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Conference on Control and Fault-Tolerant Systems (SysTol)

作者： Radhia Fazai Majdi Mansouri Kamal Abodayeh Mohamed Trabelsi Hazem Nounou Mohamed Nounou Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Department of Mathematical Sciences Prince Sultan University Riyadh Saudi Arabia Department of Electronic and Communications Engineering Kuwait College of Science and Technology Kuwait Chemical Engineering Program Texas A&M University at Qatar Doha Qatar

ISBN: (纸本)9781728103815

This paper elaborates the development of machine learning approach merged with statistical hypothesis testing aimed at enhancing the operation of photovoltaic (PV) systems by developing intelligent PV fault detection framework. Fault detection in PV systems is important to ensure optimal energy harvesting and reliable power production because PV systems usually operate in a harsh outdoor environment and tend to suffer various faults. In this paper, therefore, special attention is paid to detection of various faults during different modes of operation. The proposed approach merges the benefits of machine learning technique (MLT) with statistical hypothesis testing to enhance the fault detection and monitoring of PV systems. The proposed technique will be effective in monitoring the PV faults under both normal and abnormal conditions. For the framework developed, the modeling phase is addressed using MLT and the faults are detected using the generalized likelihood ratio test (GLRT) chart. The MLT is used to compute the residuals monitored and the GLRT chart is applied to the monitored residuals evaluated for fault detection purposes. The developed MLT-based GLRT algorithm is implemented and validated using both simulated and real PV data. The results are evaluated in terms of false alarm rates (FAR), missed detection rates (MDR) and computation time.

关键词： Ground penetrating radar Monitoring Circuit faults Testing Photovoltaic systems Fault detection

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A methodology to investigate the relationship between cancer cells cell-cycle phase and their migratory behaviors

A methodology to investigate the relationship between cancer...

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Clinical and Translational Biophotonics, TRANSLATIONAL 2018

作者： Pourfarhangi, Kamyar Esmaeili Bayarmagnai, Battuya de la Hoz, Edgar Cardenas Cohen, Andrew Gligorijevic, Bojana Bioengineering department College of Engineering Temple University PhiladelphiaPA19122 United States Department of Electrical and Computer Engineering College of Engineering Drexel University PhiladelphiaPA19104 United States Cancer Biology Program Fox Chase Cancer Center PhiladelphiaPA19111 United States

We present a methodology integrating live-cell fluorescent microscopy, cell labeling, PDMS fabricated micro-channels (2D) and tumor spheroids (3D), and automated cell tracking in order to investigate cell-cycle phase ... 详细信息

ISBN: (纸本)9781943580415

关键词： Cancer cells

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Automatic Extraction of Medication Mentions from Tweets-Overview of the BioCreative VII Shared Task 3 Competition

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Database : the journal of biological databases and curation 2023年第2023期2023卷 baac108页

