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arXiv 2020年

作者： Tanaka, Tomoki Suzuki, Yohichi Uno, Shumpei Raymond, Rudy Onodera, Tamiya Yamamoto, Naoki Quantum Computing Center Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa Yokohama223-8522 Japan Mitsubishi UFJ Financial Group Inc. MUFG Bank Ltd. 2-7-1 Marunouchi Chiyoda-ku Tokyo100-8388 Japan Graduate School of Science and Technology Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa Yokohama223-8522 Japan Mizuho Research & Technologies Ltd. 2-3 Kanda-Nishikicho Chiyoda-ku Tokyo101-8443 Japan IBM Quantum IBM Research - Tokyo 19-21 Nihonbashi Hakozaki-cho Chuo-ku Tokyo103-8510 Japan Department of Applied Physics and Physico-Informatics Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa Yokohama223- 8522 Japan

Recently we find several candidates of quantum algorithms that may be implementable in near-term devices for estimating the amplitude of a given quantum state, which is a core subroutine in various computing tasks such as the Monte Carlo methods. One of those algorithms is based on the maximum likelihood estimate with parallelized quantum circuits. In this paper, we extend this method so that it incorporates the realistic noise effect, and then give an experimental demonstration on a superconducting IBM Quantum device. The maximum likelihood estimator is constructed based on the model assuming the depolarization noise. We then formulate the problem as a two-parameters estimation problem with respect to the target amplitude parameter and the noise parameter. In particular we show that there exist anomalous target values, where the Fisher information matrix becomes degenerate and consequently the estimation error cannot be improved even by increasing the number of amplitude amplifications. The experimental demonstration shows that the proposed maximum likelihood estimator achieves quantum speedup in the number of queries, though the estimation error saturates due to the noise. This saturated value of estimation error is consistent to the theory, which implies the validity of the depolarization noise model and thereby enables us to predict the basic requirement on the hardware components (particularly the gate error) in quantum computers to realize the quantum speedup in the amplitude estimation task. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum optics

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Machine learning for diagnosis of disease in plants using spectral data

Machine learning for diagnosis of disease in plants using sp...

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2018 International Conference on Artificial Intelligence, ICAI 2018 at 2018 World Congress in Computer Science, Computer Engineering and Applied computing, CSCE 2018

作者： Owomugisha, Godliver Melchert, Friedrich Mwebaze, Ernest Quinn, John A. Biehl, Michael University of Groningen Johann Bernoulli Institute for Mathematics and Computer Science P.O. Box 407 AK Groningen9700 Netherlands Fraunhofer Institute for Factory Operation and Automation IFF Sandtorstrasse 22 Magdeburg39106 Germany Makerere University School of Computing and Informatics Technology P.O. Box 7062 Kampala Uganda Busitema University Faculty of Engineering P. O. Box 236 Tororo Uganda

ISBN: (纸本)1601324804

Automating crop disease diagnosis is an important task, particularly for regions with few experts. Most current methods detect disease by analyzing leaf images, particularly for diseases that manifest on the aerial part of the plant. To train a good classifier one requires a huge image dataset and the appropriate methods to extract relevant features from the images that represent the disease unambiguously. Image data also tends to be prone to effects of occlusion that make consistent analysis of the data hard. In this paper we take a look at the use of spectral data collected from leaves of a plant. We analyse spectral data from visibly diseased parts of a leaf as well as parts that are visibly healthy. We employ prototype based classification methods and standard classification models in a three-class classification problem configuration. Results presented show significant improvement in performance when spectral data is used and the possibility of early detection of disease before the crops become visibly symptomatic, which for practical reasons is very important. CSREA Press ©.

