检索结果-内蒙古大学图书馆

Annual Conference of the IEEE Industrial Electronics Society

作者： Ji Hoon Hyun Dong Sam Ha Daniel Daeick Han Chong-Min Kyung Bradley Department of Electrical and Computer Engineering Virginia Tech Division of Industrial Design Department of Arts & Architecture Yanbian University of Science & Technology Division of Electrical Engineering Department of Electrical Engineering & Computer Science KAIST

ISBN: (纸本)9781479917631

This paper presents a solar energy harvesting (EH) system to power a portable compact LED lamp, which can be charged during daytime and used to light during night time. The solar lamp consists of three PV panels, an EH and power management circuit, three NiMH rechargeable batteries, and an LED. A commercial off-the-shelf chip TI BQ25504 is used to prototype the EH and power management circuit for the proposed system. Experimental results show that the proposed PVsystem can harvest solar energy both in indoor and outdoor environments. The peak net power harvested by the proposed system is about 380 mW on a sunny day, 250 mW on a partly cloudy day, and 30 mW on a cloudy day.

关键词： Energy harvesting Solar energy Photovoltaic (PV) cells Solar lamp Maximum power point tracking Solar Energy maximum power point trackers energy harvesting OFFICE OF THE ASSISTANT SECRETARY FOR ENVIRONMENT, ET. AL. LED lamps Power management integrated circuit harvesting

来源：评论

学校读者我要写书评

暂无评论

A novel concept for adaptive signal processing on reconfigurable hardware 1

引用

11th International Symposium on Applied Reconfigurable Computing, ARC 2015

作者： Figuli, Peter Tradowsky, Carsten Martinez, Jose Sidiropoulos, Harry Siozios, Kostas Stenschke, Holger Soudris, Dimitrios Becker, Jürgen Institute for Information Processing Technologies Karlsruhe Institute of Technology Karlsruhe Germany School of Electrical and Computer Engineering National Technical University of Athens Athens Greece School of Music University of Applied Sciences and Arts Northwestern Switzerland Basel Switzerland

ISBN: (数字)9783319162140

ISBN: (纸本)9783319162133

Today, digital signal processing systems for applications like audio or video production are restricted as they do not exhaust the possibilities given by modern hardware. Reconfigurable hardware exploits a huge degree of parallelism and provides flexibility at an affordable energy budget, thus becoming a competitive alternative for high performance Digital Signal Processing (DSP) applications, previously dominated by general purpose processing cores and Application-Specific Integrated Circuits (ASICs). This paper describes the design and evaluation of a novel concept for adaptive signal processing on reconfigurable hardware by using an adaptive reverberation algorithm targeting real time streams. Novel solutions were adopted in several critical parts of the signal processing chain in order to achieve a high level of accuracy under real time constraints. Experimental results show the efficiency of the introduced implementation on a Virtex-7 FPGA, as we can provide reality accurate reverberation with ultra low latency of ∼ 20.8 μs. © Springer International Publishing Switzerland 2015.

关键词： Reconfigurable hardware

来源：评论

学校读者我要写书评

暂无评论

Software-defined wireless network architectures for the Internet-of-Things

Software-defined wireless network architectures for the Inte...

引用

IEEE Conference on ALocal computer Networks Workshops (LCN Workshops)

作者： Amr El-Mougy Mohamed Ibnkahla Lobna Hegazy Faculty of Media Engineering and Technology German University in Cairo Cairo Egypt Department of Electrical and Computer Engineering Queen's University Kingston Ontario

The Internet-of-Things (IoT) envisions a world where billions of everyday objects and mobile devices communicate using a large number of interconnected wired and wireless networks. Maximizing the utilization of this paradigm requires fine-grained QoS support for differentiated application requirements, context-aware semantic information retrieval, and quick and easy deployment of resources, among many other objectives. These objectives can only be achieved if components of the IoT can be dynamically managed end-to-end across heterogeneous objects, transmission technologies, and networking architectures. Software-defined Networking (SDN) is a new paradigm that provides powerful tools for addressing some of these challenges. Using a software-based control plane, SDNs introduce significant flexibility for resource management and adaptation of network functions. In this article, we study some promising solutions for the IoT based on SDN architectures. Particularly, we analyze the application of SDN in managing resources of different types of networks such as Wireless Sensor Networks (WSN) and mobile networks, the utilization of SDN for information-centric networking, and how SDN can leverage Sensing-as-a-Service (SaaS) as a key cloud application in the IoT.