作者： Davy Weissenbacher Karen O'Connor Siddharth Rawal Yu Zhang Richard Tzong-Han Tsai Timothy Miller Dongfang Xu Carol Anderson Bo Liu Qing Han Jinfeng Zhang Igor Kulev Berkay Köprü Raul Rodriguez-Esteban Elif Ozkirimli Ammer Ayach Roland Roller Stephen Piccolo Peijin Han V G Vinod Vydiswaran Ramya Tekumalla Juan M Banda Parsa Bagherzadeh Sabine Bergler João F Silva Tiago Almeida Paloma Martinez Renzo Rivera-Zavala Chen-Kai Wang Hong-Jie Dai Luis Alberto Robles Hernandez Graciela Gonzalez-Hernandez Department of Computational Biomedicine Cedars-Sinai Medical Center Los Angeles CA USA. DBEI The Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Computer Science and Information Engineering National Central University No. 300 Zhongda Rd Zhongli District Taoyuan 320 Taiwan. IoX Center National Taiwan University Da'an District Section 4 Roosevelt Rd No. 1 Barry Lam Hall Taipei 106 Taiwan. Research Center for Humanities and Social Sciences Academia Sinica No. 128 Section 2 Academia Rd Nangang District Taipei 115 Taiwan. Computational Health Informatics Program Boston Children's Hospital Boston MA USA. Department of Pediatrics Harvard Medical School Boston MA USA. NVIDIA Santa Clara CA USA. Department of Statistics Florida State University Tallahassee FL USA. Data and Analytics Chapter F. Hoffmann-La Roche Ltd Switzerland. Pharmaceutical Research and Early Development Roche Innovation Center Basel Switzerland. Speech and Language Technology Lab DFKI Berlin Germany. Department of Biology Brigham Young University Provo UT USA. Department of Computational Medicine and Bioinformatics Medical School University of Michigan Ann Arbor MI USA. Department of Learning Health Sciences Medical School University of Michigan Ann Arbor MI USA. School of Information University of Michigan Ann Arbor MI USA. Department of Computer Science Georgia State University Atlanta GA USA. CLaC Labs Concordia University Montreal Canada. DETI Institute of Electronics and Informatics Engineering of Aveiro University of Aveiro Portugal. Department of Computation University of A Coruña Spain. Computer Science and Engineering Department Universidad Carlos III de Madrid Madrid Spain. Big Data Laboratory Chunghwa Telecom Laboratories Taoyuan Taiwan. Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan. Department of Electrical Engineering College of Electrical Engineering and Computer Sci

This study presents the outcomes of the shared task competition BioCreative VII (Task 3) focusing on the extraction of medication names from a Twitter user's publicly available tweets (the user's 'timeline'). In general, detecting health-related tweets is notoriously challenging for natural language processing tools. The main challenge, aside from the informality of the language used, is that people tweet about any and all topics, and most of their tweets are not related to health. Thus, finding those tweets in a user's timeline that mention specific health-related concepts such as medications requires addressing extreme imbalance. Task 3 called for detecting tweets in a user's timeline that mentions a medication name and, for each detected mention, extracting its span. The organizers made available a corpus consisting of 182 049 tweets publicly posted by 212 Twitter users with all medication mentions manually annotated. The corpus exhibits the natural distribution of positive tweets, with only 442 tweets (0.2%) mentioning a medication. This task was an opportunity for participants to evaluate methods that are robust to class imbalance beyond the simple lexical match. A total of 65 teams registered, and 16 teams submitted a system run. This study summarizes the corpus created by the organizers and the approaches taken by the participating teams for this challenge. The corpus is freely available at https://***/tasks/biocreative-vii/track-3/. The methods and the results of the competing systems are analyzed with a focus on the approaches taken for learning from class-imbalanced data.

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SI-spreading-based network embedding in static and temporal networks

arXiv

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arXiv 2020年

作者： Zhan, Xiu-Xiu Li, Ziyu Masuda, Naoki Holme, Petter Wang, Huijuan Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands Department of Mathematics University at Buffalo State University of New York Buffalo New YorkNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York Buffalo New YorkNY14260-2900 United States Institute of Innovative Research Tokyo Institute of Technology Yokohama226-8503 Japan

Link prediction can be used to extract missing information, identify spurious interactions as well as forecast network evolution. Network embedding is a methodology to assign coordinates to nodes in a low-dimensional vector space. By embedding nodes into vectors, the link prediction problem can be converted into a similarity comparison task. Nodes with similar embedding vectors are more likely to be connected. Classic network embedding algorithms are random-walk-based. They sample trajectory paths via random walks and generate node pairs from the trajectory paths. The node pair set is further used as the input for a Skip-Gram model, a representative language model that embeds nodes (which are regarded as words) into vectors. In the present study, we propose to replace random walk processes by a spreading process, namely the susceptible-infected (SI) model, to sample paths. Specifically, we propose two SI-spreading-based algorithms, SINE and TSINE, to embed static and temporal networks, respectively. The performance of our algorithms is evaluated by the missing link prediction task in comparison with state-of-the-art static and temporal network embedding algorithms. Results show that SINE and TSINE outperform the baselines across all six empirical datasets. We further find that the performance of SINE is mostly better than TSINE, suggesting that temporal information does not necessarily improve the embedding for missing link prediction. Moreover, we study the effect of the sampling size, quantified as the total length of the trajectory paths, on the performance of the embedding algorithms. The better performance of SINE and TSINE requires a smaller sampling size in comparison with the baseline algorithms. Hence, SI-spreading-based embedding tends to be more applicable to large-scale networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Network embeddings

