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IEEE International Conference on Image Processing

作者： Li Ding Ahmed Elliethy Eitan Freedenberg S. Alana Wolf-Johnson Joshua Romphf Peter Christensen Gaurav Sharma Dept. of Electrical and Computer Engineering University of Rochester Graduate Program in Visual and Cultural Studies University of Rochester River Campus Libraries University of Rochester Dept. of Art and Art History University of Rochester

ISBN: (纸本)9781467399623

This paper reports on a novel application of computer vision and image processing technologies to an interdisciplinary project in architectural history that seeks to help identify and visualize differences between homologous buildings constructed to a common template design. By identifying the mutations in homologous buildings, we assist humanists in giving voice to the contributions of the myriad additional "authors" for these buildings beyond their primary designers. We develop a framework for comparing 3D point cloud representations of homologous buildings captured using lidar: focusing on identifying similarities and differences, both among 3D scans of different buildings and between the 3D scans and the design specifications of architectural drawings. The framework addresses global and local alignment for highlighting gross differences as well as differences in individual structural elements and provides methods for readily highlighting the differences via suitable visualizations. The framework is demonstrated on pairs of homologous buildings selected from the Canadian and Ottoman rail networks. Results demonstrate the utility of the framework confirming differences already apparent to the humanist researchers and also revealing new differences that were not previously observed.

关键词： Architectural biometrics Building difference visualization Point cloud comparison Range imaging Visual big data analytics

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Retraction: Design of Decision Support System Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method (J. Phys.: Conf. Ser. 1114 012082)

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Muhammad Iqbal Dahlan Abdullah H Hartono Cut Ita Erliana S Sriadhi Nurmawati M Adhi Prasnowo Abdurrozzaq Hasibuan Akbar Iskandar Kundharu Saddhono Abdussakir Hastuti Musa Muhammad Ikhsan Setiawan Youmeni Sagala Rumiris Siahaan Eka Mayastika Sinaga Anggraini Syahputri Feby Milanie Henry Aspan Muammar Khaddafi Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Department of Industrial Engineering Universitas Maarif Hasyim Latif Sidoarjo Indonesia Faculty of Engineering Universitas Islam Sumatera UtaraMedan-Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Mathematics Universitas Muhammadiyah Parepare Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia STIE Bina Karya Tebing Tinggi Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

This paper was retracted by IOP Publishing on 12 December 2018. This paper was published due to a technical error and was not intended to be included in this journal. Retraction published: 8 February 2019

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Author Correction: lentiMPRA and MPRAflow for high-throughput functional characterization of gene regulatory elements

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Nature protocols 2021年第7期16卷 3736页

作者： M Grace Gordon Fumitaka Inoue Beth Martin Max Schubach Vikram Agarwal Sean Whalen Shiyun Feng Jingjing Zhao Tal Ashuach Ryan Ziffra Anat Kreimer Ilias Georgakopoulos-Soares Nir Yosef Chun Jimmie Ye Katherine S Pollard Jay Shendure Martin Kircher Nadav Ahituv Department of Bioengineering and Therapeutic Sciences University of California San Francisco San Francisco CA USA. Institute for Human Genetics University of California San Francisco San Francisco CA USA. Biological and Medical Informatics Graduate Program University of California San Francisco San Francisco CA USA. Department of Bioengineering and Therapeutic Sciences University of California San Francisco San Francisco CA USA. fumitaka.inoue@ucsf.edu. Institute for Human Genetics University of California San Francisco San Francisco CA USA. fumitaka.inoue@ucsf.edu. Berlin Institute of Health (BIH) Berlin Germany. Department of Genome Sciences University of Washington Seattle WA USA. Calico Life Sciences LLC South San Francisco CA USA. Gladstone Institutes San Francisco CA USA. Department of Electrical Engineering and Computer Sciences and Center for Computational Biology University of California Berkeley Berkeley CA USA. Chan-Zuckerberg Biohub San Francisco CA USA. Division of Rheumatology Department of Medicine University of California San Francisco San Francisco CA USA. Institute for Computational Health Sciences University of California San Francisco San Francisco California USA. Department of Epidemiology and Biostatistics and Institute of Computational Health Sciences University of California San Francisco San Francisco CA USA. Department of Genome Sciences University of Washington Seattle WA USA. shendure@uw.edu. Howard Hughes Medical Institute Seattle WA USA. shendure@uw.edu. Brotman Baty Institute for Precision Medicine University of Washington Seattle WA USA. shendure@uw.edu. Berlin Institute of Health (BIH) Berlin Germany. martin.kircher@bihealth.de. Charité-Universitätsmedizin Berlin Berlin Germany. martin.kircher@bihealth.de. Department of Bioengineering and Therapeutic Sciences University of California San Francisco San Francisco CA USA. nadav.ahituv@ucsf.edu. Institute for Human Genetics University of California San