关键词： Crops

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A novel visible-infrared image fusion framework for smart city

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International Journal of Simulation and Process Modelling 2018年第2期13卷 144-155页

作者： Zhu, Zhiqin Qi, Guanqiu Chai, Yi Yin, Hongpeng Sun, Jian School of Automation Chongqing University Chongqing400044 China State Key Laboratory of Power Transmission Equipment and System Security and New Technology College of Automation Chongqing University Chongqing400044 China School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85287 United States Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing400030 China

Image fusion technology is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Image fusion technology as an efficient way to integrate information from multiple images plays a more and more important role in smart city. The quality of fused image affects the accuracy, efficiency, and robustness of the related applications. Existing sparse representation-based image fusion methods consist of overly complete and redundant dictionaries learning and sparse coding. However, overly complete and redundant dictionary does not consider the discriminative ability of dictionaries that may seriously affect the image fusion. A good dictionary is the key to a successful image fusion technique. To construct a discriminative dictionary, a novel framework that integrates an image-patches clustering and online dictionary learning methods is proposed for visible-infrared image fusion. The comparison experiments with existing solutions are used to validate and demonstrate the effectiveness of the proposed solution for image fusion. Copyright © 2018 Inderscience Enterprises Ltd.

关键词： Image fusion

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Structured point cloud data analysis via regularized tensor regression for process modeling and optimization

arXiv

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arXiv 2018年

作者： Yan, Hao Paynabar, Kamran Pacella, Massimo School of Computing Informatics & Decision Systems Engineering Arizona State University TempeAZ United States School of Industrial and Systems Engineering Georgia Institute of Technology AtlantaGA United States Dipartimento di Ingegneria dell'Innovazione University of Salento Lecce Italy

Advanced 3D metrology technologies such as Coordinate Measuring Machine (CMM) and laser 3D scanners have facilitated the collection of massive point cloud data, beneficial for process monitoring, control and optimization. However, due to their high dimensionality and structure complexity, modeling and analysis of point clouds are still a challenge. In this paper, we utilize multilinear algebra techniques and propose a set of tensor regression approaches to model the variational patterns of point clouds and to link them to process variables. The performance of the proposed methods is evaluated through simulations and a real case study of turning process optimization. Copyright © 2018, The Authors. All rights reserved.

关键词： Regression analysis

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Comparison of UAV-based multispectral sensors for detection of Solenopsis invicta Nests

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IOP Conference Series: Earth and Environmental Science 2020年第1期569卷

作者： Yuejun Song Feng Chen Kaitao Liao Jiangxi Institute of Soil and Water Conservation Nanchang 330029 China Jiangxi Key Laboratory of Soil Erosion and Prevention Nanchang 330029 China College of Computer and Information Engineering Xiamen University of Technology Xiamen 361024 China Big Data Institute of Digital Natural Disaster Monitoring in Fujian Xiamen University of Technology Xiamen 361024 China Fujian Key Laboratory of Sensing and Computing for Smart Cities School of Informatics Xiamen University Xiamen 361005 China

The invasive red imported fire ant (Solenopsis invicta Buren) (Hymenoptera: Formicidae) has been continuing to expand its range in China, resulting in adverse ecological impacts to where it has invaded. As such, the reliable detection of Solenopsis invicta Buren nests is needed to effectively manage the species. In this paper, the spectral features of the Solenopsis invicta Buren nests were demonstrated using spectra samples obtained by ASD FieldSpec 4 during field surveys in Shanggao County, Jiangxi Province. Furthermore, channel reflectance estimations for three unmanned aerial vehicle (UAV)-based multispectral sensors were simulated correspondingly. Based on the channel reflectance from individual sensors, the detection of the Solenopsis invicta Buren nests was investigated. Generally, between-class differences in reflectance were relatively significant in both Green channel and Red channel, which suggests the importance of these two channels for the detection of Solenopsis invicta Buren nest. Minor between-sensor differences observed in both Green channel and Red channel suggest that detection results obtained from UAV-based multispectral observations could be comparable among the three sensors, considering only the spectral features. There are significant differences in reflectance between the soil of Solenopsis invicta Buren nests and ordinary soil over the longwave region of near infrared (NIR). It suggests the spectral measurement over the longwave region of NIR could be more useful in distinguishing the soil of Solenopsis invicta Buren nests from ordinary soil. Nevertheless, the multispectral sensors provided with channels covering visible and the shortwave region of NIR, possibly do not meet requirements completely for application. An effective method for detecting Solenopsis invicta Buren nests using UAV-based multispectral sensors is currently being evaluated.

