检索结果-内蒙古大学图书馆

IEEE Conference on Wireless Communications and Networking

作者： Imad Ali Ronald Y. Chang Cheng-Hsin Hsu Taiwan International Graduate Program in Social Networks and Human-Centered Computing Institute of Information Science Academia Sinica Taipei Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan

ISBN: (数字)9781728131061

ISBN: (纸本)9781728131078

In a question & answer (Q& A) system, credible users provide answers of higher correctness. However, in a distributed social network based Q& A (SNQ& A) system, an asker does not know a k-hop answerer's credibility, thus making it difficult for the asker to assess the answer correctness. Therefore, a credibility-enabled distributed SNQ& A system is crucial for determining the correctness of the answers. To this end, we propose CRED, a credibility-enabled distributed SNQ& A system, which facilitates each user to assess the correctness of the provided answers. CRED utilizes subjective logic to build interestwise friend-to-friend credibility opinions under uncertainties. The developed opinions are then accumulated by CRED to get each user's aggregated credibility opinion, which may reflect the user's real credibility. CRED forwards a question to users with highest credibility beliefs in the question interest category. Our evaluation results show that, on average, CRED accomplishes higher success ratio, higher answer correctness, and lower answer uncertainty by 12.1%, 16.4%, and 22.2%, respectively, as compared to the best-performing baseline systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detecting Hemileia vastatrix using Vision AI as Supporting to Food Security for Smallholder Coffee Commodities

引用

IOP Conference Series: Earth and Environmental science 2022年第1期998卷

作者： Teddy Suparyanto Erick Firmansyah Tjeng Wawan Cenggoro Digdo Sudigyo Bens Pardamean Faculty of Agricultural Technology Institute of Agriculture STIPER Yogyakarta Indonesia 55282 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

The loss of food crops during the COVID-19 pandemic threatens food security in Indonesia as one of the world's top coffee producers. This affects the insecurity of coffee commodities which is influenced by several factors other than the pandemic such as pests, plant diseases, and extreme weather. Plant diseases, such as leaf rust, are a significant factor in the insecurity problem in coffee commodities. The fungus Hemileia vastatrix B et Br causes leaf rust disease, which is a pest that frequently damages coffee plants. This disease not only interferes with plant growth but also causes a decrease in coffee quality and quantity. This initial research aims to carry out early prevention of these diseases as supporting to food security in smallholder coffee commodities. An AI-based visual detection application is the result of this research. We collected 100 images of coffee leaves from various coffee plants. The image is reshaped to 256 x 256 pixels and randomly trimmed to 224 x 224 pixels to fulfill the size requirements of a standard Deep Learning technique. Each image was classified into two classes by a plant pest and disease specialist. The dataset was divided into training, validation, and testing series with a ratio of 60:20:20 for training procedures. The Convolutional Neural Network (CNN) research method used a variation of the ResNet CNN model with 18 layers. The best model validation was 59%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Investigating Students’ Perception towards the Use of Social Media for computing Education in Nigeria

引用

Journal of Information Systems Education 2021年第3期32卷 212-228页

作者： Agbo, Friday J. Olawumi, Olayemi Balogun, Oluwafemi S. Sanusi, Ismaila T. Olaleye, Sunday A. Sunday, Kissinger Kolog, Emmanuel A. Atsa’am, Donald D. Adusei-Mensah, Frank Adegbite, Ayobami Ipeayeda, Funmilola W. School of Computing University of Eastern Finland 80110 Joensuu 70211 Kuopio Finland Department of Marketing Management and International Business University of Oulu Oulu90570 Finland Department of Computer Science National Chengchi University Taipei Taiwan Department of Operations and MIS University of Ghana Business School Accra Ghana Department of Mathematics Statistics and Computer Science University of Agriculture Makurdi Nigeria Institute of Public Health and Clinical Nutrition University of Eastern Finland Kuopio Finland Bio Environmental Science Program Morgan State University BaltimoreMD21251 United States Department of Computer Science Ajayi Crowther University Oyo Nigeria

This study examined the use of a social media platform – WhatsApp – by computer science students for learning computing education in the context of a Nigerian education institution. Nowadays, a large community of students in higher education institutions has embraced the WhatsApp platform for social interactions which makes it a useful tool in education. In this study, students formed three closed groups, and each group had a specific computing topic they discussed. Their discussions were in the form of posting questions, providing answers to questions, or expressing knowledge on the group topic. A questionnaire was used to collect data from the participants regarding their experiences. We conducted a descriptive analysis of the students’ learning outcomes. The results show that the use of social media contributes positively to students’ learning achievement, and they are motivated to acquire more knowledge about different computing topics © 2021, Journal of Information Systems Education. All Rights Reserved.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Scientific discovery in the age of artificial intelligence