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A novel method to assess angle sensor performance for wearable exoskeletal joint kinematics

A novel method to assess angle sensor performance for wearab...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Nicholas B. Bolus Géza F. Kogler Omer T. Inan Bioengineering Graduate Research Program at the Georgia Institute of Technology Atlanta GA School of Applied Physiology at the Georgia Institute of Technology Atlanta GA School of Electrical and Computer Engineering at the Georgia Institute of Technology Atlanta GA

Full range of motion (ROM) at a joint is necessary for efficient and adaptive movement; as such, it is an essential clinical evaluation measure for assessing an individual's motor function, which can be affected by any number of musculoskeletal injuries and neuropathies. Measurement of joint ROM in the clinic has classically been accomplished statically through the use of a manual goniometer. More recent efforts in the fields of prosthetics and orthotics have demonstrated the potential utility of wearable systems (e.g., exoskeletons, orthoses) designed to control joint motion(s) and instrumented with sensors capable of capturing joint angle data dynamically. This paper presents a novel methodology to assess the performance of a variety of angle sensors in the context of wearable joint angle measurement, particularly for use in articulated ankle-foot orthoses (AFOs). Dynamic and static errors are considered, and a cost-benefit analysis of a variety of off-the-shelf and custom-built sensors is reported to provide comparative data for selecting a sensor to measure joint motion in wearable exoskeletal systems. All of the sensors considered reported angular errors below 5° across all tests, though the optical encoder consistently demonstrated the highest accuracy (

关键词： Optical sensors Potentiometers Adaptive optics Robot sensing systems Legged locomotion Magnetic hysteresis

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Parallel Solution of Diagonally Dominant Banded Triangular Toeplitz Systems Using Taylor Polynomials

Parallel Solution of Diagonally Dominant Banded Triangular T...

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IEEE International Conference on High Performance Computing and Communications

作者： Michael Kapralos Aron Wolinetz Brian J. Murphy Department of Electrical and Computer Engineering University of Connecticut Storrs CT 06269 The Graduate Center of the City University of New York Ph.D. Program in Computer Science NY NY 10016 Lehman College of the City University of New York Bronx NY 10468

ISBN: (纸本)9781509042982

We present a new numerical and inherently parallel algorithm for solving banded (strictly) diagonally dominant triangular and banded Toeplitz (BDDTT) systems of linear equations. A Taylor polynomial, derived from the matrix analog of the Taylor Series for evaluating (1-x) ~(-1)where |χ| < 1, is applied, in conjunction with other techniques, to compute an approximate solution to a BDDTT-type system. This method requires O(n log_2n) arithmetic operations (ops) and O(log_2n) parallel steps (steps). Two FFTs and an IFFT of order 2n are the main contributors to the workload. This matches the FFT count for a triangular Toeplitz-matrix-vector multiplication. Clearly then, our method improves on the many algebraic FFT based processes that first determine the triangular Toeplitz matrix that is the inverse of a BDDTT matrix in order to then solve the associated BDDTT system.

