullah Dehghan, Sina Zhao, Yang Fei, Shumin Chen, YangQuan School of Automation Southeast University Nanjing210096 China Engineering Faculty Computer Engineering Department Inonu University Malatya44280 Turkey Mechatronics Embedded Systems and Automation Lab University of California MercedCA95340 United States School of Science and Engineering Shandong University Jinan250061 China Key Laboratory of Measurement and Control of CSE Ministry of Education School of Automation Southeast University Nanjing210096 China

Since proportional-integral-derivative (PID) controllers absolutely dominate the control engineering, numbers of different control structures and theories have been developed to enhance the efficiency of PID controllers. Thus, it is essential and inspiring to operate different PID control strategies to the PID2018 Benchmark Challenge. In this paper, a novel control strategy is designed for this refrigeration system, where a feedforward compensator and a conditional integrator are utilized to compensate the disturbances and remove the steady-state error in the benchmark problem, respectively. The simulation results given in the benchmark problem show the straightforward effectiveness of the proposed control structure compared with the existing control methods. © 2018

关键词： controllers Benchmarking Disturbance rejection Electric control equipment Proportional control systems Refrigeration Three term control systems Two term control systems Conditional integrators Feed forward compensation Model based method PID controllers Refrigeration system

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Prediction-based Optimal Distributed Filtering with Communication Delay over Sensor Networks

Prediction-based Optimal Distributed Filtering with Communic...

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第三十八届中国控制会议

作者： Jun Hu Guo-Ping Liu Zidong Wang Hongxu Zhang School of Engineering University of South Wales Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology CTGT center Harbin Institute of Technology Department of Computer Science Brunel University London School of Measurement and Communication Harbin University of Science and Technology

In this paper, the prediction-based distributed filtering problem is discussed for a class of time-varying stochastic systems with communication delay and different types of noises over sensor networks. The communication delay is characterized when the state estimations are transmitted between adjacent sensor nodes. In order to compensate the effects induced by the communication delay, the prediction-based idea is employed and then the active compensation estimation is provided when designing the time-varying distributed filter. In particular, both the prediction-based state estimation and its own innovation measurements are utilized in terms of the concerned sensor networks under given topological structure. Subsequently, a locally minimum upper bound of the filtering error covariance is given by determining the filter gain at each time step. Finally, the validity and advantages of the presented prediction-based distributed filtering method are illustrated by some simulations.

关键词： Time-varying stochastic systems Sensor networks Optimal distributed filtering Communication delay Prediction compensation

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Integration of domain knowledge using medical knowledge graph deep learning for cancer phenotyping

arXiv

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arXiv 2021年

作者： Alawad, Mohammed Gao, Shang Shekar, Mayanka Chandra Hasan, S.M. Shamimul Christian, J. Blair Wu, Xiao-Cheng Durbin, Eric B. Doherty, Jennifer Stroup, Antoinette Coyle, Linda Penberthy, Lynne Tourassi, Georgia Electrical and Computer Engineering Department Wayne State University DetroitMI United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN United States Louisiana Tumor Registry Louisiana State University Health Sciences Center New OrleansLA United States Kentucky Cancer Registry and College of Medicine University of Kentucky LexingtonKY United States Utah Cancer Registry University of Utah School of Medicine Salt Lake CityUT United States New Jersey State Cancer Registry New Jersey Department of Health TrentonNJ United States Information Management Services Inc CalvertonMD United States Surveillance Research Program Division of Cancer Control and Population Sciences National Cancer Institute BethesdaMD United States National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN United States

A key component of deep learning (DL) for natural language processing (NLP) is word embeddings. Word embeddings that effectively capture the meaning and context of the word that they represent can significantly improve the performance of downstream DL models for various NLP tasks. Many existing word embeddings techniques capture the context of words based on word co-occurrence in documents and text;however, they often cannot capture broader domain-specific relationships between concepts that may be crucial for the NLP task at hand. In this paper, we propose a method to integrate external knowledge from medical terminology ontologies into the context captured by word embeddings. Specifically, we use a medical knowledge graph, such as the unified medical language system (UMLS), to find connections between clinical terms in cancer pathology reports. This approach aims to minimize the distance between connected clinical concepts. We evaluate the proposed approach using a Multitask Convolutional Neural Network (MT-CNN) to extract six cancer characteristics – site, subsite, laterality, behavior, histology, and grade – from a dataset of 900K cancer pathology reports. The results show that the MT-CNN model which uses our domain informed embeddings outperforms the same MT-CNN using standard word2vec embeddings across all tasks, with an improvement in the overall micro- and macro-F1 scores by 4.97%and 22.5%, respectively. Copyright © 2021, The Authors. All rights reserved.