引用

NATURE 2023年第7978期621卷 E33-E33页

作者： Wang, Hanchen Fu, Tianfan Du, Yuanqi Gao, Wenhao Huang, Kexin Liu, Ziming Chandak, Payal Liu, Shengchao Van Katwyk, Peter Deac, Andreea Anandkumar, Anima Bergen, Karianne Gomes, Carla P. Ho, Shirley Kohli, Pushmeet Lasenby, Joan Leskovec, Jure Liu, Tie-Yan Manrai, Arjun Marks, Debora Ramsundar, Bharath Song, Le Sun, Jimeng Tang, Jian Velickovic, Petar Welling, Max Zhang, Linfeng Coley, Connor W. Bengio, Yoshua Zitnik, Marinka Department of Engineering University of Cambridge Cambridge UK Department of Computing and Mathematical Sciences California Institute of Technology Pasadena CA USA NVIDIA Santa Clara CA USA Department of Computational Science and Engineering Georgia Institute of Technology Atlanta GA USA Department of Computer Science Cornell University Ithaca NY USA Department of Chemical Engineering Massachusetts Institute of Technology Cambridge MA USA Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Department of Computer Science Stanford University Stanford CA USA Department of Physics Massachusetts Institute of Technology Cambridge MA USA Harvard-MIT Program in Health Sciences and Technology Cambridge MA USA Mila – Quebec AI Institute Montreal Quebec Canada Université de Montréal Montreal Quebec Canada HEC Montréal Montreal Quebec Canada CIFAR AI Chair Toronto Ontario Canada Department of Earth Environmental and Planetary Sciences Brown University Providence RI USA Data Science Institute Brown University Providence RI USA Center for Computational Astrophysics Flatiron Institute New York NY USA Department of Astrophysical Sciences Princeton University Princeton NJ USA Department of Physics Carnegie Mellon University Pittsburgh PA USA Department of Physics and Center for Data Science New York University New York NY USA Google DeepMind London UK Department of Computer Science and Technology University of Cambridge Cambridge UK Microsoft Research Beijing China Department of Biomedical Informatics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Harvard Data Science Initiative Cambridge MA USA Kempner Institute for the Study of Natural and Artificial Intelligence Harvard University Cambridge MA USA Department of Systems Biology Harvard Medical School Boston MA USA Deep Forest Sciences Palo Alto CA USA BioMap Beijing China Mo

来源：评论

学校读者我要写书评

暂无评论

LOCI: A Mobile Q&A System with Multimodal Motivation Scheme for Local Intent Questions in Dynamic Social Networks

LOCI: A Mobile Q&A System with Multimodal Motivation Scheme ...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Imad Ali Ronald Y. Chang Cheng-Hsin Hsu Chi-Han Lee Taiwan International Graduate Program in Social Networks and Human-Centered Computing Institute of Information Science Academia Sinica Taipei Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan

ISBN: (数字)9781728152073

ISBN: (纸本)9781728140537

Recent research has shown that people are frequently searching for information with local intent. The existing systems fail to answer this class of questions as they are not mainly designed to handle it. In this paper, we propose LOCI, a mobile question & answer system with a multimodal motivation scheme for local intent questions where users provide timely and accurate answers in a dynamic social network. LOCI mines users' shared and contextual information to identify the most relevant users for each question. The proposed multimodal motivation scheme exploits users' social ties and monetary rewards to raise their basic motivation levels. LOCI assigns questions to the best answerers via our three proposed algorithms: (i) LOCI-RT, which immediately assigns newly arrived questions/users to available users/questions, (ii) LOCI-LO, which uses short-time batches for locally optimal questions-users assignment, and (iii) LOCI-AD, which assigns short- and long-deadline questions immediately and via batching, respectively. We conduct: (i) a survey to support our assumptions regarding the proposed multimodal motivation scheme, and (ii) trace-driven experiments to evaluate the performance of the three proposed LOCI's algorithms.

关键词： Social networking (online) Resource management Heuristic algorithms Real-time systems computer science Search engines Servers

来源：评论

学校读者我要写书评

暂无评论

BCData: A Large-Scale Dataset and Benchmark for Cell Detection and Counting 23rd

BCData: A Large-Scale Dataset and Benchmark for Cell Detecti...