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Historical growth of concept networks in Wikipedia

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Collective Intelligence 2022年第2期1卷 26339137221109839页

作者： Harang Ju Dale Zhou Ann S Blevins David M Lydon-Staley Judith Kaplan Julio R Tuma Dani S Bassett Neuroscience Graduate Group University of Pennsylvania Philadelphia PA USA Department of Bioengineering School of Engineering & Applied Science University of Pennsylvania Philadelphia PA USA Annenberg School for Communication University of Pennsylvania Philadelphia PA USA Department of History and Sociology of Science College of Arts and Sciences University of Pennsylvania Philadelphia PA USA Integrated Studies Program College of Arts and Sciences University of Pennsylvania Philadelphia PA USA Integrated Studies Program College of Arts and Sciences University of Pennsylvania Philadelphia PA USA Department of Philosophy College of Arts and Sciences University of Pennsylvania Philadelphia PA USA Department of Electrical & Systems Engineering School of Engineering & Applied Science University of Pennsylvania Philadelphia PA USA Department of Physics & Astronomy College of Arts & Sciences University of Pennsylvania Philadelphia PA USA Department of Neurology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Psychiatry Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Santa Fe Institute Santa Fe NM USA

Philosophers of science have long questioned how collective scientific knowledge grows. Although disparate answers have been posited, empirical validation has been challenging due to limitations in collecting and systematizing large historical records. Here, we introduce new methods to analyze scientific knowledge formulated as a growing network of articles on Wikipedia and their hyperlinks. We demonstrate that in Wikipedia, concept networks in subdisciplines of science do not grow by expanding from their central core to reach an ancillary periphery. Instead, science concept networks in Wikipedia grow by creating and filling knowledge gaps. Notably, the process of gap formation and closure may be valued by the scientific community, as evidenced by the fact that it produces discoveries that are more frequently awarded Nobel prizes than other processes. To determine whether and how the gap process is interrupted by paradigm shifts, we operationalize a paradigm as a particular subdivision of scientific concepts into network modules. Hence, paradigm shifts are reconfigurations of those modules. The approach allows us to identify a temporal signature in structural stability across scientific subjects in Wikipedia. In a network formulation of scientific discovery, our findings suggest that data-driven conditions underlying scientific breakthroughs depend as much on exploring uncharted gaps as on exploiting existing disciplines and support policies that encourage new interdisciplinary research.

关键词： science of science networks philosophy of science Wikipedia cavity

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Three-dimensional bioprinting of gelatin methacryloyl (GelMA)

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Bio-Design and Manufacturing 2018年第4期1卷 215-224页

作者： Guoliang Ying Nan Jiang Cunjiang Yu Yu Shrike Zhang Division of Engineering in Medicine Department of MedicineBrigham and Women's HospitalHarvard Medical SchoolCambridgeMA 02139USA School of Materials Science and Engineering Wuhan Institute of TechnologyWuhan 430205People's Republic of China School of Engineering and Applied Sciences Harvard UniversityCambridgeMA 02139USA Departments of Mechanical Engineering Electrical and Computer EngineeringBiomedical EngineeringMaterials Science and Engineering ProgramThe Texas Center for SuperconductivityUniversity of HoustonHoustonTX 77204USA

The three-dimensional (3D)bioprinting technology has progressed tremendously over the past *** controlling the size, shape,and architecture of the bioprinted constructs,3D bioprinting allows for the fabrication of tissue/organ-like constructs with strong structural-functional similarity with their in vivo counterparts at high *** bioink,a blend of biomaterials and living cells possessing both high biocompatibility and printability,is a critical component of *** particular, gelatin methacryloyl (GelMA)has shown its potential as a viable bioink material due to its suitable biocompatibility and readily tunable physicochemical *** GelMA-based bioinks and relevant bioprinting strategies for GelMA bioprinting are briefly reviewed.

