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Control of Magnetic Skyrmions in an Exchange Biased van der Waals Ferromagnet

Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 1710-1711页

作者： McCray, Arthur R C Lebedev, Dmitry Arpaci, Sevdenur Te Velthuis, Suzanne G E Lopez-Dominguez, Victor Amiri, Pedram Khalili Hersam, Mark C. Petford-Long, Amanda K. Phatak, Charudatta Materials Science Division Argonne National Laboratory Lemont IL United States Applied Physics Program Northwestern University Evanston IL United States Department of Materials Science and Engineering Northwestern University Evanston IL United States Department of Electrical and Computer Engineering Northwestern University Evanston IL United States

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SUPP & MAPP: ADAPTABLE STRUCTURE-BASED REPRESENTATIONS FOR MIR TASKS 21

SUPP & MAPP: ADAPTABLE STRUCTURE-BASED REPRESENTATIONS FOR M...

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21st International Society for Music Information Retrieval Conference, ISMIR 2020

作者： Savard, Claire Bugbee, Erin H. McGuirl, Melissa R. Kinnaird, Katherine M. Department of Physics University of Colorado Boulder United States Department of Biostatistics Brown University United States Division of Applied Mathematics Brown University United States Department of Computer Science and Program in Statistical and Data Sciences Smith College United States

ISBN: (纸本)9780981353708

Accurate and flexible representations of music data are paramount to addressing MIR tasks, yet many of the existing approaches are difficult to interpret or rigid in nature. This work introduces two new song representations for structure-based retrieval methods: Surface Pattern Preservation (SuPP), a continuous song representation, and Matrix Pattern Preservation (MaPP), SuPP’s discrete counterpart. These representations come equipped with several user-defined parameters so that they are adaptable for a range of MIR tasks. Experimental results show MaPP as successful in addressing the cover song task on a set of Mazurka scores, with a mean precision of 0.965 and recall of 0.776. SuPP and MaPP also show promise in other MIR applications, such as novel-segment detection and genre classification, the latter of which demonstrates their suitability as inputs for machine learning problems. © Claire Savard, Erin H. Bugbee, Melissa R. McGuirl, Katherine M. Kinnaird.

关键词： Information retrieval

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KLF2 maintains lineage fidelity and suppresses CD8 T cell exhaustion during acute LCMV infection

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science (New York, N.Y.) 2025年第6735期387卷 eadn2337页

作者： Fagerberg, Eric Attanasio, John Dien, Christine Singh, Jaiveer Kessler, Emily A. Abdullah, Leena Shen, Jian Hunt, Brian G. Connolly, Kelli A. De Brouwer, Edward He, Jiaming Iyer, Nivedita R. Buck, Jessica Borr, Emily R. Damo, Martina Foster, Gena G. Giles, Josephine R. Huang, Yina H. Tsang, John S. Krishnaswamy, Smita Cui, Weiguo Joshi, Nikhil S. Department of Immunobiology Yale University School of Medicine New Haven CT United States Program in Computational Biology & Bioinformatics Yale University New Haven CT United States Department of Microbiology and Immunology Geisel School of Medicine at Dartmouth NH United States Department of Pathology Feinberg School of Medicine at Northwestern University Chicago IL United States Department of Genetics and Computer Science Yale University School of Medicine New Haven CT United States Department of Medicine University of Chicago Chicago IL United States Section of Hematology Department of Internal Medicine Yale University School of Medicine New Haven CT United States Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Philadelphia PA United States Institute for Immunology Perelman School of Medicine University of Pennsylvania Philadelphia PA United States Parker Institute for Cancer Immunotherapy Perelman School of Medicine University of Pennsylvania Philadelphia PA United States Yale Center for Systems and Engineering Immunology Yale University School of Medicine New Haven CT United States New Haven CT United States Department of Biomedical Engineering Yale University New Haven CT United States Computational Biology and Bioinformatics Program Yale University CT USA New Haven United States Applied Math Program Yale University New Haven CT United States

Naïve CD8 T cells have the potential to differentiate into a spectrum of functional states during an immune response. How these developmental decisions are made and what mechanisms exist to suppress differentiation toward alternative fates remains unclear. We employed in vivo CRISPR-Cas9-based perturbation sequencing to assess the role of ~40 transcription factors (TFs) and epigenetic modulators in T cell fate decisions. Unexpectedly, we found that knockout of the TF Klf2 resulted in aberrant differentiation to exhausted-like CD8 T cells during acute infection. KLF2 was required to suppress the exhaustion-promoting TF TOX and to enable the TF TBET to drive effector differentiation. KLF2 was also necessary to maintain a polyfunctional tumor-specific progenitor state. Thus, KLF2 provides effector CD8 T cell lineage fidelity and suppresses the exhaustion program.