引用

23rd International Conference on Medical Image computing and computer-Assisted Intervention, MICCAI 2020

作者： Huang, Zhongyi Ding, Yao Song, Guoli Wang, Lin Geng, Ruizhe He, Hongliang Du, Shan Liu, Xia Tian, Yonghong Liang, Yongsheng Zhou, S. Kevin Chen, Jie School of Electronic and Computer Engineering Peking University Shenzhen China University of Chinese Academy of Sciences Beijing China Peng Cheng Laboratory Shenzhen China Shenzhen Hospital University of Chinese Academy of Sciences Shenzhen China The Second Peoples Hospital of Shenzhen Shenzhen China School of Electronics Engineering and Computer Science Peking University Beijing China Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030597214

Breast cancer is a main malignant tumor for women and the incidence is trending to ascend. Detecting positive and negative tumor cells in the immunohistochemically stained sections of breast tissue to compute the Ki-67 index is an essential means to determine the degree of malignancy of breast cancer. However, there are scarcely public datasets about cell detection of Ki-67 stained images. In this paper, we introduce a large-scale Breast tumor Cell Dataset (BCData) for cell detection and counting, which contains 1,338 images with 181,074 annotated cells belonging to two categories, i.e., positive and negative tumor cells. (We state that our dataset can only be used for non-commercial research.) Our dataset varies widely in both the distributing density of tumor cells and the Ki-67 index. We conduct several cell detection and counting methods on this dataset to set the first benchmark. We believe that our dataset will facilitate further research in cell detection and counting fields in clustering, overlapping, and variational stained conditions. Our dataset is available at https://***/view/bcdataset © 2020, Springer Nature Switzerland AG.

关键词： Cells

来源：评论

学校读者我要写书评

暂无评论

Nesting-structured nuclear norm minimization for spatially correlated matrix variate

引用

Pattern Recognition 2019年 91卷 147-161页

作者： Luo, Lei Yang, Jian Zhang, Yigong Xu, Yong Huang, Heng School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing 210094 China Bio-Computing Research Center Shenzhen Graduate School Harbin Institute of Technology Shenzhen 518055 China Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh PA United States

Integrating the structure prior in modeling has achieved considerable attention in pattern recognition and computer vision. Most current state-of-the-art methods (such as low rank representation and structured sparsity) search for a structured metric to fit the structure of the estimated variate, which either bear high time complexity (e.g., compute singular value decomposition for large-scale matrices), or cannot effectively exploit structure information of a matrix variate. In this work, we introduce a nesting-structured nuclear norm to characterize the matrix variate with structure prior and provide a unified framework for solving nesting-structured nuclear norm minimization (NSNM) problem by resorting to an improved sub-gradient method. This not only takes local and global structures of the matrix variate into joint consideration, but also enjoys the lower time complexity than traditional nuclear norm minimization. The revealed statistical meaning explains the rationality of the proposed method. Moreover, we apply NSNM to matrix regression and completion problems, respectively. The extensive experiments for face recognition and large-scale matrix completion clearly demonstrate the superiority of NSNM over some existing methods. © 2019 Elsevier Ltd

关键词： Low rank Matrix completion Matrix regression Nesting-structured nuclear norm Structured sparsity Sub-gradient method

来源：评论

学校读者我要写书评

暂无评论

Quantum coupon collector 15

Quantum coupon collector

引用

15th Conference on the Theory of Quantum Computation, Communication and Cryptography, TQC 2020

作者： Arunachalam, Srinivasan Belovs, Aleksandrs Childs, Andrew M. Kothari, Robin Rosmanis, Ansis De Wolf, Ronald IBM Research Yorktown HeightsNY United States Faculty of Computing University of Latvia Riga Latvia Department of Computer Science Institute for Advanced Computer Studies University of Maryland College ParkMD United States Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD United States Microsoft Quantum RedmondWA United States Microsoft Research RedmondWA United States Graduate School of Mathematics Nagoya University Japan QuSoft Amsterdam Netherlands CWI Amsterdam Netherlands University of Amsterdam Netherlands