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Assessment of mental workload: A comparison of machine learning methods and subjective assessment techniques 1st

Assessment of mental workload: A comparison of machine learn...

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1st International Symposium on Human Mental Workload: Models and Applications, H-WORKLOAD 2017

作者： Moustafa, Karim Luz, Saturnino Longo, Luca School of Computing Dublin Institute of Technology Dublin Ireland Usher Institute of Population Health Sciences and Informatics The University of Edinburgh Edinburgh United Kingdom The ADAPT Centre Dublin Ireland

ISBN: (纸本)9783319610603

Mental workload (MWL) measurement is a complex multidisciplinary research field. In the last 50 years of research endeavour, MWL measurement has mainly produced theory-driven models. Some of the reasons for justifying this trend includes the omnipresent uncertainty about how to define the construct of MWL and the limited use of datadriven research methodologies. This work presents novel research focused on the investigation of the capability of a selection of supervised Machine Learning (ML) classification techniques to produce data-driven computational models of MWL for the prediction of objective performance. These are then compared to two state-of-the-art subjective techniques for the assessment of MWL, namely the NASA Task Load Index and the Workload Profile, through an analysis of their concurrent and convergent validity. Findings show that the data-driven models generally tend to outperform the two baseline selected techniques. © Springer International Publishing AG 2017.

关键词： NASA

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A framework for generalized group testing with inhibitors and its potential application in neuroscience

arXiv

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arXiv 2018年

作者： Bui, Thach V. Kuribayashi, Minoru Cheraghchi, Mahdi Echizen, Isao SOKENDAI Graduate University for Advanced Studies Hayama Kanagawa Japan Graduate School of Natural Science and Technology Okayama University Okayama Japan Department of Computing Imperial College London United Kingdom National Institute of Informatics Tokyo Japan

The main goal of group testing with inhibitors (GTI) is to efficiently identify a small number of defective items and inhibitor items in a large set of items. A test on a subset of items is positive if the subset satisfies some specific properties. Inhibitor items cancel the effects of defective items, which often make the outcome of a test containing defective items negative. Different GTI models can be formulated by considering how specific properties have different cancellation effects. This work introduces generalized GTI (GGTI) in which a new type of items is added, i.e., hybrid items. A hybrid item plays the roles of both defectives items and inhibitor items. Since the number of instances of GGTI is large (more than 7 million), we introduce a framework for classifying all types of items non-adaptively, i.e., all tests are designed in advance. We then explain how GGTI can be used to classify neurons in neuroscience. Finally, we show how to realize our proposed scheme in practice. Copyright © 2018, The Authors. All rights reserved.

关键词： Neurology

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Automatic vector-based road structure mapping using multi-beam lidar

arXiv

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arXiv 2018年

作者： He, Xudong Zhao, Junqiao Sun, Lu Huang, Yewei Zhang, Xinglian Li, Jun Ye, Chen Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai Department of Computer Science and Technology School of Electronics and Information Engineering Tongji University Shanghai School of Surveying and Geo-Informatics Tongji University Shanghai China School of Automotive Studies Tongji University Shanghai China

In this paper, we studied a SLAM method for vector-based road structure mapping using multi-beam LiDAR. We propose to use the polyline as the primary mapping element instead of grid cell or point cloud, because the vector-based representation is precise and lightweight, and it can directly generate vector-based High-Definition (HD) driving map as demanded by autonomous driving systems. We explored: 1) the extraction and vectorization of road structures based on local probabilistic fusion. 2) the efficient vector-based matching between frames of road structures. 3) the loop closure and optimization based on the pose-graph. In this study, we took a specific road structure, the road boundary, as an example. We applied the proposed matching method in three different scenes and achieved the average absolute matching error of 0.07 m. We further applied the mapping system to the urban road with the length of 860 meters and achieved an average global accuracy of 0.466 m without the help of high precision GPS. Copyright © 2018, The Authors. All rights reserved.