关键词： Sensors Wireless sensor networks Protocols Control systems Cloud computing computer architecture

来源：评论

学校读者我要写书评

暂无评论

Evolutionary multi-view face tracking on pixel replaced image in video sequence

Evolutionary multi-view face tracking on pixel replaced imag...

引用

International Conference of Soft Computing and Pattern Recognition (SOCPAR)

作者： Junya Sato Takuya Akashi Department of Design & Media Technology Iwate University Iwate Japan Department of Electrical Engineering and Computer Science Faculty of Engineering Iwate University Iwate Japan

ISBN: (纸本)9781467393614

Nowadays, many computer vision techniques are applied to practical applications, such as surveillance and facial recognition systems. Some of such applications focus on information extraction from the human beings. However, people may feel psychological stress about recording their personal information, such as a face, behavior, and cloth. Therefore, privacy protection of the images and videos is necessary. Specifically, the detection and tracking methods should be used on the privacy protected images. For this purpose, there are some easy methods, such as blurring and pixelating, and they are often used in news programs etc. Because such methods just average pixel values, no important feature for the detection and tracking is left. Hence, the preprocessed images are unuseful. In order to solve this problem, we have proposed shuffle filter and a multi-view face tracking method with a genetic algorithm (GA). The filter protects the privacy by changing pixel locations, and the color information can be preserved. Since the color information is left, the tracking can be achieved by a basic template matching with histogram. Moreover, by using GA instead of sliding window when the subject in the image is searched, it can search more efficiently. However, the tracking accuracy is still low and the preprocessing time is large. Therefore, improving them is the purpose in this research. In the experiment, the improved method is compared with our previous work, CAMSHIFT, an online learning method, and a face detector. The results indicate that the accuracy of the proposed method is higher than the others.

关键词： Face Image color analysis Privacy Histograms Detectors Genetic algorithms Surveillance

来源：评论

学校读者我要写书评

暂无评论

Enhancing online and mobile experimentations using gamification strategies

Enhancing online and mobile experimentations using gamificat...

引用

Experiment@ International Conference (exp.at)

作者： Johanna Pirker Christian Gutl Yacob Astatke Institute for Information Systems and Computer Media Graz University of Technology Graz Austria Electrical and Computer Engineering Faculty Morgan State University Baltimore MD USA

ISBN: (纸本)9781467377188

In teaching theoretical topics, modern STEM education uses interactive hands-on approaches, which support students in understanding the topic instead of teaching them simply how to memorize theoretical concepts. Pedagogical strategies in fields with an abundance of abstract concepts, such as physics or electrical engineering, additionally recommend experiential experience, such as laboratory experiments, as essential learning tools. To fulfill increased demand for engineers, additional educational opportunities have been created, which include online, remote and blended learning environments. Unfortunately, providing hands-on experience in these environments, which is as effective as in-class experiments in STEM fields, is extremely challenging. Different departments have developed online and remote solutions, from single remote introductory courses with online experiments to entire off-campus programs supported by remotely conducted experiments with mobile studios. However, in online situations, students often feel lost, have issues with the technology, and experience lack of engagement. All these factors can result in increased dropout rates or lack of understanding and commitment. Current trends in online education incline towards engaging students using gamification strategies to reduce dropout rates and to increase students' motivation in a playful way. Additionally, creating playful experiences for students can be used to attract novice students to this field. In this paper, we introduce a theoretical framework, which can be used to enhance online and mobile experiments with game design strategies to raise students' engagement and commitment and reduce initial onboarding obstacles.