ISBN: (纸本)9783959771467

We study how efficiently a k-element set S ? [n] can be learned from a uniform superposition |Si of its elements. One can think of |Si = Pi?S |ii/p|S| as the quantum version of a uniformly random sample over S, as in the classical analysis of the "coupon collector problem." We show that if k is close to n, then we can learn S using asymptotically fewer quantum samples than random samples. In particular, if there are n - k = O(1) missing elements then O(k) copies of |Si suffice, in contrast to the T(k log k) random samples needed by a classical coupon collector. On the other hand, if n - k = ?(k), then ?(k log k) quantum samples are necessary. More generally, we give tight bounds on the number of quantum samples needed for every k and n, and we give efficient quantum learning algorithms. We also give tight bounds in the model where we can additionally reflect through |Si. Finally, we relate coupon collection to a known example separating proper and improper PAC learning that turns out to show no separation in the quantum case. © Srinivasan Arunachalam, Aleksandrs Belovs, Andrew M. Childs, Robin Kothari, Ansis Rosmanis, and Ronald de Wolf.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Landau Polaritons in the Ultrastrong and Superstrong Coupling Regime in a Multimode Terahertz Photonic-Crystal Cavity

Landau Polaritons in the Ultrastrong and Superstrong Couplin...

引用

International Conference on Infrared and Millimeter Waves

作者： Fuyang Tay Ali Mojibpour Stephen Sanders Shuang Liang Hongjing Xu Geoff C. Gardner Andrey Baydin Michael J. Manfra Alessandro Alabastri David Hagenmüller Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley–Curl Institute Rice University Houston TX USA Department of Physics and Astronomy Purdue University West Lafayette IN USA Birck Nanotechnology Center Purdue University West Lafayette IN USA Department of Physics and Astronomy Rice University Houston TX USA Smalley–Curl Institute Rice University Houston TX USA School of Electrical and Computer Engineering Purdue University West Lafayette IN USA School of Materials Engineering Purdue University West Lafayette IN USA ISIS (UMR 7006) Université de Strasbourg and CNRS Strasbourg France Department of Materials Science and NanoEngineering Rice University Houston TX USA

We have demonstrated ultrastrong and superstrong coupling of a Landau-quantized two-dimensional electron gas in GaAs with a multiple-mode three-dimensional terahertz photonic-crystal cavity. The cavity had an asymmetric design such that the real-space profiles of photonic modes depended on the electric field polarization. Terahertz magnetospectroscopy experiments with polarized radiation clearly showed that the degree of hybridization of multiple cavity modes is a function of the spatial overlap of the photonic modes. These findings can be utilized for the dynamical tuning of multimode light–matter interactions, which can lead to the development of novel terahertz devices.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Terahertz Cavity Phonon Polaritons in Lead Telluride in the Deep-Strong Coupling Regime

arXiv

引用

arXiv 2025年

作者： Baydin, Andrey Manjappa, Manukumara Mishra, Sobhan Subhra Xu, Hongjing Doumani, Jacques Tay, Fuyang Kim, Dasom Rappl, Paulo H.O. Abramof, Eduardo Singh, Ranjan Hernandez, Felix G.G. Kono, Junichiro Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Smalley–Curl Institute Rice University HoustonTX77005 United States Rice Advanced Materials Institute Rice University HoustonTX77005 United States Instrumentation and Applied Physics Department Indian Institute of Science Bangalore560012 India Center for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University 639798 Singapore Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley–Curl Institute Rice University HoustonTX77005 United States Group of Research and Development in Materials and Plasma National Institute for Space Research São José dos Campos São Paulo12201-970 Brazil Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Instituto de Física Universidade de São Paulo São Paulo05508-090 Brazil Department of Material Science and NanoEngineering Rice University HoustonTX77005 United States

Lead telluride is an important thermoelectric material due to its large Seebeck coefficient combined with its unusually low thermal conductivity that is related to the strong anharmonicity of phonons in this material. Here, we have studied the resonant and nonperturbative coupling of transverse optical phonons in lead telluride with cavity photons inside small-mode-volume metallic metasurface cavities that have photonic modes with terahertz frequencies. We observed a giant vacuum Rabi splitting on the order of the bare phonon and cavity frequencies. Through terahertz time-domain spectroscopy experiments, we systematically studied the vacuum Rabi splitting as a function of sample thickness, temperature, and cavity length. Under the strongest light–matter coupling conditions, the strength of coupling exceeded the bare phonon and cavity frequencies, putting the system into the deep-strong coupling regime. These results demonstrate that this uniquely tunable platform is promising for realizing and understanding predicted cavity-vacuum-induced ferroelectric instabilities and exploring applications of light–matter coupling in the ultrastrong and deep-strong coupling regimes in quantum technology. Copyright © 2025, The Authors. All rights reserved.

关键词： Phonons

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：