关键词： Bioprinting Bioink Gelatin methacryloyl (GelMA) Biofabrication -Tissue engineering Tissue model

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Discovery of ionic impact ionization (I3) in perovskites triggered by a single photon

arXiv

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arXiv 2019年

作者： Xu, Zihan Yu, Yugang Niaz, Iftikhar Ahmad Chen, Yimu Arya, Shaurya Lei, Yusheng Miah, Mohammad Abu Raihan Zhou, Jiayun Zhang, Alex Ce Yan, Lujiang Xu, Sheng Nomura, Kenji Lo, Yu-Hwa Department of NanoEngineering University of California San DiegoCA United States Material Science and Engineering Program University of California San DiegoCA United States Department of Electrical and Computer Engineering University of California San DiegoCA United States

Organic-inorganic metal halide perovskite devices have generated significant interest for LED, photodetector, and solar cell applications due to their attractive optoelectronic properties and substrate-choice flexibility1-4. These devices exhibit slow time-scale response, which have been explained by point defect migration5-6. In this work, we report the discovery of a room temperature intrinsic amplification process in methylammonium lead iodide perovskite (MAPbI3) that can be triggered by few photons, down to a single photon. The electrical properties of the material, by way of photoresponse, are modified by an input energy as small as 0.19 attojoules, the energy of a single photon. These observations cannot be explained by photo-excited electronic band-to-band transitions or prevailing model of photoexcited point defect migration since none of the above can explain the observed macroscopic property change by absorption of single or few photons. The results suggest the existence of an avalanche-like collective motion of iodides and their accumulation near the anode, which we will call "ionic impact ionization" (I3 mechanism). The proposed I3 process is the ionic analog of the electronic impact ionization, and has been considered impossible before because conventionally it takes far more energy to move ions out of their equilibrium position than electrons. We have performed first principle calculations to show that in MAPbI3 the activation energy for the I3 mechanism is appreciably lower than the literature value of the activation energy for the electronic impact ionization. The discovery of I3 process in perovskite material opens up possibilities for new classes of devices for photonic and electronic applications. Copyright © 2019, The Authors. All rights reserved.

关键词： Iodine compounds

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Iterative Motion Compensation reconstruction ultra-short TE(iMoCo UTE) for high resolution free breathing pulmonary MRI

arXiv

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arXiv 2020年

作者： Zhu, Xucheng Chan, Marilynn Lustig, Michael Johnson, Kevin Larson, Peder E.Z. UCSF/UC Berkeley Graduate Program in Bioengineering University of California San Francisco San FranciscoCA United States Department of Radiology and Biomedical Imaging University of California San Francisco San FranciscoCA United States Department of Pediatrics Division of Pediatric Pulmonology University of California San Francisco San FranciscoCA United States Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA United States Department of Medical Physics University of Wisconsin Madison MadisonWI United States Department of Radiology University of Wisconsin Madison MadisonWI United States

Purpose: To develop a high scanning efficiency, motion corrected imaging strategy for free-breathing pulmonary MRI by combining a motion compensation reconstruction with a UTE acquisition, called iMoCo UTE. Methods: An optimized golden angle ordering radial UTE sequence was used to continuously acquire data for 5 minutes. All readouts were grouped to different respiratory motion states based on self-navigator signals, then motion resolved data was reconstructed by XD Golden-angle RAdial Sparse Parallel reconstruction (XD-GRASP). One state from the motion resolved images was selected as a reference, and motion fields from the other states to the reference were derived via non-rigid registration. Finally, all motion resolved data and motion fields were reconstructed by using an iterative motion compensation reconstruction with a total generalized variation sparse constraint. Results: The iMoCo UTE strategy was evaluated in volunteers and non-sedated pediatric patient(4-6 y/o) studies. Images reconstructed with iMoCo UTE provided sharper anatomical lung structures, and higher apparent SNR and CNR, compared to using other motion correction strategies, such as soft-gating, motion resolved reconstruction, and non-rigid motion compensation(MoCo). iMoCo UTE also showed promising results in an infant study. Conclusions: The proposed iMoCo UTE combines self-navigation, motion modeling, and a compressed sensing reconstruction to increase scan efficiency, SNR, and reduce respiratory motion in lung MRI. This proposed strategy shows improvements in free breathing lung MRI scans, especially in very challenging application situations, such as pediatric MRI studies. Copyright © 2020, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Boosting the Performance of MOEA/D-DRA with a Multi-Objective Hyper-Heuristic Based on Irace and UCB Method for Heuristic Selection