关键词： Mobile communication Games computers Learning management systems Context Computational modeling

来源：评论

学校读者我要写书评

暂无评论

Author Correction: National identity predicts public health support during a global pandemic

引用

Nature communications 2022年第1期13卷 1949页

作者： Jay J Van Bavel Aleksandra Cichocka Valerio Capraro Hallgeir Sjåstad John B Nezlek Tomislav Pavlović Mark Alfano Michele J Gelfand Flavio Azevedo Michèle D Birtel Aleksandra Cislak Patricia L Lockwood Robert Malcolm Ross Koen Abts Elena Agadullina John Jamir Benzon Aruta Sahba Nomvula Besharati Alexander Bor Becky L Choma Charles David Crabtree William A Cunningham Koustav De Waqas Ejaz Christian T Elbaek Andrej Findor Daniel Flichtentrei Renata Franc Biljana Gjoneska June Gruber Estrella Gualda Yusaku Horiuchi Toan Luu Duc Huynh Agustin Ibanez Mostak Ahamed Imran Jacob Israelashvili Katarzyna Jasko Jaroslaw Kantorowicz Elena Kantorowicz-Reznichenko André Krouwel Michael Laakasuo Claus Lamm Caroline Leygue Ming-Jen Lin Mohammad Sabbir Mansoor Antoine Marie Lewend Mayiwar Honorata Mazepus Cillian McHugh John Paul Minda Panagiotis Mitkidis Andreas Olsson Tobias Otterbring Dominic J Packer Anat Perry Michael Bang Petersen Arathy Puthillam Julián C Riaño-Moreno Tobias Rothmund Hernando Santamaría-García Petra C Schmid Drozdstoy Stoyanov Shruti Tewari Bojan Todosijević Manos Tsakiris Hans H Tung Radu G Umbreș Edmunds Vanags Madalina Vlasceanu Andrew Vonasch Meltem Yucel Yucheng Zhang Mohcine Abad Eli Adler Narin Akrawi Hamza Alaoui Mdarhri Hanane Amara David M Amodio Benedict G Antazo Matthew Apps F Ceren Ay Mouhamadou Hady Ba Sergio Barbosa Brock Bastian Anton Berg Maria P Bernal-Zárate Michael Bernstein Michał Białek Ennio Bilancini Natalia Bogatyreva Leonardo Boncinelli Jonathan E Booth Sylvie Borau Ondrej Buchel C Daryl Cameron Chrissie F Carvalho Tatiana Celadin Chiara Cerami Hom Nath Chalise Xiaojun Cheng Luca Cian Kate Cockcroft Jane Conway Mateo Andres Córdoba-Delgado Chiara Crespi Marie Crouzevialle Jo Cutler Marzena Cypryańska Justyna Dabrowska Michael A Daniels Victoria H Davis Pamala N Dayley Sylvain Delouvee Ognjan Denkovski Guillaume Dezecache Nathan A Dhaliwal Alelie B Diato Roberto Di Paolo Marianna Drosinou Uwe Dulleck Jānis Ekmanis Arhan S Ertan Tom W Etienne Hapsa Hossain Farhana Fahima Farkhari Har Department of Psychology and Neural Science New York University New York NY USA. jay.vanbavel@nyu.edu. School of Psychology University of Kent Canterbury England. Department of Economics Middlesex University London London England. Department of Strategy and Management Norwegian School of Economics Bergen Norway. SWPS University of Social Sciences and Humanities Poznań Poland. Department of Psychological Sciences College of William and Mary Williamsburg VA USA. Institute of Social Sciences Ivo Pilar Zagreb Croatia. Department of Philosophy Macquarie University Sydney NSW Australia. Stanford Graduate School of Business Stanford University Stanford CA USA. Institute of Communication Science Friedrich-Schiller University Jena Jena Germany. flavio.azevedo@uni-jena.de. School of Human Sciences Institute for Lifecourse Development University of Greenwich London England. Department of Experimental Psychology University of Oxford Oxford England. Center for Human Brain Health School of Psychology University of Birmingham Birmingham England. Department of Psychology Macquarie University Sydney NSW Australia. KU Leuven Leuven Belgium. National Research University Higher School of Economics (HSE) Moscow Russia. De La Salle University Manila Philippines. Department of Psychology University of the Witwatersrand Johannesburg South Africa. Department of Political Science Aarhus University Aarhus Denmark. X University Toronto ON Canada. Department of Government Dartmouth College Hanover NH USA. Department of Psychology University of Toronto Toronto ON Canada. Gatton College of Business and Economics University of Kentucky Lexington KY USA. Department of Mass Communication National University of Science and Technology (NUST) Islamabad Pakistan. Department of Management Aarhus University Aarhus Denmark. Faculty of Social and Economic Sciences Comenius University Bratislava Slovakia. IntraMed Buenos Aires Argentina. Macedonian Academy of Sciences and