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The missing intercloud medium and spiral galaxies

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Nature 1977年第5590期265卷 123-124页

作者： JOHN S. SCOTT E. B. JENSEN WILLIAM W. ROBERTS Astronomy Program University of Maryland College Park Steward Observatory University of Arizona Tucson Applied Mathematics and Computer Science University of Virginia Charlottesville

IT is the purpose of this letter first to point out that several independent lines of evidence seem to indicate that the ‘intercloud medium’ does not exist in its usually quoted state with density≳0.1 cm−3and temperatureT∼104K. Rather, a hot, tenuous medium (n≲10−2cm−3,T∼106K) seems more consistent with observations in the neighbourhood of the Sun. That such might be the situation has been previously suggested (see refs 1 and 2). A mechanism for producing such a medium has been proposed by Cox and Smith3. Second, this letter points out several implications of such a “missing intercloud medium” on the large-scale structure of spiral galaxies.

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Imaging atomic-scale chemistry from fused multi-modal electron microscopy

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npj Computational Materials 2022年第1期8卷 164-171页

作者： Jonathan Schwartz Zichao Wendy Di Yi Jiang Alyssa J.Fielitz Don-Hyung Ha Sanjaya D.Perera Ismail El Baggari Richard D.Robinson Jeffrey A.Fessler Colin Ophus Steve Rozeveld Robert Hovden Department of Materials Science and Engineering University of MichiganAnn ArborMIUSA Mathematics and Computer Science Division Argonne National LaboratoryLemontILUSA Advanced Photon Source Facility Argonne National LaboratoryLemontILUSA Dow Chemical Co. MidlandMIUSA Department of Material Science and Engineering Cornell UniversityIthacaNew YorkUSA School of Integrative Engineering Chung-Ang UniversitySeoulRepublic of Korea Department of Physics Cornell UniversityIthacaNYUSA The Rowland Institute at Harvard CambridgeMAUSA Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMIUSA National Center for Electron Microscopy Lawrence Berkeley National LaboratoryMolecular FoundryBerkeleyCAUSA Applied Physics Program University of MIchiganAnn ArborMIUnited States

Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic ***,fused multi-modal electron microscopy offers high signal-to-noise ratio(SNR)recovery of material chemistry at nano-and atomic-resolution by coupling correlated information encoded within both elastic scattering(high-angle annular dark-field(HAADF))and inelastic spectroscopic signals(electron energy loss(EELS)or energy-dispersive x-ray(EDX)).By linking these simultaneously acquired signals,or modalities,the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector *** many cases,the dose requirements can be reduced by over one order of *** high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials.

关键词： materials chemistry fused

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Customer Service Support System by ITIL version 3 Operating Framework with the Geographic Information System 2

Customer Service Support System by ITIL version 3 Operating ...

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Thanamatee, Tawan Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Chumuang, Narumol Ketcham, Mahasak King Mongkut's University of Technology Thonburi Media Technology Program Bangkok Thailand Applied Computer Science Program King Mongkut s University of Technology Thonburi Bangkok Thailand Department of Digital Media Technology Thailand King Mongkut's University of Technology North Bangkok Department of Information Technology Management Bangkok Thailand

ISBN: (纸本)9798350336573

The purpose of this research was to develop a power consumer service support system, a case study of the Provincial Electricity Authority, Chumphon Province. By applying the ITIL version 3 operating framework to be applied in conjunction with the geographic information system, the efficiency of the application of the geographic information system was assessed, the quality of the system was assessed by experts and the satisfaction of general users was assessed. This system was developed to increase the efficiency and accuracy of electricity consumer services. receive follow-up notifications request for service and service complaints Able to display statistical reports in geographic information formats resulting in standardized customer service management. Evaluation results of the efficiency of the system in finding and displaying the coordinates of service locations have an average overall efficiency of F-Measure of 92 percent and the quality assessment of experts at a good level with an average of 4.17 deviations. The standard was 0.51 and the satisfaction assessment results of general users were at a good level with an average of 4.35 and a standard deviation of 0.42 from both groups of assessors. It can be concluded that the developed system can be applied to real work efficiently and effectively © 2023 IEEE.