关键词： Banded Triangular Toeplitz Diagonally Dominant Linear System FFT

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Dilute-nitride GaNP planar and core/shell microwire solar cells

Dilute-nitride GaNP planar and core/shell microwire solar ce...

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Indium Phosphide and Related Materials Conference

作者： Supanee Sukrittanon Ren Liu Janet L Pan Katherine L Jungjohann Shadi A Dayeh Charles W Tu Graduate Program of Materials Science and Engineering University of California San Diego United States of America Department of Electrical and Computer Engineering University of California San Diego United States of America Center for Integrated Nanotechnologies Sandia National Laboratories United States of America

ISBN: (纸本)9781509019656

Dilute nitride GaNP is potentially useful as the top junction in dual-junction solar cells on Si because it has a tunable direct-bandgap and small lattice mismatch with Si. Investigations on GaP are the first step toward this goal. Our best GaNP solar cell on GaP ([N] = 1.8%, Eg = 2.05 eV) achieves an efficiency of 7.9%, which is 3 times higher than the most efficient GaP solar cell to date and higher than other solar cells with similar direct bandgap (InGaP, GaAsP). We also report GaP/GaNP core/shell microwire solar cells utilizing top-down reactiveion etching to create the GaP cores and molecular beam epitaxy to create the GaNP shells. Systematic studies of cell performance over a series of microwire lengths, array periods, and sidewall morphologies, examined by transmission electron microscopy, were conducted to shed light on performance-limiting factors and to optimize the cell efficiency.

关键词： Photovoltaic cells Silicon Compounds computers Laboratories Junctions Lattices

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Data-driven analysis of kinaesthetic and tactile information for shape classification

Data-driven analysis of kinaesthetic and tactile information...

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2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015

作者： De Oliveira, Thiago Eustaquio Alves Prado Da Fonseca, Vinicius Huluta, Emanuil Rosa, Paulo F. F. Petriu, Emil M. School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (纸本)9781479960910

Humans sense of touch consists in a complexity of sensors and nervous system. The information inferred by this system enables the daily dexterous manipulation tasks. In biological systems, there is no conscious prioritization of sensors while performing tactile exploration and the selection of exploratory movements is driven by learning instincts and data gathered by previous movements. The development of artificial systems tries to mimic such systems with engineered sensors and strategies for movement selection. This paper presents a data-driven analysis to the problem of sensor selection in the contour following for shape discrimination task. This task consists of a 4-DOF robotic finger exploring a set of 7 synthetic shapes. The data collected from the motors, inertial measurement unit, and magnetometer was analyzed applying principal component analysis and a multilayer perceptron neural network. Results show the variation of classification rate depending on the fingertip material and sensor considered. It is worth to observe that the magnetometer was the most robust in both cases. © 2015 IEEE.

关键词： Magnetometers

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Mesoscopic quantum effects in a bad metal, hydrogen-doped vanadium dioxide

arXiv

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arXiv 2017年

作者： Hardy, Will J. Ji, Heng Paik, Hanjong Schlom, Darrell G. Natelson, Douglas Applied Physics Graduate Program Smalley-Curl Institute Rice University 6100 Main St. HoustonTX77005 United States Department of Physics and Astronomy Rice University 6100 Main St. HoustonTX77005 United States Department of Materials Science and Engineering Cornell University IthacaNY14853 United States Kavli Institute at Cornell for Nanoscale Science IthacaNY14853 United States Department of Electrical and Computer Engineering Rice University 6100 Main St. HoustonTX77005 United States Department of Materials Science and Nanoengineering Rice University 6100 Main St. HoustonTX77005 United States

The standard treatment of quantum corrections to semiclassical electronic conduction assumes that charge carriers propagate many wavelengths between scattering events, and succeeds in explaining multiple phenomena (weak localization magnetoresistance (WLMR), universal conductance fluctuations, Aharonov-Bohm oscillations) observed in polycrystalline metals and doped semiconductors in various dimensionalities. We report apparent WLMR and conductance fluctuations in HxVO2, a poor metal (in violation of the Mott-Ioffe-Regel limit) stabilized by the suppression of the VO2 metal-insulator transition through atomic hydrogen doping. Epitaxial thin films, single-crystal nanobeams, and nanosheets show similar phenomenology, though the details of the apparent WLMR seem to depend on the combined effects of the strain environment and presumed doping level. Self-consistent quantitative analysis of the WLMR is challenging given this and the high resistivity of the material, since the quantitative expressions for WLMR are derived assuming good metallicity. These observations raise the issue of how to assess and analyze mesoscopic quantum effects in poor metals. Copyright © 2017, The Authors. All rights reserved.