来源：评论

学校读者我要写书评

暂无评论

Elastic Functional Coding of Human Actions: From Vector-Fields to Latent Variables

Elastic Functional Coding of Human Actions: From Vector-Fiel...

引用

IEEE Conference on computer Vision and Pattern Recognition

作者： Rushil Anirudh Pavan Turaga Jingyong Su Anuj Srivastava School of Electrical Computer and Energy Engineering Arizona State University School of Arts Media and Engineering Arizona State University Department of Mathematics & Statistics Texas Tech University Department of Statistics Florida State University

ISBN: (纸本)9781467369657

Human activities observed from visual sensors often give rise to a sequence of smoothly varying features. In many cases, the space of features can be formally defined as a manifold, where the action becomes a trajectory on the manifold. Such trajectories are high dimensional in addition to being non-linear, which can severely limit computations on them. We also argue that by their nature, human actions themselves lie on a much lower dimensional manifold compared to the high dimensional feature space. Learning an accurate low dimensional embedding for actions could have a huge impact in the areas of efficient search and retrieval, visualization, learning, and recognition. Traditional manifold learning addresses this problem for static points in R~n, but its extension to trajectories on Riemannian manifolds is non-trivial and has remained unexplored. The challenge arises due to the inherent non-linearity, and temporal variability that can significantly distort the distance metric between trajectories. To address these issues we use the transport square-root velocity function (TSRVF) space, a recently proposed representation that provides a metric which has favorable theoretical properties such as invariance to group action. We propose to learn the low dimensional embedding with a manifold functional variant of principal component analysis (mfPCA). We show that mf-PCA effectively models the manifold trajectories in several applications such as action recognition, clustering and diverse sequence sampling while reducing the dimensionality by a factor of ～ 250×. The mfPCA features can also be reconstructed back to the original manifold to allow for easy visualization of the latent variable space.

关键词： Manifolds trajectory DIMENSIONAL collective redress Action distance metric radon Eigenvector nonlinearity

来源：评论

学校读者我要写书评

暂无评论

Designing alternative systems for local communities 33

Designing alternative systems for local communities

引用

33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015

作者： Vlachokyriakos, Vasilis Comber, Rob Crivellaro, Clara Taylor, Nick Kuznetsov, Stacey Kavanaugh, Andrea Le Dantec, Christopher A. Kim, B. Joon Culture Lab School of Computing Science Newcastle University United Kingdom Duncan of Jordanstone College of Art and Design University of Dundee United Kingdom School of Arts Media and Engineering Arizona State University PhoenixAZ United States Center for Human-Computer Interaction Virginia Tech BlacksburgVA United States School of Literature Media and Communication Georgia Institute of Technology AtlantaGA United States Seoul Korea Republic of