关键词： Geographic information systems

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A Low Complexity ML-Based Methods for Malware Classification

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computers, Materials & Continua 2024年第9期80卷 4833-4857页

作者： Mahmoud E.Farfoura Ahmad Alkhatib Deema Mohammed Alsekait Mohammad Alshinwan Sahar A.El-Rahman Didi Rosiyadi Diaa Salama Abd Elminaam Cybersecurity Department Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Computer Systems Program-Electrical Engineering Department Faculty of Engineering-ShoubraBenha UniversityCairo11629Egypt Research Center for Artificial Intelligence and Cybersecurity Electronics and Informatics OrganizationNational Research and Innovation Agency(BRIN)KST Samaun SamadikunBandung40135Republic of Indonesia Jadara Research Center Jadara UniversityIrbid21110Jordan MEU Research Unit Middle East UniversityAmman11831Jordan

The article describes a new method for malware classification,based on a Machine Learning(ML)model architecture specifically designed for malware detection,enabling real-time and accurate malware *** an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique(IFDRT),the authors have significantly reduced the feature space while retaining critical information necessary for malware *** technique optimizes the model’s performance and reduces computational *** proposed method is demonstrated by applying it to the BODMAS malware dataset,which contains 57,293 malware samples and 77,142 benign samples,each with a 2381-feature *** the IFDRT method,the dataset is transformed,reducing the number of features while maintaining essential data for accurate *** evaluation results show outstanding performance,with an F1 score of 0.984 and a high accuracy of 98.5%using only two reduced *** demonstrates the method’s ability to classify malware samples accurately while minimizing processing *** method allows for improving computational efficiency by reducing the feature space,which decreases the memory and time requirements for training and *** new method’s effectiveness is confirmed by the calculations,which indicate significant improvements in malware classification accuracy and *** research results enhance existing malware detection techniques and can be applied in various cybersecurity applications,including real-timemalware detection on resource-constrained *** and scientific contribution lie in the development of the IFDRT method,which provides a robust and efficient solution for feature reduction in ML-based malware classification,paving the way for more effective and scalable cybersecurity measures.

关键词： Malware detection ML-based models dimensionality reduction feature engineering

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Smart Bin for Covid19 2

Smart Bin for Covid19

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Ketcham, Mahasak Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Chumuang, Narumol King Mongkut's University of Technology North Bangkok Department of Information Technology Management Bangkok Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand King Mongkut's University of Technology Thonburi Media Technology Program Bangkok Thailand Department of Digital Media Technology Thailand

ISBN: (纸本)9798350336573

The purpose of this research was to develop a device that would facilitate visually impaired people in the use of lidded bins. And reduce the risk of spreading COVID-19 and other pathogens that may be contaminated with the trash area to all users Able to develop prototype devices to be used in practice and have the opportunity to extend it for practical use in the community area Or a point where there is a risk of the spread of garbage dumping information per day of that area for use in further data analysis. © 2023 IEEE.

关键词： Internet of things

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Time series mining approach for noninvasive intracranial pressure assessment: An investigation of different regularization techniques

Time series mining approach for noninvasive intracranial pre...

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2009 WRI World Congress on computer science and Information Engineering, CSIE 2009

作者： Wu, Shaozhi Xu, Peng Asgari, Shadnaz Bergsneider, Marvin Hu, Xiao Department of Neurosurgery David Geffen School of Medicine University of California Los Angeles CA United States Biomedical Engineering Graduate Program Henry Samueli School of Engineering and Applied Science University of California Los Angeles CA United States School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 China

ISBN: (纸本)9780769535074

A data mining framework has been proposed to estimate intracranial pressure (ICP) non-invasively in our previous work. In the corresponding approach, the feature vector extracted from arterial blood pressure (ABP) and flow velocity (FV) is translated to the estimated errors by the mapping function for each entry in the database. In this paper, three different mapping function solutions, linear least squares (LLS), truncated singular value decomposition (TSVD) and standard Tikhonov regularization (STR) are systemically tested to compare the possible effects of different solutions on the non-invasive ICP estimation. The conducted comparison demonstrated that the selection of mapping function solution actually influences the estimation. Among the tested three solutions for mapping function, TSVD and STR show better ICP estimation performance with smaller ICP errors than LLS. © 2008 IEEE.

关键词： Flow velocity

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Genetic programming for attribute construction in data mining

Genetic programming for attribute construction in data minin...

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6th European Conference on Genetic programming, EuroGP 2003

作者： Otero, Fernando E. B. Silva, Monique M. S. Freitas, Alex A. Nievola, Julio C. Postgraduate Program in Applied Computer Science Rua Imaculada Conceicao 1155 CuritibaPR80215-901 Brazil Computing Laboratory University of Kent Canterbury KentCT2 7NF United Kingdom

ISBN: (纸本)354000971X

For a given data set, its set of attributes defines its data space representation. The quality of a data space representation is one of the most important factors influencing the performance of a data mining algorithm. The attributes defining the data space can be inadequate, making it difficult to discover high-quality knowledge. In order to solve this problem, this paper proposes a Genetic programming algorithm developed for attribute construction. This algorithm constructs new attributes out of the original attributes of the data set, performing an important preprocessing step for the subsequent application of a data mining algorithm. © 2003, Springer-Verlag Berlin Heidelberg, All rights Reserved.

关键词： Genetic programming

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