关键词： Vanadium dioxide

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A Hybrid Deep Learning Forecasting Model Using GPU Disaggregated Function Evaluations Applied for Household Electricity Demand Forecasting

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Energy Procedia 2016年 103卷 280-285页

作者： Vitor N. Coelho Igor M. Coelho Eyder Rios Alexandre S.T. Filho Agnaldo J.R. Reis Bruno N. Coelho Alysson Alves Guilherme G. Netto Marcone J.F. Souza Frederico G. Guimarães Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Instituto de Pesquisa e Desenvolvimento de Tecnologias Ouro Preto Brazil Department of Computer Science State University of Rio de Janeiro Rio de Janeiro Brazil Institute of Computer Science Fluminense Federal University Niteroi Brazil Department of Control Engineering and Automation Universidade Federal de Ouro Preto Ouro Preto Brazil Department of Computer Science Universidade Federal de Ouro Preto Ouro Preto Brazil Department of Electrical Engineering Universidade Federal de Minas Gerais BeloHorizonte Brazil

As the new generation of smart sensors is evolving towards high sampling acquisitions systems, the amount of information to be handled by learning algorithms has been increasing. The Graphics Processing Unit (GPU) architectures provide a greener alternative with low energy consumption for mining big-data, harnessing the power of thousands of processing cores in a single chip, opening a widely range of possible applications. Here, we design a novel evolutionary computing GPU parallel function evaluation mechanism, in which different parts of time series are evaluated by different processing threads. By applying a metaheuristics fuzzy model in a low-frequency data for household electricity demand forecasting, results suggested that the proposed GPU learning strategy is scalable as the number of training rounds increases.

关键词： Microgrid Household Electricity Demand Deep Learning Graphics Processing Unit Parallel forecasting model Big Time-series Data

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An automatic calibration framework applied on a metaheuristic fuzzy model for the CIF competition

An automatic calibration framework applied on a metaheuristi...

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International Joint Conference on Neural Networks

作者： Vitor N. Coelho Igor M. Coelho Ivan R. Meneghini Marcone J. F. Souza Frederico G. Guimaraes Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Av. Ant?nio Carlos 6627 31270-901 Belo Horizonte Brazil Department of Computer Science State University of Rio de Janeiro Brazil Department of Computer Science Universidade Federal de Ouro Preto MG Brazil Departament of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil

ISBN: (纸本)9781509006212

The challenging problem of forecasting a given time series as accurately as possible is reality in different areas of expertise. The requirement of achieving reliable forecasts, for assisting the new generation of soft sensors, requests the development of novel smart mechanisms to be integrated into the available forecasting models. This current paper improves the previous work of Coelho et al. [1], [2], introduced in the 2014 WCCI, which introduced a Hybrid Self-adaptive Forecasting Model (HFM), calibrated using an evolutionary metaheuristic. Here, an expert input selection assisted by the use of Neighborhood Structures is used for learning the dataset provide in the CIF 2016 forecasting competition. Two different metaheuristic algorithms are used for training the HFM, computational experiments are conducted for optimizing both models. By selecting the maximum lag to be used by our model and, consequently, defining a rate of training cycles, we calibrate the HFM in order to minimize Symmetric Mean Absolute Percentage Errors. Blind forecasts generated by the model will be submit to the competition.

关键词： Forecasting Time series analysis Predictive models Training Computational modeling Electronic mail Prediction algorithms

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