ISBN: (纸本)9781450331463

Alternative systems ranging from self-organized skill sharing to alternative micro-economies have been critical channels of community engagement and bonding. technology is increasingly playing a role in the way people connect to these services at the (hyper)local level. While there has been considerable research on designing technology to support conventional, established systems of community organization and governance;mobile and ubiquitous technologies offer strong potential for alternative systems to be established in the local level. Do It Yourself (DIY) and maker movements are enabling grassroots activist groups to develop their own technologies or to hack existing tools to support bottom-up systems of self-organization, democracy and commerce. Based on these trends and the recent worldwide economic, political and societal crisis, this workshop will bring together researchers, practitioners and activists to re-envision how HCI tools can support alternative systems of local civic engagement.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

Construction of KAGRA: An underground gravitational wave observatory

arXiv

引用

arXiv 2017年

作者： Akutsu, T. Ando, M. Araki, S. Araya, A. Arima, T. Aritomi, N. Asada, H. Aso, Y. Atsuta, S. Awai, K. Baiotti, L. Barton, M.A. Chen, D. Cho, K. Craig, K. DeSalvo, R. Doi, K. Eda, K. Enomoto, Y. Flaminio, R. Fujibayashi, S. Fujii, Y. Fujimoto, M.-K. Fukushima, M. Furuhata, T. Hagiwara, A. Haino, S. Harita, S. Hasegawa, K. Hasegawa, M. Hashino, K. Hayama, K. Hirata, N. Hirose, E. Ikenoue, B. Inoue, Y. Ioka, K. Ishizaki, H. Itoh, Y. Jia, D. Kagawa, T. Kaji, T. Kajita, T. Kakizaki, M. Kakuhata, H. Kamiizumi, M. Kanbara, S. Kanda, N. Kanemura, S. Kaneyama, M. Kasuya, J. Kataoka, Y. Kawaguchi, K. Kawai, N. Kawamura, S. Kawazoe, F. Kim, C. Kim, J. Kim, J.C. Kim, W. Kimura, N. Kitaoka, Y. Kobayashi, K. Kojima, Y. Kokeyama, K. Komori, K. Kotake, K. Kubo, K. Kumar, R. Kume, T. Kuroda, K. Kuwahara, Y. Lee, H.-K. Lee, H.-W. Lin, C.-Y. Liu, Y. Majorana, E. Mano, S. Marchio, M. Matsui, T. Matsumoto, N. Matsushima, F. Michimura, Y. Mio, N. Miyakawa, O. Miyake, K. Miyamoto, A. Miyamoto, T. Miyo, K. Miyoki, S. Morii, W. Morisaki, S. Moriwaki, Y. Muraki, Y. Murakoshi, M. Musha, M. Nagano, K. Nagano, S. Nakamura, K. Nakamura, T. Nakano, H. Nakano, M. Nakano, M. Nakao, H. Nakao, K. Narikawa, T. Ni, W.-T. Nonomura, T. Obuchi, Y. Oh, J.J. Oh, S.-H. Ohashi, M. Ohishi, N. Ohkawa, M. Ohmae, N. Okino, K. Okutomi, K. Ono, K. Ono, Y. Oohara, K. Ota, S. Park, J. Peña Arellano, F.E. Pinto, I.M. Principe, M. Sago, N. Saijo, M. Saito, T. Saito, Y. Saitou, S. Sakai, K. Sakakibara, Y. Sasaki, Y. Sato, S. Sato, T. Sato, Y. Sekiguchi, T. Sekiguchi, Y. Shibata, M. Shiga, K. Shikano, Y. Shimoda, T. Shinkai, H. Shoda, A. Someya, N. Somiya, K. Son, E.J. Starecki, T. Suemasa, A. Sugimoto, Y. Susa, Y. Suwabe, H. Suzuki, T. Tachibana, Y. Tagoshi, H. Takada, S. Takahashi, H. Takahashi, R. Takamori, A. Takeda, H. Tanaka, H. Tanaka, K. Tanaka, T. Tatsumi, D. National Astronomical Observatory of Japan Tokyo181-8588 Japan Graduate School of Science University of Tokyo Tokyo113-0033 Japan Department of Physics Graduate School of Science University of Tokyo Tokyo113-0033 Japan Ibaraki305-0801 Japan Earthquake Research Institute University of Tokyo Tokyo113-0032 Japan Department of Physics Graduate School of Science Osaka City University Osaka558-8585 Japan Graduate School of Science and Technology Hirosaki University Aomori036-8561 Japan Department of Physics Graduate School of Science and Engineering Tokyo Institute of Technology Tokyo152-8551 Japan Institute for Cosmic Ray Research University of Tokyo Chiba277-8582 Japan Institute for Cosmic Ray Research University of Tokyo Gifu506-1205 Japan Graduate School of Science Osaka University Osaka560-0043 Japan Department of Physics Sogang University Seoul121-742 Korea Republic of University of Sannio at Benevento BeneventoI-82100 Italy Sezione di Napoli NapoliI-80126 Italy University of Toyama Toyama930-8555 Japan Department of Physics Graduate School of Science Kyoto University Kyoto606-8502 Japan Institute of Physics Academia Sinica Taipei11529 Taiwan University of Toyama Toyama930-8555 Japan Yukawa Institute for Theoretical Physics Kyoto University Kyoto606-8502 Japan Albert-Einstein-Institut Max-Planck-Institut für Gravitationsphysik HannoverD-30167 Germany Department of Physics and Astronomy Seoul National University Seoul151-742 Korea Republic of Daejeon34055 Korea Republic of Department of Physics Myongji University Yongin449-728 Korea Republic of Department of Computer Simulation Inje University Gimhae-shi50834 Korea Republic of Daejeon34047 Korea Republic of Department of Physical Science Graduate School of Science Hiroshima University Hiroshima903-0213 Japan Department of Applied Physics Graduate School of Science Fukuoka University Fukuoka814-0180 Japan Graduate School of Science and Engineer