关键词： Natural language processing systems

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Broadband enhancement of on-chip single photon extraction via tilted hyperbolic metamaterials

arXiv

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arXiv 2020年

作者： Shen, Lian Lin, Xiao Shalaginov, Mikhail Low, Tony Zhang, Xianmin Zhang, Baile Chen, Hongsheng Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Electromagnetics Academy at Zhejiang University Zhejiang University Hangzhou310027 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore637371 Singapore DepartmentofMaterialsScienceandEngineering MassachusettsInstituteofTechnology 77 MassachusettsAvenue CambridgeMA02139 United States Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States School of Physical and Mathematical Sciences Nanyang Technological University Singapore637371 Singapore

A fundamental building block for on-chip quantum photonics is a single-photon source with high repetition rates, which can enable many applications such as high-speed quantum communication and quantum information processing. Ideally, such single photon sources would then require a large on-chip photon extraction decay rate, namely the rate of excited photons coupled into nanofibers or waveguides, over a broad spectral range. However, this goal has remained elusive till date. Here we propose a feasible scheme to enhance the on-chip photon extraction decay rate of quantum emitters, through the tilting of the optical axis of hyperbolic metamaterials with respect to the end-facet of nanofibers. Importantly, the revealed scheme is applicable to arbitrarily orientated quantum emitters over a broad spectral range, e.g., up to ~80 nm for visible light. The underlying physics relies on the emerging unique feature of hyperbolic metamaterials if their optical axis is judiciously tilted. That is, their supported high-k (i.e., wavevector) hyperbolic eigenmodes, which are intrinsically confined inside them if their optical axis is un-tilted, can now become momentum-matched with the guided modes of nanofibers, and more importantly, they can safely couple into nanofibers almost without reflection. Copyright © 2020, The Authors. All rights reserved.

关键词： Nanofibers

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Experimental implementation of bias-free quantum random number generator based on vacuum fluctuation

arXiv

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arXiv 2019年

作者： Zheng, Ziyong Zhang, Yichen Yu, Song Guo, Hong State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Center for Quantum Information Technology Peking University Beijing100871 China

We experimentally demonstrate a bias-free optical quantum random number generator with real-time randomness extraction to directly output uniform distributed random numbers by measuring the vacuum fluctuation of quantum state. A phase modulator is utilized in the scheme to effectively reduce the influence of deviations between two arms of the generator caused by the imperfect practical devices, which is an innovative solution in the field of quantum random number generator. In the case where the feedback modulation frequency is much faster than the phase jitter, an unbiased result can be obtained by an additional subtraction between the compensation signal and its average value to eliminate residual deviation. A following randomness extractor is applied to eliminate the influence of residual side information introduced by the imperfect devices in practical system. Copyright © 2019, The Authors. All rights reserved.

关键词： Random number generation

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A review and discussion of decomposition-based hybrid models for wind energy forecasting applications

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Applied Energy 2019年 235卷 939-953页

作者： Zheng Qian Yan Pei Hamidreza Zareipour Niya Chen School of Instrumentation Science and Opto-electronics Engineering Beihang University Beijing China Key Laboratory of Precision Opto-Mechatronics Technology Ministry of Education Beihang University Beijing China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing 100192 China Department of Electrical and Computer Engineering University of Calgary Calgary Alberta Canada ABB Corporate Research Center Beijing China

With the continuous growth of wind power integration into the electrical grid, accurate wind power forecasting is an important component in management and operation of power systems. Given the challenging nature of wind power forecasting, various methods are presented in the literature to improve wind power forecasting accuracy. Among them, combining different techniques to construct hybrid models has been frequently reported in the literature. Decomposition-based models are a family of hybrid models that firstly decompose the wind speed/power time series into relatively more stationary subseries, and then build forecasting models for each subseries. In this paper, we present a comprehensive review of decomposition-based wind forecasting methods in order to explore their effectiveness. Decomposition-based hybrid forecasting models are classified into different groups based on the decomposition methods, such as, wavelet, empirical mode decomposition, seasonal adjust methods, variational mode decomposition, intrinsic time-scale decomposition, and bernaola galvan algorithm. We discuss decomposition methods in the context of alternative forecasting algorithms, and explore the challenges of each method. Comparative analysis of various decomposition-based models is also provided. We also explore current research activities and challenges, and identify potential directions for future research on this subject.

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