关键词： Mapping

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TiEV: The tongji intelligent electric vehicle in the intelligent vehicle future challenge of China

arXiv

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arXiv 2018年

作者： Zhao, Junqiao Ye, Chen Wu, Yan Guan, Linting Cai, Lewen Sun, Lu Yang, Tao He, Xudong Li, Jun Ding, Yongchao Zhang, Xinglian Wang, Xinchen Huang, Jinlin Zhang, Enwei Huang, Yewei Jiang, Wei Zhang, Shaoming Xiong, Lu Feng, Tiantian Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai Department of Computer Science and Technology School of electrics and Information Engineering Tongji University Shanghai School of Surveying and Geo-Informatics Tongji University Shanghai China School of Automotive Studies Tongji University Shanghai China

TiEV is an autonomous driving platform implemented by the Tongji University of China. The vehicle is drive-by-wire and is fully powered by electricity. We devised the software system of TiEV from scratch, which is capable of driving the vehicle autonomously in urban paths as well as on fast express roads. We describe our whole system, especially novel modules of probabilistic perception fusion, large-scale mapping and updating, the 1st and the 2nd planning and the overall safety concern. TiEV finished 2016, and 2017 Intelligent Vehicle Future Challenge of China held at Changshu. We show our experiences on the development of autonomous vehicles and discuss the future trends. Copyright © 2018, The Authors. All rights reserved.

关键词： Autonomous vehicles

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The Effects of Breaststroke Kick Electromyography Muscle Activity

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Psychology Research 2021年第8期11卷 363-368页

作者： Takahisa Ide M.A. William F.Johnson Sadafumi Takise Jan Konarzewski Noriko Inada Hiromasa Fujimori Takeharu Fujimori Emi Moronuki Ken A.Barcinas Kohei Kawamoto Kazuki Watanabe Asahi Nagahata Iryna Glavnyk Daniil Antipov Mark Nikolaev Bogdan Plavin Osaka University of Health and Sport Sciences OsakaJapanPhoenix Swim ClubParadise ValleyUSAGrand Canyon UniversityPhoenixUSA TexasA&M University Corpus Christi Corpus ChristiUSA Osaka University of Health and Sport Sciences OsakaJapan University of Edinburgh in Computer Science B.A.in Informatics and Social ComputingUniversity of MichiganSwimming SciencPhoenix Swim ClubParadise ValleyUSA. Department of Education Waseda UniversitySwimming SciencePhoenix Swim ClubParadise ValleyUSA. Faculty of Sport Science of Nippon Sports Science University Swimming SciencePhoenix Swim ClubParadise ValleyUSA. School of Health and Physical Education Tsukuba UniversitySwimming SciencePhoenix Swim ClubParadise ValleyUSA. Faculty of Management Information of Yamanashi Gakuin University JapanSwimming SciencePhoenix Swim ClubParadise ValleyUSA. Department of Economics Faculty of EconomicsChuo UniversitySwimming SciencesPhoenix Swim ClubParadise ValleyUSA. Meiji University School of CommercePhoenix Swim ClubParadise ValleyUSA. Business Administration with an Emphasis i Busiiness Intelligence Grand CanyonUniversityPhoenixUSA. Bussiness Management of Marketing and Enterpreneurship Grand Canyon UniversityPhoenixUSA. Arts in Goverment with an Emphasis in Legal Studies Grand Canyon UniversityPhoenixUSA.Grand Canyon UniversityPhoenixUSA. Grand Canyon University PhoenixUSAWashingtonD.C.TridentBaarSwitzerland. Grand Canyon University PhoenixUSAScience in Information TechnologyValparaiso UniversityValparaisoUSA.

This paper evaluates the efficiency of using a downward breaststroke kick in a sample of eight elite *** a downward breaststroke kick increases the one stroke velocity and max speed but also increases production of lactate *** the downward breaststroke kick we find the 100-meter and 100-yard breaststroke times decrease from 1:05.10s to 1:01.97s and find the downward breaststroke kick increases muscle activity of the quadriceps,biceps,and *** increases in performance were observed from measuring the world class swimmers are highly correlated to duration of the kick aerodynamic buoyant force in breaststroke.

关键词： swimming breaststroke electromyography downward kick Olympians psychology

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