Major construction and initial-phase operation of a second-generation gravitational-wave detector KAGRA has been completed. The entire 3-km detector is installed underground in a mine in order to be isolated from background seismic vibrations on the surface. This allows us to achieve a good sensitivity at low frequencies and high stability of the detector. Bare-bones equipment for the interferometer operation has been installed and the first test run was accomplished in March and April of 2016 with a rather simple configuration. The initial configuration of KAGRA is named iKAGRA. In this paper, we summarize the construction of KAGRA, including the study of the advantages and challenges of building an underground detector and the operation of the iKAGRA interferometer together with the geophysics interferometer that has been constructed in the same tunnel. Copyright © 2017, The Authors. All rights reserved.

关键词： Interferometers

来源：评论

学校读者我要写书评

暂无评论

Probability fuzzy SVM for image retrieval

Probability fuzzy SVM for image retrieval

引用

International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Deshan Liu Deqin Yan Yonghua Tang Shenglan Liu School of Computer and Information Technology Liaoning Normal University Dalian China School of Computer Science and Technology Luxun Academy of Fine Arts Dalian China Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9781467376839

In the scheme of relevance feedback (RF) of conventional content-based image retrieval (CBIR) systems, only the labeled samples will be trained for learning, which gives rise to the small sample size (sss) problem. To solve the problem, a variety of RF schemes have been developed with exploiting support vector machine (SVM) which concentrates on enhancing classification ability of the schemes. In fact, there is not only classification distribution but also probability distribution in both numeric value data and image data. In fact, probability distribution existing in the images with multi-semantic meaning is more crucial for building a better scheme of RF. For modeling the scheme of RF under the consideration of both classification distribution and probability distribution, a framework of probability fuzzy support vector machine (PFSVM) is developed in this paper. In the framework, every pseudo-label sample is assigned both a fuzzy and a probability membership which are integrated into mechanism of PFSVM for active learning. Experimental results with a database of 1,000 images demonstrate the effectiveness of the proposed method.

关键词： Support vector machines Probability distribution Radio frequency Image retrieval Training Linear programming Labeling

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：