Boosting the Performance of MOEA/D-DRA with a Multi-Objectiv...

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Congress on Evolutionary Computation

作者： Lucas Prestes Myriam R. Delgado Ricardo Lüders Richard Gonçalves Carolina P. Almeida Graduate Program in Electrical and Computer Engineering UTFPR Computer Science Department UNICENTRO

Multi-Objective Evolutionary Algorithm based on Decomposition with Dynamical Resource Allocation (MOEA/D-DRA) is one of the most successful decomposition based multiobjective algorithm. Its main feature is a mechanism to allocate different computational effort proportional to the difficult of each subproblem. Despite its success, MOEA/D-DRA has a large set of parameters and operators, whose selection could be a difficult task. This paper aims at improving the performance of MOEA/D-DRA by means of a hyper-heuristic using two parameter/operator selection phases: one off-line strongly based on Iterated Race Automatic Algorithm Configuration (Irace) and another one (online) based on the Upper Confidence Bound (UCB) technique. The proposed approach is compared with the original MOEA/D-DRA, NSGAII and IBEA over 51 instances of 7 well known benchmarks (CEC 2009, GLT, LZ09, MOP, DTLZ, ZDT and WFG). Results show that Irace and UCB are interesting methods to support the hyper-heuristic functioning when selecting parameters/operators of MOEA/D-DRA in the addressed problems.

关键词： Optimization Evolutionary computation Resource management Sociology Statistics Tuning Task analysis

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THz generation by exchange-coupled spintronic emitters

npj Spintronics

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npj Spintronics 2024年第1期2卷 1-8页

作者： Roman Adam Derang Cao Daniel E. Bürgler Sarah Heidtfeld Fangzhou Wang Christian Greb Markus Büscher Claus M. Schneider Jing Cheng Debamitra Chakraborty Ivan Komissarov Roman Sobolewski Martin Mikulics Hilde Hardtdegen Peter Grünberg Institute Research Centre Jülich Jülich Germany College of Physics Qingdao University Qingdao China Faculty of Physics University Duisburg-Essen Duisburg Germany Institut für Laser- und Plasmaphysik Heinrich-Heine Universität Düsseldorf Düsseldorf Germany Materials Science Graduate Program University of Rochester Rochester NY USA Laboratory for Laser Energetics University of Rochester Rochester NY USA Department of Electrical and Computer Engineering University of Rochester Rochester NY USA Ernst Ruska Centre Research Centre Jülich Jülich Germany

The mechanism of THz generation in ferromagnet/metal (F/M) bilayers has been typically ascribed to the inverse spin Hall effect (ISHE). Here, we fabricated Pt/Fe/Cr/Fe/Pt multilayers containing two back-to-back spintronic THz emitters separated by a thin (tCr≤ 3nm) wedge-shaped Cr spacer. In such an arrangement, magnetization alignment of the two Fe films can be controlled by the interplay between Cr-mediated interlayer exchange coupling (IEC) and an external magnetic field. This in turn results in a strong variation of the THz amplitudeA, withA↑↓reaching up to 14 timesA↑↑(arrows indicate the relative alignment of the magnetization of the two magnetic layers). This observed functionality is ascribed to the interference of THz transients generated by two closely spaced THz emitters. Moreover, the magnetic field dependenceA(H) shows a strong asymmetry that points to an additional performance modulation of the THz emitter via IEC and multilayer design.

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